Related Fields Research Articles

Research on filling missing GNSS precipitable water vapor time series data using the PSORF model combined with reanalysis datasets

Abstract The inversion of precipitable water vapor (PWV) using the Global Navigation Satellite System (GNSS) has advantages such as all-weather observation, high precision, low cost, and high temporal resolution. Currently, long-term GNSS-PWV data has become an important data source for studying climate change. However, due to factors such as equipment failures, observation technology limitations, and estimation model errors, missing data and outliers often occur in real-time or post-processed PWV time series data. Furthermore, the main sources of GNSS-PWV errors are influenced by the atmospheric weighted mean temperature (Tm) and surface meteorological data (pressure and temperature). The results indicate that the European Centre for Medium⁃Range Weather Forecasts Reanalysis v5 (ERA5) dataset exhibits high accuracy in the Chinese region, making it suitable for GNSS-PWV inversion. By utilizing ERA5 meteorological data to calculate hourly GNSS-PWV and conducting accuracy assessments, it is demonstrated that the PWV inverted based on GNSS and ERA5 meteorological parameters possesses high precision. Based on this, this study selects GNSS stations from the Crustal Movement Observation Network of China (CMONOC) where the proportion of missing measured data is less than 8%. By combining ERA5, random forest (RF), and particle swarm optimization (PSO) algorithms, a new model called PSORF is proposed to fill in missing values in GNSS-PWV time series data. The research findings reveal that the R2 and RMSE of PSORF-PWV are 0.98 and 2.16 mm, respectively. Additionally, GNSS stations with more than 8% missing measured data are utilized to validate the accuracy of the PSORF model. A comparative analysis is conducted between the results obtained through the PSORF model and the ERA5-PWV acquired via traditional interpolation methods. The MAE and RMSE of PSORF-PWV are reduced by 21% and 17%, respectively, indicating that the PSORF model excels in filling missing data and effectively enhances the accuracy and reliability of PWV time series analysis. This study not only presents an effective approach for processing missing PWV data but also evaluates the applicability and accuracy of the ERA5 dataset in PWV inversion. This provides crucial technical support and data security for climate change research, short-term humidity field forecasting, and studies in related fields.

Sino-Us Competitive Cooperation Relationship: AIIB’s Projects in Africa and Practical Application of SDGs

Introduction: This article explores the Sino-US competitive cooperation relationship in Africa, focusing on infrastructure development by the AIIB and the DFC. Examining the strategic roles, operational approaches, and impacts of these institutions on African development. It also delves to geopolitical implications, through the African infrastructure, can proves the different trajectory of US and China rivalry in Africa.And also what influences for Sino-US hegemony competition. Using realism and Neo-realism theory as the framework to analysis Sino-US competitive cooperation relationship. And in this article will also talk about the connection between AIIB and DFC investment in Africa and SDG. And how AIIB and DFC investment influence Africa’s SDG to help Africa’s SDGs development. For the Methodology used in this article is qualitative research, can interview some experts in the Africa investment or SDGs development to collect some data and analysis these data. For the research result will also discuss in different factors such as development goals, geopolitical dynamics, Africa’s future prospects. The value of this article is know what is the Sino-US competitive cooperation relationship in Africa, And how these investment help Africa’s development to help Africa achieve SDGs. Like Lake Turkana Wind Power Project in Kenya, is provide affordable and clean energy in Africa, help Africa to achieve No.7 SDGs. Objective: This article aims to analyze how the AIIB and DFC help African infrastructure, and also the development of Africa. Secondly, examining the strategic roles of AIIB and DFC, how these two organizations help the US and China in global competition. Thirdly, to explore the broader geopolitical implications of the Sino-US competitive cooperation relationship in Africa, examining how the activities of AIIB and DFC reflect and influence the geopolitical dynamics between China and the United States. And how AIIB and DFC investment influence Africa achieve SDGs. Theoretical Framework: In this topic, the main concepts and theories that underpin the research are presented. Through realism and Neo-realism stand out, providing a solid basis for understanding the context of the investigation. Method: The methodology adopted for this research comprises is qualitative research method will be used in conducting this research. The qualitative method is used to gather opinions, experiences and thoughts from the research respondents. Data collection was carried out through use interview no matter online or face to face. And also select for some focus group to do the comparison with different factors of the research, and find the connections and how these factors influence with other factors in the research. Results and Discussion: The findings highlight that the contributions of both institutions to African development, emphasizing the complex dynamics that shape their interactions and impact on the continent. And also through the Africa infrastructure how the US and China compete with each other. In the discussion part, it divides as different part to talk about the influence in Africa and Sino-US competition in different periods. Research Implications: The practical and theoretical implications of this article are discussed, providing insights into how the results can be applied or influence practices in the field of Sino-US competitive cooperation relations and how AIIB and DFC investment help Africa to achieve SDGs. These implications could encompass Sino-US relationship, Africa’s development and Geopolitical Dynamics . Originality/Value: This study contributes to the literature by finding how AIIB and DFC investment help Africa’s SDG development in order to try to find Sino-US competitive cooperation way. The relevance and value of this research are evidenced by how the AIIB and DFC investment influence Africa’s develop SDG, and during the process what about Sino-US relations development to prove.

