bluuebunny/crossref_metadata_2025_split huggingface dataset:
How to make noncoherent problems more productive: Towards an AMR management plan for low resource livestock sectors
Authors: Butcher Andrea , Cañada Jose A. , Sariola Salla 
Published: November 2021

AbstractGlobal policy for managing antimicrobial resistance (AMR) is underpinned by a standardised and coherent global framework for reducing antibiotic use in clinical health, veterinary health, and food production sectors. Within the framework, problematic antibiotic use (a significant driver of AMR) is treated as a knowledge deficit on the part of users and prescribers, which can be remedied by educating them to make better informed treatment decisions. This narrow approach to AMR management conceals the socioeconomic and material drivers of antibiotic decision-making, creating challenges for low resource regions that rely on antibiotic therapies to manage uncertainty and precarity. Thus, there is a need for a global AMR policy that acknowledges the diversity of sociomaterial arrangements and practices that antibiotics form part of, if their use is to be reduced without undermining productivity or the attainment of poverty reduction indicators. Drawing upon research of antibiotic use in West Africa’s livestock sector, this article analyses the interrelation of antibiotics, AMR action plans, and production management strategies in ecologies of livestock breeding practices. We apply the STS-influenced perspective of noncoherence to analyse how seemingly contradictory practices and institutional logics productively coalesce. We argue that observing noncoherent practices increases our understanding of antibiotic use in relation to local breeding conditions that are frequently not of the producers’ making, whilst drawing attention to context-specific possibilities for improving livestock management capacities and reducing reliance on antibiotic therapies in low-resource settings. The article concludes by calling for an AMR global policy that is more responsive to local specificity rather than enforcing universal standardisation.
An improved study of HCO+ and He system: Interaction potential, collisional relaxation, and pressure broadening
Authors: Tonolo F. , Bizzocchi L. , Melosso M. , Lique F. , Dore L. , Barone V. , Puzzarini C. 
Published: November 2021

In light of its ubiquitous presence in the interstellar gas, the chemistry and reactivity of the HCO+ ion requires special attention. The availability of up-to-date collisional data between this ion and the most abundant perturbing species in the interstellar medium is a critical resource in order to derive reliable values of its molecular abundance from astronomical observations. This work intends to provide improved scattering parameters for the HCO+ and He collisional system. We have tested the accuracy of explicitly correlated coupled-cluster methods for mapping the short- and long-range multi-dimensional potential energy surface of atom–ion systems. A validation of the methodology employed for the calculation of the potential well has been obtained from the comparison with experimentally derived bound-state spectroscopic parameters. Finally, by solving the close-coupling scattering equations, we have derived the pressure broadening and shift coefficients for the first six rotational transitions of HCO+ as well as inelastic state-to-state transition rates up to j = 5 in the 5–100 K temperature interval.
Host genotype structures the microbiome of a globally dispersed marine phytoplankton
Authors: Ahern Olivia M. , Whittaker Kerry A. , Williams Tiffany C. , Hunt Dana E. , Rynearson Tatiana A. 
Published: November 2021

Significance
Microscale interactions between marine phytoplankton and their bacterial microbiomes can influence ecosystem functioning and global biogeochemical cycling through complex exchanges of metabolites and sophisticated ecological processes. Previous investigation of the phytoplankton microbiome has not focused on the role of a host’s underlying genetic background. Through examination of a single phytoplankton species’ microbiome across the global ocean, we found that host genotype strongly influenced microbiome community composition, with associations that potentially persist across generations and ocean basins but assemble rapidly (within days). The long-term association of microbiomes with host genetic background could explain the evolution and maintenance of intricate phytoplankton–bacteria interactions.
Embodied cognition in the booth
Authors: Martín de León Celia , Fernández Santana Alba 
Published: November 2021

