bluuebunny/crossref_metadata_2025_split huggingface dataset:
COVID-19 and Diabetic Nephropathy
Authors: Maremonti Francesca , Locke Sophie , Tonnus Wulf , Beer Kristina , Brucker Anne , Gonzalez Nadia Zamora , Latk Marcus , Belavgeni Alexia , Hoppenz Paul , Hugo Christian , Linkermann Andreas 
Published: April 2022

AbstractDiabetic nephropathy is the most common condition that requires a chronic renal
replacement therapy, such as hemodialysis, peritoneal dialysis, kidney
transplantation, or simultaneous kidney-pancreas transplantation. Chronic kidney
disease progression, that is the loss of nephrons, which causes the continuous
decline of the eGFR, underlies the pathogenesis of diabetic nephropathy. During
the COVID-19 pandemic, it became clear that diabetic nephropathy is amongst the
independent risk factors that predicts unfavourable outcome upon SARS-CoV2
infection. While we still lack conclusive mechanistic insights into how nephrons
are rapidly lost upon SARS-CoV2 infection and why patients with diabetic
nephropathy are more susceptible to severe outcomes upon SARS-CoV2 infection,
here, we discuss several aspects of the interface of COVID-19 with diabetic
nephropathy. We identify the shortage of reliable rodent models of diabetic
nephropathy, limited treatment options for human diabetic nephropathy and the
lack of knowledge about virus-induced signalling pathways of regulated necrosis,
such as necroptosis, as key factors that explain our failure to understand this
system. Finally, we focus on immunosuppressed patients and discuss vaccination
efficacy in these and diabetic patients. We conclude that more basic science and
mechanistic understanding will be required both in diabetic nephropathy as well
as in host immune responses to the SARS-CoV2 virus if novel therapeutic
strategies are desired.
Copper-Catalyzed Direct C(sp2)–H Sulfuration of Aryl Alkenes by Using Tetraalkylthiuram Disulfides for the Synthesis of Alkenyl Dithiocarbamates
Authors: Zhang Zhipeng , Jiao Jing 
Published: April 2022

AbstractCopper-catalyzed direct C(sp2)–H sulfuration of aryl alkenes by using tetraalkylthiuram disulfides as sulfuration reagents has been developed. The reaction provides an efficient method for the synthesis of a variety of alkenyl dithiocarbamates, which are important structure motifs widely applied in materials, pharmaceuticals, and agrochemicals.
An Efficient One-Pot Synthesis of 5-Sulfanyl-1-[2-(vinyloxy)ethyl]-1H-pyrrol-2-amines as Precursors of 1-Vinylpyrroles
Authors: Nedolya Nina A. , Trofimov Boris A. , Tarasova Olga A. , Albanov Alexander I. 
Published: April 2022

AbstractSequential processing of monolithiated tertiary propargylamines with 2-(vinyloxy)ethyl isothiocyanate and t-BuOK–DMSO results in the introduction of a highly reactive 2-(vinyloxy)ethyl group at the position 1 of the pyrrole ring thus formed. In this way, a series of new 5-sulfanyl-1-[2-(vinyloxy)ethyl]-1H-pyrrol-2-amines were obtained in a yield of up to 92%. The latter in the presence of t-BuOK–DMSO system (110–120 °C, 10–15 min) eliminates vinyl alcohol to give rare-functionalized 1-vinylpyrroles, namely 5-sulfanyl-1-vinyl-1H-pyrrol-2-amines, inaccessible by the known methods.
Dichlorination of β-Keto Esters and 1,3-Diketones Mediated by Oxone/Aluminum Trichloride Mixture in Aqueous Medium
Authors: Smonou Ioulia , Giannopoulos Vasileios , Katsoulakis Nikolaos 
Published: April 2022

AbstractA new method for the α,α-dichlorination of β-keto esters using Oxone/aluminum trichloride mixture in aqueous medium has been developed. This useful process has also been applied successfully for the dichlorination of 1,3-diketones. The dichlorinated compounds have been produced in one step, high yields, and short reaction times.
An Exploratory Study of Allied Health Students' Experiences of Electronic Medical Records During Placements
Authors: Baysari Melissa Therese , Wells Jacqueline , Ekpo Ernest , Makeham Meredith , Penm Jonathan , Alexander Nathaniel , Holden Alexander , Ubeja Raj , McAllister Sue 
Published: April 2022