“If it can be done, it will be done:” AI Ethical Standards and a dual role for public relations

This research reports a five-year study with different types of participants to examine questions related to ethics in artificial intelligence (AI) and the use of AI in public relations and professional communication. AI specialists from computer engineering and closely related fields, as well as CCOs, communication directors/managers, public affairs officers, and CEOs participated in this research, explaining and assessing the role of ethics in AI. Through numerous points of data collection, the topic of AI ethics in public relations was examined through a mixed method approach. This study offers insight into the ethics and design of AI systems that communication professionals must not only use in practice but also understand, advise upon, ethically oversee, and occasionally defend in the public sphere when used (or commissioned) by our organizations. After a review of broad literature and longitudinal data from hundreds of sources, recommendations for a more robust framework for AI ethics in public relations are proposed. Ethical considerations and quantum and neuromorphic computing are posed as means to avoid technocracy, and base use of these advanced systems on moral values.

The Interplay Between the Built Environment, Health, and Well-Being—A Scoping Review

Objective: This scoping review aims to investigate the complex interplay between the built environment, health, and well-being and to provide a comprehensive overview of the knowledge needed for crucial health and well-being enhancement in cities. Method: A scoping review method has been chosen using four databases. The first sample was reduced from 2819 papers to 71 papers by implementing exclusion criteria, snowballing, and direct searches to find a relevant final sample. Results: Built environmental elements such as the neighborhood, urban architecture, activities, public spaces, greenery, lights, safety, aesthetics, and amenities were identified to be impactful on health and well-being outcomes. The two-way association of each environmental factor and its criteria with specific types of health and well-being issues such as cancer, cardiovascular diseases, stress, etc. was determined to identify solutions and ways for improvement. Conclusions: This scoping review provides a comprehensive overview of the intricate interplay between the built environment, health, and well-being. By synthesizing existing knowledge of the built environmental factors, it explores the basis for evidence-based strategies to enhance health and well-being. By illuminating theoretical knowledge of the built environment on health and well-being, our findings will provide a deeper foundation of sources and practical insights for related fields.

Intraventricular baclofen for intractable spasticity and secondary dystonia: a frame-based stereotactic approach and case series

