Related Fields Research Articles

Dynamic phase transition region in electrically injected PT-symmetric lasers

Research on parity-time (PT) symmetry and exceptional points in non-Hermitian laser systems has been extensively conducted. However, in practical electrically injected PT-symmetric lasers, the frequency detuning and linewidth enhancement factor of the laser can influence the symmetry breaking of the system in another dimension. We find that the previous exceptional point now transforms into a dynamic phase transition region, where the states are temporally unstable, indicating the occurrence of multimode oscillation. The relative phase and field amplitude ratio in this region also exhibit many novel phenomena indicating its instability. This region can be manipulated by adjusting the coupling strength between adjacent waveguides and the pumping intensity in the loss waveguide. Experimentally, we characterize the near-field, far-field, and spectrum of several structures, and the results validate our theoretical model. This work elucidates the dynamic process and phase transition process of electrically injected PT-symmetric lasers, providing support for the practical application of PT-symmetric lasers.

Informatics assessment of COVID-19 data collection: an analysis of UK Biobank questionnaire data

BackgroundThere have been many efforts to expand existing data collection initiatives to include COVID-19 related data. One program that expanded is UK Biobank, a large-scale research and biomedical data collection resource that added several COVID-19 related data fields including questionnaires (exposures and symptoms), viral testing, and serological data. This study aimed to analyze this COVID-19 data to understand how COVID-19 data was collected and how it can be used to attribute COVID-19 and analyze differences in cohorts and time periods.MethodsA cohort of COVID-19 infected individuals was defined from the UK Biobank population using viral testing, diagnosis, and self-reported data. Changes over time, from March 2020 to October 2021, in total case counts and changes in case counts by identification source (diagnosis from EHR, measurement from viral testing and self-reported from questionnaire) were also analyzed. For the questionnaires, an analysis of the structure and dynamics of the questionnaires was done which included the amount and type of questions asked, how often and how many individuals answered the questions and what responses were given. In addition, the amount of individuals who provided responses regarding different time segments covered by the questionnaire was calculated along with how often responses changed. The analysis included changes in population level responses over time. The analyses were repeated for COVID and non-COVID individuals and compared responses.ResultsThere were 62 042 distinct participants who had COVID-19, with 49 120 identified through diagnosis, 30 553 identified through viral testing and 934 identified through self-reporting, with many identified in multiple methods. This included vast changes in overall cases and distribution of case data source over time. 6 899 of 9 952 participants completing the exposure questionnaire responded regarding every time period covered by the questionnaire including large changes in response over time. The most common change came for employment situation, which was changed by 74.78% of individuals from the first to last time of asking. On a population level, there were changes as face mask usage increased each successive time period. There were decreases in nearly every COVID-19 symptom from the first to the second questionnaire. When comparing COVID to non-COVID participants, COVID participants were more commonly keyworkers (COVID: 33.76%, non-COVID: 15.00%) and more often lived with young people attending school (61.70%, 45.32%).ConclusionTo develop a robust cohort of COVID-19 participants from the UK Biobank population, multiple types of data were needed. The differences based on time and exposures show the important of comprehensive data capture and the utility of COVID-19 related questionnaire data.

Magnetic sludge-derived biochar for Cu (II) removal: RSM-based preparation and BP artificial neural network adsorption modeling

Magnetic sludge-derived biochar (MSDB) was synthesized using response surface methodology (RSM) optimization, with sludge as the raw material and sodium pyrophosphate as the modifier. The structure and surface properties of MSDB were characterized using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), vibrating sample magnetometer (VSM), and Brunauer-Emmett-Teller (BET) analysis. These analyses revealed that MSDB is rich in functional groups and exhibits magnetic properties, facilitating the adsorption of Cu(II) via complexation and easy separation of MSDB through magnetic means. Batch adsorption experiments showed that under conditions of 25 °C and pH 3.0, with an MSDB dosage of 0.75 g L−1, a Cu(II) removal efficiency of 95.67 % was achieved. Thermodynamic studies demonstrated maximum adsorption capacities of 173.69 mg g−1 at 25 °C, 183.26 mg g−1 at 35 °C, and 197.96 mg g−1 at 45 °C. Additionally, the BP neural network model showed a high coefficient of determination (R2 = 0.9396) and a low mean squared error (MSE = 0.0268) in simulating the MSDB-Cu(II) adsorption process, confirming the robustness of the model in both data simulation and predictive accuracy. This method offers a promising approach for kinetic modeling and predicting adsorption behavior in related fields of study.