AbstractFrom an enactivist perspective, cognition can be described as embodied, since it is determined by our bodily, multisensory, affective interaction with the environment, in particular by our social interaction. In recent years, interpreting has been defined as a multimodal, embodied cognitive activity of inter-lingual mediation, and research on gestures in conference interpreting has found that simultaneous interpreters, although not visible for their audience, do gesture in the booth. However, gestures in interpreting are yet understudied. This paper presents an exploratory, in-depth descriptive study with the aim of generating hypotheses about the cognitive functions of gestures in simultaneous interpreting. To this end, we investigate the different types of gesture that emerge throughout a whole process of simultaneous interpreting, in conjunction with the concurrent speech, the interpreter’s interaction with her environment and her own description of her production of mental images and gestures. The research question guiding our investigation is: What functions do the different types of gestures play in the interpreting process? The results suggest that, in the analyzed material, referential gestures tend to support the construction of meanings, while the main role of pragmatic gestures consists in helping to manage the progress of the interpreting process.
Towards a methodological toolset for the psycholinguistics of translation
Authors: Jacob Gunnar , Schaeffer Moritz , Oster Katharina , Hansen-Schirra Silvia , Allen Shanley E. M. 
Published: November 2021

Abstract
The manuscript provides readers with a basic methodological toolset for experimental psycholinguistic studies on
translation. Following a description of key methodological concepts and the rationale behind experimental designs in
psycholinguistics, we discuss experimental paradigms adopted from bilingualism research, which potentially constitute a
methodological foundation for studies investigating the psycholinguistics of translation. Specifically, we show that
priming paradigms possess several inherent advantages which make them particularly suitable for research on
translation. The manuscript critically discusses key methodological problems associated with such paradigms and illustrates the
opportunities they may offer for translation research, concludes with a review of past and current translation process research
highlighting ways in which these can contribute to the issues raised by cross-linguistic priming studies.
Investigating how we read translations
Authors: Walker Callum 
Published: November 2021

AbstractSince its inception, Translation Studies has hinged on theoretical concepts of effects and reception, with various reader-oriented notions such as equivalent effect,skopos, acceptability and adequacy, and user-centredness, to name but a few, having pervaded the discipline for decades. Despite this preoccupation with the phenomenology of translations, we still know very little about how translations are actually experienced –writtentranslations especially. This article calls for an expansion of research into the reception and experience of source texts and their translations, reviewing the opportunities afforded by recent technological developments in eye-tracking, galvanic skin response sensors, echocardiogram monitors, and other multi-sensory devices. Using a short case study, a number of research questions and an outline of an experimental method are proposed to contrast the reading experience of two translations of the same source text, serving as a prompt for future research of this kind. By drawing inspiration from the few existing examples of research in this incipient paradigm and the considerations offered in the example, this article aims to stimulate future research to explore the vast untapped potential in this area and to arrive at a better understanding of the effects that different translation approaches yield and the potential variation in effects between source and target text.
An on-chip test structure to measure the Seebeck coefficient of thermopile sensors
Authors: Huang Peng , Fu Jianyu , Lu Yihong , Liu Jinbiao , Zhang Jian , Chen Dapeng 
Published: November 2021

Abstract
Thermopile sensors have a wide range of applications in consumer and industry. Seebeck coefficient is a basic thermal parameter of thermopile sensors. Extracting the Seebeck coefficient of both materials and thermocouple in thermopile sensors is of great importance. In this work, an on-chip test structure is designed. It consists of a substrate, a framework, supporting legs and a sensitive region which has a resistor serving as both heater and temperature detector. A set of on-chip test structures are fabricated along with a thermopile sensor. Its measurement results are analyzed and compared with apparatus measurement results. These results are consistent with each other, and the validity of structure is verified.
Double Power Supplies and Cross-zero Clocks Lead to Low Noises and High Efficiency in Digital Integrated Circuits
Authors: Wu Tao 
Published: November 2021