ObjectiveIntraventricular baclofen has been reported as an alternative to intrathecal baclofen for managing refractory spasticity and dystonia in some circumstances. In this report, we described a frame-based stereotactic approach for precisely positioning of the infusion catheter into the third ventricle.Material and methodsHigh resolution contrast-enhanced anatomical MR sequences was acquired prior to surgery for pre-planning. Catheter trajectory was planned to pass from the lateral ventricle to the third ventricle through the Foramen of Monro. The surgical procedure was adapted from the frame-based deep brain stimulation surgery. The Touch-Loc kit (SceneRay, China) was used to temporarily secure the catheter in place during the surgery. From July 2022 to December 2022, three patients suffering from intractable spasticity and/or secondary dystonia received IVB successfully using the described technique.ResultsNo severe adverse events, including death, intracranial hemorrhage, infection, catheter migration or fracture, were documented at the last follow-up (range: 12‒24 months). Transient side effects included mild nausea following the initiation of infusion or the increase in infusion rate. All three patients responded to the IVB.ConclusionsThe described frame-based stereotactic technique for IVB catheter implant is feasible and could be quickly mastered by neurosurgeons in related fields. Larger prospective cohorts with longer follow-up periods are necessary to further evaluate the long-term safety and efficacy of this procedure.

Critique beyond relation: The stakes of working with the negative, the void and the abyss

AbstractThe ‘relational turn’ has been widely embraced in Human Geography and related fields over the last couple of decades as an alternative to the hubris of modern and colonial reasoning. Yet, increasingly, concerns over the extent that contemporary conceptualisations are overly ‘generative’, ‘productivist’ and ‘affirmational’ has come to the fore. There is significant interest in the possibilities for more negative understandings, highlighting failure, attrition, voiding, exhaustion, impotentiality, incompleteness and attributes of ‘non‐relation’. We draw out how, to date, most of these approaches have developed a hermeneutic approach, seeking to bring the negative and the non‐relational into the world as forces of disruption and refusal, holding open other possibilities of knowing and being in the world and enabling alternative political imaginaries. This paper seeks to outline an alternative mode of critique, one that places both relational and negative approaches under the scrutiny of an ‘abyssal’ approach. Here, after Fanon, the world violently forged into the global colour line is bifurcated via the construction of the modern subject, capable of reading itself as a subject in the world and through Human Geography as a field of study. In this always already antiblack world, the goal of ‘Abyssal Geography’ is not to continue worlding the modern subject in new ways, but to analyse and critique the mechanisms and shifts in critical thought through which Human Geography continues to salvage and to redeem the purchase of the modern subject and the world.

Bibliometric analysis of chimeric antigen receptor T-cell therapy

Objective: Chimeric antigen receptor T-cell (CAR-T) therapy refers to the genetic material with specific antigen recognition domain and T cell activation signal is transferred into T cells through gene modification technology. By engineering T-cells to specifically target and eliminate tumor cells, CAR-T therapy has shown remarkable efficacy in treating certain hematological malignancies. Understanding its advancements helps optimize therapeutic strategies, enhance patient outcomes, and guide future innovations in immunotherapy. Therefore, this study aims to investigate the progress of CAR-T therapy by bibliometrics. Methods: By using the keywords of “CAR-T therapy” and “immune cells”, all relevant literature were comprehensively searched from the Web of Science. Research trends in related field were analyzed by using VOSviewer, Pajek, Microsoft Excel and Endnote software, to explore research hotspots, development trends, and future directions for CAR-T therapy. Results: The United States emerges as the most productive country in related field, and the institutions with the highest number of publications is the University of Pennsylvania. As for journals, Frontiers in Immunology appears to be one of the most productive journals. Notably, Gottschalk Stephen publishes the largest number of articles. Keyword cluster analysis shows that the current research trend is more focused on immune cell, so as to explore the mechanisms and modalities of CAR-T therapy. Conclusion: This study provides a comprehensive summary and analysis of global research trends in CAR-T therapy. In the past 5 years, the number of high-quality papers in this field has increased significantly. CAR-T therapy has emerged as a beacon of hope for tumor treatment, representing a significant advancement in healthcare for a wide range of patients, including those with major diseases and suboptimal health conditions.

