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"Decolonizing Geography: An Introduction" by Sarah A. Radcliffe explores the decolonization of Anglophone geographical curricula. The book emphasizes the importance of approaching fieldwork with humility, respecting local knowledge, and avoiding the imposition of Western paradigms. It calls for action to avoid blinders, respect counternarratives, question official histories, acknowledge privilege, employ collaborative research, and entertain alternative epistemologies. The book also highlights the significance of indigenous environmental knowledge in physical geography and addresses the lack of diversity in the discipline. Overall, "Decolonizing Geography" offers a comprehensive exploration of decolonial approaches in geography and provides practical examples and suggestions for further research. [Extracted from the article]

"Settler Colonial City: Racism and Inequity in Postwar Minneapolis" by David Hugill examines the history of racism, inequity, and settler-colonial structures in Minneapolis, particularly focusing on the post-World War II era. The book explores the impact of urban change, racialized policing, and American imperialism on marginalized communities, with a particular emphasis on Indigenous peoples. Hugill highlights the structural barriers faced by marginalized groups and the need to dismantle white supremacist and settler-colonial structures. While the book primarily focuses on the violent aspects of settler-colonial urban policy, it also touches on the need to examine more subtle elements such as access to education, healthcare, and legal services. Overall, the book provides a critical perspective on the history of Minneapolis and challenges the perception of the city as progressive and inclusive. [Extracted from the article]

The Continental Congress foray into printed money during the American Revolution was so disastrous that the United States printed no more money for nearly a century, the one exception being a brief period during the War of 1812. After that Congress chartered and unchartered its national bank twice. The American economy henceforth (1816–1836) was often structurally short of coins, and without any national coinage Americans had to find substitute forms of currency to finance the burgeoning economy. The Supreme Court ruled that sovereign States and individuals could authorize both State and private banks to issue their own notes. In consequence, nearly all paper money in circulation was either State or private banknotes based on a limited reserve of gold. This generally proved insufficient to adequately fund major infrastructure projects. The federal government also had no institution for raising or transferring large amounts of money to fund these national improvements. Nonetheless, Hamilton's U.S. Bank, without the help of a national currency, was an institutional precursor for what would not take final form until 1913. There would be no Federal Reserve today without the Whig-Republican agenda institutionally incarnated in the First and Second U.S. Bank. [ABSTRACT FROM AUTHOR]

Residential owned solar panels mounted on roof-tops generated 1.4% of the U.S. electricity supply in 2022. Utilities compensate residential customers using a net metering system by which each kilowatt-hour generated by the customer reduces the customer's bill by the amount the utility charges for one kilowatt. Despite the small impact of roof-top solar on the total market, in 2022, thirty-two states conducted ninety-four proceedings investigating whether to change the net metering system. In these proceedings, utilities advocated changing the rates to discourage residential investment in solar panels. Utilities argue that net metering provides a subsidy to solar customers because the rate the utility pays is greater than the avoided cost of energy. That excess payment allows solar customers to avoid paying for the distribution network. The cost of the distribution network is shifted to non-solar customers. This article will evaluate these claims. It will show that if the social cost of carbon were in the calculation, it would generate a Kapp cost shift from solar customers to non-solar customers. The size of the Kapp cost shift is greater than the cost of distribution networks, reversing any private cost shift that utilities have estimated. [ABSTRACT FROM AUTHOR]

In cotton yarn bundles and fabric layers, wicking and rate are accounted as crucial indigenous liquid transportation properties, playing a significant role in temperature reduction on their surfaces and being used to extend the food and agricultural storage life. In this article, manual test methods are described to measure water wickability and wicking rate of cotton yarn bundles and plain weave fabric layers. These methods described the water flow through the in-plane surface of yarn bundles and fabric layers oriented in either vertical or horizontal lines without external force. The wicking lengths and wicking growth rates in both untreated and treated cotton yarn bundles and fabric samples in either in-plane vertical or horizontal orientations were compared. The highest to lowest wicking length and rate were found in the treated yarn bundles, treated fabric layers, untreated yarn bundles, and untreated fabric strips, respectively. The wicking height and length obtained in untreated yarn bundles and untreated fabric layers was lower than the Kraft paper. The higher wicking and rate values indicate a considerable potential for liquid water migration. The results indicated that treated yarn bundles and fabric layers that are oriented horizontal direction are the best options for constructing capillary evaporative cooling. [ABSTRACT FROM AUTHOR]

"Near Woods: A Year in an Allegheny Forest" by Kevin Patrick is a book that explores the natural and cultural phenomena of White's Woods, a 500-acre stand of mixed hardwood forest near Indiana, Pennsylvania. The author, who has lived in the area for three decades, highlights the beauty and richness of this local sylvan gem, emphasizing the importance of appreciating and exploring the forests in our own backyards. The book combines geomorphological, natural historical, and physical and cultural geographic background to provide a comprehensive understanding of the area. Through vivid prose and stunning photography, Patrick invites readers to stop, listen, and interpret the wonders of nature. [Extracted from the article]

Quantitative geographical methods have played an important role in COVID-19 research. To complement and extend previous review studies, we conduct a scoping review of COVID-19 studies employing quantitative geographical approaches by focusing on 331 papers published in 45 journals in geography, urban studies, and planning. We identify four major research themes (clusters): (1) how SARS-CoV-2 viruses spread in cities, (2) the COVID-19 mortality (death) rates and their association with socioeconomic variables, (3) how the COVID-19 pandemic changed people's mobilities, and (4) how the COVID-19 pandemic affects air pollution. We conclude that spatial models play a key role in COVID-19 quantitative geographical approaches, and human mobility is an important and widely studied topic. We also reveal a lack of research focusing on environmental pollution (other than air pollution) that potentially worsened during the pandemic. [ABSTRACT FROM AUTHOR]

