bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of Chinese Named Entity Recognition Results Based on Different Paradigm
Authors: Luan Fangjun , Sun Xiaotang 
Published: February 2023

Abstract
Named-entity recognition (NER) is a sub-task of information extraction. Currently, there are various approaches to achieve the NER task and the results are getting better. However, the internal structure of the models is becoming more and more complex, making them much less comparable. In view of the above reasons, we categorize NER methods and implement three different NER paradigms (classification-based model, sequence annotation-based model, and pointer network-based model) using the simplest structure for three Chinese NER datasets (PeopleDailyNER, FinanceSinaNER, and CLUENER). We find that the pointer network-based model works well for datasets with short sentence lengths and large data sizes; the classification-based model is good for datasets with large data sizes and numerous entity categories; in the vast majority of cases, the sequence annotation-based model has better entity recognition performance than the other two models.
Research on online test question recommendation technology based on multi-dimensional user dynamic portrait
Authors: Lei Qingfeng , Yang Hua , Deng Taiyong , Liu Jiangrong , Jiang Falin 
Published: February 2023

Abstract
This paper proposes a research method of personalized recommendation of test questions for users by fully collecting and studying the user’s characteristic data in multiple dimensions, establishing a dynamic user portrait, and mining and analyzing the characteristic information of test questions in the test question bank. Firstly, collect the user’s data, calculate the user’s similarity by analyzing the user’s behavior sequence, and use the cosine similarity algorithm to calculate the text similarity of the test questions. Then, the tag system is established to analyze the user activity, and the TF-IDF algorithm is used to calculate the user’s proficiency in different keyword classification questions. Based on the above information, a hybrid recommendation mechanism is adopted to provide users with personalized test question recommendation services.
The Design of Calibration System Based on Cable Accessories
Authors: Zhao Tiemin , Liu Jianshu , Zheng Shiyang , LeYang  , Ding Zhen , Li Dongsheng , Li Kai , Li Wenpeng , Yang Xue , Chai Fangsen 
Published: February 2023

Abstract
In today’s society, people can’t live without electricity. During the operation of power equipment, there may be various potential safety risks. In particular, partial discharge is easy to occur at the terminal. If people can not deal with the problem of partial discharge in time, equipment continue to live.Setting can cause security, so the electric power industry staff attaches great importance to the local discharge monitoring problem.Ultrasonic technology is better so it is gradually into the application of partial discharge detection.But the ultrasonic detection technology is to detect the intensity of ultrasound, and our traditional method is to measure the discharge of partial discharge method, Therefore, in order to obtain the relationship between ultrasonic intensity and partial discharge, the following experiments are made. After we pass the power frequency voltage withstand device, the transformer is continuously pressurized.Gain DB and discharge PC were obtained by digital partial discharge instrument and ultrasonic partial discharge instrument. After fitting, the linear relation is obtained and the quality inspection of PD detector is completed.It can make the detection effect of partial discharge detector more complete, and provide the basis for the quality inspection of the detector, This system also provides a strong support for the wide application of ultrasonic partial discharge detector.
Research on short-term power load forecasting method based on multi-factor feature analysis and LSTM
Authors: Zeng Bing , Qiu Yupeng , Yang Xiaopin , Chen Wu , Xie Yunmin , Wang Yifan , Jiang Pengfei 
Published: February 2023

Abstract
In order to improve the accuracy of short-term power load forecasting and fully consider the influence of weather factors on power load, a short-term power load forecasting model based on multi-factor analysis and Long-Short Term Memory (LSTM) neural network is proposed. Firstly, the correlation between different weather factors and load is analysed using the Spearman coefficient method to extract the weather features that have a greater impact on power load. Then the original time series data are reconstructed using the sliding window method. Finally, the forecasting model is established by using LSTM. The proposed model is validated by using the power load data from the 2016 Electrician’s Cup modelling competition, and compared with other models. The results show that the average absolute percentage error of the forecasting model proposed in this paper reaches 7.41% and the average absolute value error is 380.67 MW, which is better than the other models mentioned in the paper.
Study on ultrasonic detection method of a honeycomb sandwich panel
Authors: Wang Zhulin , He Xiao 
Published: February 2023