Abstract
Background Allowing students to access and document in electronic medical records (eMRs) during clinical placements is viewed as critical for ensuring that graduates have a high level of digital proficiency prior to entering the workforce. Limited studies have explored student access to eMRs in health disciplines outside of medicine and nursing.
Objective Our main objective was to examine allied health students' experiences and perceptions of the opportunity to develop eMR competencies during their placement, across a range of allied health disciplines and placement settings.
Methods An explanatory sequential design was used, comprising a quantitative survey (n = 102) followed by qualitative semi-structured interviews (n = 6) with senior allied health students to explore their experiences and perceptions of eMR access during placements.
Results Of the 93 students who responded to the question about their placement eMR, nine (10%) reported their placement site did not use an eMR and four students reported that they were not allowed to access the eMR during their placement. Most students (64%, 54 out of 84) accessed the system using their own credentials, but 31% (26 out of 84) used someone else's log-in and password. Students were satisfied with the eMR training and support received while on placement, but there was significant variability across sites on the level of training and support provided. All students believed that eMR access was beneficial for learning and preparation for work, improved delivery of care, taking ownership of work, and feeling responsible for patient care.
Conclusion Providing students with access to eMRs during placements is fundamental to the development of a student's professional identity and to recognizing their role in the delivery of interprofessional patient care. For graduates to be equipped to effectively contribute to multi-disciplinary care in a digital health environment, universities need to work with practice partners to standardize and formalize eMR access, registration, training, and support, and to provide students with early exposure and training on eMRs in university courses.
Going beyond the AHA! moment: insight discovery for transdisciplinary research and learning
Authors: Pearce BinBin J. , Deutsch Lisa , Fry Patricia , Marafatto Francesco Femi , Lieu Jenny 
Published: April 2022

AbstractIn this paper, we develop and apply the concept of ‘insight discovery’ as a key competence for transdisciplinary research and learning. To address complex societal and environmental problems facing the world today, a particular expertise that can identify new connections between diverse knowledge fields is needed in order to integrate diverse perspectives from a wide range of stakeholders and develop novel solutions. The capacity for “insight discovery” means becoming aware of personal mental representations of the world and being able to shape and integrate perspectives different from one’s own. Based on experiences and empirical observations within the scope of an educational programme for Masters students, PhD candidates and post-doctoral researchers, we suggest that insights are the outcome of a learning process influenced by the collective and environment in which they are conceived, rather than instant moments of individual brilliance. The process which we describe, named the insight discovery process (IDP), is made up of five aspects. Within a group setting, a person begins with an “original mental model”, experiences an “insight trigger”, processes new information within the “liminal space”, “formulates an insight” and eventually forms an “adapted mental model”. There is a potential for incorporating such process as a fundamental competence for transdisciplinary curricula in undergraduate and graduate programmes by cultivating specific practices and safe learning environments, focused on the enquiry, exchange and integration of diverse perspectives.
Translating citizen-generated air quality data into evidence for shaping policy
Authors: Mahajan Sachit , Chung Ming-Kuang , Martinez Jenny , Olaya Yris , Helbing Dirk , Chen Ling-Jyh 
Published: April 2022

AbstractThe practice of participatory sensing for environment monitoring has rapidly evolved over the years. There has been a steady growth of citizen-based air quality monitoring projects that aim to build partnerships, knowledge-sharing platforms, awareness, and ultimately resilience to issues related to air quality. Whilst citizen science has reshaped air quality research by bringing a fresh perspective on democratizing science for the public good, there is little research about how citizen-generated data can be used for facilitating and improving evidence-based policymaking. To address the problem in a structured manner, we examine the existing literature related to citizen science, air quality, and policymaking to understand the existing gaps and opportunities. That is followed by a review of major grassroots and collaborative citizen science air quality monitoring initiatives in Asia, Africa, Europe, and Latin America. We explore the range of citizen science methods and applications to understand how they are creating opportunities for dialog between practitioners and policymakers, discuss the concerns about citizen-generated data, and see if the data is used for policy action. Finally, we propose a methodology for integrating data-based evidence into shaping policy. The methodology combines scientific evidence, participation, and deliberation to realize the full potential of citizen science in air quality monitoring.
Spatial heterogeneity of the seed bank at a peat lake in Australia
Authors: Ling Joanne E. , Wen Li , Ellis Ben , Krogh Martin 
Published: April 2022

