bluuebunny/crossref_metadata_2025 huggingface dataset:
Mixed Communication Design of Phasor Data Concentrator in Distribution Network
Authors: Wu Yan , Tao Weiqing , Zhang Yingjie , Li Xueting
Published: July 2022

Phase Data Concentrator (PDC) is an important part of Wide Area Measurement System (WAMS) and is widely used in transmission systems. WAMS technology will also be applied in smart distribution network, which has many nodes, complex architecture and various types of data transmission services, and a single communication mode cannot meet its needs. In order to solve this problem, this paper first introduces the composition of WAMS system, communication network mode, and discusses the access layer communication network mode. According to the main station, sub-station interaction process design a synchronous phase data set device that can carry out up-down communication and mix network by various means of communication. Finally, the experimental environment of Power Line Carrier (PLC) and twisted pair network communication is set up to verify.
Control Model Design for Monitoring the Trust of E-logistics Merchants
Authors: Sun Susie Y.
Published: July 2022

In order to improve the subjectivity bias of the traditional autocorrelation function analysis method, this paper tries to introduce the mutual correlation criterion to establish the asymptotic control model in the e-logistics trust degree control application. By pre-constructing the resource database structure model of e-logistics, we adopt the DOI mutual correlation criterion to describe the user’s trust degree evaluation of resources, and then form the user trust Simulation experiments show that the model has a good asymptotic control performance on the trust degree of e-logistics with accurate trust evaluation and high estimation accuracy. The decision making approach based on the mutual correlation criterion, in which two or more users jointly make the normalized evaluation of the mutual trust value model, can effectively improve the traditional model autocorrelation active selection bias. The new model realizes the progressive control of e-logistics trust degree based on the mutual correlation criterion, which can significantly improve the supervision of e-logistics enterprises.
Certificateless Identity Management and Authentication Scheme Based on Blockchain Technology
Authors: Han Chao , Wen Fengtong
Published: July 2022

Identity management and authentication in cyberspace is crucial for all forms of remote communication. The traditional authentication technology has great security risks due to its central third-party structure, such as single point of failure, malicious server attacks and so on. The emergence of blockchain technology provides a new way of thinking to solve this problem. This paper focuses on the identity management and authentication scheme based on blockchain technology. Using the decentralized, open and transparent characteristics of blockchain to make up for the shortcomings of traditional identity management and authentication mechanisms. In this paper, we analyze the BIDaaS [1] identity management and authentication scheme proposed by Jong-Hyouk and point out the obvious shortcomings of the scheme, such as suffer impersonating attack simply, virtual identities are not unique. We combine the specificity of biological characteristics to implement a unique virtual identity on the chain and improve the off-chain identity authentication process using a certificateless scheme to build a reasonable and secure identity management and authentication scheme, which realizes two-way authentication and session key agreement. The analysis shows that the scheme has a high level of safety.
The Ground-State Potential Energy Surface of F-Li2 Polymer
Authors: Wang Yue , Li Qingling , Liu Guoqing , Gong Wenhao , Yu Shijun , Liu Yu , Dong Xiaozhou , Chen Shiwen , Zhang Chengwen
Published: July 2022

The first three-dimensional potential energy surface (PES) for the ground-state of F-Li2 polymer by CCSD(T) method were present. Two Jacobi coordinates, R and θ and the frozen molecular equilibrium geometries were used. We mixed basis sets aug-cc-pCVQZ for the Li atom and aug-cc-pCVDZ for the F atom, with an additional (3s3p2d) set of midbond functions. The total of about 365 points were generated for the PES. Our ab initio calculations were consistent with the experimental data very well.
Research on Campus Card and Virtual Card Information System
Authors: Cheng Shuai
Published: July 2022

Campus card system is the core business and platform of University Information System. After more than ten years of development, it covers all aspects of campus life: learning, teaching and research. This paper explains the current situation of campus card system from the perspective of card, account and billing, descripts system design and account model. Based on current system, this paper analyses the development of virtual campus card and describes a Data docking method in Information System.
An Improved Time Series Network Model Based on Multitrack Music Generation
Authors: Zhao Junchuan
Published: July 2022

Deep learning architecture has become a cutting-edge method for automatic music generation, but there are still problems such as loss of music style and music structure. This paper presents an improved network structure of time series model based on multi-track music. A context generator is added to the traditional architecture. The context generator is responsible for generating cross-track contextual music features between tracks. The purpose is to better generate single-track and multi-track music features and tunes in time and space. A modified mapping model was further added to further modify the prediction results. Experiments show that compared with traditional methods, the proposed will partially improve the objective music evaluation index results.
Research on EEG Feature Extraction and Recognition Method of Lower Limb Motor Imagery
Authors: Li Dong , Peng Xiaobo
Published: July 2022

