Reviewerly/exHarmony huggingface dataset:
The role of complexity in the ability to notice incoherent uses of connectives for L2

Authors:
raw_author_name: Mathis Wetzel
raw_affiliation_string: University of Bern, Switzerland
raw_author_name: Sandrine Zufferey
raw_affiliation_string: University of Bern, Switzerland
raw_author_name: Pascal Gygax
raw_affiliation_string: University of Fribourg, Switzerland

Abstract: Abstract When learning a second language, some connectives are more difficult to acquire and to master than others. While previous research has assessed different factors responsible for this difficulty by using offline tasks, little is known about the extent to which L2-readers are sensitive to different connectives while reading . In our study, we compared self-paced reading times of native and non-native speakers of French for sentences that were correctly or incorrectly marked with either the infrequent connective cependant (‘however’) or the more frequent mais (‘but’). Results showed that incorrect uses only produced longer reading times when mais was used. Yet, in a sentence-evaluation-task using the same set of sentences, L2-speakers were able to discriminate incorrectly marked sentences with cependant from correctly marked ones. We conclude that a good theoretical understanding of connectives for L2 (Experiment 2) does not always warrant a quick activation of their meaning while reading (Experiment 1).
Detection of Pumping Unit in Complex Scenes by YOLOv7 with Switched Atrous Convolution

Authors:
raw_author_name: Kai Zhang
raw_affiliation_string: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
raw_author_name: Huaqing Zhang
raw_affiliation_string: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
raw_author_name: Xia Yan
raw_affiliation_string: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
raw_author_name: Liming Zhang
raw_affiliation_string: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China

Abstract: The petroleum and natural gas industries exhibit a high dependency on lifting equipment for oil and gas. Any malfunction in these devices can lead to severe economic losses. Therefore, continuous and timely monitoring of the status of pumping equipment is of paramount importance to proactively prevent potential issues. In an effort to enhance this monitoring process, this study delves into multi-source data images at the well site and extends traditional information analysis methods. It introduces an improved YOLOv7 method based on switchable atrous convolution. While the YOLOv7 algorithm achieves a balance between speed and accuracy, its robustness in non-standard environments is suboptimal. To address this limitation, we propose the utilization of a switchable atrous convolution method for enhancement, thereby augmenting the adaptability of the model. Images of pumping units from diverse scenarios are actively collected and utilized to construct training, validation, and test sets. Different models, including YOLOv7SAC, YOLOv7, and YOLOv5-n, undergo testing, and their detection performances are systematically compared in complex environments. Experimental findings demonstrate that YOLOv7SAC consistently attains optimal detection results across various scenes. In conclusion, the study suggests that the combination of the YOLOv7 model with switchable atrous convolution proves effective for detecting pumping unit equipment in complex scenarios. This provides robust theoretical support for the detection and identification of pumping equipment issues under challenging conditions.
A Unified Spatial-Pressure Sensitivity Partitioning and Leakage Detection Method within a Deep Learning Framework

Authors:
raw_author_name: Bo Dong
raw_affiliation_string: Architectural Engineering Institute, Chuzhou Vocational and Technical College, Chuzhou 239000, China; College of Environmental Science and Engineering, State Environmental Protection Engineering Center for Pollution Treatment and Control in Textile Industry, Donghua University, Shanghai 201620, China
raw_author_name: Shihu Shu
raw_affiliation_string: College of Environmental Science and Engineering, State Environmental Protection Engineering Center for Pollution Treatment and Control in Textile Industry, Donghua University, Shanghai 201620, China