The article discusses the importance of the peer-review process in contributing to the field of research. The author shares a positive experience with an author who received constructive feedback on their declined paper and expressed gratitude for the opportunity to improve their work. The article also explains the peer-review process used by the journal, which involves a desk review, gatekeeper review, and full peer-review. The goal of the process is to ensure that published papers contribute to the body of knowledge in the field. The article acknowledges that the peer-review process may have imperfections but emphasizes the volunteer efforts of the community in sharing research and providing expertise. [Extracted from the article]

This article sets out the findings of a systematic review on research into career guidance policy in the Nordic countries between 2008 and 2022. In total 60 papers were reviewed from across the Nordic region. They focused on national career guidance systems, career guidance systems for young people, the adult guidance system and career guidance for migrants. The corpus proved to be methodologically diverse with studies utilizing a wide range of different research strategies, although important differences were found between academic and grey literature. Most of the papers reviewed were atheoretical, with the remaining, mainly academic, literature drawing heavily on critical theory. The thematic analysis identified four major themes in the corpus: the context for career guidance policy; career guidance provision and practice; technologies of governance; and beneficiaries and outcomes of career guidance policies. The findings are discussed in relation to the strengths and weakness of the corpus and used to propose a research programme for the next 15 years. [ABSTRACT FROM AUTHOR]

"Big Bend National Park: Mexico, the United States, and a Borderland Ecosystem" by Michael Welsh is a historical exploration of Big Bend National Park, situated on the border between Mexico and the United States. The book examines the unique landscape of the park, shaped by the Rio Grande river, and the challenges posed by its borderland ecosystem. Welsh discusses the efforts of conservationists, politicians, and scientists in establishing the park and highlights the potential for binational cooperation and collaboration. The book also addresses the tensions between preservation and development in national parks and the need to navigate the changing cultural and political landscape. While the book lacks an examination of the park's future in the face of climate change and public policy, it offers valuable insights for students and scholars interested in national identity, border relations, and environmental protectionism. [Extracted from the article]

"Wayfaring Strangers: The Musical Voyage from Scotland and Ulster to Appalachia" is a book by Fiona Ritchie and Doug Orr that explores the cultural pathways of traditional Scottish and Irish folk music as it traveled to Appalachia. The book examines the influences of Welsh, English, German, Dutch, French, African American, and Cherokee cultures on these songs. It is structured into three main sections and includes photographs, maps, and sidebars covering various topics related to folk music. The authors also exchange letters discussing their perspectives on Old and New World music. The book sheds light on the history of American folk music and its connection to immigrant experiences. It includes a contextual timeline, resource centers, a discography, and a bibliography for further exploration. Scholars and music enthusiasts will find this book to be a valuable resource. [Extracted from the article]

Copyright of European Journal of Psychotraumatology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the maturity of information and communication technology (ICT), numerous innovative applications are proposed in different arenas including smart living environments. Technology-enabled smart living has transformed the traditional living system to an enhanced user satisfaction model by providing a balanced environment, thus, securing the residents from disruptions and risks. Besides these magnified advantages, it is found almost full of faints in emergency situations. The researchers and architects put their full potential towards the development of new applications, but no significant attention is paid to analyze the existing designs to identify flaws and suggest enhanced solutions accordingly. To bridge this gap in the literature, this paper presents a comprehensive review to evaluate the capabilities of available smart home designs to counter any emergency situations. Along with highlighting safety, healthcare, and many other unwanted challenges, we also discussed the key problems that obfuscate the trustworthiness of smart homes for its residents. Moreover, the design limitations to present an early alarming and automatic evacuation mechanism especially for deaf, blind, and other visually impaired people is another big challenge to tackle. Finally, we elaborate on the limitations of available smart home solutions and suggest various open research problems that require further development. [ABSTRACT FROM AUTHOR]

The market of courier, express and parcel services (CEP) is characterized by the presence of requests for the transfer of goods and documents. During the COVID-19 pandemic, the global postal and CEP infrastructure played a key role in enabling governments to respond to the emerging challenges. In this paper, the competitiveness and the rank of four observed CEP service providers are analyzed using ratio indicators, the Ordinal Priority Approach method (OPA) and the Weighted Sum Method (WSM). We use the OPA method because there is no need for a pairwise comparison matrix and no need for normalization. The paper aims to examine the liquidity, economy and profitability of CEP service providers to get a true picture of the situation in the market of postal and CEP services in the Serbia. In the analysis of business performance and the implementation of the OPA method, the opinions of experts were taken into account. This paper yields a key insight: the identification of the top-performing provider within the group of service providers is accomplished through the utilization of both the OPA and WSM methods. Sensitivity analysis is shedding light on the varying impact of the provider's rank on the final ranking of the CEP providers. [ABSTRACT FROM AUTHOR]

Nowadays, an increasing number of crises worldwide, triggered by climate extremes, natural and human-made hazards, the coronavirus pandemic, and more, pose a high pressure on crisis, emergency, and disaster management. Spatial data and Volunteered Geographic Information (VGI) are key issues in the successful and immediate response to crises. This paper aims to explore the use of VGI in crisis management, including emergency and disaster management, based on a scoping review of existing literature in English for five years (2016–2020). Specifically, the research intends to answer Scoping Review Questions (SRQ) regarding the use of VGI in crisis, emergency, and disaster management, and the verified cases' spatial distribution, the VGI sources utilized (e.g. OpenStreetMap – OSM, Crowdsourcing, Twitter), the types of hazards (e.g. natural and human-made hazards, pandemic), the specific tasks in crisis, emergency or disaster management and VGI use in the management of actual crisis events, e.g. COVID-19 pandemic, Hurricane Katrina, etc. Eligible papers on VGI use in crisis, emergency, and disaster management are geolocated based on first-author affiliation, and as a result, a spatial bibliography is provided. Thus, the term Spatial Scoping Review is introduced. Scoping Review Questions are answered, and the results are analyzed and discussed. Finally, implementing the "VGICED Atlas", a web atlas, permits the publication of the research results to a broad audience and the visualization of the analysis with several interactive maps. [ABSTRACT FROM AUTHOR]