Aiming at the problems of difficult signal acquisition, low signal-to-noise ratio and poor classification accuracy of BCI technology, based on the theory of EEG, this paper designs a leg raising EEG experiment of lower limb motor imagery and collects EEG signal data from 20 subjects to improve the accuracy of classification and recognition The process of feature extraction and classification recognition is explored, and a multi domain fusion method is proposed for EEG signal feature extraction from time domain, frequency domain, time-frequency domain and spatial domain. At the same time, bagging and gradient boosting ensemble learning algorithms are applied to EEG signal classification and recognition, and multi domain fusion features are tested by constructing different classifiers, The final classification accuracy reaches 87.8% and 93%, which is better than the traditional SVM classification method.
Circular L(j,k)-Labeling Numbers of Cartesian Product of Three Paths
Authors: Wu Qiong , Rao Weili
Published: July 2022

The circular $$L(j,k)$$

L
(
j
,
k
)

-labeling problem with $$k\ge j$$

k
≥
j

arose from the code assignment in the wireless network of computers. Given a graph $$G$$
G
and positive numbers $$j,k,\sigma $$

j
,
k
,
σ

, and a circular $$\sigma $$
σ
-$$L(j,k)$$

L
(
j
,
k
)

-labeling of a graph $$G$$
G
is an assignment $$f$$
f
from $$[0,\sigma )$$

[
0
,
σ
)

to the vertices of $$G$$
G
, for any two vertices $$u$$
u
and $$v$$
v
, such that $$|f(u)-f(v){|}_{\sigma }\ge j$$

|
f

(
u
)

-
f

(
v
)

|
σ

≥
j

if $$uv\in E(G)$$

u
v
∈
E
(
G
)

, and $$|f(u)-f(v){|}_{\sigma }\ge k$$

|
f

(
u
)

-
f

(
v
)

|
σ

≥
k

if $$u$$
u
and $$v$$
v
are distance two apart, where $$|f\left(u\right)-f\left(v\right){|}_{\sigma }=min\left\{|f(u)-f(v)|, \sigma -|f(u)-f(v)|\right\}$$

|
f

u

-
f

v

|
σ

=
m
i
n

|
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(
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)
-
f
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,
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-
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f
(
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-
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. The minimum $$\sigma $$
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such that graph $$G$$
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has a circular $$\sigma $$
σ
-$$L(j,k)$$

L
(
j
,
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)

-labeling of a graph $$G$$
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, which is called the circular $$L(j,k)$$

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(
j
,
k
)

-labeling number of graph $$G$$
G
and is denoted by $${\sigma }_{j,k}(G)$$

σ

j
,
k

(
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)

. In this paper, we determine the circular $$L(j,k)$$

L
(
j
,
k
)

-labeling numbers of Cartesian product of three paths, where $$k\ge 2j.$$

k
≥
2
j
.
A Formalization of Topological Spaces in Coq
Authors: Yan Sheng , Fu Yaoshun , Guo Dakai , Yu Wensheng
Published: July 2022

It is a wish for Wu Wen-tsun to implement the mechanical proving of theorems in topology. Topological spaces constitute a fundamental concept of general topology, which is significant in understanding the essential content of general topology. Based on the machine proof system of axiomatic set theory, we presented a computer formalization of topological spaces in Coq. Basic examples of topological spaces are formalized, including indiscrete topological spaces and discrete topological spaces. Furthermore, the formal description of some well-known equivalent definitions of topological spaces are provided, and the machine proof of equivalent definitions based on neighborhood system and closure is presented. All the proof code has been verified in Coq, and the process of proof is standardized, rigorous and reliable.
A Storage Scheme for Access Control Record Based on Consortium Blockchain
Authors: Shi Yunmei , Li Ning , Hou Shoulu
Published: July 2022

The heterogeneous access control information scattered around different organizations or units is difficult to be gathered and audited, however, easy to be maliciously tampered. Aiming at the problems, this paper presents a blockchain-based storage scheme to store access control information, which can protect information privacy and facilitate the audit work. This is achieved by exploiting consortium blockchain, cryptography technology. Based on the scheme, we define the format of Access Control Record (ACR), design upload and download protocols, and realize the signature and encryption process for ACRs in a simulation environment. Theoretical analyses demonstrate that the proposed storage scheme needs lower storage cost and has higher efficiency compared with existing schemes, and can resist typical malicious attacks effectively.
A Multi-modal Seq2seq Chatbot Framework
Authors: Ji Zhi
Published: July 2022

The pandemic has forced young people to stay away from school and friends, complete online learning at home and live at home. Therefore, various mental illnesses such as anxiety and depression occur more frequently. Chatbot is a communication method that is more acceptable to young people. This paper proposes a multi-modal chatbot seq2seq framework, which divides the mental state of young people into different types through multi-modal information such as text and images entered by users in the chatbot. This model combines image description and text summarization modules with the attention mechanism in a multi-modal model to control related content in different modalities. Experiments on multi-modal data sets show that this method has 70% average accuracy and real users who use this system also believe that this method has good judgment ability.
Five Application Modes of Mobile Government
Authors: Yu Gangqiang , Li Dongze , Liu Jinyu
Published: July 2022

