bluuebunny/crossref_metadata_2025_split huggingface dataset:
HIP: a method for high-dimensional multi-view data integration and prediction accounting for subgroup heterogeneity
Authors: Butts Jessica , Verace Leif , Wendt Christine , Bowler Russel P , Hersh Craig P , Long Qi , Eberly Lynn , Safo Sandra E 
Published: September 2024

Abstract
Epidemiologic and genetic studies in many complex diseases suggest subgroup disparities (e.g. by sex, race) in disease course and patient outcomes. We consider this from the standpoint of integrative analysis where we combine information from different views (e.g. genomics, proteomics, clinical data). Existing integrative analysis methods ignore the heterogeneity in subgroups, and stacking the views and accounting for subgroup heterogeneity does not model the association among the views. We propose Heterogeneity in Integration and Prediction (HIP), a statistical approach for joint association and prediction that leverages the strengths in each view to identify molecular signatures that are shared by and specific to a subgroup. We apply HIP to proteomics and gene expression data pertaining to chronic obstructive pulmonary disease (COPD) to identify proteins and genes shared by, and unique to, males and females, contributing to the variation in COPD, measured by airway wall thickness. Our COPD findings have identified proteins, genes, and pathways that are common across and specific to males and females, some implicated in COPD, while others could lead to new insights into sex differences in COPD mechanisms. HIP accounts for subgroup heterogeneity in multi-view data, ranks variables based on importance, is applicable to univariate or multivariate continuous outcomes, and incorporates covariate adjustment. With the efficient algorithms implemented using PyTorch, this method has many potential scientific applications and could enhance multiomics research in health disparities. HIP is available at https://github.com/lasandrall/HIP, a video tutorial at https://youtu.be/O6E2OLmeMDo and a Shiny Application at https://multi-viewlearn.shinyapps.io/HIP_ShinyApp/ for users with limited programming experience.
iTraNet: a web-based platform for integrated trans-omics network visualization and analysis
Authors: Sugimoto Hikaru , Morita Keigo , Li Dongzi , Bai Yunfan , Mattanovich Matthias , Kuroda Shinya 
Published: September 2024

Abstract

Motivation
Visualization and analysis of biological networks play crucial roles in understanding living systems. Biological networks include diverse types, from gene regulatory networks and protein–protein interactions to metabolic networks. Metabolic networks include substrates, products, and enzymes, which are regulated by allosteric mechanisms and gene expression. However, the analysis of these diverse omics types is challenging due to the diversity of databases and the complexity of network analysis.

Results
We developed iTraNet, a web application that visualizes and analyses trans-omics networks involving four types of networks: gene regulatory networks, protein–protein interactions, metabolic networks, and metabolite exchange networks. Using iTraNet, we found that in wild-type mice, hub molecules within the network tended to respond to glucose administration, whereas in ob/ob mice, this tendency disappeared. With its ability to facilitate network analysis, we anticipate that iTraNet will help researchers gain insights into living systems.

Availability and implementation
iTraNet is available at https://itranet.streamlit.app/.
Deep learning disconnectomes to accelerate and improve long-term predictions for post-stroke symptoms
Authors: Matsulevits Anna , Coupé Pierrick , Nguyen Huy-Dung , Talozzi Lia , Foulon Chris , Nachev Parashkev , Corbetta Maurizio , Tourdias Thomas , Thiebaut de Schotten Michel 
Published: September 2024

Abstract
This study investigates the efficacy of deep-learning models in expediting the generation of disconnectomes for individualized prediction of neuropsychological outcomes one year after stroke. Utilising a 3D U-Net network, we trained a model on a dataset of N = 1333 synthetic lesions and corresponding disconnectomes, subsequently applying it to N = 1333 real stroke lesions. The model-generated disconnection patterns were then projected into a two-dimensional ‘morphospace’ via uniform manifold approximation and projection for dimension reduction dimensionality reduction. We correlated the positioning within this morphospace with one-year neuropsychological scores across 86 metrics in a novel cohort of 119 stroke patients, employing multiple regression models and validating the findings in an out-of-sample group of 20 patients. Our results demonstrate that the 3D U-Net model captures the critical information of conventional disconnectomes with a notable increase in efficiency, generating deep-disconnectomes 720 times faster than current state-of-the-art software. The predictive accuracy of neuropsychological outcomes by deep-disconnectomes averaged 85.2% (R2 = 0.208), which significantly surpassed the conventional disconnectome approach (P = 0.009). These findings mark a substantial advancement in the production of disconnectome maps via deep learning, suggesting that this method could greatly enhance the prognostic assessment and clinical management of stroke survivors by incorporating disconnection patterns as a predictive tool.
Understanding visual perception in visual snow syndrome: a battery of psychophysical tests plus the 30-day clinical diary
Authors: Garobbio Simona , Mazloum Reza , Rosio Michael , Popovova Jeanette , Schöpfer Raphaela , Fierz Fabienne C , Disse Leah R , Weber Konrad Peter , Schankin Christoph J , Michels Lars , Herzog Michael H 
Published: September 2024

