bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiple proceedings and abuse of procedure on BRI disputes
Authors: Gotsiridze Mariam 
Published: November 2023

Abstract
This article argues that specific mechanisms and best practices should be adopted by different players in the Belt and Road Initiative (BRI) dispute resolution ecosystem to mitigate the risks of multiple proceedings and abuse of procedure. Specifically, (i) states should enhance their multilateral and bilateral treaty practices; (ii) arbitral institutions should enhance their arbitral rules as well as cooperate with each other; and (iii) states should direct more efforts to dispute prevention and amicable dispute settlement. This article will explain what these best practices and mechanisms are. The ‘The BRI’ section will provide a general background on the nature and architecture of the BRI. The ‘Problem of multiple proceedings and abuse of procedure’ section will discuss the notion of multiple proceedings and abuse of procedure. The ‘Potential of multiple, parallel proceedings and abuse of procedure on BRI projects’ section will focus on possible multiple proceedings and abuse of procedure on BRI disputes. The ‘Possible solutions and recommendations’ section will identify possible solutions and provide recommendations. Conclusions section will draw final conclusions.
The precarity of the police powers doctrine in investment arbitration: Rockhopper v Italy
Authors: Carvosso Rhys 
Published: November 2023

Abstract
This article analyses the reasoning of the ICSID tribunal in Rockhopper v Italy with respect to the police powers doctrine. It contends that, in upholding the investors’ claim that the Italian government had unlawfully expropriated their investment in an oil and gas field off the Italian coast by passing a law banning hydrocarbon exploitation and refusing their application for a production permit on that basis, the Tribunal approached the police powers doctrine in an insufficiently clear and rigorous way. First, the Tribunal’s reasons were scant and lacked any articulation of the content of the doctrine or engagement with the extensive body of relevant arbitral jurisprudence and scholarship, making it difficult to comprehend how the doctrine was understood and why it was rejected. Secondly, the Tribunal’s assessment of the validity of Italy’s regulatory purpose, being the only aspect of the doctrine with which it engaged, lacked careful engagement with the evidence. As a result of these shortcomings, the Tribunal’s reasons lend a precarity to the police powers doctrine which belies its relatively settled status in investor-state arbitration and reveals the need for greater rigour and lucidity in its future application.
Soil prokaryotic characterization in response to natural moisture gradient in the temperate grassland ecosystems
Authors: Chen Xin , Wang Yujue , Shen Yuting , Sang Weiguo , Xiao Nengwen , Xiao Chunwang 
Published: November 2023

Abstract
Soil moisture, which is an important factor affecting ecosystem function, can maintain microbial activity and ultimately change the microbial community by altering vegetation diversity and controlling the diffusion and transport of soil nutrients. To explore the effects of soil water content (SWC) on soil prokaryotic community, we established a study area covering a natural soil moisture gradient and subdivided it into high (HW, 4.80 ± 1.18%), medium (MW, 2.17 ± 0.09%) and low water contents (LW, 1.85 ± 0.14%) in the grassland ecosystem along the south shore of Hulun Lake in Inner Mongolia, China. Environmental factors were determined by field surveys and laboratory analyses. Soil prokaryotes were determined by high-throughput sequencing techniques. Vegetation characteristics and soil physicochemical properties had a significant effect on prokaryotic richness diversity, and SWC was the most important factor influencing prokaryotic richness diversity. In the MW, the number of differential prokaryotes was lowest, and prokaryotic microorganisms had the highest diversity and relative abundance at the phylum level, which may reflect less intrinsic variation and higher overall activity of the prokaryotic community in the MW. In addition, HW and LW had lower prokaryotic diversity and relative abundance at the phylum level, and phenotypic predictions for both groups indicated a more tolerant prokaryotic community. In summary, the prokaryotic community responded significantly to the natural moisture gradients in grassland ecosystems along the south shore of Hulun Lake, and both too high and too low soil moisture increased prokaryotic stress resistance.
Karrikin signalling: impacts on plant development and abiotic stress tolerance
Authors: Kamran Muhammad , Melville Kim T , Waters Mark T 
Published: November 2023