To solve the problem that traditional e-government tends to lose real-time control of content and process, mobile government was created, it has 5 main application modes, which are mG2G mode between government departments and other government departments, mG2E mode between government and internal staff, mG2B mode between government and business, mG2C mode between government and the public, and mG2V mode between government and organizations & people outside the country. Mobile government uses mG2C, mG2B and mG2V as the external service mode and mG2G and mG2E mode as the internal management mode to continuously improve the quality and level of external services through continuous optimization of internal management.
Human Action Recognition Based on Attention Mechanism and HRNet
Authors: Liu Siqi , Wu Nan , Jin Haifeng
Published: July 2022

A human action recognition network (AE-HRNet) based on high-resolution network (HRNet) and attention mechanism is proposed for the problem that the semantic and location information of human action features are not sufficiently extracted by convolutional networks. Firstly, the channel attention (ECA) module and spatial attention (ESA) module are introduced; on this basis, new base (EABasic) and bottleneck (EANeck) modules are constructed to reduce the computational complexity while obtaining more accurate semantic and location information on the feature map. Experimental results on the MPII and COCO validation sets in the same environment configuration show that AE-HRNet reduces the computational complexity and improves the action recognition accuracy compared to the high-resolution network.
Design of the Electric Power Spot Market Operation Detection System
Authors: Zeng Min , Mu Qichun
Published: July 2022

With the continuous deepening of the construction of the electric power pot market, it is necessary to optimize the operation mechanism of the spot market according to the operation of the spot market, study the information interaction and data integration technology of the spot market to support the coordinated operation of multiple markets, and design the overall architecture, application architecture, functional architecture of the information interaction and data integration platform of the spot market for the coordinated operation of multiple markets Hardware architecture and security protection system provide technical support for information interaction and data integration of multiple market coordinated operation of the power spot market. Through data visualization technology, this paper realizes the data visualization and background management of the provincial power spot market operation detection system, which is convenient for decision-makers to carry out data analysis and management.
Analysis of the Micro Implicit Feedback Behavior of User Network Exploring Based on Mobile Intelligent Terminal
Authors: Wang Wei , Zhang Chuang , Zheng Xiaoli , Du Yuxuan
Published: July 2022

In the face of the information recommendation requirements in mobile Internet applications, in order to better use the user micro implicit feedback behavior obtained by the mobile intelligent terminal to improve the recommendation efficiency, this paper intends to carry out the analysis of the implicit feedback behavior by analyzing the behavior distribution and behavior correlation. The analytical results reveal the particularity of the implicit feedback behavior in mobile intelligent terminal.
A Novel Home Safety IoT Monitoring Method Based on ZigBee Networking
Authors: An Ning , Li Peng , Wang Xiaoming , Wu Xiaojun , Dang Yuntong
Published: July 2022

This paper realizes the design of home safety early warning system by studying the wireless communication networking technology of ZigBee and WiFi, as well as sensor communication technology, which is based on taking home safety monitoring as the application background. In this study, CC2530 chip was used as ZigBee wireless communication module. A novel home security IoT monitoring method was proposed through sensor triggering, human activity trajectory perception algorithm design, and wireless networking and communication optimization. Meanwhile, the safety early warning and remote monitoring of home staff can be realized, and home safety can be guaranteed. The system can achieve the purpose of home monitoring and early warning with low software and hardware cost through the experimental design and result analysis. It can not only provide reference for the design of sensor communication system, but also provide technical reference for aging society and response.
An Improved Raft Consensus Algorithm Based on Asynchronous Batch Processing
Authors: Li Hao , Liu Zihua , Li Yaqin
Published: July 2022

The consensus algorithm has been popular in current distributed systems as it is more effective in solving server unreliability. It ensures a group of servers can form a coordinated system, and the entire system continues to work when a part of the service point fails. Raft is a well-known and widely used distributed consensus algorithm, but as it has a built-in purpose of comprehensibility, it is always compromised in terms of performance as a trade-off. In this paper, we mainly aim to improve the traditional Raft consensus algorithm’s performance problem, especially in high concurrency scenarios. We introduce a pre-proposal stage on top of the algorithm to achieve efficiency optimization through batch asynchronous log replicated and disk flushing. The experiment proved that the improved Raft could increase the system throughput by 2–3.6 times, and the processing efficiency for parallel requests can be increased by 20% or more.
Design and Implementation of a Novel Interconnection Architecture from WiFi to ZigBee
Authors: Gu Yu , Wu Chun , Li Jiangan
Published: July 2022

The signal layer heterogeneous communication technology is a cross-technology communication (CTC) technology, which is a direct communication technology between different wireless devices. Since ZigBee and WiFi have overlapping spectrum distribution, the ZigBee transmission will affect the CSI sequence. We propose a CTC technology based on machine learning and neural network, from Zigbee to WiFi, leveraging only WiFi channel state information (CSI). By classifying WiFi CSI, we can distinguish whether there is ZigBee signal transmission in WiFi signal. This paper uses the machine learning method and neural network method to classify CSI sequence analyzes the importance of CSI sequence features to the classifier, improves the accuracy of machine learning classifier by extracting multiple CSI sequence features, and improves the classification accuracy by neural network classifier. In our experimental data set, the highest accuracy can reach 95%. The evaluation results show that our accuracy is higher than the existing methods.
Robust Controller Design for Steer-by-Wire Systems in Vehicles
Authors: El Akchioui Nabil , El Fezazi Nabil , El Fezazi Youssef , Idrissi Said , El Haoussi Fatima
Published: July 2022

