bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying chaotic dynamics in noisy time series through multimodal deep neural networks
Authors: Giuseppi Alessandro , Menegatti Danilo , Pietrabissa Antonio 
Published: August 2024

Abstract
Chaos detection is the problem of identifying whether a series of measurements is being sampled from an underlying set of chaotic dynamics. The unavoidable presence of measurement noise significantly affects the performance of chaos detectors, as discerning chaotic dynamics from stochastic signals becomes more challenging. This paper presents a computationally efficient multimodal deep neural network tailored for chaos detection by combining information coming from the analysis of time series, recurrence plots and spectrograms. The proposed approach is the first one suitable for multi-class classification of chaotic systems while being robust with respect to measurement noise, and is validated on a dataset of 15 different chaotic and non-chaotic dynamics subject to white, pink or brown colored noise.
Neural force functional for non-equilibrium many-body colloidal systems
Authors: Zimmermann Toni , Sammüller Florian , Hermann Sophie , Schmidt Matthias , de las Heras Daniel 
Published: August 2024

Abstract
We combine power functional theory and machine learning to study non-equilibrium overdamped many-body systems of colloidal particles at the level of one-body fields. We first sample in steady state the one-body fields relevant for the dynamics from computer simulations of Brownian particles under the influence of randomly generated external fields. A neural network is then trained with this data to represent locally in space the formally exact functional mapping from the one-body density and velocity profiles to the one-body internal force field. The trained network is used to analyse the non-equilibrium superadiabatic force field and the transport coefficients such as shear and bulk viscosities. Due to the local learning approach, the network can be applied to systems much larger than the original simulation box in which the one-body fields are sampled. Complemented with the exact non-equilibrium one-body force balance equation and a continuity equation, the network yields viable predictions of the dynamics in time-dependent situations. Even though training is based on steady states only, the predicted dynamics is in good agreement with simulation results. A neural dynamical density functional theory can be straightforwardly implemented as a limiting case in which the internal force field is that of an equilibrium system. The framework is general and directly applicable to other many-body systems of interacting particles following Brownian dynamics.
Regulating the development of accurate data-driven physics-informed deformation models
Authors: Newman Will , Ghaboussi Jamshid , Insana Michael 
Published: August 2024

Abstract
The challenge posed by the inverse problem associated with ultrasonic elasticity imaging is well matched to the capabilities of data-driven solutions. This report describes how data properties and the time sequence by which the data are introduced during training influence deformation-model accuracy and training times. Our goal is to image the elastic modulus of soft linear-elastic media as accurately as possible within a limited volume. To monitor progress during training, we introduce metrics describing convergence rate and stress entropy to guide data acquisition and other timing features. For example, a regularization term in the loss function may be introduced and later removed to speed and stabilize developing deformation models as well as establishing stopping rules for neural-network convergence. Images of a 14.4 cm3 volume within 3D software phantom visually indicate the quality of modulus images resulting over a range of training variables. The results show that a data-driven method constrained by the physics of a deformed solid will lead to quantitively accurate 3D elastic modulus images with minimum artifacts.
Learning on the correctness class for domain inverse problems of gravimetry
Authors: Chen Yihang , Li Wenbin 
Published: August 2024

Abstract
We consider end-to-end learning approaches for inverse problems of gravimetry. Due to ill-posedness of the inverse gravimetry, the reliability of learning approaches is questionable. To deal with this problem, we propose the strategy of learning on the correctness class. The well-posedness theorems are employed when designing the neural-network architecture and constructing the training set. Given the density-contrast function as a priori information, the domain of mass can be uniquely determined under certain constrains, and the domain inverse problem is a correctness class of the inverse gravimetry. Under this correctness class, we design the neural network for learning by mimicking the level-set formulation for the inverse gravimetry. Numerical examples illustrate that the method is able to recover mass models with non-constant density contrast.
Engineering empathy
Authors: Gerrans Philip 
Published: August 2024