Abstract: This study introduces an innovative approach for leak detection in water distribution systems (WDSs), integrating three-order embedding, k-means clustering, and long short-term memory (LSTM) networks, with pressure-sensitive analysis techniques. This comprehensive methodology segments the network into distinct partitions, utilizes simulated leak events to train the deep learning networks, and establishes a sophisticated model for accurately identifying leak partitions. This approach generates a leak dataset by adjusting water demands, which could effectively pinpoint the leaks in a specific partition by leveraging both the pressure sensitivity and spatial coordinates of nodes, allowing for the elimination of the need for manual work and precise identification of leaks in targeted areas. Through the analysis of two case studies, the model demonstrates its ability to effectively pinpoint potential leak partitions, significantly enhancing operational efficiency and reliability in managing the complex problems of urban water resource management. This approach not only optimizes leak detection but also paves the way for advanced, data-driven strategies in WDSs, ensuring sustainable and secure water distribution in urban settings.
Nonequilibrium quantum probing through linear response

Authors:
raw_author_name: G. Zicari
raw_affiliation_string: Centre for Quantum Materials and Technologies, School of Mathematics and Physics, Queen's University Belfast, University Road, Belfast BT7 1NN, United Kingdom
raw_author_name: A. Belenchia
raw_affiliation_string: Centre for Quantum Materials and Technologies, School of Mathematics and Physics, Queen's University Belfast, University Road, Belfast BT7 1NN, United Kingdom; Institut für Theoretische Physik, Eberhard-Karls-Universität Tübingen, 72076 Tübingen, Germany
raw_author_name: A. Ferraro
raw_affiliation_string: Centre for Quantum Materials and Technologies, School of Mathematics and Physics, Queen's University Belfast, University Road, Belfast BT7 1NN, United Kingdom; Dipartimento di Fisica Aldo Pontremoli, Università degli Studi di Milano, I-20133 Milano, Italy
raw_author_name: M. Paternostro
raw_affiliation_string: Centre for Quantum Materials and Technologies, School of Mathematics and Physics, Queen's University Belfast, University Road, Belfast BT7 1NN, United Kingdom; Università degli Studi di Palermo, Dipartimento di Fisica e Chimica—Emilio Segrè, via Archirafi 36, Palermo I-90123, Italy

Abstract: The formalism of linear response theory can be extended to encompass physical situations where an open quantum system evolves toward a nonequilibrium steady state. Here, we use the framework put forward by Konopik and Lutz [Phys. Rev. Res. 1, 033156 (2019)] to go beyond unitary perturbations of the dynamics. Considering an open system comprised of two coupled quantum harmonic oscillators, we study the system's response to unitary perturbations, affecting the Hamiltonian dynamics, as well as nonunitary perturbations, affecting the properties of the environment, e.g., its temperature and squeezing. We show that linear response, combined with a quantum probing approach, can effectively provide valuable quantitative information about the perturbation and characteristics of the environment, even in cases of nonunitary dynamics.
SEDD: Robust Blind Image Watermarking With Single Encoder And Dual Decoders

Authors:
raw_author_name: Yuyuan Xiang
raw_affiliation_string: Key Laboratory of Data Protection and Intelligent Management (Sichuan University) , Ministry of Education, 610207 , China; School of Cyber Science and Engineering, Sichuan University , Chengdu 610065 , China
raw_author_name: Hongxia Wang
raw_affiliation_string: Key Laboratory of Data Protection and Intelligent Management (Sichuan University) , Ministry of Education, 610207 , China; School of Cyber Science and Engineering, Sichuan University , Chengdu 610065 , China
raw_author_name: Ling Yang
raw_affiliation_string: Key Laboratory of Data Protection and Intelligent Management (Sichuan University) , Ministry of Education, 610207 , China; School of Cyber Science and Engineering, Sichuan University , Chengdu 610065 , China
raw_author_name: Mingze He
raw_affiliation_string: Key Laboratory of Data Protection and Intelligent Management (Sichuan University) , Ministry of Education, 610207 , China; School of Cyber Science and Engineering, Sichuan University , Chengdu 610065 , China
raw_author_name: Fei Zhang
raw_affiliation_string: Key Laboratory of Data Protection and Intelligent Management (Sichuan University) , Ministry of Education, 610207 , China; School of Cyber Science and Engineering, Sichuan University , Chengdu 610065 , China