Context In the face of global biodiversity decline, understanding the effects of potential climate change on the persistence of soil seed banks is critical, especially in wetland ecosystems. Although studies have explored the response of soil seed banks to changes in periodically inundated wetlands, little is understood about seed banks in peatlands. Aims We examined the spatial variability of soil seed banks during a recent drying event, the last of which occurred over 60 years ago. Methods We sampled the soil seed bank in three zones away from the centre of the dry lakebed at five depth intervals down to 50 cm. Key results Our study showed that the seed bank distribution in a peatland reflected the wetland plants examined at the time of the drying event. The distribution of seeds was along a flood gradient, suggesting an interaction between historical inundation intensity (Zone) and vertical (Depth) distribution of seeds, and correlated with the extant vegetation, as determined during a significant water drawdown period. Conclusions and implications This study shows that the ability of seeds to survive burial, either submerged or desiccated, even after long periods, may prove to have advantages for plant survival and establishment.
Estudio cognitivo e intercultural del eufemismo chino y español de muerte
Authors: Dai Xin 
Published: April 2022

Abstracta
Dadas las características generales e intemporales a nivel universal del tabú de la muerte, este artículo tiene el
objetivo de realizar un análisis contrastivo del eufemismo en chino y español de este tema a través de asociaciones
conceptualizadas de metáfora, metonimia y su interacción. La base teórica en la que se sustenta el estudio deriva del modelo
cognitivo propuesto por Lakoff & Johnson en 1980 en su célebre libro
Metáforas de la vida cotidiana. Construimos diez principales mecanismos comunes y tres específicos
respectivos de proyección conceptual en ambas lenguas respecto a dicho tema. Al final, basándonos en las muestras resultantes,
concluimos con la importancia de las características de la cultura material, la psicológica y la institucional de ambas regiones a
la hora de desarrollar manifestaciones eufemísticas de la muerte.
Corpus-based bilingual terminology extraction in the power engineering domain
Authors: Ivanović Tanja , Stanković Ranka , Todorović Branislava Šandrih , Krstev Cvetana 
Published: April 2022

Abstract
This paper presents the resources and tools used to extract and evaluate bilingual, English-Serbian terminology in
the power engineering domain. The resources consist of existing general and domain lexica, and a domain parallel corpus; tools
include term extractors for both languages and a tool for aligning the segments belonging to corpus sentences. The system was
tested by varying a match function that establishes the presence of an extracted term in an aligned segment (a chunk), ranging
from very loose to strict. The evaluation of results showed that the precision of English term extraction was 92%, Serbian term
extraction 86%, while the precision of bilingual pair extraction was 72% based on the strictest match function. The result of
extraction was 2,684 correct bilingual pairs that enhanced the terminology database and can further be used to support the search
of the power engineering aligned collection stored in a digital library.
Enhancing photon entanglement in a three-mode optomechanical system via imperfect phonon measurements
Authors: Qiu Jing , Chen Dongni , Wang Ying-Dan , Chesi Stefano 
Published: April 2022

Abstract
By considering a 3-mode optomechanical system formed by two cavities interacting with a common mechanical mode, we demonstrate that phonon-counting measurements lead to a significant enhancement of entanglement in the output of the two cavities. This conclusion still holds for an inefficient detector, but the dependence on system parameters changes qualitatively from the ideal limit of perfect projective measurements. We find non-trivial optimal points for the entanglement as functions of detector efficiency, measurement outcome, and optical drive strengths. We characterize both the highest achievable entanglement as well as a ‘typical’ value, obtained at the most likely measurement outcome. Numerical results are well understood within an approximate analytical approach based on perturbation theory around the ideal detector limit.
Angstrom-precise fabrication of surface nanoscale axial photonics (SNAP) microresonators with a flame
Authors: Sumetsky Misha , Vassiliev Victor 
Published: April 2022