Poverty has always been a global concern that has restricted human development. The first goal (SDG 1) of the United Nations Sustainable Development Goals (SDGs) is to eliminate all forms of poverty all over the world. The establishment of a scientific and effective localized SDG 1 evaluation and monitoring method is the key to achieving SDG 1. This paper proposes SDG 1 China district and county-level localization evaluation method based on multi-source remote sensing data for the United Nations Sustainable Development Framework. The temporal and spatial distribution characteristics of China's poverty areas and their SDG 1 evaluation values in 2012, 2014, 2016, and 2018 have been analyzed. Based on the SDGs global indicator framework, this paper first constructed SDG 1 China's district and county localization indicator system and then extracted multidimensional feature factors from nighttime light images, land cover data, and digital elevation model data. Secondly, we establish SDG 1 China's localized partial least squares estimation model and SDG 1 China's localized machine learning estimation model. Finally, we analyze and verify the spatiotemporal distribution characteristics of China's poverty areas and counties and their SDG 1 evaluation values. The results show that SDG 1 China's district and county localization indicator system proposed in this study and SDG 1 China's localized partial least squares estimation model can better reflect the poverty level of China's districts and counties. The estimated model R2 is 0.65, which can identify 72.77% of China's national poverty counties. From 2012 to 2018, the spatial distribution pattern of SDG evaluation values in China's districts and counties is that the SDG evaluation values gradually increase from western China to eastern China. In addition, the average SDG 1 evaluation value of China's districts and counties increased by 23% from 2012 to 2018. This paper is oriented to the United Nations SDGs framework, explores the SDG 1 localized evaluation method of China's districts and counties based on multisource remote sensing data, and provides a scientific and rapid regional poverty monitoring and evaluation program for the implementation of the 2030 agenda poverty alleviation goals. [ABSTRACT FROM AUTHOR]

The launch of large language models (LLMs) like ChatGPT in late 2022 and the anticipated arrival of future GPT-x iterations have marked the beginning of the generative artificial intelligence (GAI) era. We conducted a systematic review of how to integrate LLMs including GPT and other GAI models into geospatial science, based on 293 papers obtained from four databases of academic publications -- Web of Science (WoS), Scopus, SSRN and arXiv -- 26 papers were eventually included for analysis. We statistically outlined the share of domains where LLMs and other GAI models, the type of data that have been used for these models, and the modelling tasks and roles that they play. We also pointed out the challenges and future directions for the next research agenda -- along with which we could better position ourselves in the mainstream of science and the cutting-edge research paradigm as others leverage insights from the growing data deluge. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic had a significant impact on the education sector, forcing institutions, instructors, students, and parents to adapt to online or hybrid learning models. The Journal of Statistics & Data Science Education has published fifteen papers that describe approaches to addressing the challenges of the pandemic, with a focus on improving inclusive and flexible learning environments. The current issue of the journal features ten papers on various topics, including emergency online teaching, technology-enhanced instruction, and engaging students with COVID-19 journal articles. The journal also explores other timely topics such as causal inference, personalized education, and case studies using data from the U.S. Geological Survey. The collection of papers is available for free online and can provide valuable insights for the community to learn from this challenging time. [Extracted from the article]

This document discusses the importance of understanding the physicochemical properties of aerosol particles in order to comprehend aerosol dynamics and transformations. It highlights the need for new laboratory, theoretical, and modeling studies to address barriers in our understanding of aerosol physical chemistry. The document mentions two conferences that focused on aerosol physical chemistry and microphysics, which provided a platform for interdisciplinary discussions and the exchange of ideas. The document also introduces a special issue that collects papers on topics such as particle surfaces, particle phase, and particle acidity, which address complex aspects of aerosol physical chemistry. Several papers in the special issue explore how different physical properties of aerosols can influence heterogeneous reaction rates involving atmospheric organics. Other papers examine the limitations of experimental techniques and propose improvements, while some highlight the applications of aerosol microphysics in areas such as ice nucleation, cloud activation, and bioaerosols. The document concludes by expressing gratitude to the authors and hopes that the collection stimulates further discussion on these important topics. [Extracted from the article]

The OECD is an inevitable force in contemporary education. This paper illustrates how the OECD affects recent education policy-making in Iceland with a particular focus on recent documents establishing the new Education Policy 2030 in Iceland and on OECD reports that directly relate to this policy. We illustrate the relationship between these documents both topically and chronologically and use Marilyn Strathern's (2006) reasoning about policy making by bullet-points to understand these policy products. Our conclusions are that education policy 2030 is a clear step into a more Nordic tradition of policymaking, in terms of basing policy in previous works and official reports as well as increasing involvement by stakeholders. However, they are characterized by politically admirable, albeit lofty, formulations of ambitions and focus areas, rather than measurable, actionable and implementable policies. The OECD is given a great influence not only as a referential point and a tool to legitimate particular policies, but also a post-hoc policy-implementation adviser and auditor of the policy. Even though the OECD is asked for evaluation of the visionary policy and seems to be the solution to the perceived lack of professional procedure in Icelandic governance, the time-frame seems not to have allowed a thorough use of their advice. [ABSTRACT FROM AUTHOR]