Modeling Civil Aviation Emissions with Actual Flight Trajectories and Enhanced Aircraft Performance Model

Aviation emissions are continuously increasing along with the rapid development of air transportation, and results in the deterioration in regional air quality and the global climate. Accurate emission estimation is of great importance for relevant policies promotion and the sustainable development of the environment. Previous studies focused on the total emissions of a flight and lacked high precision in both spatial and temporal resolutions, especially aviation activities near ground. In this research, we propose an open-sourced emission calculation framework based on actual flight trajectories (TrajEmission), which calculates both the ground and airborne emissions simultaneously according to the configuration parameters, trajectory characteristics, and ambient conditions. We compare the emission results with five emission inventory methods. The results indicate that pollutant (nitrogen oxides, carbon monoxide, and unburned hydrocarbons) emissions in the landing and takeoff (LTO) cycle might usually be underestimated due to a lack of trajectory-based methods. In addition, in the overall results, the method based on the great circle route leads to an overestimation of 56.8% of pollutant emissions compared to the method based on actual routes. We also investigate the extent to which other factors could influence the emission results. To summarize, the TrajEmission framework can build inventories for the whole process of flight movements with high spatial–temporal resolutions and provide solid data support for environmental science and other related fields.

Family Functioning and Cohesion Scale: Validation of a Short Instrument for the Assessment of Intrafamily Relations.

Most available scales for assessing family relationships are lengthy. Our aim was to develop and validate the Family Functioning and Cohesion Scale (FFCS), a self-reported, short instrument consisting of 14 items. The FFCS was validated through its administration to 481 subjects via an online platform. Cronbach's alpha was 0.85 (ranging from 0.83 to 0.86 if any one item was deleted), signifying high internal consistency. The scale can be considered as a sole factor based on its high consistency, while factor analysis produced three factors corresponding to "communication", "anger/resentment/aggression", and "values and beliefs". The test-retest reliability correlation coefficient was found to be 0.88 at a 2-week interval. Regarding external validity, the correlation coefficient of the FFCS with the general functioning subscale of the McMaster Family Assessment Device (FAD) was 0.83. The high measures of consistency, reliability, and validity of the FFCS, combined with its short length, make it a most valuable tool for use by researchers as well as by professionals dealing with families in psychiatry, psychology, social work, or other related fields.

A Novel Fractional High-Order Sliding Mode Control for Enhanced Bioreactor Performance

This research introduces a fractional high-order sliding mode control (FHOSMC) method that utilises an inverse integral fractional order, 0<β<1, as the high order on the FHOSMC reaching law, exhibiting a novel contribution in the related field of study. The application of the proposed approach into a bioreactor system via diffeomorphism operations demonstrates a notable improvement in the management of the bioreactor dynamics versus classic controllers. The numerical findings highlight an improved precision in tracking reference signals and an enhanced plant stability compared to proportional–integral–derivative (PID) controller implementations within challenging disturbance scenarios. The FHOSMC effectively maintains the biomass concentration at desired levels, reducing the wear of the system as well as implementation expenses. Furthermore, the theoretical analysis of the convergence within time indicates substantial potential for further enhancements. Subsequent studies might focus on extending this control approach to bioreactor systems that integrate sensor technologies and the formulation of adaptive algorithms for real-time adjustments of β-type fractional-orders.

UNeXt: An Efficient Network for the Semantic Segmentation of High-Resolution Remote Sensing Images

The application of deep neural networks for the semantic segmentation of remote sensing images is a significant research area within the field of the intelligent interpretation of remote sensing data. The semantic segmentation of remote sensing images holds great practical value in urban planning, disaster assessment, the estimation of carbon sinks, and other related fields. With the continuous advancement of remote sensing technology, the spatial resolution of remote sensing images is gradually increasing. This increase in resolution brings about challenges such as significant changes in the scale of ground objects, redundant information, and irregular shapes within remote sensing images. Current methods leverage Transformers to capture global long-range dependencies. However, the use of Transformers introduces higher computational complexity and is prone to losing local details. In this paper, we propose UNeXt (UNet+ConvNeXt+Transformer), a real-time semantic segmentation model tailored for high-resolution remote sensing images. To achieve efficient segmentation, UNeXt uses the lightweight ConvNeXt-T as the encoder and a lightweight decoder, Transnext, which combines a Transformer and CNN (Convolutional Neural Networks) to capture global information while avoiding the loss of local details. Furthermore, in order to more effectively utilize spatial and channel information, we propose a SCFB (SC Feature Fuse Block) to reduce computational complexity while enhancing the model’s recognition of complex scenes. A series of ablation experiments and comprehensive comparative experiments demonstrate that our method not only runs faster than state-of-the-art (SOTA) lightweight models but also achieves higher accuracy. Specifically, our proposed UNeXt achieves 85.2% and 82.9% mIoUs on the Vaihingen and Gaofen5 (GID5) datasets, respectively, while maintaining 97 fps for 512 × 512 inputs on a single NVIDIA GTX 4090 GPU, outperforming other SOTA methods.