Abstract: Abstract Blind image watermarking is regarded as a vital technology to provide copyright of digital images. Due to the rapid growth of deep neural networks, deep learning-based watermarking methods have been widely studied. However, most existing methods which adopt simple embedding and extraction structures cannot fully utilize the image features. In this paper, we propose a novel Single-Encoder-Dual-Decoder (SEDD) watermarking architecture to achieve high imperceptibility and strong robustness. Precisely, the single encoder utilizes normalizing flow to realize watermark embedding, which can effectively fuse the watermark and cover image. For watermark extraction, we introduce a parallel dual-decoder to improve the imperceptibility and extracting ability. Extensive experiments demonstrate that better watermark robustness and imperceptibility are obtained by SEDD architecture. Our method achieves a bit error rate less than 0.1% under most attacks such as JPEG compression, Gaussian blur and crop. Besides, the proposed method also obtains strong robustness under combined attacks and social platform processing.
Quantum Dicke battery supercharging in the bound-luminosity state

Authors:
raw_author_name: S. S. Seidov
raw_affiliation_string: MIEM, HSE University, Moscow 115054, Russia; Theoretical Physics and Quantum Technologies Department, NUST "MISIS", Moscow 119049, Russia
raw_author_name: S. I. Mukhin
raw_affiliation_string: Theoretical Physics and Quantum Technologies Department, NUST "MISIS", Moscow 119049, Russia

Abstract: Quantum batteries, which are quantum systems to be used for the storage and transformation of energy, have been recently attracting research interest. A promising candidate for their investigation is the Dicke model, which describes an ensemble of two-level systems interacting with a single-mode electromagnetic wave in a resonator cavity. In order to charge the battery, a coupling between the ensemble of two-level systems and resonator cavity should be turned off at a certain moment of time. This moment of time is chosen in such a way that the energy gets fully stored in an ensemble of two-level systems. In our previous works we have investigated a bound-luminosity superradiant state of the extended Dicke model and found analytical expressions for the dynamics of coherent energy transfer between the superradiant condensate and the ensemble of two-level systems. Here, using our previous results, we have derived analytically the superlinear law for the quantum battery charging power $P\ensuremath{\sim}{N}^{3/2}$ as a function of the number $N$ of two-level systems in the battery, and also the $N$ dependence for the charging time ${t}_{c}\ensuremath{\sim}{N}^{\ensuremath{-}1/2}$. The $N$ exponent $3/2$ of the charging power is in quantitative correspondence with the recent result $1.541$ obtained numerically by other authors. The physics of Dicke quantum battery charging is considered in detail.
Quantum Computing and Machine Learning on an Integrated Photonics Platform

Authors:
raw_author_name: Huihui Zhu
raw_affiliation_string: Institute of Quantum Technologies (IQT), The Hong Kong Polytechnic University, Hong Kong SAR, China; School of Electrical and Electronic Engineering, Nanyang Technological University, Block S2.1, 50 Nanyang Avenue, Singapore 639798, Singapore
raw_author_name: Hexiang Lin
raw_affiliation_string: School of Electrical and Electronic Engineering, Nanyang Technological University, Block S2.1, 50 Nanyang Avenue, Singapore 639798, Singapore
raw_author_name: Shaojun Wu
raw_affiliation_string: Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610051, China
raw_author_name: Hui Zhang
raw_affiliation_string: Institute of Quantum Technologies (IQT), The Hong Kong Polytechnic University, Hong Kong SAR, China
raw_author_name: Yuancheng Zhan
raw_affiliation_string: School of Electrical and Electronic Engineering, Nanyang Technological University, Block S2.1, 50 Nanyang Avenue, Singapore 639798, Singapore
raw_author_name: Xiaoting Wang
raw_affiliation_string: Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610051, China
raw_author_name: Aiqun Liu
raw_affiliation_string: Institute of Quantum Technologies (IQT), The Hong Kong Polytechnic University, Hong Kong SAR, China; School of Electrical and Electronic Engineering, Nanyang Technological University, Block S2.1, 50 Nanyang Avenue, Singapore 639798, Singapore
raw_author_name: Leong Chuan Kwek
raw_affiliation_string: Centre for Quantum Technologies, National University of Singapore, Singapore 117543, Singapore; MajuLab, CNRS-UNS-NUS-NTU International Joint Research Unit, UMI 3654, Singapore 637616, Singapore; School of Electrical and Electronic Engineering, Nanyang Technological University, Block S2.1, 50 Nanyang Avenue, Singapore 639798, Singapore