Abstract
We demonstrate the fabrication of surface nanoscale axial photonics bottle microresonators with angstrom precision using a flame. We observe strongly unscalable behavior of the whispering gallery mode cutoff wavelengths with different radial quantum numbers along the fibre length.
SOC Estimation of Lithium-ion Battery Based on RLS-EKF for Unmanned Aerial Vehicle
Authors: Zhang Shuaishuai , Tao Hongfei , Bi Kaitao , Yan Wenxu , Ni Hongyu 
Published: April 2022

Abstract
In recent years, in the civil and military unmanned aerial vehicle(UAV) market, the demand for UAV is increasing day by day, the iteration cycle of UAV products is significantly shortened, and UAV has developed rapidly. Among them, lithium battery has the advantages of high energy density, lightweight and bendability. At present, as the main power source of electric UAV, lithium battery affects the range and flight time of UAV, and is the key factor that directly restricts the development and application of UAV. Therefore, accurate estimation of battery state of charge (SOC) has always been the focus and difficulty in the field of UAV battery research. This paper mainly improves the accuracy of SOC estimation of power battery from the following aspects:
First, the significance of researching power batteries is clarified, the advantages of lithium-ion power batteries are pointed out, the definition of SOC and its influencing factors are discussed, and the common methods of battery SOC estimation are more comprehensively introduced and analyzed.
Next, a second-order RC network equivalent circuit model that is convenient for engineering realization is established, and its state-space model is deduced. The SOC-OCV relationship was measured.
Then, the recursive least squares (RLS) method suitable for real-time calculation is used to identify the parameters of the equivalent circuit model of lithium-ion battery on-line, and the parameters of the equivalent circuit model are identified under UDDS conditions, which proves the correctness and rationality of the identification method.
Finally, it is proposed to use the extended Kalman filter (EKF) algorithm to estimate the SOC of the lithium-ion battery, that is, use the EKF algorithm to estimate the open circuit voltage of the battery, and then estimate the battery SOC according to the open circuit voltage method. The accuracy of the joint estimation algorithm to estimate SOC is verified under simulated conditions.
Design of Intelligent Wireless Laser Engraving Machine
Authors: Zhang Yan , Feng Bin , Sang ShengJu 
Published: April 2022

Abstract
The wireless laser engraving machine system is designed by using the wireless data transmission and programming processing ability of MCU esp8266. The browser of computer accesses the micro web server built in MCU through wireless channel to realize real-time control of engraving.
MCU establishes and maintains the Wi-Fi channel for computer connection. The computer browser downloads and runs the HTML5 Web APP stored in MCU flash memory to generate the operation interface. The APP completes the image loading, graying, binarization, thinning, vectorization and other processing. In the browser, the final G-codes are generated and sent back to MCU in real time. The MCU executes G-codes line by line. According to the intention of G-codes, MCU uses linear interpolation algorithm to control stepping motor and PWM to control laser intensity. Finally, the engraving or cutting is completed in a perfect way.
The core hardware circuit requires only one MCU and two driver ICs. So the design is portable, easy to be assembled, precise to be controlled and low cost. And the open software architecture makes it more extensible, compatible and easy to be deployed.
The Detection and Following of Human Legs Based on Feature Optimized HDBSCAN for Mobile Robot
Authors: Liu Penghua , Yao Hanchen , Dai Houde , Fu Wei 
Published: April 2022

Abstract
Accurate target recognition and stable follow in real clutter environment are important tasks for following a random robot. In this paper, a scheme of detecting and tracking human legs using a single lidar is proposed. The HDBSCAN algorithm is optimized by human leg characteristics, and the leg line features are fused on the basis of the density characteristics of the leg laser radar data, and the leg information of the target is clustered and its location is obtained. Based on the relative shift angle of target moving and the lock-in algorithm of tracking distance, the single target detection and tracking in unstructured environment can be realized. The lidar dataset in multiple scenes verifies that the clustering algorithm based on feature optimization improves the accuracy of target legs detection by more than 10% compared with the original algorithm. The scheme performs follow-up experiments on a self-built solid robot. The experimental results show that the robot can achieve accurate and stable human target follow in clutter environment.
Optimal scheduling of electric vehicle aggregators based on sac reinforcement learning
Authors: Yu Fancheng , Lao Penghui 
Published: April 2022