On the study of solitary wave dynamics and interaction phenomena in the ultrasound imaging modelled by the fractional nonlinear system

This research work focuses on investigating the propagation of ultrasonic waves, which propagate mechanical vibrations of molecules or particles inside materials. Ultrasound imaging is extensively used and deeply rooted in the medical field. The key technologies that form the basis for many different uses in the area include transducers, contrast agents, pulse compression, beam shaping, tissue harmonic imaging, techniques for measuring blood flow and tissue motion, and three-dimensional imaging. The third-order non-linear β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta$$\\end{document}-fractional Westervelt model has been used as a governing model in the imaging process for securing the different wave structures. The exact solutions of different types, including mixed, dark, singular, bright-dark, bright, complex and combined solitons are extracted. These solutions are obtained by using two newly introduced techniques, namely modified generalized Riccati equation mapping method and modified generalized exponential rational function method. Moreover, breather, lump and other waves are extracted by the assistance of logarithmic transformation and different test functions. The used methodologies are extremely effective and possess substantial computing capacity to effectively address the different solutions with a high level of accuracy in these systems. The techniques used are well-known for being effective, simple, and flexible enough to integrate multiple soliton systems into a unified framework. In addition, we provide 2D and 3D graphs that explain the behavior of the solution at various parameter values, under the influence of β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta$$\\end{document}-fractional derivatives. The results offered in this study may improve the comprehension of the nonlinear dynamic behavior of the specific system and confirm the efficacy of the approaches used. We expect that our approaches will be beneficial for a wide range of nonlinear models and other problems in the related fields.

Ancient Yi Script Handwriting Sample Repository

The ancient Yi script has been used for over 8000 years, which can be ranked with Oracle,Sumerian,Egyptian,Mayan and Harappan,and is one of the six ancient scripts in the world. In this article, we collected 2922 handwritten single word samples of commonly used ancient Yi characters. Each character was written by 310 people respectively, with a total of 427,939 valid characters. We completed continuous handwritten text sampling, written by 250 people, with 5 texts per person, covering topics such as Yi astronomy, geography, rituals, and agriculture. In the process of data collection, we proposed an automatic sampling method for ancient Yi script, and completed the automatic cutting and labeling of handwritten samples. Furthermore, we tested the recognition performance of the sorted data set under different deep learning network models. The results show that ancient Yi script has diverse shape structures and rich writing styles, which can be used as a benchmark data set in related fields such as handwritten text recognition and handwritten text generation.

Numerical Method for the Variable-Order Fractional Filtration Equation in Heterogeneous Media

This paper presents a study of the application of the finite element method for solving a fractional differential filtration problem in heterogeneous fractured porous media with variable orders of fractional derivatives. A numerical method for the initial-boundary value problem was constructed, and a theoretical study of the stability and convergence of the method was carried out using the method of a priori estimates. The results were confirmed through a comparative analysis of the empirical and theoretical orders of convergence based on computational experiments. Furthermore, we analyzed the effect of variable-order functions of fractional derivatives on the process of fluid flow in a heterogeneous medium, presenting new practical results in the field of modeling the fluid flow in complex media. This work is an important contribution to the numerical modeling of filtration in porous media with variable orders of fractional derivatives and may be useful for specialists in the field of hydrogeology, the oil and gas industry, and other related fields.

Beyond the mix: Advancements in simultaneous detection and quantification of human, dog, and cat DNA.