The task of change detection (CD) in optical and SAR images is an ever-evolving and demanding subject within the realm of remote sensing (RS). It holds great significance to identify the target areas by using complementary information between the two. Due to the distinct imaging mechanisms employed by optical and SAR sensors, effectively and accurately identifying changing regions can be challenging. To this end, a novel heterogeneous RS images CD network (Twin-Depthwise Separable Convolution Connect Network, TDSCCNet) is proposed in this paper. Image domain transformation is a front-end task, while the back-end employs a single-branch bilayer depthwise separable convolutionconnected encoder-decoder to accomplish CD work. Specifically, first, the cycle-consistent adversarial network (CycleGAN) serves to integrate the optical and SAR visual domains, and a consistent feature expression is obtained. Second, the single-branch encoder structure of bilayer depthwise separable convolution is employed to realize change feature extraction. Finally, the multiscale connected decoder reconstructed by change map is utilized to reconstruct the original images and solve the local discontinuities and holes in the binary change map. Multiscale loss is designated for optimizing the global and local effects to alleviate the class imbalance problem. It was tested on four representative datasets from Gloucester, Shuguang Village, Italy and WV-3 datasets with an overall accuracy of 97.36%, 97.01%, 97.62%, and 98.01% respectively. By comparing the existing methods, experimental results confirmed the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Despite natural image super-resolution (SR) methods have achieved great success, super-resolution methods for hyperspectral image (HSI) with rich spectral features are still a very challenging task. Furthermore, due to the diversity of HSI captured by different cameras, their degradation conditions vary. Currently available HSI SR methods are mainly based on fixed degradation models, and their performance is severely affected when the actual degradation does not match the assumed degradation model. To address this issue, this paper proposes a single-band hyperspectral image super-resolution (SBHSR) method for HSI. This method assumes that the degradation Gaussian blur kernel parameters of the HSI are unknown, and adapts to various degradation conditions by conducting blind super-resolution on the image. It also combines another band with better spatial structure as an auxiliary band for feature fusion. To address the spectral differences between the super-resolution band and the auxiliary band, we use the Spatial Adaptation Module (SAM) to map the feature distribution, ensuring consistent spectral brightness between the auxiliary band and the super-resolution band. Due to the use of blind degradation super-resolution method, our method is more robust compared to previous HSI SR methods. Additionally, as it is specifically designed for single-band hyperspectral image super-resolution, it has the advantage of being faster and more efficient. Experimental validation on two hyperspectral datasets demonstrates the superiority of our method, as it improves the spatial resolution of the image while preserving the spectral features, and performs better than existing blind super-resolution methods. [ABSTRACT FROM AUTHOR]

Existing deep learning-based change detection networks encounter challenges related to the temporal dependency inherent in dual-temporal images. In this study, a weight-shared dual-difference change detection network (DDCDNet) model is proposed based on feature extraction networks. The model employs feature discrimination modules fused with spatial and channel attention mechanisms at different hierarchical levels of the backbone network. In the encoding phase, the tiny version of the Swin Transformer is utilized as the backbone network, with a weightsharing strategy applied to extract feature information from bitemporal remote sensing images. The proposed model in this paper is experimented on the LEVIR-CDþand DSIFN datasets, achieving F1-scores (F1) of 87.71% and 85.79%, recalls of 83.87% and 81.17%, and IoU (Intersection over Union) scores of 78.11% and 75.12%, respectively. These results indicate that the proposed model significantly outperforms other comparative models, demonstrating a better capability of identifying temporal changes in buildings, excellent generalization capability. [ABSTRACT FROM AUTHOR]

This paper is intended to summarize the research conducted during the first 2 years of the Dragon 5 project 59,332 (geophysical and atmospheric retrieval from Synthetic Aperture Radar (SAR) data stacks over natural scenarios). Monitoring atmospheric phenomena, encompassing both tropospheric and ionospheric conditions, holds pivotal significance for various scientific and practical applications. In this paper, we present an exploration of advanced techniques for estimating tropospheric and ionospheric phase screens using stacks of Synthetic Aperture Radar (SAR) images. Our study delves into the current state-of-the-art in atmospheric monitoring with a focus on spaceborne SAR systems, shedding light on their evolving capabilities. For tropospheric phase screen estimation, we propose a novel approach that jointly estimates the tropospheric component from all the images. We discuss the methodology in detail, highlighting its ability to recover accurate tropospheric maps. Through a series of quantitative case studies using real Sentinel-1 satellite data, we demonstrate the effectiveness of our technique in capturing tropospheric variability over different geographical regions. Concurrently, we delve into the estimation of ionospheric phase screens utilizing SAR image stacks. The intricacies of ionospheric disturbances pose unique challenges, necessitating specialized techniques. We dissect our approach, showcasing its capacity to mitigate ionospheric noise and recover precise phase information. Real data from the Sentinel-1 satellite are employed to showcase the efficacy of our method, unraveling ionospheric perturbations with improved accuracy. The integration of our techniques, though presented separately for clarity, collectively contributes to a comprehensive framework for atmospheric monitoring. Our findings emphasize the potential of SAR-based approaches in advancing our knowledge of atmospheric processes, thus fostering advancements in weather prediction, geophysics, and environmental management. [ABSTRACT FROM AUTHOR]

In this paper, the Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technology is adopted to monitor the Line of Sight (LOS) displacement of Fushun West Opencast Coal Mine (FWOCM) and its surrounding areas in northeast China using Sentinel-1 Synthetic Aperture Radar (SAR) images acquired from 2018 to 2022. The spatial-temporal evolution of urban subsidence and the south-slope landslide are both analyzed in detail. Comparison with ground measurements and cross-correlation analysis via cross wavelet transform with monthly precipitation data are also conducted, to analyze the influence factors of displacements in FWOCM. The monitoring results show that a subsidence basin appeared in the urban area near the eastern part of the north slope in 2018, with settlement center located at the intersection of E3000 and fault F1. The Qian Tai Shan (QTS) landslide on the south slope, which experienced rapid sliding during 2014 to 2016, presents seasonal deceleration and acceleration with precipitation, with the maximum displacement in vicinity of the Liushan paleochannel. The results of this paper have fully taken in account for the complications of large topographic relief, geological conditions, spatial distribution and temporal evolution characteristics of surface displacements in opencast mining area. The wide range and long time series dynamic monitoring of opencast mine are of great significance to ensure mine safety production and geological disaster prevention in the investigated mining area. [ABSTRACT FROM AUTHOR]