Abstract
Plants rely upon a diverse range of metabolites to control growth and development, and to overcome stress that results from suboptimal conditions. Karrikins (KARs) are a class of butenolide compounds found in smoke that stimulate seed germination and regulate various developmental processes in plants. KARs are perceived via a plant α/β-hydrolase called KARRIKIN INSENSITIVE2 (KAI2), which also functions as a receptor for a postulated phytohormone, provisionally termed KAI2 ligand (KL). Considered natural analogues of KL, KARs have been extensively studied for their effects on plant growth and their crosstalk with plant hormones. The perception and response pathway for KAR–KL signalling is closely related to that of strigolactones, another class of butenolides with numerous functions in regulating plant growth. KAR–KL signalling influences seed germination, seedling photomorphogenesis, root system architecture, abiotic stress responses, and arbuscular mycorrhizal symbiosis. Here, we summarize current knowledge of KAR–KL signalling, focusing on its role in plant development, its effects on stress tolerance, and its interaction with other signalling mechanisms.
Image classification for historical documents: a study on Chinese local gazetteers
Authors: Chen Jhe-An , Hou Jen-Chien , Tsai Richard Tzong-Han , Liao Hsiung-Ming , Chen Shih-Pei , Chang Ming-Ching 
Published: November 2023

Abstract
We present a novel approach for automatically classifying illustrations from historical Chinese local gazetteers using modern deep learning techniques. Our goal is to facilitate the digital organization and study of a large quantity of digitized local gazetteers. We evaluate the performance of eight state-of-the-art deep neural networks on a dataset of 4,309 manually labeled and organized images of Chinese local gazetteer illustrations, grouped into three coarse categories and nine fine classes according to their contents. Our experiments show that DaViT achieved the highest classification accuracy of 93.9 per cent and F1-score of 90.6 per cent. Our results demonstrate the effectiveness of deep learning models in accurately recognizing and categorizing historical local gazetteer illustrations. We also developed a user-friendly web service to enable researchers easy access to the developed models. The potential for extending this method to other collections of scanned documents beyond Chinese local gazetteers makes a significant contribution to the study of visual materials in the arts and history in the digital humanities field. The dataset used in this study is publicly available and can be used for further research in the field.
Module 3: Identifying and Understanding your Emotions after Covid-19
Authors: Jaywant Abhishek , Oberlin Lauren E. , Cherestal Stephanie , Bueno Castellano Christina , Wilkins Victoria M. , Kanellopoulos Dora 
Published: November 2023

Abstract
This chapter provides a framework for identifying emotions and becoming more aware of them when they occur. Emotions are an important part of being human, especially when they direct attention to important internal and external events and help inform and guide behavior. However, people with persistent COVID-19 symptoms may have difficulty understanding their emotions, which then could intensify their feelings of distress and discomfort. Learning to recognize and validate emotions can reduce the intensity of difficult emotions and improve the client’s coping. Worksheets in this chapter focus on identifying emotions, myths, and unhelpful judgments. The importance of home practice is emphasized.
Module 7: Reframing Unhelpful Thoughts
Authors: Jaywant Abhishek , Oberlin Lauren E. , Cherestal Stephanie , Bueno Castellano Christina , Wilkins Victoria M. , Kanellopoulos Dora 
Published: November 2023

Abstract
This chapter covers how clients with persistent COVID-19 symptoms can learn to reframe automatic thoughts that contribute to difficult emotions and behaviors that are not beneficial in the long term. Unhelpful thoughts often contain thinking traps in which the brain automatically interprets an ambiguous event as reflecting a worst-case scenario without considering alternative results. Reframing these automatic thoughts can help shift perspectives so that the client takes into account the full context of the situation, thus reducing feelings of anxiety or depression. Worksheets are provided so the client can record automatic thoughts, highlighting the importance of self-validation and acknowledging the uncertainty of the situation.
Module 9: Managing Cognitive Difficulties and “Brain Fog”
Authors: Jaywant Abhishek , Oberlin Lauren E. , Cherestal Stephanie , Bueno Castellano Christina , Wilkins Victoria M. , Kanellopoulos Dora 
Published: November 2023

