bluuebunny/crossref_metadata_2025_split huggingface dataset:
Beat Bad Microbes
Authors: Walker Sue , Halai Manjula , Warner Rachel , Bravo Josefina 
Published: March 2021

Abstract
Health-related information design has made a difference to people’s lives through clear explanation of procedures,
processes, disease prevention and maintenance. This paper provides an example of user-centered design being applied to engage
people with the prevention of drug-resistant infection. In particular, we focus on antibiotic resistance in the specific location
of a community pharmacy in Rwanda. We describe an information campaign, Beat Bad Microbes, and summarize the challenges and
opportunities of working in Rwanda on a cross-disciplinary project in which design research and practice are closely
integrated.
Super-resolution ultrasound localization microscopy based on a high frame-rate clinical ultrasound scanner: an in-human feasibility study
Authors: Huang Chengwu , Zhang Wei , Gong Ping , Lok U-Wai , Tang Shanshan , Yin Tinghui , Zhang Xirui , Zhu Lei , Sang Maodong , Song Pengfei , Zheng Rongqin , Chen Shigao 
Published: March 2021

Abstract
Non-invasive detection of microvascular alterations in deep tissues in vivo provides critical information for clinical diagnosis and evaluation of a broad-spectrum of pathologies. Recently, the emergence of super-resolution ultrasound localization microscopy (ULM) offers new possibilities for clinical imaging of microvasculature at capillary level. Currently, the clinical utility of ULM on clinical ultrasound scanners is hindered by the technical limitations, such as long data acquisition time, high microbubble (MB) concentration, and compromised tracking performance associated with low imaging frame-rate. Here we present a robust in-human ULM on a high frame-rate (HFR) clinical ultrasound scanner to achieve super-resolution microvessel imaging using a short acquisition time (<10 s). Ultrasound MB data were acquired from different human tissues, including a healthy liver and a diseased liver with acute-on-chronic liver failure, a kidney, a pancreatic tumor, and a breast mass using an HFR clinical scanner. By leveraging the HFR and advanced processing techniques including sub-pixel motion registration, MB signal separation, and Kalman filter-based tracking, MBs can be robustly localized and tracked for ULM under the circumstances of relatively high MB concentration associated with standard clinical MB administration and limited data acquisition time in humans. Subtle morphological and hemodynamic information in microvasculature were shown based on data acquired with single breath-hold and free-hand scanning. Compared with contrast-enhanced power Doppler generated based on the same MB dataset, ULM showed a 5.7-fold resolution improvement in a vessel based on a linear transducer, and provided a wide-range blood flow speed measurement that is Doppler angle-independent. Microvasculatures with complex hemodynamics can be well-differentiated at super-resolution in both normal and pathological tissues. This preliminary study implemented the ultrafast in-human ULM in various human tissues based on a clinical scanner that supports HFR imaging, indicating the potentials of the technique for various clinical applications. However, rigorous validation of the technique in imaging human microvasculature (especially for those tiny vessel structure), preferably with a gold standard, is still required.
BCI learning induces core-periphery reorganization in M/EEG multiplex brain networks
Authors: Corsi M-C , Chavez M , Schwartz D , George N , Hugueville L , Kahn A E , Dupont S , Bassett D S , De Vico Fallani F 
Published: March 2021