The steer-by-wire (SbW) technology enables to facilitate better steering control as it is based on an electronic control technique. The importance of this technology lies in replacing the traditional mechanical connections with steering auxiliary motors and electronic control and sensing units as these systems are of paramount importance with new electric vehicles. Then, this research paper discusses some difficulties and challenges that exist in this area and overcomes them by presenting some results. These results meet the SbW’s robust performance requirements and compensate oscillations from the moving part of the steering rack in the closed-loop system model: modeling, analysis and design. Thus, the issue of robust control for nonlinear systems with disturbances is addressed here. Finally, the results are validated through detailed simulations.
Study on the Comparison and Selection of County Energy Internet Planning Schemes Based on Integrated Empowerment-Topsis Method
Authors: Tan Qingkun , Yin Jianbing , Wu Peng , Xu Hang , Tang Wei , Chen Lin
Published: July 2022

Energy Internet is an important way to solve current energy and environmental problems. It combines the planning of multi-energy systems such as electricity, natural gas, heat and transportation, combines energy conversion and utilization with comprehensive demand response, and integrates energy supply network planning with sources and loads. Energy hub planning is combined. Firstly, through the literature survey method and expert interview method to identify the factors that affect planning, and establish a factor index system. Secondly, in order to make the calculation results more meaningful, subjective and objective weighting are combined, and the expert scoring method and the entropy weight method are used to determine the weight of the factors at each stage. Finally, a calculation example is used to verify the rationality of the topsis method for county-level energy Internet collaborative planning. The results of the calculation example show that collaborative planning can avoid the shortcomings of single-subject planning, and the model has certain applicability.
Application of Big Data Technology in Equipment System Simulation Experiment
Authors: Hou Jiajun , Zhan Hongtu , Jia Jia , Li Shu
Published: July 2022

In order to solve the problem of single utility between system data in simulation experiment, the simulation experiment method and experimental framework of equipment system development are analyzed. This paper constructs the experimental framework of big data technology in equipment system simulation, uses big data analysis technology, analyzes the application process in equipment system simulation experiment, and puts forward the shortcomings and difficulties of applying big data technology in equipment system simulation experiment. By introducing big data technology, it provides a reference basis for weapon equipment system development demonstration.
Complex Relative Position Encoding for Improving Joint Extraction of Entities and Relations
Authors: Cai Hua , Xu Qing , Shen Weilin
Published: July 2022

Relative position encoding (RPE) is important for transformer based pretrained language model to capture sequence ordering of input tokens. Transformer based model can detect entity pairs along with their relation for joint extraction of entities and relations. However, prior works suffer from the redundant entity pairs, or ignore the important inner structure in the process of extracting entities and relations. To address these limitations, in this paper, we first use BERT with complex relative position encoding (cRPE) to encode the input text information, then decompose the joint extraction task into two interrelated subtasks, namely head entity extraction and tail entity relation extraction. Owing to the excellent feature representation and reasonable decomposition strategy, our model can fully capture the semantic interdependence between different steps, as well as reduce noise from irrelevant entity pairs. Experimental results show that the F1 score of our method outperforms previous baseline work, achieving a better result on NYT-multi dataset with F1 score of 0.935.
The Research of Adaptive Modulation Technology in OFDM System
Authors: Zhang Xiuyan , Tao Guobin
Published: July 2022

Orthogonal frequency division multiplexing (OFDM) as a special multi-carrier transmission technology has good resistance to narrow-band interference and frequency selective fading ability. Compared with traditional modulation techniques, adaptive modulation can enhance bandwidth efficiency and system capacity. Therefore, applying adaptive modulation in OFDM systems can take full advantage of spectrum resources, and it is suitable for the high-speed and reliable mobile communication systems in the future. The purpose of this paper is to improve traditional OFDM adaptive algorithms (Hughes-Hartogs, Chow) to realize bits allocation, power allocation better. In this paper, simulation results demonstrated that the improved Levin-Campello algorithm lowers algorithm’s complexity greatly and owns better flexibility, at the same time, it guarantees good the bit error rate (BER) performance and can be applied to speech communication (fixed rate) and data communication (variable rate) in wireless communication systems.
Unsupervised MRI Images Denoising via Decoupled Expression
Authors: Zhang Jiangang , Pan Xiang , Lv Tianxu
Published: July 2022

Magnetic Resonance Imaging (MRI) is widely adopted in medical diagnosis. Due to the spatial coding scheme, MRI image is degraded by various noise. Recently, massive methods have been applied to the MRI image denoising. However, they lack the consideration of artifacts in MRI images. In this paper, we propose an unsupervised MRI image denoising method called UEGAN based on decoupled expression. We decouple the content and noise in a noisy image using content encoders and noise encoders. We employ a noising branch to push the noise decoder only extract the noise. The cycle-consistency loss ensures that the content of the denoised results match the original images. To acquire visually realistic generations, we add an adversarial loss on denoised results. Image quality penalty helps to retain rich image details. We perform experiments on unpaired MRI images from Brainweb datesets, and achieve superior performances compared to several popular denoising approaches.
Segmenting of the Sonar Image from an Undersea Goal Using Two Dimensional THC Entropy
Authors: Liu Yu , Wang Ruiyi , Guo Haitao
Published: July 2022