Abstract
This chapter details several skills to address cognitive difficulties people have after contracting COVID-19. It also introduces the concept of brain fog. After becoming ill with COVID-19, some people report feeling as if their thinking has slowed down, while others have difficulty in focusing and multitasking. Unhelpful thoughts and distressing emotions in reaction to cognitive difficulties can interfere with thinking and make it harder to concentrate, process information, and remember. The chapter offers strategies that may help with cognitive difficulties and brain fog symptoms, such as creating a task list or making environmental modifications. Home practice can increase the effectiveness of cognitive strategies.
Module 11: Participating in Medical Treatment
Authors: Jaywant Abhishek , Oberlin Lauren E. , Cherestal Stephanie , Bueno Castellano Christina , Wilkins Victoria M. , Kanellopoulos Dora 
Published: November 2023

Abstract
This chapter covers the importance of adherence to medical treatment for clients who have persistent COVID-19 symptoms. Adherence to medical and rehabilitation recommendations can improve clients’ daily functioning, reduce disability, and help them return to a more independent and satisfying life. However, multiple barriers and obstacles can make it difficult for individuals to engage in medical care, such as insurance and transportation issues, the cost of treatment and medications, and the evolving healthcare system. Anxiety, depression, hopelessness, and other uncomfortable emotions can also have a major impact on participation in medical treatment. Other topics discussed in this chapter are how to prepare for medical appointments and telehealth visits.
Module 12: Putting it all Together and Managing Uncertainty
Authors: Jaywant Abhishek , Oberlin Lauren E. , Cherestal Stephanie , Bueno Castellano Christina , Wilkins Victoria M. , Kanellopoulos Dora 
Published: November 2023

Abstract
This chapter explores ways that clients can put together and maintain the skills they learned in this treatment program. The key to sustaining gains over time is continuous practice of the skills and techniques learned in therapy. Practicing can help clients to manage ongoing uncertainty about COVID-19 symptoms, navigate setbacks, and prevent relapse into unhealthy cognitive and behavioral patterns. Habit-forming strategies to maintain skills over time include establishing a routine, rewarding oneself, and modifying the environment. The chapter also explains the difference between temporary setbacks (which are inevitable) and the persistent re-emergence of mood or anxiety symptoms (which need further treatment).
Narrow-line Seyfert 1 galaxies in Sloan Digital Sky Survey: a new optical spectroscopic catalogue
Authors: Paliya Vaidehi S , Stalin C S , Domínguez Alberto , Saikia D J 
Published: November 2023

ABSTRACT
Narrow-line Seyfert 1 (NLSy1) galaxies are an enigmatic class of active galactic nuclei (AGN) that exhibit peculiar multiwavelength properties across the electromagnetic spectrum. For example, these sources have allowed us to explore the innermost regions of the central engine of AGN using X-ray observations and have also provided clues about the origin of relativistic jets considering radio and gamma-ray bands. Keeping in mind the ongoing and upcoming wide-field, multifrequency sky surveys, we present a new catalogue of NLSy1 galaxies. This was done by carrying out a detailed decomposition of &gt;2 million optical spectra of quasars and galaxies from the Sloan Digital Sky Survey Data Release 17 (SDSS-DR17) using the publicly available software ‘Bayesian AGN Decomposition Analysis for SDSS Spectra’. The catalogue contains 22656 NLSy1 galaxies which is more than twice the size of the previously identified NLSy1s based on SDSS-DR12. As a corollary, we also release a new catalogue of 52273 broad-line Seyfert 1 (BLSy1) galaxies. The estimated optical spectral parameters and derived quantities confirm the previously known finding of NLSy1 galaxies being AGN powered by highly accreting, low-mass black holes. We conclude that this enlarged sample of NLSy1 and BLSy1 galaxies will enable us to explore the low-luminosity end of the AGN population by effectively utilizing the sensitive, high-quality observations delivered by ongoing/upcoming wide-field sky surveys. The catalogue has been made public at https://www.ucm.es/blazars/seyfert.
The formation of bars and warps in rotating haloes
Authors: Joshi Robin , Widrow Lawrence M 
Published: November 2023