Abstract

Objective. Brain–computer interfaces (BCIs) constitute a promising tool for communication and control. However, mastering non-invasive closed-loop systems remains a learned skill that is difficult to develop for a non-negligible proportion of users. The involved learning process induces neural changes associated with a brain network reorganization that remains poorly understood. Approach. To address this inter-subject variability, we adopted a multilayer approach to integrate brain network properties from electroencephalographic and magnetoencephalographic data resulting from a four-session BCI training program followed by a group of healthy subjects. Our method gives access to the contribution of each layer to multilayer network that tends to be equal with time. Main results. We show that regardless the chosen modality, a progressive increase in the integration of somatosensory areas in the α band was paralleled by a decrease of the integration of visual processing and working memory areas in the β band. Notably, only brain network properties in multilayer network correlated with future BCI scores in the α
2 band: positively in somatosensory and decision-making related areas and negatively in associative areas. Significance. Our findings cast new light on neural processes underlying BCI training. Integrating multimodal brain network properties provides new information that correlates with behavioral performance and could be considered as a potential marker of BCI learning.
Enhancing the accuracy of a data-driven reconstruction of bivariate jump-diffusion models with corrections for higher orders of the sampling interval
Authors: Aslim Esra , Rings Thorsten , Zabawa Lina , Lehnertz Klaus 
Published: March 2021

Abstract
We evaluate the significance of a recently proposed bivariate jump-diffusion model for a data-driven characterization of interactions between complex dynamical systems. For various coupled and non-coupled jump-diffusion processes, we find that the inevitably finite sampling interval of time-series data negatively affects the reconstruction accuracy of higher-order conditional moments that are required to reconstruct the underlying jump-diffusion equations. We derive correction terms for conditional moments in higher orders of the sampling interval and demonstrate their suitability to strongly enhance the data-driven reconstruction accuracy.
Talking about the Application Analysis of Electronic Information Technology in the Internet of Things
Authors: Ye Jingjing 
Published: March 2021

Abstract
With the advent of information and intelligence era, electronic information technology has been rapidly developed and widely used. In the era of the Internet of Things, electronic information technology will continue to play an important role. This article will verify the integration of electronic information technology and the Internet of Things by exploring the application of electronic information technology in the Internet of Things. The integration of electronic information technology and the Internet of Things realizes the interconnection of people and people, things and things, people and things, satisfies people’s needs for information transmission of goods, and provides great convenience for people’s daily work.
Research on The Application of Ceramic 3D Printing Technology
Authors: Zhao Bin 
Published: March 2021

Abstract
Ceramic 3D printing technology is using computer aid design techniques to model and produce ceramic products. The basic principle is through X, Y, Z axis of the ceramic 3D printer displacement layer to create the computer-designed 3D ceramic shape, and combined with traditional pottery hand-made techniques to finally complete it. Analysis and utilize the advantages of ceramic 3D printing technology, in order to inject new vitality into the traditional ceramic production industry.
Low-latency resource elements scheduling based on deep reinforcement learning model for UAV video in 5G network
Authors: Jiang Jilian , Qiu Yuhe , Su Yu , Zhou Jian 
Published: March 2021

Abstract
We consider the problem of resource elements allocation in a network environment with multiple users. Previous studies have done a lot of works using traditional methods in terms of bandwidth allocation, which is sufficient to serve for 4G network. However, it cannot be neglected to provide more efficient and intelligent scheduling policies in haste, due to growing demands on high resolution video and image transmission in 5G network. To fit the condition taking resource elements as scheduling unit in 5G network, we proposed deep Q network (DQN) algorithm based on the requirement of low time latency and high resource utilization rate to solve resource elements (RE) scheduling problem. Ultimately, we give out the optimal allocation scheme of resource elements (RE) for four users in fixed condition of time latency and resource utilization rate.
Research on the Influencing Factors of Manufacturing Transformation and Upgrading Based on Grounded Theory
Authors: Shuili Yang , Xiang Lv , Yi Yang 
Published: March 2021