Sonar image segmentation is the basis of undersea goal detection and recognition. The THC (Tsallis-Havrda-Charvát) entropy can describe the statistical properties of the non-extensive systems and has a wider range of applications. There are multiple choices for the two features of the two-dimensional histograms, such as the gray value, the average gray value within a neighborhood, the median gray value within a neighborhood, the mode of gray values within a neighborhood, and so on. This paper investigates the segmentation results of a sonar image from an undersea goal using THC entropies of a variety of two-dimensional histograms, and gives the evaluation indexes for the segmentation results.
A High-Efficiency Knowledge Distillation Image Caption Technology
Authors: Li Mingxiao
Published: July 2022

Image caption is wildly considered in the application of machine learning. Its purpose is describing one given picture into text accurately. Currently, it uses the Encoder-Decoder architecture from deep learning. To further increase the semantic transmitted after distillation by feature representation, this paper proposes a knowledge distillation framework to increase the results of the teacher section, extracting features by different semantic levels from different fields of view, and the loss function adopts the method of label normalization. Handle unmatched image-sentence pairs. In order to achieve the purpose of a more efficient process. Experimental results prove that this knowledge distillation architecture can strengthen the semantic information transmitted after distillation in the feature representation, achieve a more efficient training model on less data, and obtain a higher accuracy rate.
Crayfish Quality Analysis Based on SVM and Infrared Spectra
Authors: Ye Zijian , Mou Yi
Published: July 2022

Different algorithms combined with Near-infrared spectroscopy were investigated for the detection and classification of crayfish quality. In this study, the crawfish quality was predicted by partial least square-support vector machine, principal component analysis-support vector machine, BP neural network and support vector machine after pre-processing the NIR spectral data of crawfish. The result shows that the accuracy of near-infrared spectroscopy technology combined with SVM to classify crayfish quality can reach 100%, and the prediction can guide the sampling of crayfish food safety in practice, thus improving food safety and quality.
Complete collection of one-loop triple-collinear splitting operators for dimensionally-regulated QCD
Authors: Czakon Michał , Sapeta Sebastian
Published: July 2022

Abstract

We provide results for the one-loop triple-collinear color/spin-space splitting operators for the five possible processes, q → $$ {qq}^{\prime }{\overline{q}}^{\prime } $$

qq
′

q
¯

′

, q → $$ qq\overline{q} $$
qq

q
¯

, q → qgg, g → $$ gq\overline{q} $$
gq

q
¯

and g → ggg. The expressions are exact in dimensionally-regulated massless QCD up to a single integral, which we expand to second order in the dimensional-regularisation parameter. We also evaluate the related splitting functions. Our results are both sufficient and indispensable for the construction of subtraction and integrated-subtraction terms for triple-collinear singularities of one-loop double-real-emission cross-section contributions as part of a next-to-next-to-next-to leading order subtraction scheme.
Surface cholesterol-enriched domains specifically promote invasion of breast cancer cell lines by controlling invadopodia and extracellular matrix degradation
Authors: Maja Mauriane , Mohammed Danahe , Dumitru Andra C. , Verstraeten Sandrine , Lingurski Maxime , Mingeot-Leclercq Marie-Paule , Alsteens David , Tyteca Donatienne
Published: July 2022

Tumor cells exhibit altered cholesterol content. However, cholesterol structural subcellular distribution and implication in cancer cell invasion are poorly understood mainly due to difficulties to investigate cholesterol both quantitatively and qualitatively and to compare isogenic cell models. Here, using the MCF10A cell line series (non-tumorigenic MCF10A, pre-malignant MCF10AT and malignant MCF10CAIa cells) as a model of breast cancer progression and the highly invasive MDA-MB-231 cell line which exhibits the common TP53 mutation, we investigated if cholesterol contributes to cancer cell invasion, whether the effects are specific to cancer cells and the underlying mechanism. We found that partial membrane cholesterol depletion specifically and reversibly decreased invasion of the malignant cell lines. Those cells exhibited dorsal surface cholesterol-enriched submicrometric domains and narrow ER-plasma membrane and ER-intracellular organelles contact sites. Dorsal cholesterol-enriched domains can be endocytosed and reach the cell ventral face where they were involved in invadopodia formation and extracellular matrix degradation. In contrast, non-malignant cells showed low cell invasion, low surface cholesterol exposure and cholesterol-dependent focal adhesions. The differential cholesterol distribution and role in breast cancer cell invasion provide new clues for the understanding of the molecular events underlying cellular mechanisms in breast cancer.
Neurologie in der DDR: eine systematische Literaturübersicht zur historischen Aufarbeitung
Authors: Armbruster Jan , Grothe Matthias , Haack Kathleen , Kumbier Ekkehardt
Published: July 2022

Hintergrund

Die Entwicklung der Neurologie verlief in beiden deutschen Staaten nach 1945 unterschiedlich, wobei nur wenig über die Neurologie in der DDR bekannt ist.