Doing co-design and co-production is challenging, resource intensive, and outcomes do not always translate into action. Evaluations of processes are needed to identify what enables and constrains 'co' efforts. This paper draws on the findings of an evaluation of a co-design process undertaken by Aotearoa New Zealand's Biological Heritage National Science Challenge, Ngā Koiora Tuku Iho (BHNSC) in 2019. The independent evaluation, commissioned by the BHNSC, draws on process observations and 25 semi-structured interviews with BHNSC leaders and process participants. In this paper, we present key insights from the evaluation through the application of co-production quality assessment principles and a knowledge governance conceptual framework. Our analysis identifies the BHNSC's values as a critical factor in its journey to conduct a process that would foster collaboration between mātauranga Māori and Western science knowledge systems and deliver impact-focused biodiversity and biosecurity research. We propose an additional principle for assessing the quality of co-production processes: values-inspired. [ABSTRACT FROM AUTHOR]

Central bank communication plays a crucial role in the conduct of monetary policy, yet the research on central bank communication, while growing, is still scarce. In this paper, we analyze the communication reaction function of the European Central Bank (ECB) through topic-based indices derived from the bank's speeches. These indices are used as dependent variables in policy and communication reaction function models, as suggested by recent literature. The topics are extracted using Latent Dirichlet Allocation (LDA), a popular text mining algorithm for topic extraction. The ECB has recently reviewed its monetary policy strategy, which led to an increase in studies incorporating the new methods offered by text mining for analyzing the policy reaction function of the bank. We show how indices built through topic modelling can be used to study the communication reaction function of a central bank, and we examine which variables are significant for every topic communicated by the ECB. [ABSTRACT FROM AUTHOR]

Unlike existing flexible display technologies such as foldable, rollable, or slidable displays, stretchable displays can change the size of surface areas. Furthermore, they can be transformed into a multi-curvature shape in any direction. These may be the reasons they are often called freeform displays. Stretchability, the extent displays can be stretched, is one of the most important performance factors of stretchable displays. The length ratio before and after stretching is widely utilized to represent one- or two-dimensional stretchability. However, the length ratio cannot be directly applied to three-dimensional stretching. Hence, this paper introduces new measures of three-dimensional stretchability. The pros and cons of the proposed measures are explained. In addition, experimental results to evaluate the proposed measures' performance are presented. [ABSTRACT FROM AUTHOR]

Zero watermarking constructs the watermark information according to the characteristics of the original data, without changing the data structure and data accuracy. Maintaining high data accuracy is the premise of building information modelling (BIM) usability, so zero watermarking is a hotspot in the research of BIM data security protection. BIM model is a type of 3D model, however, most of the existing zero watermarking algorithms for 3D models are difficult to be better applied to BIM data due to data structure differences. To solve this problem, a zero-watermarking algorithm for BIM data based on distance partitioning and skewness measure is proposed. Firstly, after spatial partitioning based on element paradigm value, the mapping relationship between different partitions and watermarking bits is established. Then, the skewness of elements is calculated, and the skewness measure sign is used as the feature to obtain the binary sequence. Finally, the dissimilarity operation is performed on the binary sequence and the original watermarking sequence which was disordered to construct the zero watermark of the BIM data. The experimental results show that the zero watermarks constructed from different BIM data are unique and robust to translation, rotation, element deletion, element addition, and format conversion attacks. In addition, the superiority of this paper's algorithm over the comparison algorithm in terms of robustness is compared. Therefore, the proposed algorithm can effectively provide technical support for BIM data copyright protection. [ABSTRACT FROM AUTHOR]

This paper shows a 2-step procedure for obtaining a variable-bandwidth recursive digital filter whose structure contains cascaded second-order (2nd-order) sections. Such a cascade-form structure is insensitive to the round-off noises that come from filter-coefficient quantizations in hardware implementations. This paper also shows how to utilize a 2-step procedure to get a variable-bandwidth recursive filter that is absolutely stable. The first step (Step-1) of the 2-step procedure designs a series of constant-bandwidth filters for approximating a series of evenly discretized variable specifications, and the second step (Step-2) fits the coefficient values obtained from Step-1 by employing individual polynomials. To ensure the stability of the resultant constant-bandwidth filters in Step-1, coefficient transformations are first executed on the 2nd-order transfer function's denominator-coefficients, and then each coefficient of both numerator and transformed denominator is found as an individual polynomial. Once all the polynomials are obtained, the polynomials corresponding to the transformed denominator are further converted to composite functions for ensuring the stability. Hence, the 2-step procedure not only produces a cascade-form variable-bandwidth filter that has low quantization errors, but also ensures the stability. A lowpass example is included for verifying the achieved stability and showing the high approximation accuracy. [ABSTRACT FROM AUTHOR]