Abstract
Double power supplies are widely used in analog integrated circuits for the sake of power export and dynamic ranges. By contrast, single power supply and the ground line are regular in digital integrated circuits so far. In this paper, it is shown that double power supplies with cross-zero clocks help decrease the power consumption and noises in digital integrated circuits. They are firstly explained in frequency domain and then by a three-level energy system.
Practical Time Optimization of DSP Program for High-frequency Applications
Authors: Xun Zhuyu , Ding Hongfa , He Zhou 
Published: November 2021

Abstract
The rapid development of the high frequency power conversion techniques makes great demands on the methods that can reduce the execution time of the program effectively. This paper is aiming at reducing the execution time of the program in several aspects such as sampling, complex expressions, and so on. As one of the most widely applied methods, reducing the execution time of the program at the cost of the memory space is adopted in this paper. Furthermore, in order to confirm the feasibility and superiority of programs that are proposed in this paper, they are compared with other programs that can realize the same function in terms of the execution time.
Fault Diagnosis of Wind Turbine Generator System Based on PMI-LSSVM
Authors: Zhang Wei , Zhang Zhizhi , Yao Qi , Zhang Xiao , Liu Di , Liu Zesan , Meng Hongmin , Qin Weiming 
Published: November 2021

Abstract
Considering the multi-source wind power information such as wind speed, rotation speed, spindle horizontal and vertical vibration, a fault diagnosis method of wind turbine generator system based on partial mutual information (PMI) and least squares support vector machine (LSSVM) was proposed. A large amount of data containing fault status, such as blade fault, converter fault, generator fault, pitch bearing fault and yaw system fault, was analyzed. The PMI method was used to screen the characteristic parameters of the operation state of the wind turbine to identify the fault of the unit. The characteristic parameters of the wind turbine in various states were trained by LSSVM method to establish the mapping relationship between the parameter vectors of different characteristics and the fault types, so as to achieve the purpose of fault diagnosis. Besides, the different fault history data of wind turbine was used to test the fault model performance. The results compared with artificial neural network (ANN) method showed that the proposed method had good fault recognition ability and fast operation speed, which was suitable for fault diagnosis of multibrid technology wind turbine generator system, and can meet the requirements of online fault diagnosis.
Research on the Architecture of Integrated Platform of Intelligent Substation Auxiliary Monitoring System
Authors: Yang Chuankai , Wu Jingfeng , Zhao Jiansong , Zhang Xiaolan , Li Liangshu , Mu Jianxue 
Published: November 2021

Abstract
For the problems existing in the current substation auxiliary monitoring system, such as various types of equipment, inconsistent standards and poor interaction, the structure design scheme of integrated platform of intelligent substation auxiliary monitoring system is proposed. The structure, function and algorithm of the system are introduced in detail. Firewall isolation technology and security partition technology are adopted to ensure the security and of the system, and give consideration to the real-time data transmission. Through the use of software bus technology, multi data fusion technology and interface standardization technology, the availability and reliability of data are effectively improved and the reliability of the system is improved. Combined with the integrated monitoring platform, the characteristics of intelligent linkage technology of main and auxiliary equipment are put forward. The intelligent linkage and unified management between auxiliary equipment is realized, which effectively improves the intelligent operation and maintenance level of substation auxiliary system.
Power System Small-signal Stability Assessment Model Based on Residual Graph Convolutional Networks
Authors: Su Yinsheng , Guo Mengxuan , Yao Haicheng , Guan Lin , Huang Jiyu , Zhu Siting , Zhong Zhi 
Published: November 2021

Abstract
Small-signal stability (SSA) is important to power system security. A data-driven approach is established for rapid prediction of the power system oscillation characteristics. The key of the approach is the Graph Convolution Networks (GCN) with residual mechanism, which works to aggregate features from high-dimension steady-state operation information and is denoted as ResGCN (RESidual GCN) in the paper. The residual mechanism helps to overcome the network degradation phenomenon. Both the oscillation frequency and damping ratio of multiple modes can be predicted by the proposed model. The performance of the proposed scheme as well as its adaptability to the power system topological changes is verified on the IEEE 39 Bus system.
A Joint Grid-Source Planning Method Considering Adaptability of Power System
Authors: Deng Yingying , Wang Haiyan , Liu Xu’na , Chen Bo , Yang Xinting , Chen Wenye 
Published: November 2021