Animal-related crimes have increased with an increase in the number of pets worldwide, underscoring the importance of animal-related biological evidence at crime scenes. Evidence obtained in cases involving dogs and cats often includes a mixture of human and animal DNA. In this study, we developed a method using droplet digital polymerase chain reaction (ddPCR) to simultaneously identify and quantitatively detect human, dog, and cat DNA in mixed samples. HLA-DRA was chosen as a human-specific marker, OR6D7 as a dog-specific marker, and FLAI-K as a cat-specific marker. The species specificity of each target was confirmed using 14 control DNA samples from 11 mammals and 3 birds. Sensitivity tests determined the limit of detection to be 0.0008 ng/μL for human DNA and 0.00061 ng/μL for dog and cat DNA. In the mixture test, each DNA sample was independently and accurately detected in samples containing trace amounts of all three types of DNA. This study demonstrated the effectiveness of applying ddPCR to forensic case samples from dog- and cat-related incidents. We have presented a reliable method for the accurate identification and quantification of human, dog, and cat DNA simultaneously, offering possibilities for advancements in forensic DNA analysis and related fields.

Modeling and Energy Flow Calculation of Integrated Energy System Based on Partial Differential Equation Model

This paper discusses the modeling and energy flow calculation method of integrated energy system based on partial differential equation model. By constructing a model that integrates power, heat, and natural gas networks, we analyze in detail the process of energy transmission, conversion, and storage in the system. In the process of modeling, the influence of compressor in constant compression ratio, constant outlet pressure and constant natural gas flow is specially considered, and the accuracy of the model is verified by specific data. In terms of energy flow calculation methods, we compare the performance of the unified solution method and the decomposition solution method. Data analysis shows that the non-gradient descent iterative method, gradient descent iterative method and decomposition solution method show consistency in calculation accuracy, that is, the calculation results of the three methods are the same. However, in terms of computational efficiency, the gradient descent iterative method shows significant advantages. Specifically, under identical computing conditions, our analysis reveals that the gradient descent iterative method exhibits a convergence rate approximately 30% faster than the decomposition solution method, resulting in a notable reduction of around 25% in computational time. This pivotal observation serves as a solid foundation for selecting a more computationally efficient approach in practical applications. To further enhance the computational efficiency, we have delved into deriving the Jacobian matrix of the model and subsequently proposed an advanced gradient descent iterative calculation technique. Through the actual test, this method not only improves the calculation speed, but also ensures the stability and accuracy of the calculation. The research in this paper not only provides a strong theoretical support for the optimal operation of the integrated energy system, but also provides a valuable reference for future research in related fields. Through specific data analysis, we prove the effectiveness and practicability of the proposed method, laying a solid foundation for the sustainable development of integrated energy systems.

Bibliographical Exploration of Public Relations and Diplomacy: Public, Organisational, and Civil Society Perspectives

Abstract: This paper aims to describe, infer and interpret the corpus of references extracted from the book “Diplomacy, Organisations and Citizens. A European Communication Perspective” (Sebastião & Spínola, 2022), a collective volume published as an output of a three-year research and educational project exploring the intersection of public relations with public, organisational and civil society diplo¬macy, from a European perspective. A mixed methods approach of quantita¬tive and statistical techniques in conjunction with social network analysis (SNA) was applied to a corpus formed out of 785 unique entries corresponding to the book references. Borrowing from bibliometric approaches, the techniques of di¬rect citation networks, co-citation networks, and topic networks were used to map perspectives used in the book. Results point to a clear linguistic preference for English, to a saliency of journal articles overlapping with the increase in re¬search accessibility through digitalisation, to a clear dominance of a few journals coming from the fields of public relations and public diplomacy, and to a clear alignment of the perspectives on public, organisational and civil society diplo¬macy at the intersection of public relations and diplomacy, albeit from a debatable European perspective. The research is relevant to any scholar or practitioner in¬terested in how public relations and the democratised forms of diplomacy intersect and influence each other. It can also serve as a roadmap to how the explo¬ration of the bibliographical universe of a research project can be used as a self-reflection and evaluation tool. Keywords: public relations, public diplomacy, organisational diplomacy, civil society diplomacy, bibliography, social network analysis.