Abstract: Integrated photonic chips leverage the recent developments in integrated circuit technology, along with the control and manipulation of light signals, to realize the integration of multiple optical components onto a single chip. By exploiting the power of light, integrated photonic chips offer numerous advantages over traditional optical and electronic systems, including miniaturization, high-speed data processing and improved energy efficiency. In this review, we survey the current status of quantum computation, optical neural networks and the realization of some algorithms on integrated optical chips.
On the reasons for the removal of A.T. Tvardovsky from the position of head of the editorial office of the magazine “New World”

Authors:
raw_author_name: Chuyao Wang

Abstract: The subject of the article is the activities of the “New World” journal in the 1950-1960s. The author examines the role of the magazine at the beginning of the reform of Russian literature; the position of the editor-in-chief of “New World” regarding the function of literature designed to reflect reality; the reasons why A. Tvardovsky was removed from the post of editorial director. The work indicates that A. Tvardovsky served as editor-in-chief of the “New World” for 16 years, but during his career he faced dismissal twice. The article reflects the direction and main ideas of liberal thought of the New World magazine, which in the 1950s and 1960s was under the leadership of the editor-in-chief A. Tvardovsky. When studying the problems associated with the magazine’s position on the need to provide literary creativity with a certain freedom. When considering the activities of the magazine and its editor in certain historical and sociocultural conditions, a comparative historical method was used. The main conclusion of the study is that A. Tvardovsky, through his activities as editor-in-chief of the publication “New World” and his principled position on the freedom of literary creativity, made it possible to outline the beginning of the Thaw period in the Soviet literary process. The novelty of the research lies in the fact that the article systematizes information about the reasons for the removal of A. Tvardovsky from the post of editorial director and proves the role of the periodical in question in the process of making a turn in Russian literature towards the realistic tradition. A. Tvardovsky even published those works that were rejected by other leading journals due to the discrepancy between the author’s ideas and the ideas of the ruling party.
GraphSAGE++: Weighted Multi-scale GNN for Graph Representation Learning

Authors:
raw_author_name: Yinglong Zhang
raw_affiliation_string: School of Physics and Information Engineering, Minnan Normal University, Zhangzhou, 363000, Fujian, China
raw_author_name: Hong Wang
raw_affiliation_string: School of Physics and Information Engineering, Minnan Normal University, Zhangzhou, 363000, Fujian, China
raw_author_name: Xuewen Xia
raw_affiliation_string: School of Physics and Information Engineering, Minnan Normal University, Zhangzhou, 363000, Fujian, China
raw_author_name: Xing Xu
raw_affiliation_string: School of Physics and Information Engineering, Minnan Normal University, Zhangzhou, 363000, Fujian, China

Abstract: Abstract Graph neural networks (GNNs) have emerged as a powerful tool in graph representation learning. However, they are increasingly challenged by over-smoothing as network depth grows, compromising their ability to capture and represent complex graph structures. Additionally, some popular GNN variants only consider local neighbor information during node updating, ignoring the global structural information and leading to inadequate learning and differentiation of graph structures. To address these challenges, we introduce a novel graph neural network framework, GraphSAGE++. Our model extracts the representation of the target node at each layer and then concatenates all layer weighted representations to obtain the final result. In addition, the strategies combining double aggregations with weighted concatenation are proposed, which significantly enhance the model’s discernment and preservation of structural information. Empirical results on various datasets demonstrate that GraphSAGE++ excels in vertex classification, link prediction, and visualization tasks, surpassing existing methods in effectiveness.
Countermeasure Strategies to Address Cybersecurity Challenges Amidst Major Crises in the Higher Education and Research Sector: An Organisational Learning Perspective