Internet-based psychological treatments for depression have been around for more than 20 years. There has been a continuous line of research with new research questions being asked and studies conducted. In this paper, the author reviews studies with a focus on papers published from 2020 and onwards based on a Medline and Scopus search. Internet-based cognitive behavior therapy (ICBT) programs have been developed and tested for adolescents, older adults, immigrant groups and to handle a societal crisis (e.g. COVID-19). ICBT works in regular clinical settings and long-term effects can be obtained. Studies on different treatment orientations and approaches such as acceptance commitment therapy, unified protocol, and tailored treatments have been conducted. Effects on quality-of-life measures, knowledge acquisition and ecological momentary assessment as a research tool have been reported. Factorial design trials and individual patient data meta-analysis are increasingly used in association with internet intervention research. Finally, prediction studies and recent advances in artificial intelligence are mentioned. Internet-delivered treatments are effective, in particular if therapist guidance is provided. More target groups have been covered but there are many remaining challenges including how new tools like artificial intelligence will be used when treating depression. [ABSTRACT FROM AUTHOR]

The multi-level modeling technology of Building Information Modeling (BIM), combined with Three-dimensional Geographic Information System (3DGIS) macro-scene visualization technology and location information, can realize the transmission of decentralized information from various disciplines to multi-disciplinary collaborative information sharing services. It can be applied independently for the whole life cycle, which plays a positive role in reducing the cost and improving the efficiency of engineering planning, design, construction, operation, and maintenance. In this paper, the data integration and function integration methods of 3DGIS and BIM are designed. In order to avoid the breaking problems caused by attribute information loss and excessive simplification in the process of BIM data integration, the attribute mapping between 3DGIS and BIM based on Industry Foundation Classes (IFC) and City Geography Markup Language (CityGML) and the data simplification method considering the geometric characteristics of BIM are designed. By setting the relevant preconditions and thresholds of patch merging, on the premise of maintaining the structural characteristics of BIM data surface, reduce the amount of model data to improve the efficiency of BIM data loading, rendering and display effect in 3D geospatial scene. Through the data and function integration of 3DGIS and BIM, we can effectively manage the data of large-scale model, and calculate and obtain the geospatial location and direction of key parts of buildings through the coordinate transformation of BIM, which can effectively assist the rapid and accurate positioning of BIM in virtual 3D scene and expand the visualization ability of 3DGIS. By effectively integrating 3DGIS and BIM, this paper gives full play to the spatial management advantages of 3DGIS and the component management advantages of BIM. The rationality and operability of the method are verified by its application in the operation and maintenance management project of concealed facilities in actual buildings. [ABSTRACT FROM AUTHOR]

This paper proposes a new testing method, phased array ultrasonic testing, for the internal defects of gear teeth, which can be used to inspect the teeth of final products, breaking the limitations of incomplete volume coverage of conventional ultrasonic testing. This paper mainly discusses the inspection process of phased array ultrasonic testing, and verifies the feasibility of phased array ultrasonic testing for gear teeth defects of finished products by using physical and chemical inspection technology. The practical application results show that the phased array ultrasonic testing technology uses sector scanning mode to scan the area comprehensively between the pitch circle and the base circle, and the inspection image displayed by the equipment is intuitive, which can clearly identify defects. The number of defects inspected by phased array ultrasonic testing is consistent with the results of the physical and chemical inspection technology. The above summary shows that phased array ultrasonic testing is feasible, and the test results are reliable. [ABSTRACT FROM AUTHOR]

This paper revisits a classical problem in linkage mechanism design, specifically the design of centric crank-rocker mechanisms for a specified rocker stroke with unit time ratio. Beyond the traditional objective of minimizing the transmission angle's deviation from 90 degrees, this paper uses another objective: maximizing the shortest-to-longest link-length ratio in the linkage. The former objective ensures motion transmission quality in the mechanism, while the latter aims to make the mechanism less sensitive to variations in link lengths. It is shown that these two objectives are inherently conflicting, necessitating a trade-off solution. To address this, a Pareto front is developed by analyzing the governing design equations. The front is further normalized by relating each objective to its limit value. A design example using the normalized front is provided that showcases different optimization options. The TOPSIS method is used to illustrate the selection of a preferred design alternative. [ABSTRACT FROM AUTHOR]

In recent times, there has been a growing focus on multi-micro-grids (MMGs) system, owing to its well-suited structures for efficiently accommodating large-scale integration of distributed energy resources (DER). This attention is driven by the system's cost-effectiveness, enhanced efficiency, stability, and reliability performance, achieved through the collaborative exchange of power flow among individual micro-grids (MGs) and the main grid. Fundamental strategies for attaining optimal energy flow and sharing involve the optimal sizing of MGs and the implementation of an Energy Management System (EMS). These strategies play a crucial role in addressing uncertainties associated with intermittent generation, load fluctuations and energy market dynamics. This paper offers a review of grid-connected MMG topologies, EMS structures, coordination methods and current optimization approaches designed to meet EMS objectives. To address the inherent volatilities, the paper introduces various uncertainty quantification techniques along with current challenges. Additionally, it suggests future directions, emphasizing intelligent and predictive modeling to handle uncertainties, as well as recommending the incorporation of energy storage systems (ESSs) to align with emerging trends. [ABSTRACT FROM AUTHOR]

In multi-antenna systems, advanced techniques such as massive multiple-input multiple-output (MIMO), beamforming, and beam selection depend heavily on the accurate acquisition of the channel state. However, pilot contamination (PC) can be a major source of interference which degrades they are performance. Moreover, the severity of PC increases as more pilots are reused between users in the wireless systems. Researchers have shown that PC can be mitigated by using deep learning (DL) approaches. Nevertheless, when minimizing PC, the examination that identifies the applications and factors that distinguish these DL approaches is still limited. This paper reviews these DL approaches and the improvements needed to enhance their performance. Simulation results confirm that DL networks that learn to predict the channels directly have superior performance under PC. [ABSTRACT FROM AUTHOR]