Fragestellung

Der Stand der historischen Forschung zur Neurologie in der DDR soll aufgezeigt werden.

Material und Methode

Es erfolgte eine systematische Literaturrecherche für den Zeitraum 1991 bis 2021 sowie eine Einordnung der jeweiligen Beiträge in verschiedene Kategorien.

Ergebnisse

Neben einer regional sehr unterschiedlichen Aufarbeitung zu spezifischen Themen zeigt sich insgesamt ein Mangel an einer thematischen Gesamtdarstellung sowie an Arbeiten zu gesellschaftspolitischen Zusammenhängen innerhalb der DDR und vergleichenden Aspekten im deutsch-deutschen, aber auch internationalen Maßstab.

Schlussfolgerungen

Die systematische Forschung der Geschichte der Neurologie in der DDR unter Berücksichtigung der Rolle innerhalb des sozialistischen Gesundheitswesens sollte im Rahmen eines separaten Forschungsprojekts aufgearbeitet werden und dabei vergleichende Aspekte einbeziehen.
Preparation, Characterization and In vitro Biological activity of 5-Fluorouracil Loaded onto poly (D, L-lactic-co-glycolic acid) Nanoparticles
Authors: Samy Moshera , Abdallah Heba M. , Awad Hanem M. , Ayoub Magdy M. H.
Published: July 2022

Nanoscale devices offer a lot of potential in drug delivery because of their small size. The goal of this work was to increase the oral bioavailability of the anti-cancer hydrophilic drug as 5-fluorouracil (5-FU) by incorporating it into poly (D, L-lactide-co-glycolide) nanoparticles (PLGNPs) using the double emulsion process, 5-FU- PLGNPs nanoparticles were created. Various factors, such as drug, polymer, and stabilizer concentrations, were investigated for assembly in order to arrive at the most effective formulation of 5-FU-PLGNPs. PLGNPs had a drug encapsulation efficiency of 9.75 to 24.8%. The prepared nanoparticles had a spherical shape and an average size of 212.3–285 nm, as shown by TEM. The dispersion of the drug into the prepared PLGNPs was confirmed by XRPD and FTIR. The optimized nanoparticles (F225) had high encapsulation efficiency 24.8 ± 0.21%, low particles size 212.3 ± 48.2 nm with an appropriate PDI value of 0.448, and ZP of − 48.3 ± 2.7 mV. The molecular dispersion of the medication within the system was validated by thermal behavior studies (DSC). In vitro drug release from the best-selected formulations revealed a sustained release of nanoparticles, with slower release reported when lower PVA concentrations were utilized. Three 5-FU-PLGNPs formulations were tested for anticancer efficacy against cell cultures of HCT-116 (human colorectal carcinoma), MCF-7 (human breast carcinoma), and HepG2 (human hepatocellular carcinoma). The created formulations were examined for in vitro cytotoxic activity, revealing that they appeared to be promising effective anticancer formulations when compared to the positive controlled (doxorubicin).
Exercise-induced hypoalgesia (EIH) in response to different exercise intensities
Authors: Tomschi Fabian , Lieverkus Dennis , Hilberg Thomas
Published: July 2022

Purpose

Acute physical activity leads to exercise-induced hypoalgesia (EIH). The aim of this study was to investigate the effects of four different exercise intensities on EIH.

Methods

25 male (age: 24.7 ± 3.0) subjects underwent four different exercise sessions on a bicycle ergometer for 30 min each at 60, 80, 100, and 110% of the individual anaerobic threshold on separate days in a randomized crossover design. Before, as well as 5- and 45-min post-exercise, pain sensitivity was measured employing pain pressure thresholds (PPT) at the elbow, knee, and ankle joints as well as the sternum and forehead. Besides, conditioned pain modulation (CPM) was conducted using thermal test- and conditioned stimuli before, 5-, and 45-min post-exercise.

Results

A main time effect was observed regarding PPT at all landmarks except for the forehead with higher values observed 5 and 45 min post-exercise compared to the pre-values. Yet, no interaction effects occurred. CPM did not change in response to any of the intensities used.

Conclusion

EIH occurs 5 and 45 min after exercise regardless of the intensity used at the joints and sternum which might be explained by local pain-inhibiting pathways and probably to a limited degree by central mechanisms, as no hypoalgesia was observed at the forehead and no changes in CPM occurred.
Iron-catalyzed cascade synthesis of nitrogen polycycles from alkynoic acids and functionalized amines
Authors: de Sarralde Jokin Diaz , Astobieta Elene , Sevilla Ania , Rincón Yuliet , Herrero María Teresa , Urgoitia Garazi , SanMartin Raul
Published: July 2022