Abstract
Patients with visual snow syndrome (VSS) experience uncountable flickering tiny dots in the entire visual field. Symptoms often persist over the years. Very little is known about altered perception in VSS. VSS is diagnosed based on subjective reports because there is no manual with objective measures. In this study, 20 patients with VSS and 17 healthy controls performed a battery of tests assessing visual acuity, contrast sensitivity, illusion perception, spatial–temporal vision, motion perception, visual attention, and selective attention. Surprisingly, except for one test, which is the honeycomb illusion, patients performed at the same level as controls. Patients reporting black and white visual snow performed better in the Stroop test compared to patients reporting other visual snow colours. In addition to a clinical visit, the 30-day clinical diary was administered to patients to broadly measure their symptom severity. We found that better performance in the tests, in particular in the contrast and coherent motion tests, was correlated with lower VSS symptoms, weaker VS characteristics (e.g. density and size) and lower VS severity. Our results suggest that, even if visual abilities are not deteriorated by VSS, they can determine how severe symptoms are, and show that VSS is an heterogenous disorder where symptoms and visual abilities vary between patients, for instance depending on the VS colour. The study was primarily designed to identify tests where performance differs between controls and patients. In addition, exploratory analyses were conducted to initiate an understanding of the overall pattern of relationships between patients’ visual abilities and symptoms, which is of clinical relevance. Future studies with more power are necessary to validate our findings.
Photocatalytic water splitting over K3Li2Ta5O15 with a C-site-filled tungsten bronze structure and influence of metal cations at C-site on photocatalytic properties
Authors: Moriya Misa , Kato Hideki , Iwase Akihide 
Published: September 2024

Abstract
K3Li2Ta5O15 is found as a novel photocatalyst for overall water splitting under ultraviolet light irradiation. K3Li2Ta5O15 possesses a characteristic crystal structure with Li+ ion-filled C-sites in (A1)4(A2)2C4M10O30 as the general formula of a tungsten bronze-type metal oxide. Most of the reported photocatalysts with a tungsten bronze structure possess empty C-sites. K6Ta10.8O30 also possesses a C-site-filled tungsten bronze structure in which C-sites are partially filled with Ta5+ ions. In diffuse reflectance spectra, K6Ta10.8O30 has an absorption edge at a longer wavelength than K3Li2Ta5O15. This narrower band gap of K6Ta10.8O30 than K3Li2Ta5O15 is considered to be due to the presence of Ta5+ ions at C-sites in K6Ta10.8O30. Ta5+ ions that are located at 9-fold coordination C-sites with a totally different surrounding environment from the 6-fold coordination M-sites will form the conduction band minimum at a lower potential than those located at 6-fold coordination M-sites. The optimized K3Li2Ta5O15 shows almost the same water-splitting activity as the optimized K6Ta10.8O30. Thus, it is found that the conduction band that is formed by Ta5+ ions at C-sites is also effective for photocatalytic reaction, being similar to that formed by Ta5+ ions at M-sites.
Mechanical strategies to promote vascularization for tissue engineering and regenerative medicine
Authors: Wang Yiran , Liu Meixuan , Zhang Wei , Liu Huan , Jin Fang , Mao Shulei , Han Chunmao , Wang Xingang 
Published: September 2024

Abstract
Vascularization is a major challenge in the field of tissue engineering and regenerative medicine. Mechanical factors have been demonstrated to play a fundamental role in vasculogenesis and angiogenesis and can affect the architecture of the generated vascular network. Through the regulation of mechanical factors in engineered tissues, various mechanical strategies can be used to optimize the preformed vascular network and promote its rapid integration with host vessels. Optimization of the mechanical properties of scaffolds, including controlling scaffold stiffness, increasing surface roughness and anisotropic structure, and designing interconnected, hierarchical pore structures, is beneficial for the in vitro formation of vascular networks and the ingrowth of host blood vessels. The incorporation of hollow channels into scaffolds promotes the formation of patterned vascular networks. Dynamic stretching and perfusion can facilitate the formation and maturation of preformed vascular networks in vitro. Several indirect mechanical strategies provide sustained mechanical stimulation to engineered tissues in vivo, which further promotes the vascularization of implants within the body. Additionally, stiffness gradients, anisotropic substrates and hollow channels in scaffolds, as well as external cyclic stretch, boundary constraints and dynamic flow culture, can effectively regulate the alignment of vascular networks, thereby promoting better integration of prevascularized engineered tissues with host blood vessels. This review summarizes the influence and contribution of both scaffold-based and external stimulus-based mechanical strategies for vascularization in tissue engineering and elucidates the underlying mechanisms involved.
Students and the BCS
Authors: Shaw R , Treleaven P 
Published: September 2024