Vegetation segmentation via point cloud data can provide important information for urban planning and environmental protection. The point cloud dataset is obtained using light detection and ranging (LiDAR) or RGB-D images. Oblique photogrammetry has received little attention as another important source of point cloud data. We present a pointwise annotated oblique photogrammetry point-cloud dataset that contains rich RGB information, texture, and structural features. This dataset contains five regions of Bengbu, China, with more than twenty thousand samples in this paper. Obviously, previous indoor point cloud semantic segmentation models are no longer applicable to oblique photogrammetry point clouds. A random sampling point transformer (RSPT) network is proposed to enhance vegetation segmentation accuracy. The RSPT model offers both efficient and lightweight architecture. In RSPT, random point sampling is utilized to downsample point clouds, and a local feature aggregation module based on self-attention is designed to extract additional representation features. The network also incorporated residual and dense connections (ResiDense) to capture both local and comprehensive features. Compared to state-of-the-art models, RSPT achieves notable improvements. The intersection over union (IoU) metric increased from 96.0% to 96.5%, the F1-score increased from 90.8% to 97.0%, and the overall accuracy (OA) increased from 91.9% to 96.9%. [ABSTRACT FROM AUTHOR]

Urban rail transit (URT) systems play an evident role in shaping city spatial structures; however, the principles and mechanisms behind this influence are not fully understood. This paper reviews research progress on the coupling relationship between URT and urban space, focusing on big data analysis methods and the timeliness and sequence of coupling effects. It highlights the importance of the temporal dimension in coupling analysis. By thoroughly exploiting data value and extracting key elements, big data technology imparts temporal attributes to these elements, exploring their interaction and influence mechanisms over different time sequences. The paper also discusses the potential application of big data to urban planning to support sustainable urban development. Finally, the paper outlines future research directions, including the deepened application of big data to urban spatial analysis and the role of new data sources in understanding and shaping the coupling relationship between URT and urban space. This analysis offers new perspectives and methodologies for urban development and transportation planning. [ABSTRACT FROM AUTHOR]

Remote sensing image building segmentation, which is essential in land use and urban planning, is evolving with advancements in deep learning. Conventional methods using convolutional neural networks face limitations in integrating local and global information and establishing long-range dependencies, resulting in suboptimal segmentation in complex scenarios. This paper proposes LMSwin_PNet, a novel segmentation network that addresses the SwinTransformer encoder's deficiency in local information processing through a local feature extraction module. Additionally, it features a multiscale nonparametric merging attention module to enhance feature-channel correlations. The network also incorporates the pyramid large-kernel convolution module, replacing the traditional 3 x 3 convolution in the decoder with multibranch large-kernel convolution, thereby achieving a large receptive field and detailed information capture. Comparative analyses on three public building datasets demonstrated the model's superior segmentation performance and robustness. The results show that LMSwin_PNet produced outputs closely matching labels, showing its potential for broader application in remote sensing image segmentation tasks. It achieved achieving an IoU of 72.35% on the Massachusetts Building Dataset, 91.30% on the WHU Building Dataset, and 78.99% on the Inria aerial-image building dataset. The source code will be freely available at https://github.com/ziyanpeng/pzy. [ABSTRACT FROM AUTHOR]

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Delayed graft function (DGF) is an early complication after kidney transplantation. The literature on DGF has experienced substantial growth. However, there is a lack of bibliometric analysis of DGF. This study aimed to analyze the scientific outputs of DGF and explore its hotspots from 2013 to 2023 by using CiteSpace and VOSviewer. The 2058 pieces of literature collected in the Web of Science Core Collection (WOSCC) from 1 January 2013 to 31 December 2023 were visually analyzed in terms of the annual number of publications, authors, countries, journals, literature co-citations, and keyword clustering by using CiteSpace and VOSviewer. We found that the number of papers published in the past ten years showed a trend of first increasing and then decreasing; 2021 was the year with the most posts. The largest number of papers was published by the University of California System, and the largest number of papers was published by the United States. The top five keyword frequency rankings are: ‘delayed graft function’, ‘kidney transplantation’, ‘renal transplantation’, ‘survival’, and ‘recipients’. These emerging trends include ‘brain death donors’, ‘blood absence re-injection injuries’, ‘tacrolimus’, ‘older donors and recipients’, and ‘artificial intelligence and DGF’. In summary, this study reveals the authors and institutions that could be cooperated with and discusses the research hotspots in the past ten years. It provides a reference and direction for future research and application of DGF. [ABSTRACT FROM AUTHOR]

The study of yield gaps has become more complex, prompting the use of varied approaches to measure yields and a wider range of factors to explain these gaps. In the Global North, the focus is on precision farming, whereas in sub-Saharan Africa (SSA), a broader perspective is necessary due to pronounced variability in farmland conditions. While biogeophysical and management factors have been traditional focal points in yield gap analyses, socio-economic and institutional factors are increasingly recognized as significant, especially in SSA. This review synthesizes research from the past decade in SSA that integrates biogeophysical, management, farm characteristics, and institutional factors in yield gap discussions. The findings indicate a slow shift in including socio-economic factors, with management, particularly nutrient supply and crop management, remaining predominant. However, there is a growing trend towards methodological diversity, such as the adoption of remote sensing and GIS in recent years. Case studies from Kenya and Ghana, utilizing field surveys, interviews, panel data, and spatial analysis, highlight how a multifaceted approach can enhance our understanding of the various elements influencing maize yield gaps in SSA. [ABSTRACT FROM AUTHOR]