ABSTRACT
We investigate the effects of halo kinematics on the dynamics of stellar discs by simulating the evolution of isolated disc–halo systems from equilibrium initial conditions. Our main results come from four simulations where the initial disc is identical and the halo is either treated as a rigid potential or is ‘live’ with isotropic orbits or orbits that preferentially rotate with or counter to the disc. We confirm previous results that bar formation is more vigorous in models with a live halo than a rigid one and is further enhanced when halo orbits preferentially rotate with the disc. We discuss two types of buckling events with different symmetries about the mid-plane, one that occurs just as the bar is forming and the other well after the bar has been established. We also show that warps are most easily excited and maintained when the halo is counter-rotating with the disc, in agreement with theoretical predictions. Our most novel result is the discovery of a rotating halo instability, which causes the disc and halo cusp to spiral outward from the centre-of-mass of the system whether the halo rotates with the disc or counter to it and also occurs in a disc–bulge–halo system that does not form a bar. We provide a heuristic linear model that captures the essential dynamics of the instability.
Supercoiling-dependent DNA binding: quantitative modeling and applications to bulk and single-molecule experiments
Authors: Kolbeck Pauline J , Tišma Miloš , Analikwu Brian T , Vanderlinden Willem , Dekker Cees , Lipfert Jan 
Published: November 2023

Abstract
DNA stores our genetic information and is ubiquitous in applications, where it interacts with binding partners ranging from small molecules to large macromolecular complexes. Binding is modulated by mechanical strains in the molecule and can change local DNA structure. Frequently, DNA occurs in closed topological forms where topology and supercoiling add a global constraint to the interplay of binding-induced deformations and strain-modulated binding. Here, we present a quantitative model with a straight-forward numerical implementation of how the global constraints introduced by DNA topology modulate binding. We focus on fluorescent intercalators, which unwind DNA and enable direct quantification via fluorescence detection. Our model correctly describes bulk experiments using plasmids with different starting topologies, different intercalators, and over a broad range of intercalator and DNA concentrations. We demonstrate and quantitatively model supercoiling-dependent binding in a single-molecule assay, where we directly observe the different intercalator densities going from supercoiled to nicked DNA. The single-molecule assay provides direct access to binding kinetics and DNA supercoil dynamics. Our model has broad implications for the detection and quantification of DNA, including the use of psoralen for UV-induced DNA crosslinking to quantify torsional tension in vivo, and for the modulation of DNA binding in cellular contexts.
The SysteMHC Atlas v2.0, an updated resource for mass spectrometry-based immunopeptidomics
Authors: Huang Xiaoxiang , Gan Ziao , Cui Haowei , Lan Tian , Liu Yansheng , Caron Etienne , Shao Wenguang 
Published: November 2023