Abstract
Under the background of China’s economy gradually entering the new normal, transformation and upgrading has become the only way for manufacturing industry to improve market competitiveness and sustainable development. In order to promote the transformation and upgrading of manufacturing enterprises, this paper takes 96 literatures on the influencing factors of the transformation and upgrading of manufacturing industry as the research object, and conducts a systematic study based on the grounded theory. Through the collection, collation and coding of literature, many categories are formed. After analysis, it is concluded that the influencing factors of the transformation and upgrading of manufacturing industry include five aspects, namely, the willingness of transformation and upgrading, the ability of transformation and upgrading, the environment of transformation and upgrading, the resources of transformation and upgrading and the development trend. Among them, the willingness and the ability of transformation and upgrading belong to the subjective category. Technological innovation ability is the most important factor affecting the transformation and upgrading of manufacturing industry. Accordingly, this paper puts forward relevant strategies and suggestions to promote the transformation and upgrading of manufacturing industry.
Research on the Relationship between Motivation and Innovation Performance of Knowledge Workers Based on Computer Algorithms
Authors: Sun Weixing 
Published: March 2021

Abstract
For many enterprises, knowledge workers have become an important human resource. As the human capital that can add value, the management of knowledge employees has become an important issue of concern for enterprises. At present, there are still some problems in the incentive research of knowledge workers in China, such as the incomplete research object, the relatively single industry, the lack of pertinence and operability of the research content, the lack of tools and methods to measure the incentive effect of knowledge workers. In the management practice, the incentive of knowledge employees is mainly based on salary, with little attention paid to other incentive measures, the enterprise’s understanding of it is not deep enough, the incentive mechanism is not sound, the incentive effect is not significant and other problems need to be solved.
Experimental investigation of the performance of a thermoelectric generator at various operating conditions
Authors: Gao H B , Zong S C , Zhang C W , Li H J , Huang G H 
Published: March 2021

Abstract
Thermoelectric generators (TEG) is the device that can directly convert heat into electricity by the Seebeck effect, which is fascinated for waste heat recovery. An experiment was setup to study the influence of heat flux through the thermoelectric module on the power output and efficiency of a commercial Bi2Te3-based thermoelectric modules. The experimental result indicated that the power output evidently increased with the increasing heat flux through the thermoelectric module (TEM), while the conversion efficiency increased significantly at first then the tendency became mild with the increasing heat flux for a given air flow velocity and flow temperature. The temperature differences across the thermoelectric module are almost identical with various air velocity, while the power output and efficiency increased with the increase of cooling flow velocity with a fixed heat flux through the TEM. The power output and efficiency almost linearly decreased with the increase of cooling flow temperature with a fixed heat flux through the TEM and a fixed cooling flow velocity. The maximum output power can be obtained by maximization heat flux without exceeding the upper temperature limit of thermoelectric module.
Key Variable Screening Method for Complex Industry System Based on Muti-source Monitoring Data
Authors: Wang Wei , Xie Juntai , Gao Zhiyong , Chen Xiangpeng 
Published: March 2021

Abstract
Aiming at the problem that the value density of variables in the state-aware network of complex industry system is low, which leads to poor timeliness of state evaluation, a key variable screening method for state-aware network is proposed. Firstly, a causal network model that can accurately reflect the interaction mode between the monitoring variables of the system is established. Secondly, each node of the causal network can be ranked by the LeaderRank algorithm and the variable set can be divided into multiple sets of variables. Finally, each variable set can be used to evaluate the performance state of the system, and the effectiveness index of variable screening is constructed to evaluate the accuracy and timeliness of the evaluation results of each variable set, then the key variables can be obtained. The Tennessee Eastman (TE) process data is used to test the proposed method, the result shows that the key variables obtained by the method can effectively improve the evaluation efficiency of the performance state.
A new toxic and harmful gas analyzer based on DOAS technology
Authors: Yuan Zhengyang , Zhou Jiayong , Qian Xinyan , Wang Shizhong , Zhao Juntao , Shi Hongqi 
Published: March 2021

Abstract
This paper introduces a new type of toxic and harmful gas analyzer based on DOAS (differential optical absorption spectroscopy) technology. Combined with the least square method, it can monitor H2S, NH3, SO2, NO2 and CH3SH online at the same time, and the prescribed minimum is as low as 0.1ppb, the detection breadth and accuracy are higher than those of the current common DOAS instruments.
Dark matter searches using accelerometer-based networks
Authors: Figueroa Nataniel L , Budker Dmitry , Rasel Ernst M 
Published: March 2021