Abstract
Human intelligence has a built-in locus of concern, the self, to drive and structure cognition and action. The creativity and adaptability (as well as characteristic biases and defects) of human thinking are products of an architecture that embeds emotional processing and self representation at the core of cognition. These themes are raised and addressed in different ways by work in artificial intelligence that connects artificial emotions, general intelligence and self awareness. Although much of that work is conducted in ‘classical’ AI paradigms the themes are equally to forms of generative AI that define the current landscape. The aim of this chapter is to show how these issues arise for AI and to suggest that current debates about AI, reasoning, consciousness, morality, and autonomy lack a key ingredient: the attention to the nature of the self for whom these activities are existentially vital. There are as yet no AI systems that co-ordinate systemic function based on a predictive model of the consequences of action for a self on whose behalf action is performed.
Critical Time Intervention in Criminal Legal Settings
Authors: Barrenger Stacey , Kriegel Liat S , Angell Beth 
Published: August 2024

Abstract
Many persons with mental illnesses cycle through the criminal legal system, accumulating the structural disadvantages linked to both their illnesses and their incarceration histories. After release from prison, persons with mental illnesses are at especially high risk of recidivism, homelessness, and other adverse outcomes and typically encounter substantial barriers to accessing the limited resources that exist to meet their complex needs. This chapter discusses the use of Critical Time Intervention (CTI) with individuals with mental illness re-entering the community from correctional institutions. Evidence suggests that CTI enhances continuity of support and access to post-release mental health services, but further research is needed to examine its impact on criminal recidivism, homelessness, and other outcomes. Implementation challenges unique to this transition are identified, including limited prison access for CTI workers, unpredictable release timing, and restrictive eligibility for potential community resources.
Critical Time Intervention With Persons Experiencing First-Episode Psychosis
Authors: Lee Rufina J , Nossel Ilana R 
Published: August 2024

Abstract
This chapter focuses on an adaptation of the Critical Time Intervention (CTI) model for young people who have been psychiatrically hospitalized for their first time with a diagnosis of primary psychotic disorder. It first provides a brief overview of the recent literature on specialized early interventions for first-episode psychosis (FEP). It highlights the importance of early identification and linkage to such services to reduce disability in young people who have been recently diagnosed. It then describes how the CTI model is utilized with this population, locating it within the context of a public mental health framework that targets early identification and linkage. Finally, it presents initial findings regarding implementation and considers the model’s potential to further inform services and treatments for the FEP population.
Critical Time Intervention in European Countries
Authors: Thorning Helle , Sandø Martin , Vet René de , Lako Danielle , Smith Alex , Wolf Judith 
Published: August 2024

Abstract
Growing interest in applying Critical Time Intervention (CTI) to address service delivery challenges related to homelessness and other social problems in Europe has led to significant research and implementation activity there. This chapter describes the implementation of CTI in three western European countries: the Netherlands, England, and Denmark. For each country, the authors provide the background and impetus for the decision to use CTI, followed by a brief history of its use and research conducted on the model. They then describe how the model has been adapted to the local context and target populations, addressing both adaptation and implementation processes as well as selected outcomes from both research and non-research settings. Challenges to successful model translation and implementation include a discussion of the impact of sociopolitical and cultural differences between these countries and the United States.
Model Diffusion and Current Developments
Authors: Herman Daniel B , Conover Sarah A , Susser Ezra S 
Published: August 2024

Abstract
This chapter discusses factors associated with the widespread diffusion of the Critical Time Intervention (CTI) model. These include early randomized trials conducted by the model developers, followed soon after by other investigators; growing emphasis by funders of homelessness services to apply empirically supported interventions; and the development of a training collaborative that could help support training and implementation. Other factors include the creation of tools that promote model fidelity and training material—both of which were made freely available—supported by a new Center for the Advancement of Critical Time Intervention at Hunter College in New York City to serve as a virtual clearinghouse for relevant information and expertise. As a result of these efforts, CTI is currently being widely deployed by the US Veterans Health Administration throughout its large homelessness services system. Several American states are also currently developing statewide programs.
Syrene Soundes
Authors: Chan Eleanor 
Published: August 2024