Catalysis by first-row transition metals is of increasing interest in the context of the scarcity of chemical resources. For instance, iron is promising due to its abundance, low toxicity and unique electronic features. Here we synthesized quinazoline alkaloids from alkynoic acids and functionalized amines in the presence of iron dibromide and pyridine in toluene or, alternatively, in a solventless reaction system. We studied iron sources, reaction media and the effect of additives. Results show 39–99% yields and regioselective preparation of nitrogen- and oxygen-containing scaffolds. This is the first example of a cascade process involving alkynoic acids catalyzed by iron. Fe is more abundant, cheaper and less toxic than other Au, Cu and Ru catalysts previously reported for similar transformations.
The Possible Time and Region of Host Switches of Ancient Malaria Parasites with Reference to the Pliocene–Quaternary Archaeological Sites in Africa
Authors: Trájer Attila J.
Published: July 2022

About 96% of all malaria deaths occur in Africa, and the malignant falciparum malaria also originated on the continent. Although falciparum malaria only appeared in the Holocene period, it can be hypothesized that the transfer of malaria parasites from other primates to humans occurred several times in history parallel to human evolution. This study develops the model that examines the possible coexistence of the potential original host apes, human ancestors, and the diverse anopheline mosquito species; and how, where, and when the host switch of these parasites from great apes to humans occurred. Based on the Pliocene-early Pleistocene archaeological sites, it was found that certain early hominin populations could have lived in malaria areas where the anopheline mosquito fauna was moderately diverse. The people of the Lupemban Culture, as well as the Greenlandian and Northgrippian human populations of East and West-Central Africa, lived close to the high diversity of anopheline fauna and the territories of such great apes as Gorilla gorrilla. African mid-Holocene cultures likely came in contact with gorilla populations — the original hosts of Plasmodium falciparum — along the coasts of the Gulf of Guinea and the East African Rift Valley during their migration to southern Africa. The host switch of the ancestor of the falciparum malaria parasite likely occurred in these regions.
Evaluating conversational recommender systems
Authors: Jannach Dietmar
Published: July 2022

Conversational recommender systems aim to interactively support online users in their information search and decision-making processes in an intuitive way. With the latest advances in voice-controlled devices, natural language processing, and AI in general, such systems received increased attention in recent years. Technically, conversational recommenders are usually complex multi-component applications and often consist of multiple machine learning models and a natural language user interface. Evaluating such a complex system in a holistic way can therefore be challenging, as it requires (i) the assessment of the quality of the different learning components, and (ii) the quality perception of the system as a whole by users. Thus, a mixed methods approach is often required, which may combine objective (computational) and subjective (perception-oriented) evaluation techniques. In this paper, we review common evaluation approaches for conversational recommender systems, identify possible limitations, and outline future directions towards more holistic evaluation practices.
A review of nonlinear piezoelectric energy harvesting interface circuits in discrete components
Authors: Zhang Bin , Liu Hongsheng , Zhou Shengxi , Gao Jun
Published: July 2022

Piezoelectric energy harvesting is considered as an ideal power resource for low-power consumption gadgets in vibrational environments. The energy extraction efficiency depends highly on the interface circuit, and should be highly improved to meet the power requirements. The nonlinear interface circuits in discrete components have been extensively explored and developed with the advantages of easy implementation, stable operation, high efficiency, and low cost. This paper reviews the state-of-the-art progress of nonlinear piezoelectric energy harvesting interface circuits in discrete components. First, the working principles and the advantages/disadvantages of four classical interface circuits are described. Then, the improved circuits based on the four typical circuits and other types of circuits are introduced in detail, and the advantages/disadvantages, output power, efficiency, energy consumption, and practicability of these circuits are analyzed. Finally, the future development trends of nonlinear piezoelectric energy harvesting circuits, e.g., self-powered extraction, low-power consumption, and broadband characteristic, are predicted.
A brief review of metamaterials for opening low-frequency band gaps
Authors: Wang Kai , Zhou Jiaxi , Tan Dongguo , Li Zeyi , Lin Qida , Xu Daolin
Published: July 2022

Metamaterials are an emerging type of man-made material capable of obtaining some extraordinary properties that cannot be realized by naturally occurring materials. Due to tremendous application foregrounds in wave manipulations, metamaterials have gained more and more attraction. Especially, developing research interest of low-frequency vibration attenuation using metamaterials has emerged in the past decades. To better understand the fundamental principle of opening low-frequency (below 100 Hz) band gaps, a general view on the existing literature related to low-frequency band gaps is presented. In this review, some methods for fulfilling low-frequency band gaps are firstly categorized and detailed, and then several strategies for tuning the low-frequency band gaps are summarized. Finally, the potential applications of this type of metamaterial are briefly listed. This review is expected to provide some inspirations for realizing and tuning the low-frequency band gaps by means of summarizing the related literature.
Long-term changes in bryophyte diversity of central European managed forests depending on site environmental features
Authors: Cacciatori Cecilia , Czerepko Janusz , Lech Paweł
Published: July 2022