Abstract
Dark matter (DM) is one of the biggest open questions in physics today. It is known that it interacts gravitationally with luminous matter, so accelerometer-based searches are inherently interesting. In this article we present recent (and future) searches for DM candidates such as feebly interacting matter trapped inside the Earth, scalar-matter domain walls and axion quark nuggets, with accelerometer networks and give an outlook of how new atomic-interferometry-based accelerometer networks could support DM searches.
Observation of high contrast ratio asymmetric transmission for linearly and circularly polarized waves
Authors: Wu Xiaohu 
Published: March 2021

Abstract
Asymmetric transmission of light has important applications in integrated photonic systems for communications and information processing. Various Lorentz-reciprocal devices have been explored to achieve asymmetric transmission. However, the contrast ratio is limited. Here we show that the asymmetric transmission of linearly polarized and circularly polarized waves can both be achieved by combining polarization conversion and selective transmission. What is perhaps most important here is that the proposed asymmetric transmission devices for operation at wavelength 633 nm experimentally display asymmetric transmission with contrast ratio exceeding 37 dB and 34 dB for linearly polarized wave and circularly polarized wave, respectively. The high contrast ratios are much higher than previous results in published literature. The proposed reciprocal approach holds promising for utilization in integrated photonic systems.
Impact of microstructures and viscous liquid loading on electromechanical coupling factor and surface wave transference in a prestressed piezoelectric smart material layered structure
Authors: Sharma Vanita , Kumar Satish 
Published: March 2021

Abstract
The electromechanical coupling factor (K
2) is a key parameter in acoustic devices that acquaints the affect of piezoelectricity on the phase velocity of elastic waves. For conventional engineering applications, greater electromechanical coupling factor (K
2) are expected in surface acoustic wave (SAW) devices. This present study investigates the impact of microstructures and viscous liquid loading on transference of Love-type surface wave in a prestressed piezoelectric smart material layered structure. A micropolar material as substrate is employed for capturing the microstructural influence. The study involves the extraction of dispersion equations for both electrically open and short conditions depicting explicitly the effects of viscosity and density of viscous liquid, microstructural parameters of the substrate, electromechanical coupling factor and material parameters of the prestressed piezoelectric layer. Some particular cases of the problem are derived and the obtained results are matched with the classical Love wave equation. PZT − 5H ceramic material as piezoelectric material and Aluminium-Epoxy as micropolar material, are considered for the investigation. The present study is meaningful in intensifying the performance of chemical and biochemical sensors working in a liquid environment.
79 Relationship Between Depression and Nutritional Status Among the Elderly Attending Selected Primary Healthcare Centers in Lagos
Authors: Akodu B A , Akinwunmi S O , Onajole A 
Published: March 2021

Abstract

Introduction
Depression causes and worsens malnutrition. The prevalence of malnutrition in the elderly of the developed world was about 22.6% and about 40% of hospitalized elderly are malnourished while about 4.8% have one major depressive episode in people aged 50 and above. Food rich in omega-3 has antidepressant effect and its low intake is linked with dementia. Decrease dietary folate has been linked with depression. This study was aimed at determining the relationship between depression and nutritional status among the elderly in selected primary healthcare centers (PHC) in Lagos Nigeria.

Method
A descriptive cross-sectional study was conducted using multi-stage technique to select 219 participants by systematic sampling method from the selected PHC centers. Data was collected using structured interviewer-administered questionnaires. Nutritional status and Depression were assessed using Mini-Nutritional Assessment and Geriatric Depression Scale respectively. Data analysis was carried out using Epi-info 7.1. Associations were tested using Chi-square for categorical variables while t-test and analysis of variance were used for continuous variables. Associations were statistically significant if two-tailed probability was less than 5% (0.05).