Abstract
The SysteMHC Atlas v1.0 was the first public repository dedicated to mass spectrometry-based immunopeptidomics. Here we introduce a newly released version of the SysteMHC Atlas v2.0 (https://systemhc.sjtu.edu.cn), a comprehensive collection of 7190 MS files from 303 allotypes. We extended and optimized a computational pipeline that allows the identification of MHC-bound peptides carrying on unexpected post-translational modifications (PTMs), thereby resulting in 471K modified peptides identified over 60 distinct PTM types. In total, we identified approximately 1.0 million and 1.1 million unique peptides for MHC class I and class II immunopeptidomes, respectively, indicating a 6.8-fold increase and a 28-fold increase to those in v1.0. The SysteMHC Atlas v2.0 introduces several new features, including the inclusion of non-UniProt peptides, and the incorporation of several novel computational tools for FDR estimation, binding affinity prediction and motif deconvolution. Additionally, we enhanced the user interface, upgraded website framework, and provided external links to other resources related. Finally, we built and provided various spectral libraries as community resources for data mining and future immunopeptidomic and proteomic analysis. We believe that the SysteMHC Atlas v2.0 is a unique resource to provide key insights to the immunology and proteomics community and will accelerate the development of vaccines and immunotherapies.
Quantification and modeling of turnover dynamics of de novo transcripts in Drosophila melanogaster
Authors: Grandchamp Anna , Czuppon Peter , Bornberg-Bauer Erich 
Published: November 2023

Abstract
Most of the transcribed eukaryotic genomes are composed of non-coding transcripts. Among these transcripts, some are newly transcribed when compared to outgroups and are referred to as de novo transcripts. De novo transcripts have been shown to play a major role in genomic innovations. However, little is known about the rates at which de novo transcripts are gained and lost in individuals of the same species. Here, we address this gap and estimate the de novo transcript turnover rate with an evolutionary model. We use DNA long reads and RNA short reads from seven geographically remote samples of inbred individuals of Drosophila melanogaster to detect de novo transcripts that are gained on a short evolutionary time scale. Overall, each sampled individual contains around 2500 unspliced de novo transcripts, with most of them being sample specific. We estimate that around 0.15 transcripts are gained per year, and that each gained transcript is lost at a rate around 5× 10−5 per year. This high turnover of transcripts suggests frequent exploration of new genomic sequences within species. These rate estimates are essential to comprehend the process and timescale of de novo gene birth.
The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species
Authors: Putman Tim E , Schaper Kevin , Matentzoglu Nicolas , Rubinetti Vincent P , Alquaddoomi Faisal S , Cox Corey , Caufield J Harry , Elsarboukh Glass , Gehrke Sarah , Hegde Harshad , Reese Justin T , Braun Ian , Bruskiewich Richard M , Cappelletti Luca , Carbon Seth , Caron Anita R , Chan Lauren E , Chute Christopher G , Cortes Katherina G , De Souza Vinícius , Fontana Tommaso , Harris Nomi L , Hartley Emily L , Hurwitz Eric , Jacobsen Julius O B , Krishnamurthy Madan , Laraway Bryan J , McLaughlin James A , McMurry Julie A , Moxon Sierra A T , Mullen Kathleen R , O’Neil Shawn T , Shefchek Kent A , Stefancsik Ray , Toro Sabrina , Vasilevsky Nicole A , Walls Ramona L , Whetzel Patricia L , Osumi-Sutherland David , Smedley Damian , Robinson Peter N , Mungall Christopher J , Haendel Melissa A , Munoz-Torres Monica C 
Published: November 2023

Abstract
Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch's APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch's data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch's analytic tools by developing a customized plugin for OpenAI’s ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app.
GproteinDb in 2024: new G protein-GPCR couplings, AlphaFold2-multimer models and interface interactions
Authors: Pándy-Szekeres Gáspár , Taracena Herrera Luis P , Caroli Jimmy , Kermani Ali A , Kulkarni Yashraj , Keserű György M , Gloriam David E 
Published: November 2023

Abstract
G proteins are the major signal proteins of ∼800 receptors for medicines, hormones, neurotransmitters, tastants and odorants. GproteinDb offers integrated genomic, structural, and pharmacological data and tools for analysis, visualization and experiment design. Here, we present the first major update of GproteinDb greatly expanding its coupling data and structural templates, adding AlphaFold2 structure models of GPCR–G protein complexes and advancing the interactive analysis tools for their interfaces underlying coupling selectivity. We present insights on coupling agreement across datasets and parameters, including constitutive activity, agonist-induced activity and kinetics. GproteinDb is accessible at https://gproteindb.org.