Abstract
With the large-scale renewable energy access to the power grid, the construction and operation state of the power system have been greatly changed. Therefore, the adaptability of power system to deal with the fluctuation and uncertainty of renewable energy is of great significance to ensure the safe and stable operation of the system and promote the consumption of renewable energy. Based on the structural characteristics and operation status of the power system with high proportion of renewable energy, the adaptability index of the system construction and generators capacity is proposed, which takes into account the security, validity, stability and supply-demand balance of the power system, and comprehensively evaluates the acceptance capacity of the system to the renewable energy. On this basis, a multi-objective power system planning model based on grid-source coordination considering both economy and adaptability is established. The optimal scheme is obtained through the comprehensive decision of the optimal scheme set by the nonlinear improved principal component analysis. Finally, the effectiveness of the adaptability index and the planning model is verified by an example simulation with the improved Gaver-18 system.
An Autonomous Vibration-Sensing System for Power Transmission Lines Monitoring
Authors: Meng Qingpu , Huo Fuguang , Teng Song , Ding Zushan , Gu Tun , Cao Chuang 
Published: November 2021

Abstract
An autonomous vibration-sensing system including of ring magnetoelectric energy scavenger, an energy management module, a plurality of wireless acceleration sensor nodes and APP mobile terminal for power transmission lines monitoring was presented. The ring-type ferrite/piezoelectric composite with strong magnetoelectric couplings and a coil wound around it is used to scavenge the electromagnetic energy around the conductor, and the energy management module successively fulfill the functions of inductive/capacitive resonance matching, rectification and voltage stabilization and storage/release of the scavenged electric energy, and then provides driving power for signal acquisition and data transmission of 4G wireless acceleration sensor nodes. Testing results show that the collected energy can fulfill the power-supplying requirements of ADXL345, and the real-time as well as historical data curves within a specified time can be acquired through 4G and narrowband internet of things technologies.
Implementation and Verification of 5G Network Slicing for Smart Grids
Authors: Sun Lei , Wang Li , Yang Peng , Zhong Yuqing , Hong Danke , Zhang Guoyi , Zhu Hailong , Qian Peng , Li Jing 
Published: November 2021

Abstract
In this paper, 5G slicing networks are proposed to be deployed to address the issues associated with current communication networks in power grid systems and to enable smart grid applications. 5G slice architecture and the corresponding schemes including radio resource reservation, QoS scheduling strategy, VLAN, VPN and 5QI are applied for the access network, the transport network and the core network in the system, based on which a real 5G slicing network is implemented for smart grid applications. It is shown by field trial that the performance requirement regarding service isolation, bandwidth, delay and reliability required by various smart grid applications can be satisfied using the proposed schemes in the real system.
Optimal Operation Model of Park Integrated Energy System Considering Uncertainty of Flexible Electrical, Thermal and Gas Load
Authors: Li Peifeng , Wang Wei , Wei Jun , Li Da , Long Chuan , Chen Wenye 
Published: November 2021

Abstract
Flexible Load (FL) of electricity, heat and gas can improve the operation economy, flexibility and reliability of PIES. Aiming at the uncertainty of FL in the actual operation of the park integrated energy system (PIES), an optimal operation model of PIES with uncertainty of FL is proposed. Firstly, the uncertainty models of shiftable electric load and transferable load response are established, respectively. And then an adjustable heat load response model considering the uncertainty of solar radiation intensity is established. On this basis, an optimal operation model of PIES considering the uncertainty of the FL with the goal of maximizing the total revenue is constructed and is solved by the enhanced-interval linear programming method. Simulation indicate that FL can improve the operating economy of PIES and renewable energy consumption.
Multi-task Transient Contingency Screening with Temporal Graph Convolutional Network in Power Systems
Authors: Su Yinsheng , Huang Jiyu , Yao Haicheng , Guan Lin , Guo Mengxuan , Zhong Zhi 
Published: November 2021