Optimization Analysis of Low-Noise Amplifier

This paper mainly analyzes the important component of a wireless receiver – low-noise amplifiers (LNA). Low-noise amplifiers can reduce the effect of noise on the received signal and amplify signals. For the better development of wireless communication technology, remote control, and other related fields, it is necessary to optimize the design of low-noise amplifiers, so that low-noise operational amplifiers can finally obtain high gain, low noise figure, and other advantages. This paper analyzes the optimization design of LNA in the field of Global Navigation Satellite Systems (GNSS). This paper analyzes a low-noise amplifier design with the operation of concurrent dual-band for GNSS receivers with a single channel. The optimized design of a low-noise amplifier in this field uses a low-cost 0.18µm CMOS tube and adds load capacitances and a feedforward path to reduce the noise figure (NF) of the system. Noise figures in 1.2 GHz and 1.57 GHz bands are reduced by about 0.9 dB. In addition, the high gain, high linearity, and other excellent properties are shown in 1.2 GHz and 1.57GHz. In the application of 5G/6G network technology, the optimized design of Gallium Arsenide (GaAs) PHEMT technology with a gate length of 0.3µmm and inductively degraded common source topology phase structure is adopted. From this optimization, the noise figure is optimized to 1.3-1.4, and the gain of the system is 20-22 dB. At the same time, good linearity is also shown. Then, the prospects of semiconductor materials such as Gallium Nitride (GaN) and Indium Phosphide (InP), which have the advantages of high electron mobility and low-cost design, in optimizing low noise operational amplifiers. To a certain extent, the in-depth study of the optimal design of LNA can improve the technical level of wireless communication, aerospace, and other fields.

From early to future learner corpus research

Abstract The aim of this article is to survey the field of learner corpus research from its origins to the present day and to provide some future perspectives. Key aspects of the field — learner corpus design and collection, learner corpus methodology, statistical analysis, research focus and links with related fields, in particular SLA, FLT and NLP — are compared in first-generation LCR, which extends from the late 1980s to 2000, and second-generation LCR, which covers the period from the early 2000s until today. The survey shows that the field has undergone major theoretical and methodological changes and considerably extended its range of applications. Future developments that are likely to gain ground are grouped into three categories: increased diversity, increased interdisciplinarity and increased automation.

A Brief Analysis of The Economic Impact of Major Sporting Event on The Host City

The study of sports competition is a crucial field of research that comprises subjects such as economics, sociology, and other related fields. Scholars in this endeavour to tackle paramount questions with profound practical ramifications, which includes exploring the qualities and movements that underlie sports competition. Exploring the factors that influence sports competition outcomes and the ways in which these factors shape diverse competitive landscapes is a valuable and significant research area. This research examines the economic impact of major sports events on the host city. The aim of this research is to provide a thorough analysis of the economic consequences that follow from hosting such events. Through a synthesis of existing literature and empirical analysis, the research investigates the various facets of the economic impact of major sports events, encompassing employment, local commerce, tourism, and infrastructure development. The results indicate that such events can yield significant economic gains, ultimately promoting regional growth and development. However, a thorough analysis of the available evidence emphasises the importance of adopting a multidimensional viewpoint that takes into the account the social, cultural, and environmental ramifications. Despite the intricacies and constraints in accurately measuring the magnitude of the effects, this research ascertains that organising major sports events can generate favourable economic consequences for the locality. The results emphasise the significances of thorough analyses and additional research to enhance our comprehension of the economic implications of hosting such events.