Results
It was found that 57.9% and 47.1% were malnourished and depressed respectively. There was a statistically significant association between the sex of the participants and the nutritional status (p = 0.048). Statistically significant association existed between sex (p = 0.024), marital status (p = &lt;0.001), educational qualification and depression. Statistically significant association between monthly income (p = &lt;0.001), living arrangement (p = 0.002) and depression was demonstrated. There was a statistically significant association between family support (p = &lt;0.001), nutritional status (p = &lt;0.001) and depression. There was statistically significant difference between the height (p = 0.00885), weight (p = 0.00052, waist-hip ratio (p = 0.036) and the nutritional status. Remarkably, there was statistically significant difference between the waist (p = 0.023) and hip circumference (p = 0.047) and their level of depression.

Conclusion
A high prevalence of poor nutritional status and depression existed among the elderly primary healthcare centers.
Prediction of cognitive response to surgery in elderly patients with primary hyperparathyroidism
Authors: Koman A , Bränström R , Pernow Y , Bränström R , Nilsson I -L 
Published: March 2021

Abstract

Background
Primary hyperparathyroidism (pHPT) can be associated with potentially reversible cognitive impairment, which is occasionally mistaken for natural ageing and dementia. The aim was to evaluate short-term medical normalization of hypercalcaemia in surgical decision-making for elderly patients with mild cognitive deficiency.

Methods
Patients with pHPT were included in a prospective observational study. A test panel including the Montreal Cognitive Assessment (MoCA) and validated tools for estimation of psychological status (Hospital Anxiety and Depression Scale, HADS), and muscle strength (timed-stands test, TST) was applied at baseline, after 4 weeks of calcimimetic treatment, and after parathyroidectomy. Mild cognitive impairment was defined by a MoCA score below 26. A longitudinal increase in MoCA score of at least 2 points 6 months after surgery was considered clinically meaningful.

Results
Of 110 patients who underwent testing, 35 aged 50 years or more were identified to have mild cognitive dysfunction, including 19 who were aged at least 70 years (median MoCA score 23, i.q.r. 21–24). Calcimimetic treatment resulted in normalization of calcium levels, and improvements in MoCA and HADS scores, and TST time. Normal MoCA scores (at least 26) were reached in 17 patients by 6 months after surgery, of whom 10 were aged 70 years or older. Long-term increase in MoCA score correlated with the decrease in ionized calcium concentration (r = –0.536, P = 0.022). Baseline calcium concentration and improvement in MoCA with calcimimetic treatment were identified as independent predictors of favourable outcome after parathyroidectomy.

Conclusion
Medical normalization of hypercalcaemia can aid in predicting outcome after parathyroidectomy.
Take my breath away: studying pathogen invasion of the human lung using primary tissue models
Authors: L. Dragan Amanda , E. Voth Daniel 
Published: March 2021

ABSTRACT
The human pulmonary environment is complex, containing a matrix of cells, including fibroblasts, epithelial cells, interstitial macrophages, alveolar macrophages and neutrophils. When confronted with foreign material or invading pathogens, these cells mount a robust response. Nevertheless, many bacterial pathogens with an intracellular lifecycle stage exploit this environment for replication and survival. These include, but are not limited to, Coxiella burnetii, Legionella pneumophila, Yersinia pestis, Mycobacterium tuberculosis and Staphylococcus aureus. Currently, few human disease-relevant model systems exist for studying host–pathogen interactions during these bacterial infections in the lung. Here, we present two novel infection platforms, human alveolar macrophages (hAMs) and human precision-cut lung slices (hPCLS), along with an up-to-date synopsis of research using said models. Additionally, alternative uses for these systems in the absence of pathogen involvement are presented, such as tissue banking and further characterization of the human lung environment. Overall, hAMs and hPCLS allow novel human disease-relevant investigations that other models, such as cell lines and animal models, cannot completely provide.