Abstract
False relations remain one of the great enigmas of English Renaissance musical culture. Contemporary theoretical treatises explicitly discouraged their use, yet these deliberate dissonances are hallmarks of English Renaissance music. Over the centuries they have accumulated a surfeit of subsequent connotations that have obscured how they once functioned, yet they have never been fully critically explored or elucidated in an English context. Syrene Soundes excavates beneath strata of accumulated meanings to uncover the way that false relations delighted and confounded their original listeners and performers. It presents a holistic investigation of the phenomenon, examining the cultural, literary, visual, and material understanding of such dissonances in relation to the broader culture of incongruity, surprise, and error and metaphors of harmony that captured the imagination of the English in the sixteenth and seventeenth centuries. Eleanor Chan argues that interdisciplinary angles can galvanize understanding of technical musical theoretical tropes like the false relation. She demonstrates that the false relation and its graphic ephemerality can productively be explored through the lens of English Renaissance visual culture and its idiosyncratic representational strategies, and as matters of textuality and reading. By anchoring it within the milieu of the English Reformation, burgeoning aspirations towards empire, and the increasing need for a self-fashioned collective English identity, she reveals that the false relation was key to the mythology of an inherited English tradition of music-making.
Introduction
Authors: Chan Eleanor 
Published: August 2024

Abstract
The false relation was a trope of carefully mannered dissonance that was much loved by composers, performers, and listeners in the English Renaissance. Nevertheless, it remained nameless until the nineteenth century. This chapter introduces readers to the multilayered histories of its reception, use, and meanings. Along the way, it reveals that false relations had an impact that percolated far outside the musical. Beyond their role as musical theoretical tropes, they can productively be considered issues that shed light on early modern reading and English Renaissance visual culture. They are of use to those seeking to nuance their understanding of the English Renaissance from textual, art historical, devotional, and educational angles. Alongside an exploration of the origins of the false relation in hexachord mutation, this chapter also explores the mythologization of the false relation by early twentieth-century composers and musicologists in their search for a definitively ‘English’ musical style.
Factors influencing older adult community fall prevention exercise implementation: a scoping review
Authors: Sibley Kathryn M , Tittlemier Brenda , Olarinde Faith , Leadbetter Brianna K , Bouchard Danielle R 
Published: August 2024

Abstract

Background
Exercise that challenges balance is the most effective fall prevention intervention in community-dwelling older adults. Identifying factors influencing implementation of community fall prevention exercise programs is a critical step in developing strategies to support program delivery.

Objective
To identify implementation facilitators, barriers, and details reported in peer-reviewed publications on community fall prevention exercise for older adults.

Design
Scoping review.

Methods
We searched multiple databases up to July 2023 for English-language publications that reported facilitators and/or barriers to implementing an evidence-based fall prevention exercise program in adults aged 50+ years living independently. At least two reviewers independently identified publications and extracted article, implementation, and exercise program characteristics and coded barriers and facilitators using the Consolidated Framework for Implementation Research (CFIR).

Results
We included 22 publications between 2001 and July 2023 that reported factors influencing implementation of 10 exercise programs. 293 factors were reported: 183 facilitators, 91 barriers, 6 described as both a facilitator and barrier, and 13 unspecified factors. Factors represented 33 CFIR constructs across all five CFIR domains: implementation inner setting (n = 95 factors); innovation (exercise program) characteristics (n = 84); individuals involved (n = 54); implementation process (n = 40) and outer setting (n = 20). Eight publications reported implementation strategies used; 6 reported using a conceptual framework; and 13 reported implementation outcomes.

Conclusion
The high number of factors reflects the complexity of fall prevention exercise implementation. The low reporting of implementation strategies, frameworks and outcomes highlight the ongoing need for work to implement and sustain community fall prevention exercise programs.
Clinical review of substitutions or alternatives for critical chemotherapy drug shortages in hematologic malignancies
Authors: Tinajero Jose , Markary Tanya , Chen Jason , Agrawal Vaibhav , Ngo Dat 
Published: August 2024

Abstract

Purpose
Over the past decade, drug shortages have become increasingly more problematic for clinicians, with over 300 drug shortages reported in the first quarter of 2023. Shortages of chemotherapy drugs can have a negative impact on patient care, as omission or delay of treatment can lead to worse outcomes. Although many articles have been published on this topic, currently no review articles discuss strategies for using alternative regimens or substitutions in the event of severe chemotherapy drug shortages.