Exploring the Formation, Characteristics, and Impact of Consumer Psychological Expectations on Consumer Behavior in the Chinese Environment

Consumer decision-making is a complex process influenced by numerous factors, among which psychological expectations, as a potential force, play a key role in various consumer activities and have a profound impact on consumer purchasing behavior. This study aims to deeply analyze the formation mechanism, typical characteristics, and specific manifestations of consumer psychological expectations in the Chinese consumer market environment, and explore how these psychological expectations affect purchasing decisions. By revealing the inherent laws of consumer psychological expectations, this article aims to provide strategic guidance for enterprises, helping them improve sales performance and customer satisfaction by effectively managing consumer psychological expectations. The results of this study not only help enterprises to more accurately grasp consumer demand, optimize products and services in fierce market competition, but also provide empirical support for the development of consumer behavior theory, thereby enriching and deepening academic research in related fields.

Analysis of Digital Marketing Strategies in the Interactive Entertainment Industry: A Case Study of ‘Valorant’

This study aims to analyze the digital marketing strategies in the interactive entertainment industry and to conduct an in-depth discussion using Valorant as an example. With the advancement of technology and the change in people’s online habits, digital marketing plays an increasingly important role in the interactive entertainment industry. Understanding consumer behavior and intentions can help reflect and improve advertising and related fields. By distributing questionnaires to collect and analyze consumers’ attitudes and reactions to different marketing strategies, the study finds that the synergy between digital marketing and outdoor advertising significantly increased brand awareness and user engagement. Social media advertising attracts potential users, while outdoor advertising enhances brand visual impact and loyalty. Through the analysis of the successful “Valorant” case, this study reveals the critical factors of digital marketing in user acquisition, retention, and stickiness. It explores these strategies’ replicability and innovation in other interactive entertainment products. Meantime provides a valuable empirical reference for the industry.

The Advantage of Board Game with Deep Reinforcement Learning and Causal Inference

With the continuous progress of artificial intelligence technology, the deep reinforcement learning method combining behaviourism and connectionism has shown fantastic performance far beyond the human level in chess games. This paper systematically introduces two mainstream chess games, including the standard algorithms of artificial intelligence technology in chess and Go, including Monte Carlo and deep reinforcement learning, and expounds on their algorithm principles and the core reasons for their strong learning ability. In addition, this paper discusses the limitations of existing methods in interpretability and puts forward the possibility of applying causal reasoning to deep reinforcement learning to solve interpretable problems. This study will provide a valuable reference for practitioners in related fields.

A Review of on China by Henry Kissinger: Insights into Diplomacy and History and its Implications for Afghans

This book review critically examines On China by Henry Kissinger, exploring its significance in the fields of international relations, diplomacy, and history. The review summarizes the book's key themes and sections, with a focus on Chinese foreign policy and the evolution of Chinese leadership. Additionally, it contextualizes the book's relevance for Afghan scholars, policymakers, and students by highlighting China's expanding influence in Afghanistan. The review emphasizes the importance of understanding China’s geopolitical strategies and concludes with insights into how the book can inform future policy decisions.

Translational science and related disciplines.

Translational research moves scientific discoveries and innovations across the development spectrum for a particular target or disease, trying to bridge in a multidisciplinary fashion the gap between laboratory scientific discoveries and practical, real-world applications in medicine and in healthcare. Translational research aims to move research findings across settings, specific languages, methodologies, and study designs, from laboratory to clinical practice and ultimately into community- and population-level health benefits. In contrast, translational science is a distinct field, which evolved over time toward a systematic study and practice of operationalizing the translation of content from one language, ecosystem, environment, contextual landscape, culture, discipline, area, or domain into another. It involves systematic and transdisciplinary integration of knowledge from basic science, clinical research and population science to improve human health, better longevity, and to ensure disease- and disability-free lives. Translational science often uses knowledge, operational frameworks, and specific capabilities borrowed from other specialties, disciplines, and fields such as operations management, implementation and dissemination science, quality improvement and management, project management, public health, intervention science, change management and leadership, decision science, design thinking, functional design, data science, communication and marketing science, etc. The main goal of this article is to open a series of thematic reviews in this journal, introducing the reader to the main definitions, contingencies, touchpoints, and overlapping areas between translational science and these related specialties, disciplines, and fields of study. Transdisciplinary capabilities borrowing from these related specialties can create a robust translational science machinery for health systems, research organizations, and innovation hubs.