Cryptogamic diversity is a reliable indicator of the state of forest ecosystems. In this study we analysed the variations in both bryophyte species richness overall and number of hemerophobic bryophyte species in Central European managed forests over a 20-year time span, based on data collected in 132 plots scattered across Poland. We tested differences in species richness among five temporal replicates, as well as among site types grouped based on elevation a.s.l., dominant tree species and stand age. The analyses revealed no significant trend in species richness across years. Meanwhile, species richness significantly increased along with elevation a.s.l., especially in broadleaved forests. No significant difference in species number between spruce and pine dominated stands emerged for mature stands, while there was a strong difference for young stands, with spruce forest hosting a much higher number of species. Species richness exhibited a slight, but not significant, increase over time in broadleaved forests, no significant variations in pine dominated stands and significant fluctuations in spruce dominated stands, yet without a significant trend. Out of the tested drivers, dominant tree species exhibited the strongest impact on species community composition. Number of hemerophobic and strongly hemerophobic species did not undergo significant variations across years either. The lack of bryophyte diversity trends highlighted in this study suggests Central European managed forests are in an equilibrium sate, maintained by the opposing effects of climate changes, on one side and of more sustainable forest management and pollutant deposition decline, from the other.
Prediction of the minimum effective size of a population viable in the long term
Authors: Pérez-Pereira Noelia , Wang Jinliang , Quesada Humberto , Caballero Armando
Published: July 2022

The establishment of the minimum size for a viable population (MVP) has been used as a guidance in conservation practice to determine the extinction risks of populations and species. A consensus MVP rule of 50/500 individuals has been attained, according to which a minimum effective population size of Ne = 50 is needed to avoid extinction due to inbreeding depression in the short term, and of Ne = 500 to survive in the long term. However, the large inbreeding loads (B) usually found in nature, as well as the consideration of selection affecting genetic diversity, have led to a suggestion that those numbers should be doubled (100/1000). Purging of deleterious mutations can also be a main factor affecting the suggested rules. In a previous simulation study, the reduction of B by the action of purging pointed towards an MVP intermediate between the two rules for short term survival. Here, we focused on the consequences of purging in the establishment of MVPs for long term survival. We performed computer simulations of populations under the action of purging, drift, new mutation, and environmental effects on fitness to investigate the extinction times and the loss of genetic diversity for a range of effective population sizes. Our results indicate that purging can reduce the MVP needed for a population to persist in the long term, with estimates close to Ne = 500 for species with moderately large reproductive rates. However, MVP values appear to be of at least Ne = 1000 when the species´ reproductive rates are low.
Functional localization of audiovisual speech using near infrared spectroscopy
Authors: Butera Iliza M. , Larson Eric D. , DeFreese Andrea J. , Lee Adrian KC , Gifford René H. , Wallace Mark T.
Published: July 2022

Visual cues are especially vital for hearing impaired individuals such as cochlear implant (CI) users to understand speech in noise. Functional Near Infrared Spectroscopy (fNIRS) is a light-based imaging technology that is ideally suited for measuring the brain activity of CI users due to its compatibility with both the ferromagnetic and electrical components of these implants. In a preliminary step toward better elucidating the behavioral and neural correlates of audiovisual (AV) speech integration in CI users, we designed a speech-in-noise task and measured the extent to which 24 normal hearing individuals could integrate the audio of spoken monosyllabic words with the corresponding visual signals of a female speaker. In our behavioral task, we found that audiovisual pairings provided average improvements of 103% and 197% over auditory-alone listening conditions in −6 and −9 dB signal-to-noise ratios consisting of multi-talker background noise. In an fNIRS task using similar stimuli, we measured activity during auditory-only listening, visual-only lipreading, and AV listening conditions. We identified cortical activity in all three conditions over regions of middle and superior temporal cortex typically associated with speech processing and audiovisual integration. In addition, three channels active during the lipreading condition showed uncorrected correlations associated with behavioral measures of audiovisual gain as well as with the McGurk effect. Further work focusing primarily on the regions of interest identified in this study could test how AV speech integration may differ for CI users who rely on this mechanism for daily communication.
National attribution of historical climate damages
Authors: Callahan Christopher W. , Mankin Justin S.
Published: July 2022

Quantifying which nations are culpable for the economic impacts of anthropogenic warming is central to informing climate litigation and restitution claims for climate damages. However, for countries seeking legal redress, the magnitude of economic losses from warming attributable to individual emitters is not known, undermining their standing for climate liability claims. Uncertainties compound at each step from emissions to global greenhouse gas (GHG) concentrations, GHG concentrations to global temperature changes, global temperature changes to country-level temperature changes, and country-level temperature changes to economic losses, providing emitters with plausible deniability for damage claims. Here we lift that veil of deniability, combining historical data with climate models of varying complexity in an integrated framework to quantify each nation’s culpability for historical temperature-driven income changes in every other country. We find that the top five emitters (the United States, China, Russia, Brazil, and India) have collectively caused US$6 trillion in income losses from warming since 1990, comparable to 11% of annual global gross domestic product; many other countries are responsible for billions in losses. Yet the distribution of warming impacts from emitters is highly unequal: high-income, high-emitting countries have benefited themselves while harming low-income, low-emitting countries, emphasizing the inequities embedded in the causes and consequences of historical warming. By linking individual emitters to country-level income losses from warming, our results provide critical insight into climate liability and national accountability for climate policy.