Abstract
Aiming at the optimal scheduling problem of electric vehicle aggregators, a charge change load optimal scheduling strategy based on sac deep reinforcement learning is proposed. The strategy fully considers the users, power system and power market in the process of load regulation, and can realize the friendly interaction between electric vehicle and power system. Based on the establishment of the joint optimal scheduling framework of charging pile and exchange station, considering the multiple temporal and spatial characteristics of optimal scheduling of charging and exchange station, the optimal scheduling model of adjustable charging and exchange load in different scenarios is constructed, and the real-time scheduling scheme of grid connected charging and exchange load is solved based on sac algorithm. An example is given to verify the economy and efficiency of sac algorithm applied to the real-time optimal scheduling of charging and changing load of large-scale electric vehicles.
Multi-sensor fusion of sparse point clouds based on neuralnet works
Authors: Yang Qiming , Liu Fei , Qu Jingjing , Jing Hui , Kuang Bing , Chai Wenjing 
Published: April 2022

Abstract
The fusion of laser point cloud and visual image depends on the point cloud density and the target framing effect, the traditional laser point cloud processing for sparse point cloud clustering effect is poor, it is difficult to frame small objects as well as medium and long distance objects. Then the subsequent sensor fusion is easy to miss the recognition of obstacles. In this paper, we improve the frame selection method for sparse point clouds, firstly build a deep learning framework pointpillar, use pointpillar to frame the sparse laser point clouds, then spatially calibrate the lidar coordinate system and camera coordinate system, project the lidar point clouds to the camera image, improve the late fusion method, effectively use the detection results of single sensor, and finally The late-fusion is performed with the target detection results of the camera image to output the exact distance as well as the category of the target. Experiments show that compared with the recognition effect of the traditional fusion algorithm, the number of frames is increased by 6 and the missed recognition rate is reduced from 31.41% to 12.31%.
Centralized Control System for Smart Street Lights Based on STM32 and LoRa
Authors: Qu Yuanchi , Yang Yanhua , Li Yaoyao 
Published: April 2022

Abstract
In order to solve the problem of waste of power and human resources in the traditional street lamp control system, this paper designs a smart street lamp centralized control system based on STM32 and LoRa technology. The centralized control system consists of a centralized control device and multiple single lamp control devices. The STM32F103 is the MCU of the centralized control device. The system uses the characteristics of low communication cost and long transmission distance of LoRa technology to realize the communication between the centralized control device and the single lamp control device. The centralized control device uses the Modbus RTU protocol to communicate with the sensor module, and adjusts according to environmental factors. The brightness of the street lamp realizes the "on-demand lighting" of the street lamp, and an adaptive rate algorithm is proposed to optimize the communication of the LoRa network and improve the working efficiency of the system. This centralized control system combines embedded and wireless communication technology and has advantages in cost, reliability, energy saving and intelligent control. It can be applied to street lamp lighting control in various environments. It has a high degree of intelligence and has a strong market potential.
Workspace Analysis of Cable-driven Continuum Manipulator with Cable-constrained Synchronous Rotating Mechanism
Authors: Zhou Zhen , Zheng Xudong , Chen Zhang , Wang Xueqian , Liang Bin , Wang Qi 
Published: April 2022

Abstract
In this paper, a cable-driven continuum manipulator with cable-constrained synchronous rotating mechanism (CCSRM) is studied. The purpose of this paper is to give the workspace for the cable-driven continuum manipulator, where the friction effects and the allowable range of cable tension are considered. The problem of solving workspace is transformed into a linear programming problem, which is solved by dual-simplex algorithm. On this basis, the influence of the pre-tightening force of the connecting cable on the workspace is analyzed. In addition, the tension of the motor on each driving cable is optimized to minimize the control error. Finally, the load range that the manipulator can withstand within the workspace is analyzed.