Authors:
raw_author_name: Samreen Mahmood
raw_affiliation_string: Centre for Smart Analytics (CSA), Federation University, MT Helen Campus, Ballarat 3350, Australia
raw_author_name: Mehmood Chadhar
raw_affiliation_string: Centre for Smart Analytics (CSA), Federation University, MT Helen Campus, Ballarat 3350, Australia
raw_author_name: Selena Firmin
raw_affiliation_string: Centre for Smart Analytics (CSA), Federation University, MT Helen Campus, Ballarat 3350, Australia

Abstract: Purpose: The purpose of this research paper was to analyse the counterstrategies to mitigate cybersecurity challenges using organisational learning loops amidst major crises in the Higher Education and Research Sector (HERS). The authors proposed the learning loop framework revealing several counterstrategies to mitigate cybersecurity issues in HERS. The counterstrategies are explored, and their implications for research and practice are discussed. Methodology: The qualitative methodology was adopted, and semi-structured interviews with cybersecurity experts and top managers were conducted. Results: This exploratory paper proposed the learning loop framework revealing introducing new policies and procedures, changing existing systems, partnership with other companies, integrating new software, improving employee learning, enhancing security, and monitoring and evaluating security measures as significant counterstrategies to ensure the cyber-safe working environment in HERS. These counterstrategies will help to tackle cybersecurity in HERS, not only during the current major crisis but also in the future. Implications: The outcomes provide insightful implications for both theory and practice. This study proposes a learning framework that prioritises counterstrategies to mitigate cybersecurity challenges in HERS amidst a major crisis. The proposed model can help HERS be more efficient in mitigating cybersecurity issues in future crises. The counterstrategies can also be tested, adopted, and implemented by practitioners working in other sectors to mitigate cybersecurity issues during and after major crises. Future research can focus on addressing the shortcomings and limitations of the proposed learning framework adopted by HERS.
Distinguishing Geogenic Load and Anthropogenic Contribution to Soil Contamination in Mineralised Mountain Landscape of Ore Mountains (Czech Republic) Using Cumulative Distribution Functions

Authors:
raw_author_name: Michal Hošek
raw_affiliation_string: Faculty of Environment, Jana Evangelisty Purkyně University in Ústí nad Labem, 400 96 Ústí nad Labem, Czech Republic
raw_author_name: Tomáš Matys Grygar
raw_affiliation_string: Faculty of Environment, Jana Evangelisty Purkyně University in Ústí nad Labem, 400 96 Ústí nad Labem, Czech Republic

Abstract: In ore regions impacted by mining and metal smelting emissions, distinguishing between geogenic anomalies and anthropogenic contamination poses a significant challenge. In a study from two areas with different mining histories in the Ore Mountains, Czech Republic, we demonstrate that sampling of topsoils and subsoils respecting local geology and correct soil data treatment respecting soil textural variability effects are indispensable to the correct construction and interpretation of geochemical maps and identification of anthropogenic contamination by As, Cu, Pb, and Zn. The list of analysed elements must include both potentially toxic and lithogenic elements, otherwise natural controls of soil composition cannot be deciphered. By using empirical cumulative distribution functions, we found that local backgrounds for As/Fe and Pb/Ti are naturally elevated (5.7 to 9.8 times and 2.1 to 2.7 times higher, respectively) compared to the global averages. We constructed geochemical maps with topsoil minus subsoil concentrations to show the main directions of spreading anthropogenic contamination. The anthropogenic diffuse contamination contribution was calculated and expressed as an enrichment relative to the local background (16% and 12% for As/Fe and 17% and 14% for Pb/Ti, respectively). This corresponds to topsoil enrichment by ca. 15 and 14 mg kg−1 for As and ca. 35 and 42 mg kg−1 for Pb in the two study areas. The obtained estimates were comparable to the results from the local peat archives. The approach we used is efficient in deciphering natural and anthropogenic controls of PTEs in geochemically complicated areas.