Abstract
A new material for the structure of the honeycomb sandwiched XinBi board has been in active service. In this paper, structural defects are embedded in the easily damaged parts of this new material, and the ultrasonic method is used to detect the easily damaged parts, and the acoustic signals and defect echo signals of the easily damaged parts are obtained, which provides a reference for damage evaluation of this kind of structures in site detection.
Process Mineralogy Automatic Detection System in Research of a Gold Polymetallic Mine
Authors: Ji Qiang , Li Guangsheng , Zhu Xingfu , Gao Tengyue , Qin Guanglin , Xu Chao , Cai Mingming , Lu Zhongbo , Chen Yanbo , Zhang Juntong , Qin Xiangwei , Wang Junjie 
Published: February 2023

Abstract
Automatic process mineralogy detection system has been widely used in beneficiation process parameters detection, cause finding, and defect diagnosis in concentrators. A gold ore composition in Shandong is more complex, and recovery is difficult. To clarify the ore properties, mineral composition, main minerals, embedded characteristics, and monomer dissociation characteristics, the scanning electron microscope, BPMA, and energy spectrometer are used for the ore sample process mineralogy research to provide a reliable basis for the study of the selection process. The research shows that the main valuable elements in the ore are gold and copper, copper and gold symbiotic ore. Meanwhile, the gold, copper, and iron-containing minerals are closely embedded, pyrite and magnetite are the main minerals for sulfur recovery, and magnetite and limonite are the main minerals for producing iron concentrate. Automatic process mineralogy has played an important role in determining the selectability research and beneficiation process of the polymetallic gold ore.
Development of an Eight-channel Full-bridge Strain Signal Synchronous Collector
Authors: Tao Aihua , Xu Yue , Liu Wang , Zhou Zhijian , Lyu Qing , Qiao Liyan 
Published: February 2023

Abstract
Wind tunnel test is widely used in automotive, aerospace, and other fields. The overall effect of the test depends on the accuracy of the data collected by the acquisition system. To collect the balanced strain signal with high precision, an eight-channel full-bridge strain signal synchronization collector is developed in this paper. The article gives the hardware and software design of the collector, respectively. The hardware adopts a modular design with STM32H743 MCU and MAX10 series FPGA, which implements the signal condition, the Butterworth low pass filter, the analog to digital conversion, and the wireless data transmission with WIFI. In terms of software design, the article not only gives the firmware of MCU and FPGA but also designs the software of the host computer with LabVIEW. Finally, the data are tested and analyzed according to the requirements of technical indexes.
Application on DCPD Real-Time Monitoring of Fatigue Crack Propagation
Authors: Liu Zhengzhen , Zhuang Zecheng , Huang Mingda , He Mingjian 
Published: February 2023

Abstract
The formation, propagation, and detection of fatigue cracks are the key issues for the life extension of pressure pipelines and metal welded joints. Especially in the high-temperature and high-pressure water environment of nuclear power. Since the interference of measuring instruments and noise would affect the monitoring of potential signals that characterize crack growth. Combined with the relevant information and various methods of fatigue crack growth detection were analyzed, it can be seen that the Direct Current Potential Drop (DCPD) method has significant advantages in many crack detection methods. Firstly, the development history and current situation of fatigue crack research were analyzed. Secondly, its basic principles and key problems were summarized. Based on the existing crack detection methods, the real-time monitoring system was introduced, and the overall research status was evaluated and analyzed, which a reliable scientific basis for the numerical analysis of fatigue life and a reference were provided for the research on this field.
Neural Network Analysis Based on Data Parallelism
Authors: Lu Jiawei 
Published: February 2023