MFHARFNet: Multi-branch feature hybrid and adaptive receptive field network for image segmentation

Abstract Accurate segmentation of medical images is crucial for disease diagnosis and understanding disease changes. Deep learning methods, utilizing encoder-decoder structures, have demonstrated cutting-edge performance in various medical image segmentation tasks. However, the pooling operation in the encoding stage results in feature loss, which makes the network lack the ability to fuse multi-scale information at different levels, hinders its effective perception of multi-scale information, and leads to poor segmentation performance. Drawing inspiration from the U-shaped network, this study introduces a multi-branch feature hybrid attention and adaptive receptive field network (MFHARFNet) for medical image segmentation. Building upon the encoder-decoder framework, we initially devise a multi-branch feature hybrid attention module (MFHAM) to seamlessly integrate feature maps of varying scales, capturing both fine-grained features and coarse-grained semantics across the entire scale. Furthermore, we redesign the skip connection to amalgamate feature information from different branches in the encoder stage and efficiently transmit it to the decoder, providing the decoder with global context feature maps at different levels. Finally, the adaptive receptive field (ARF) module is introduced in the decoder feature reconstruction stage to adapt and focus on related fields, ensuring the model's adaptation to different segmentation target features, and achieving different weights for the output of different convolution kernels to improve segmentation performance. We comprehensively evaluate our method on medical image segmentation tasks, by using four public datasets across CT and MRI. Remarkably, MFHARFNet method consistently outperforms other state-of-the-art methods, exceeding UNet by 2.1%, 0.9%, 6.6% and 1.0% on Dice on ATLAS, LiTs, BraTs2019 and Spine and intervertebral disc datasets, respectively. In addition, MFHARFNet minimizes network parameters and computational complexity as much as possible. The source codes are in https://github.com/OneHundred99/MFHARFNet.

Commercial Law and its Evaluation in International Law

The ease and prevalence of capital movement across international borders has led to its expansion in trade and the economy in recent years, and this may make resolving legal disputes more challenging. As a result of all these changes, national markets are becoming more and more global marketplaces, and commerce is expanding. Legal processes in this process must first be identified, and their characteristics ascertained in order to resolve legal disputes. While research has been done on qualified merchants in commercial law and related fields, no research has been done on qualified merchant requirements on an international scale. This study has, therefore, evaluated the global nature of the qualified trader under commercial law. Semiotic analysis and content analysis techniques were used in the study to evaluate conceptual studies carried out in academic settings. The research findings indicate that while certain national laws exist in the field of commercial law for eligible merchants, significant shortcomings persist in this domain, even within domestic legal frameworks. Confusion in domestic law stems from a number of factors, including the distinction made between the concepts of tradesman and merchant, the definition of "commercial enterprise," and the use of the term "part of" in reference to the requirement of operating a portion of the commercial company. International legal confusion results from inadequate representation of the qualifications of domestic and foreign traders in the legal system, which in turn affects local and national definitions of qualified traders and international activity areas. As a result, both domestically and globally, a more flexible, inclusive, and problem-solving legal strategy is needed.