Abstract
During recent months, the Society has been taking an increasing interest in students of computing and allied fields. During 1973/74, the first student member of Council, Richard Jennings of the Hull Branch, was elected and one of the authors, Philip Treleaven, is the student representative for the current year. As further evidence of the Society’s interest, Council at its January meeting approved the formation of a student affairs committee, under the chairmanship of Rodney Shaw, to oversee policies and activities connected with students and student membership of the Society. It was also agreed to approve the abatement of the annual subscriptions for those students undergoing full-time courses of study leading to a qualification acceptable to the Society as part of its membership requirement. Such students will now pay £1.50 annually as Student members of the Society.
Resolving the conflict between OA and DP
Authors: Fox Peter 
Published: September 2024

Abstract
Office automation operates at two levels: a) the personal use of the computing tools available in the office, and b) the corporate level of using information technology to control the flow of information between offices. Data processing departments have in many cases seized on the latter reason for deciding what users want in the way of OA. ‘After all’, the argument goes, ‘a global viewpoint is necessary and we have been doing just that for years.’ To this the OA specialist retorts: ‘Ah yes but there’s something else you’ve been doing for years – and that’s not catering properly for user’s needs’. There is a lot of bad blood, empire building, and struggling for survival (politics) in the atmosphere which permeates a majority of large organisations. In extreme cases the DP department, having the established powerbase, simply sees the OA specialists off the premises.
P-TIMA: a framework of T witter threat intelligence mining and analysis based on a prompt-learning NER model
Authors: You Yizhe , Jiang Zhengwei , Yang Peian , Jiang Jun , Zhang Kai , Wang Xuren , Tu Chenpeng , Feng Huamin 
Published: September 2024

Abstract
Open-source information platforms such as Twitter continuously provide the latest threat intelligence, including new vulnerabilities and in-the-wild exploitations of advanced persistent threat (APT) groups. Automated extraction of threat intelligence from Twitter has become crucial for defenders to access up-to-date threat knowledge. However, existing studies mainly rely on supervised learning methods to extract threat intelligence knowledge, such as entities, which require a large amount of annotated data. This paper presents Threat Intelligence Mining and Analysis based on Prompt Learning (P-TIMA), a framework specifically crafted for extracting and analyzing threat intelligence from Twitter. P-TIMA employs our innovative few-shot entity recognition method, SecEntPrompt (SEP), built on prompt learning, to extract vulnerability intelligence from Twitter. Additionally, P-TIMA analyzes and profiles the overarching vulnerability intelligence obtained from Twitter, along with in-the-wild exploitation intelligence of APT groups. The SEP improves the average entity recognition F1 score by 3.62-4.40 compared with the best-performing comparison model and outperforms the method based on the large language model on recognition performance and inference time. To validate our framework, we apply P-TIMA to extract vulnerability-related threat intelligence from real Twitter data. Through case studies, we then analyze trends in vulnerability threats and the exploitation capabilities of APT groups. In conclusion, our framework provides a more efficient and accurate method for extracting threat intelligence from Twitter, enabling defenders to stay up-to-date with the latest threat trends and helping them improve their defense strategies against cyber attacks.
The Dark Side of Infrastructure: Roads, Repression and Land in Authoritarian Paraguay
Authors: González Felipe , Miquel-Florensa Josepa , Prem Mounu , Straub Stéphane 
Published: September 2024

Abstract
Transportation infrastructure is associated with economic development, but it can also be used for social control and to benefit the governing elite. We explore the connection between the construction of road networks, state-led repression and illegal land allocations in the longest dictatorship in South America: Alfredo Stroessner’s military regime in Paraguay. Using novel panel data from the Truth and Reconciliation Commission, we show that proximity to newly constructed roads facilitated state-led repression, illegal allocation of agricultural plots to dictatorship allies and hindered sustainable economic development in the following decades.
The middle tier of states and the Russia–Ukraine war
Authors: Wu Zhengyu , Ding Yuhang 
Published: September 2024

Abstract
This article examines the concept of the ‘middle tier of states’ proposed by Halford Mackinder in 1919, its failure to prevent German–Soviet Union rapprochement in the interwar years, its recent revival and its geopolitical implications. Mackinder's ‘heartland thesis’ comprises two interrelated parts: the geopolitical significance of the heartland, and the middle tier of states, which he suggested could counteract the pernicious impact of the heartland. Although the middle tier of states paralleled the 1919 Versailles settlement in east-central Europe, its failure to play the role that Mackinder suggested has never been properly investigated. Over the past decade, the middle tier of states has been revived by a range of regional cooperation projects in east-central Europe, while the Russia–Ukraine war attests to its necessity and viability in the current context. The Russia–Ukraine war has shown that a strengthened middle tier of NATO and European Union states will not just reshape the geopolitical landscape of Europe but will have significant implications for world politics.
Politics and power in the global tennis circuit
Authors: Eggeling Kristin Anabel 
Published: September 2024