Abstract
With the development of Internet technology, many image data emerge on the Internet, and deep learning algorithms can extract abstract features from these data for image classification by using multi-layer nonlinear transformation. Therefore, deep learning algorithm has become a research hotspot in image processing. Aiming at the complex semantic features of images, an efficient deep learning algorithm has essential research significance for extracting and analyzing the semantic information about images quickly and effectively. This paper mainly explores the application of deep learning in image classification. Three neural models, LeNet, VGG, and ResNet are selected to test CIFAR10, and their training duration and accuracy are compared. Secondly, this paper further explores the impact of trying three neural network models on different graphics cards on their performance, and further researches and learns the application of these models. Finally, this paper tests the data parallelism solution of PyTorch, and the results and problems of the three models in this process are analyzed.
Study on an abnormal temperature detection method for CAFe facility
Authors: Xie N. , Wang B.J. , Guo Y.H. , Gu R.F. , Wang R. 
Published: February 2023

Abstract
Beam availability is an important indicator of the operational stability and safety of the accelerator. As the front-end prototype of CiADS (China initiative Accelerator Driven System), the CAFe (Chinese ADS Front-end Demo Linac) accelerator is used to verify the feasibility of the key technologies of CiADS, which plays an important role in the development of nuclear waste safety treatment technology. The accelerator is often affected by uncontrollable factors during operation, triggering false temperature alarms from the BPM (Beam Position Monitor), causing the accelerator machine protection system to cut the beam, significantly reducing the availability of the beam. In addition, the prevailing method of manually setting the machine protection system threshold increases the beam conditioning time and the probability of false beam cuts. Therefore, it is urgent to study and discriminate the anomalies that cause beam cutting in order to reduce the beam cutting times caused by false alarms. In this paper, a BPM temperature anomaly prediction model based on Isolation Forest is developed, and the historical BPM temperature data from the CAFe accelerator is pre-processed using the Kalman filter to eliminate the influence of noise. The experimental results show that the scheme can accurately predict the abnormal state of the accelerator to remove the anomalous values, thereby avoiding false interlocks, and provide an effective interlock reference for the threshold setting of the machine protection system, thereby improving the beam availability.
Simulation study on optical transmission performance and time resolution of Shashlik tower
Authors: Peng X. , Zhu J. , He L. , Xiao W. , Luo F. , Xiao M. , Wang X. 
Published: February 2023

Abstract
The Shashlik tower is a significant component to measure the energy, time, and position of
photons and electrons in the Electromagnetic Calorimeter (ECal), a vital detector of the
Multi-Purpose Detector (MPD) in the Nuclotron-based lon Collider fAcility (NICA), Dubna,
Russia. Based on the GEANT4 simulation toolkit, a variation of physical behavior in the tower was
simulated, including the changes of photons during transmission, and used the rising edge
detection method to measure the time-resolving ability of the module for natural muons and
electron beams. Results show that 3 GeV electrons enter the tower, photons emitted by the
scintillator are transmitted, 10665 photoelectrons are collected on Silicon Multipliers (SiPMs),
yield is 3555 pe/GeV, and the light output is 0.16%. The time resolution of the module for
muons is better than 160 ps, but the value of each tower is different. In addition, by changing
the electron beam energy in the simulation, we observed that a larger number of photoelectrons
collected by SiPMs leads to a better time resolution. At an electron beam energy of 1 GeV, the
time resolution of the tower could be better than 101 ps. The simulated measuring results, and the
methods of the tower photon transmission performance and the time resolution, will provide
references and new optimum methods for subsequent experiential tests.
O’Connor v Donaldson (1975): Legal Challenges, Psychiatric Authority, and the Dangerousness Problem in Deinstitutionalization
Authors: Hirshbein Laura 
Published: February 2023