Improving SME Performance Through the Utilization of Usable Digital Technology in the Gunung Kawi Area, Wonosari, Malang

The development of digital technology has changed the way society consumes information and makes decisions, including in the tourism sector and other related fields, including small and medium enterprises (SMEs) around the tourist areas. The Mount Kawi area, known for its religious tourism, natural beauty, and cultural heritage, seems to continue to attract visitors even though it has not fully recovered as it was before the Covid-19 pandemic. This also impacts the development of the performance of existing SMEs. This community service aims to introduce user-friendly digital marketing technology to small and medium enterprises (SMEs), so they do not have to rely solely on the local market. The approach used is the initiation model, which involves stages of introduction, demonstration, evaluation, improvement, and reinforcement. The participants of the event consisted of 20 SMEs, ranging from batik to various types of food. The instruments for success used are observation sheets and portfolios. The results of the activities show an increase in digital knowledge among SMEs, particularly in utilizing social media for product content that supports online marketing strategies, as well as the ability to create content and operate digital technology based on market feasibility. The recommendation from this community service activity is the need for assistance in certifying their products to enhance consumer trust.

Diagnostic and Dialogic OD Approaches in a Collaborative Inquiry for Change: How and Why are They Successfully Coapplied?

Change leaders who want to invite members’ spirit of inquiry face a challenge; the conditions under which change practitioners successfully blend the strengths of diagnostic and dialogic approaches are not explicitly incorporated within the established theories. This article aims to describe how changing meaning-making systems (in other words, changing mindsets) can be crucial in facilitating successful coapplication of diagnostic and dialogic approaches. A new conditional combination (shared focus on realizing desired performance and change agents’ dialogic anchoring) for the emergence of the practitioners’ integrative mindset is examined, and its implications for research in blending diagnostic and dialogic OD approaches and related fields are discussed.

Organizational Support as an Influencer of Teachers’ Performance in Chinese Colleges and Universities

This study aims to explore the relationship between organizational support and faculty performance in Chinese higher education institutions in order to fill the gaps in the existing literature and provide new insights into human resource management in higher education. Given the importance of university faculty performance in the field of higher education, this study has important theoretical and practical implications. This study expects to provide solutions to improve faculty performance and to have an impact on policies/practices related to organizational support in higher education. The study used quantitative research methods to obtain data by means of questionnaires. The subjects of the study were Lingnan Normal University, Guangzhou University and Zhanjiang College of Science and Technology, and the sample size was 359. For data analysis, the study utilized SPASS statistical software and methods such as mean, standard deviation, t-test, one-way ANOVA and Pearson r to ensure the accuracy and reliability of the results. Ethical guidelines were followed during the study to ensure the validity and fairness of the study. The results of the study indicate that organizational support positively and significantly influences the performance of college teachers, supporting the research hypotheses and theories. Through an in-depth analysis of the data/results, this study reveals that organizational support (Vocational support, Instrumental support, Emotional support, Adaptive support, Organizational equity, psychological contract) on teacher performance (Task performance, Relationship Performance, Adaptive Performance) in higher education. In addition, the study found that providing teachers with the necessary tools and resources is particularly important in promoting good relationships with colleagues and leaders. This provides a fresh perspective for research in related fields. The findings of this study are instructive for college and university administrations to develop organizational support policies to improve faculty performance and provide a foundation for subsequent research.

DenseFusion-DA2: End-to-End Pose-Estimation Network Based on RGB-D Sensors and Multi-Channel Attention Mechanisms.

Notably, 6D pose estimation is a critical technology that enables robotics to perceive and interact with their operational environment. However, occlusion causes a loss of local features, which, in turn, restricts the estimation accuracy. To address these challenges, this paper proposes an end-to-end pose-estimation network based on a multi-channel attention mechanism, DA2Net. Firstly, a multi-channel attention mechanism, designated as "DA2Net", was devised using A2-Nets as its foundation. This mechanism is constructed in two steps. In the first step, the essential characteristics are extracted from the global feature space through the second-order attention pool. In the second step, a feature map is generated by the integration of position and channel attention. Subsequently, the extracted key features are assigned to each position of the feature map, enhancing both the feature representation capacity and the overall performance. Secondly, the designed attention mechanism is introduced into both the feature fusion and pose iterative refinement networks to enhance the network's capacity to acquire local features thus improving its overall performance. The experimental results demonstrated that the estimation accuracy of DenseFusion-DA2 on the LineMOD dataset was approximately 3.4% higher than that of DenseFusion. Furthermore, the estimation accuracy surpassed that of PoseCNN, PVNet, SSD6D, and PointFusion by 8.3%, 11.1%, 20.3%, and 23.8%, respectively. The estimation accuracy also shows a significant advantage on the Occluded LineMOD and HR-Vision datasets. This research not only presents a more efficient solution for robot perception but also introduces novel ideas and methods for technological advancements and applications in related fields.