Abstract
Like most global sports, professional tennis is eager to claim that politics has no place on its playing field. On closer investigation, however, this ‘myth of autonomy’ soon cracks. In addition to adding tennis as a much-needed case to the study of sport and international affairs, this article develops the concept of ‘the circuit’ to approach phenomena that criss-cross traditional levels of analysis in international relations. In its first part, the article zooms in on the practice of writing celebratory messages onto the lenses of TV cameras as an example of the power relations that exist in and around professional tennis courts today. In its second part, it zooms out to map the themes and questions that have framed tennis as a political activity around the world and over time. The analysis identifies and characterizes the global tennis circuit as a site within which many of the most pressing political questions of our time are contained, focusing on the prestigious tournaments which make up the Grand Slam, and the elite athletes that participate in them.
Uniportal thoracoscopic plication of diaphragmatic eventration: loop needle technique for better visualization
Authors: Kumagai Ryosuke , Kabemura Shinsaku , Kojima Fumitsugu , Bando Toru 
Published: September 2024

Abstract
Symptomatic unilateral diaphragmatic eventration require surgical intervention. A 56-year-old woman complained of dyspnoea on exertion and was noted to have left diaphragm elevation on chest radiographs. Dynamic magnetic resonance imaging showed paradoxical movement of the left diaphragm. We performed diaphragmatic plication by uniportal thoracoscopy with knifeless endostaplers and a loop needle device. Her symptoms significantly improved immediately after the operation, and this condition had been maintained for 6 months. We thus suggest this minimally invasive technique as an easy and safe method for diaphragmatic plication.
Infodemic, Ignorance, or Imagination? The Problem of Misinformation in Health Emergencies
Authors: Kirk Jessica 
Published: September 2024

Abstract
In understanding and responding to the problem of misinformation during global health emergencies, health experts and organizations such as the WHO have relied on the concept of the “infodemic,” or the idea that there is such an overabundance of information that ascertaining trustworthy sources and reliable guidance is difficult. Is this the best way to understand the problem of misinformation, however? A large and multidisciplinary literature has argued that such an approach misses the important role of individual psychological factors and societal “mega-trends” such as hyperpolarization, structural shifts in the media, and public mistrust in elites. This article argues that such contributions are important in understanding the multifaceted problem of misinformation but may miss another, equally important component: the politics of emergency. Specifically, the prominent role of speculation during moments of emergency—the need to respond to “what ifs” rather than just “what is”—provides a conducive context for misinformation, facilitating its production and spread while also problematizing efforts to correct it. The article illuminates this relationship through a discourse analysis of prominent misinformation claims during the US responses to Ebola in 2014 and COVID-19 in 2020.
MS Pattern Explorer: interactive visual exploration of temporal activity patterns for multiple sclerosis
Authors: Morgenshtern Gabriela , Rutishauser Yves , Haag Christina , von Wyl Viktor , Bernard Jürgen 
Published: September 2024

Abstract

Objectives
This article describes the design and evaluation of MS Pattern Explorer, a novel visual tool that uses interactive machine learning to analyze fitness wearables’ data. Applied to a clinical study of multiple sclerosis (MS) patients, the tool addresses key challenges: managing activity signals, accelerating insight generation, and rapidly contextualizing identified patterns. By analyzing sensor measurements, it aims to enhance understanding of MS symptomatology and improve the broader problem of clinical exploratory sensor data analysis.

Materials and Methods
Following a user-centered design approach, we learned that clinicians have 3 priorities for generating insights for the Barka-MS study data: exploration and search for, and contextualization of, sequences and patterns in patient sleep and activity. We compute meaningful sequences for patients using clustering and proximity search, displaying these with an interactive visual interface composed of coordinated views. Our evaluation posed both closed and open-ended tasks to participants, utilizing a scoring system to gauge the tool’s usability, and effectiveness in supporting insight generation across 15 clinicians, data scientists, and non-experts.

Results and Discussion
We present MS Pattern Explorer, a visual analytics system that helps clinicians better address complex data-centric challenges by facilitating the understanding of activity patterns. It enables innovative analysis that leads to rapid insight generation and contextualization of temporal activity data, both within and between patients of a cohort. Our evaluation results indicate consistent performance across participant groups and effective support for insight generation in MS patient fitness tracker data. Our implementation offers broad applicability in clinical research, allowing for potential expansion into cohort-wide comparisons or studies of other chronic conditions.

Conclusion
MS Pattern Explorer successfully reduces the signal overload clinicians currently experience with activity data, introducing novel opportunities for data exploration, sense-making, and hypothesis generation.