Bibliometric and visualized analysis of peripartum respiratory complications from 2004 to 2023.

Peripartum respiratory complications are a major reason for pregnant women's admission to the ICU, even endangers the maternal life. This bibliometric analysis was designed to elucidate the spectrum of diseases and risk factors for various respiratory complications during the peripartum period, as well as the future research directions in this field. Relevant publications were downloaded from the Web of Science Core Collection on November 1, 2023. CiteSpace was utilized for conducting the scientometric study. A total of 2,331 articles and reviews on respiratory complications during pregnancy published between 2004 and 2023 were retrieved, comprising 87,244 co-cited references, originating from 568 institutions across 104 countries/regions. The United States emerged as the leading country in this domain, with Harvard University standing out as the most actively engaged institution. Bibliometric analysis reveals that the current research hotspots include "COVID-19 pandemic," "venous thromboembolism," "respiratory distress syndrome" and "cardiovascular diseases." Meanwhile, "venous thromboembolism," cytokine storm" and supportive management such as "extracorporeal membrane oxygenation" might represent potential future research directions. Over the past two decades, research on respiratory system complications in pregnancy has continually evolved. This study contributes to enabling researchers in the related field to understand future research hotspots and trends, providing information on potential collaborators, institutions, countries, and citation references.

Gerakan Perubahan (Renaissence) Oleh Dinasti Umayyah II (Islam di Andalusia) Terhadap Berkembangnya Intelektual dan Kebudayaan di Eropa

The second period of the Umayyad dynasty, known as the Andalusian Umayyads, had a significant influence on the development of European civilization in the Middle Ages. After the fall of Damascus, this dynasty continued its rule in the Iberian Peninsula with its center in Cordoba. This article aims to analyze the influence of the Umayyad Dynasty II on Europe, especially in the fields of science, art, architecture and cross-cultural relations. The research method used in this article is a literature review, where literature study is a method that involves collecting, evaluating and synthesizing existing literature to answer research questions or understand a particular topic comprehensively. According to Danial and Warsiah, Literary Studies is research carried out by researchers by collecting a number of books and magazines related to research problems and objectives. The findings show that the Umayyad Dynasty in Andalusia not only contributed to the spread of Islamic knowledge, such as astronomy, medicine, and mathematics, but also became a catalyst for the development of science in Europe through intellectual transfer and translation of scientific texts. Apart from that, the architectural style promoted by the Umayyad II Dynasty played a role in the formation of European architectural styles, especially the Gothic and Romanesque styles. Through cultural interactions, the Umayyad II Dynasty introduced irrigation techniques, agriculture, and government systems that inspired European nations. The results of this study underline the importance of the influence of Islamic civilization in Andalusia in the development of European science and culture, which later became the foundation for the Renaissance.

A Case Study of an Antibiotic Discovery Laboratory Autonomous Learning Assignment—An Evaluation of Undergraduate Students’ Disciplinary Bias

Current higher education trends are moving towards interdisciplinary curricula to provide new tools for solving complex issues. However, course design and learning tracks still create divisions between scientific disciplines. This study aimed to evaluate the disciplinary bias of second-year undergraduate students of biotechnology engineering in the organic chemistry laboratory class through a laboratory setting involving blended disciplines. An experiment on antibiotic discovery that integrates parallel and combinatorial organic chemistry syntheses with microbiology techniques was chosen. As a part of an activity, students had free choice in designing the arrangement of the organic compounds and the two bacterial species by setting up the layout for a 96-well plate. The study visually analyzed students’ plate layouts (N = 74) according to discipline classification and the spatial arrangements of organic compounds (e.g., products and libraries). The results identified four themes that are suggested to reflect students’ vertical, lateral, and interdisciplinary thinking, as most were found to be in the procedural knowledge range and between Bloom’s application and analysis dimensions. Using this study’s thematic analysis methodology in chemistry and related educational fields can provide a pedagogical reflective tool and advance personalized teaching and interdisciplinarity.