For an academic field to remain vital, it is necessary to reflect upon its conceptual foundations and learn from adjacent disciplines. On that note, aesthetics can provide significant insights into advertising. While aesthetic elements have received attention in advertising research, no systematic attempts have been made to provide a comprehensive overview of this literature. The purpose of this conceptual article is to bring different branches of aesthetic theory into advertising studies. Marketers have historically focused on product functionality and often appeal to consumers through explicit messages. This article fills an important gap by delineating and advocating the conceptual foundation of advertising aesthetics as a research area worthy of further attention. In short, we understand advertising aesthetics as the artlike properties of and sensory responses to ads. A review of 309 papers provides the thematic outline of the study. Seven key themes are identified: (1) the nature of advertising aesthetics, (2) advertising creativity, (3) textuality, (4) social aesthetics, (5) cross-cultural differences, (6) the role of media in creating aesthetic opportunities, and (7) aesthetic categories beyond the beautiful and sublime. These themes offer a novel way of exploring contemporary issues in advertising. The article concludes with suggestions for future research. [ABSTRACT FROM AUTHOR]

Tumor-infiltrating lymphocytes (TILs) have been investigated as prognostic factors in melanoma. Recent advancements in assessing the tumor microenvironment in the setting of more widespread use of immune checkpoint blockade have reignited interest in identifying predictive biomarkers. This review examines the function and significance of TILs in cutaneous melanoma, evaluating their potential as prognostic and predictive markers. A literature search was conducted on papers covering tumor infiltrating lymphocytes in cutaneous melanoma available online in PubMed and Web of Science from inception to 1 December 2023, supplemented by citation searching. This article encompasses the assessment of TILs, the role of TILs in the immune microenvironment, TILs as a prognostic factor, TILs as a predictive factor for immunotherapy response, and clinical applications of TILs in the treatment of cutaneous melanoma. Tumor-infiltrating lymphocytes play a heterogeneous role in cutaneous melanoma. While they have historically been associated with improved survival, their status as independent prognostic or predictive factors remains uncertain. Novel methods of TIL assessment, such as determination of TIL subtypes and molecular signaling, demonstrate potential for predicting therapeutic response. Further, while their clinical utility in risk-stratification in melanoma treatment shows promise, a lack of consensus data hinders standardized application. [ABSTRACT FROM AUTHOR]

Due to the strong penetrability, long-wavelength synthetic aperture radar (SAR) can provide an opportunity to reconstruct the three-dimensional structure of the penetrable media. SAR tomography (TomoSAR) technology can resynthesize aperture perpendicular to the slant-range direction and then obtain the tomographic profile consisting of power distribution of different heights, providing a powerful technical tool for reconstructing the three-dimensional structure of the penetrable ground objects. As an emerging technology, it is different from the traditional interferometric SAR (InSAR) technology and has advantages in reconstructing the three-dimensional structure of the illuminated media. Over the past two decades, many TomoSAR methods have been proposed to improve the vertical resolution, aiming to distinguish the locations of different scatters in the unit pixel. In order to cope with the forest mission of European Space Agency (ESA) that is designed to provide P-band SAR measurements to determine the amount of biomass and carbon stored in forests, it is necessary to systematically evaluate the performance of forest height and underlying topography inversion using TomoSAR technology. In this paper, we adopt three typical algorithms, namely, Capon, Multiple Signal Classification (MUSIC), and Compressed Sensing (CS), to evaluate the performance in forest height and underlying topography inversion. The P-band airborne full-polarization (FP) SAR data of Lopè National Park in the AfriSAR campaign implemented by ESA in 2016 is adopted to verify the experiment. Furthermore, we explore the effects of different baseline designs and filter methods on the reconstruction of the tomographic profile. The results show that a better tomographic profile can be obtained by using Hamming window filter and Capon algorithm in uniform baseline distribution and a certain number of acquisitions. Compared with LiDAR results, the root-mean-square error (RMSE) of forest height and underlying topography obtained by Capon algorithm is 2.17 m and 1.58 m, which performs the best among the three algorithms. [ABSTRACT FROM AUTHOR]

The capsule robot has become an important tool in covering the entire spectrum of digestive tract disease diagnosis. To achieve magnetic capsule-robot localization, the Levenberg-Marquardt (LM) algorithm has become a mainstream approach that provides accurate solutions in the general case. In practice, however, to meet the requirements of wearability, fewer sensors and lower power consumption are required. When the number of sensor observations becomes smaller, local convergences and outliers may occur in positioning results. To mitigate this issue, this paper makes two contributions to enhance the robustness of capsule-endoscope positioning, especially when the quality of magnetic observations is low. First, it proposes a two-step approach that initializes the capsule attitude by using inertial measurements before estimating the position. Second, it presents an improved LM-based positioning algorithm based on vest-type magnetic sensor arrays. Furthermore, to verify the proposed approach, a vest-type wearable device with two low-cost magnetometer arrays is designed. Test results have shown the effectiveness of the proposed LM method in enhancing positioning when there is a lack of observations. [ABSTRACT FROM AUTHOR]

The significance of this review lies in addressing the limitations of passive locomotion in capsule endoscopes, hindering their widespread use in medical applications. The research focuses on evaluating existing miniature in vivo remote-controlled capsule endoscopes, examining their locomotion designs, and working theories to pave the way for overcoming challenges and enhancing their applicability in diagnostic and treatment settings. This paper explores control methods and dynamic system modeling in the context of self-propelled remote-controlled capsule endoscopes with a two-mass arrangement. The literature search, conducted at Queen Mary University of London Library from 2000 to 2022, utilized a systematic approach starting with the broad keyword 'Capsule Endoscope' and progressively narrowing down to specific aspects such as 'Capsule Endoscope Control' and 'Self-propelled Capsule Endoscope' using various criteria. Efficiently driving and controlling remote-controlled capsule endoscopes have the potential to overcome the current limitations in medical technology, offering a viable solution for diagnosing and treating gastrointestinal diseases. Successful control of the remote-controlled capsule endoscope, as demonstrated in this review paper, will lead to a step change in medical engineering, establishing the remote-controlled capsule endoscope as a swift standard in the field. [ABSTRACT FROM AUTHOR]