Abstract
In 1975, the Supreme Court heard the case of O’Connor v Donaldson, in which Kenneth Donaldson disputed the decision of his psychiatrists at the Florida State Hospital to keep him incarcerated for 15 years for a mental illness, though he was not dangerous or receiving treatment. The Donaldson decision pitted activist attorneys against psychiatrists who were increasingly beleaguered in their efforts to assert expertise about mental illness in American society. This case and its context offer a window into the psychiatric and legal conversations within the deinstitutionalization movement. During a time when both psychiatry and the law were shifting in their professional claims and emphases, each side was captured by an idea of reform based on how they imagined the problems to be configured. Examining themes of place, authority, right to treatment, and dangerousness reveals the limitations of the reforms and the hardening of a narrative that limited state action to the elision of mental illness with dangerousness.
Photosynthetic 1,8-cineole production using cyanobacteria
Authors: Sakamaki Yutaka , Ono Mizuki , Shigenari Nozomi , Chibazakura Taku , Shimomura Kenji , Watanabe Satoru 
Published: February 2023

ABSTRACT
Terpenoid is an important group of compounds not only as biocomponents but also as useful secondary metabolites. A volatile terpenoid 1,8-cineole, which is used as a food additive, flavoring agent, cosmetic, etc., is also attracting attention from a medical perspective due to its antiinflammation and antioxidation. The 1,8-cineole fermentation using a recombinant Escherichia coli strain has been reported, although a carbon source supplement is necessary for a high-yield 1,8-cineole production. We constructed the 1,8-cineole-producing cyanobacteria toward a carbon-free and sustainable 1,8-cineole production. cnsA, the 1,8-cineole synthase gene in Streptomyces clavuligerus ATCC 27064, was introduced and overexpressed in the cyanobacterium Synechococcus elongatus PCC 7942. We succeeded in producing an average of 105.6 µg g−1 wet cell weight of 1,8-cineole in S. elongatus 7942 without supplementing any carbon source. Using the cyanobacteria expression system is an efficient approach to producing 1,8-cineole by photosynthesis.
Reflections on Becoming a New CIO
Authors: Haywood Andy 
Published: February 2023

Abstract
Andy Haywood joined the Welsh Ambulance Services NHS Trust (WAST) in January 2020 as its first director of digital services, an executive CIO role on the trust board. Now a managing consultant at Channel 3 Consulting, he discusses the lessons he learned in two and a half years as a new NHS CIO during the COVID–19 pandemic.
Digital in Business Life 2023 Report
Authors: Runciman Brian 
Published: February 2023

Abstract
Over the years we have looked at future IT needs in various guises, this year BCS surveyed members who are IT leaders and digital professionals to help us get a feel for differences in perception between the two groups as we look ahead at 2023. Brian Runciman MBCS looks at some of the key findings of BCS’s ‘Digital in Business Life 2023.’
Artificial Intelligence in Inflammatory Bowel Disease Endoscopy: Implications for Clinical Trials
Authors: Ahmad Harris A , East James E , Panaccione Remo , Travis Simon , Canavan James B , Usiskin Keith , Byrne Michael F 
Published: February 2023

Abstract
Artificial intelligence shows promise for clinical research in inflammatory bowel disease endoscopy. Accurate assessment of endoscopic activity is important in clinical practice and inflammatory bowel disease clinical trials. Emerging artificial intelligence technologies can increase efficiency and accuracy of assessing the baseline endoscopic appearance in patients with inflammatory bowel disease and the impact that therapeutic interventions may have on mucosal healing in both of these contexts. In this review, state-of-the-art endoscopic assessment of mucosal disease activity in inflammatory bowel disease clinical trials is described, covering the potential for artificial intelligence to transform the current paradigm, its limitations, and suggested next steps. Site-based artificial intelligence quality evaluation and inclusion of patients in clinical trials without the need for a central reader is proposed; for following patient progress, a second reading using AI alongside a central reader with expedited reading is proposed. Artificial intelligence will support precision endoscopy in inflammatory bowel disease and is on the threshold of advancing inflammatory bowel disease clinical trial recruitment.
A Multi-Community Approach in Biodiversity Assessment of a Peat Bog in the Southern Carpathians (Romania) and Implications for Conservation
Authors: Băncilă Raluca I , Cogӑlniceanu Dan , Manu Minodora , Plăiaş̧u Rodica , Stănescu Florina , Memedemin Daniyar , Skolka Marius , Tofan Lucica , Lăcătuşu Anca 
Published: February 2023