AbstractRapid transient stability assessment (TSA) is an essential requirement for power system security. In real-world applications, transient contingency screening (TCS) applies TSA approaches to address the pre-defined contingency sets under online operation conditions. TSA by time domain simulation (TDS) is time-consuming, hence we propose a high-speed temporal graph convolutional network (TGCN) that achieves TSA decisions such that a large-scale contingency set can be scanned quickly with enough precision. Based on multi-graph inputs to reflect the transient process, the TGCN utilizes the graph convolutional network (GCN) to extract topology representations and temporal convolution (TC) layers to encode temporal relations. After above graph embedding, two downstream networks are designed for stability classification and critical generator prediction, respectively. Test results on IEEE 39 Bus system demonstrate its superiority over existing models under different operation topologies, fault locations and clearing modes.
The Electric Vehicle Routing Problem with Time Windows under Travel Time Uncertainty
Authors: Wang Dan , Zhou Hong 
Published: November 2021

Abstract
Due to environmental friendliness, electric vehicles have become more and more popular nowadays in the transportation system. For many express companies, it is more and more important to meet the predetermined time window of customers. The uncertainty in travel times often causes uncertain energy consumption and uncertain recharging time, thus electric vehicles may miss the time windows of customers. Therefore, this paper addresses the electric vehicle routing problem with time windows under travel time uncertainty, which aims to determine the optimal delivery strategy under travel time uncertainty. To solve this problem, a robust optimization model is built based on the route-dependent uncertainty sets. However, considering the complexity of the problem, the robust model can only solve few instances including the small number of customers. Thus, a hybrid metaheuristic consisting of the adaptive large neighborhood search algorithm and the local search algorithm is proposed. The results show that the algorithm can obtain the optimal solution for the small-sized instances and the large-sized instances.
Key Techniques of SINS/DVL Integrated Navigation System
Authors: Li Wanli , Chen Mingjian , Li Yun 
Published: November 2021

Abstract
Doppler Velocity Log (DVL) aided Strapdown Inertial Navigation System (SINS) is commonly used for the applications of Autonomous Underwater Vehicles (AUVs). In lack of other aiding sensors, how to maintain precise integrated navigation is still a challenge issue. In this paper, the structure and basic principles of the SINS is presented. Alignment calibration of SINS and DVL, fast in-motion alignment and data fusion are key factors which has great influence on the navigation accuracy. Research efforts taken in these fields in recent years are surveyed. This paper may provide a firm foundation for the researchers in related areas.
Effect of Dynamics Control Strategy on Performance of FSEC Racing Car
Authors: Ma Lingyue 
Published: November 2021

Abstract
The control strategy of driving system for the distributed electric drive DRe20 car of Tongji University DIAN Racing team is developed and optimized according to the competition rules of Formula Student Electric China (FSEC). The VI-grade and Matlab Simulink cosimulation experimental platform is established to study the effects of different dynamic control strategies, such as equal distribution, open-loop electronic differential and limited slip differential, on the performance of the DRe20 racing car. The simulation platform is also used to optimize the control algorithm and the setting of different parameters in the program, then the results of simulation analysis and optimization are applied to the actual car experiment, providing a lot of reference data for the adjustment of suspension system and electronic control system of the DRe20 car. The simulation and actual test results show that the limited slip differential control strategy we developed and optimized in 2020 can give full play to the design performance of the DRe20 car, and the comprehensive performances have been improved compared with those in previous years. The optimized dynamics control strategy has been applied to Tongji DIAN Racing car during the 2020 Formula Student Electric China competition, in which Tongji DIAN Racing Team wins the championship.