Mapping the evolution and impact of ketogenic diet research on diabetes management: a comprehensive bibliometric analysis from 2005 to 2024

ObjectiveThe ketogenic diet (KD) has been explored for diabetes management; however, a quantitative synthesis of its specific effects on diabetes has not yet been conducted. This study aims to examine the current status and research hotspots of KD in diabetes management from 2005 to 2024, providing a reference for future research.MethodsWe retrieved articles published between 2005 and 2024 from the Web of Science database and analyzed them using R software, VOSviewer, and CiteSpace.ResultsThis study includes 432 relevant publications. From 2005 to 2024, the volume of literature in this field has shown a steady upward trend, with a notable increase from 2017 to 2021, and a slight decline observed from 2021 to 2023. The United States is the leading country in terms of the number of publications, followed by China, Australia, and Canada. The United States not only leads in publication volume but also maintains a broader international collaboration network. Nutrients and the American Journal of Clinical Nutrition are the most frequently published and cited journals. Current research hotspots primarily focus on the impact of KD on blood glucose control, insulin resistance, and lipid metabolism in diabetic patients. Mechanistic studies on KD in diabetes management concentrate on aspects such as the “regulation of genes by β-hydroxybutyrate,” “anti-inflammatory effects,” and “oxidative stress.” The role of the gut microbiome is also emerging as an important research area. Currently, exploring the application of KD in managing different age groups and types of diabetes has become a significant research trend.ConclusionAs an emerging dietary intervention, KD is gradually attracting widespread attention from researchers around the world and is expected to become a major research focus in the future for diabetes management and control. This paper provides a systematic review and analysis of the current research status and hotspots of KD in diabetes management, offering important references and insights for future research in related fields.

Progress on the Sound Absorption of Viscoelastic Damping Porous Polymer Composites.

Porous polymer composites (PPC) have developed rapidly recently, which are widely used in various industrial fields. Viscoelastic damping is an important behavior of porous polymer composites, and it can determine the sound absorption for noise reduction applications. This review has mainly covered the viscoelastic damping and sound absorption of porous polymer composites. Different fabrication approaches of porous polymer composites are gathered. The mechanism of viscoelastic damping behavior is described, and also the sound absorption properties. Followed by the introduction of enhanced sound absorption of viscoelastic damping porous polymer composites, including the incorporation of fillers, microstructures modification, combination with nanofibrous materials, and multilayer configuration, etc. The incorporated fillers can effectively adjust the interfacial area in composites, and obtain desired bonding conditions. Microstructures modification is an effective tool to improve the morphologies of both polymer matrix and fillers, which can be achieved by chemical treatment and surface coating. The combination with lightweight nanofibrous layer can increase the low frequency absorption. The configuration of multilayer composites can improve both acoustical and mechanical properties for engineering applications. It is hoped that this comprehensive review is benefit for the promising development of porous polymer composites in related fields.

Ideas and Methods of Cognitive Science in the Studies of International Relations and Foreign Policy

International studies have recently witnessed a renaissance of interest in the study of decision-making patterns related to the influence of individual and group actors and the resulting need to understand their deep psychology, the nature of their incentives and motivations. Such studies update the application of behavioral and cognitive sciences in the field of international relations and foreign policy, and encourage the adaptation of the methodology of specialized disciplines to solve complex socio-political problems. The present paper is an attempt to inventory key research subject areas and related literature, as well as to demonstrate the application of existing theories to the analysis of current political issues.