Abstract
Although natural peatlands have been recognized as an important type of wetlands because they support high biodiversity and provide important ecosystem services, the value of peatlands both in biodiversity research and conservation is still largely underestimated. Our study characterizes the biodiversity and conservation value of Peşteana peat bog, an upland mesotrophic peat bog, located in the Southern Carpathians, Romania. More specifically, we: (1) characterized the invertebrate (i.e., top soil, surface litter, and plant-dwelling) and plant communities along a humidity gradient in Peşteana peat bog and nearby habitats (i.e., treeline, ecotone, lowland and highland meadow, and forest), (2) assessed the main environmental factors driving the invertebrate community diversity and composition, and (3) determined the relationship between invertebrate community diversity and vegetation, focusing on the top soil invertebrates. Our study revealed a high diversity of invertebrates spanning over 43 taxonomic groups and a high number of plant indicator species, emphasizing the role of natural peatlands in preserving diverse communities in a small area. The results showed that the composition of top soil invertebrate community was determined by depth of organic layer, vegetation cover, and soil compaction. We found that the diversity of top soil invertebrate community was strongly influenced by habitat type and soil attributes and weakly by vegetation. Overall, the invertebrate and plant communities showed different responses to habitat conditions along the humidity gradient. This highlights the importance of using a multi-community approach to support the design of effective conservation and management actions beneficial for a wide range of taxa.
Digest: Salamanders reveal novel trajectories of amphibian MHC evolution
Authors: Kettenburg Gwenddolen 
Published: February 2023

AbstractHow does amphibian MHC diversity fit in the landscape of vertebrate evolution? Mimnias et al. (2022) address this gap in the field of MHC evolution by focusing on the lesser described MHC class I in salamanders. These findings contribute to understanding MHC diversity and the susceptibility of amphibians to pathogens, which could lead to future research on a major threat to amphibian biodiversity, chytrid fungi.
Large-scale population structure and genetic architecture of agronomic traits of garlic
Authors: Jia Huixia , Zhao Qing , Song Jiangping , Zhang Xiaohui , Yang Wenlong , Du Zhenzhen , Zhu Yue , Wang Haiping 
Published: February 2023

Abstract
Garlic, an asexually propagated crop, is the second important bulb crop after the onion and is used as a vegetable and medicinal plant. Abundant and diverse garlic resources have been formed over thousands of years of cultivation. However, genome variation, population structure and genetic architecture of garlic agronomic traits were still not well elucidated. Here, 1 100 258 single nucleotide polymorphisms (SNPs) were identified using genotyping-by-sequencing in 606 garlic accessions collected from 43 countries. Population structure, principal component and phylogenetic analysis showed that these accessions were divided into five subpopulations. Twenty agronomic traits, including above-ground growth traits, bulb-related and bolt-related traits in two consecutive years were implemented in a genome-wide association study. In total, 542 SNPs were associated with these agronomic traits, among which 188 SNPs were repeatedly associated with more than two traits. One SNP (chr6: 1896135972) was repeatedly associated with ten traits. These associated SNPs were located within or near 858 genes, 56 of which were transcription factors. Interestingly, one non-synonymous SNP (Chr4: 166524085) in ribosomal protein S5 was repeatedly associated with above-ground growth and bulb-related traits. Additionally, gene ontology enrichment analysis of candidate genes for genomic selection regions between complete-bolting and non-bolting accessions showed that these genes were significantly enriched in ‘vegetative to reproductive phase transition of meristem’, ‘shoot system development’, ‘reproductive process’, etc. These results provide valuable information for the reliable and efficient selection of candidate genes to achieve garlic genetic improvement and superior varieties.