Summary
In this article, we review the literature on antineoplastic agents used to treat hematologic malignancies that experienced a drug shortage from 2010 through 2023, providing recommendations for substitutions and alternative regimens in the event of a critical shortage. In particular, we discuss how shortages of fludarabine, cytarabine, daunorubicin, methotrexate, and platinum agents may be addressed, including supporting clinical evidence.

Conclusion
Further publications assessing possible alternatives and substitutions for chemotherapy agents and examining the efficacy of previous strategies are needed to mitigate potentially devastating interruptions to care for patients with cancer during severe drug shortages.
On the dilemma for partial subjunctive supposition
Authors: Zhang Snow 
Published: August 2024

Abstract
In ‘The logic of partial supposition’, Eva and Hartmann present a dilemma for a normative account of partial subjunctive supposition: the natural subjunctive analogue of Jeffrey conditionalization is Jeffrey imaging, but this rule violates a natural monotonicity constraint. This paper offers a partial defence of Jeffrey imaging against Eva and Hartmann’s objection. I show that, although Jeffrey imaging is non-monotonic in Eva and Hartmann’s sense, it is what I call status quo monotonic. A status quo monotonic credal revision rule is monotonic in Eva and Hartmann’s sense if it is conservative in the sense of Meehan and Zhang (‘Jeffrey meets Kolmogorov’), but Jeffrey imaging is in general non-conservative. On the other hand, Jeffrey imaging satisfies a different constraint that I call convexity, and the only rule that is both convex and conservative is Jeffrey conditionalization. To this extent, the real dilemma for a normative account of partial subjunctive supposition is not between monotonicity (broadly construed) and Jeffrey imaging, but between convexity and conservativeness.
Soft Tissue Facial Changes Following Massive Weight Loss Secondary to Medical and Surgical Bariatric Interventions: A Systematic Review
Authors: Jafar Ali B , Jacob Jerril , Kao Wee Katherine , Ho Tang 
Published: August 2024

Abstract

Bariatric interventions, both surgical and medical, are increasingly employed by patients to achieve weight reduction and enhance overall health. However, there is growing concern about the associated changes in soft tissue facial aesthetics resulting from these interventions. In this systematic review, the authors aimed to analyze the existing literature regarding soft tissue facial changes after bariatric interventions, with a focus on the influence of massive weight loss on facial aging, attractiveness, and considerations for facial rejuvenation. A systematic review was conducted until February 10, 2024, using electronic databases such as PubMed, Scopus, Web of Science, Embase, and Google Scholar. This review was registered in the open science framework. The Covidence software (Melbourne, VIC, Australia) facilitates title, abstract, and full-text screening, as well as data extraction. In total, 309 papers were identified, 94 duplicates were removed, and 194 studies were excluded on the basis of inclusion criteria. Of the remaining 21 studies, 13 met the inclusion criteria with an additional single study from the conference abstract. Descriptive analysis was conducted. We observed a correlation between massive weight loss and facial aging. The most significant fat regional devolumization was observed along the mid-cheek region and with central neck skin laxity. The apparent age of patients was higher among those with massive weight loss. In our study, we demonstrated that massive weight loss causes accelerated facial aging, manifested through fat devolumization, and increased skin laxity. Further quantitative volumetric facial analyses postbariatric surgery would yield valuable results.

Level of Evidence: 3 (Therapeutic)
Inhibitory effects of extracts from Eucalyptus gunnii on α-synuclein amyloid fibrils
Authors: So Masatomo , Ono Misaki , Oogai Shigeki , Kondo Minako , Yamazaki Kaede , Nachtegael Charlotte , Hamajima Hiroshi , Mutoh Risa , Kato Masaki , Kawate Hisaya , Oki Tomoyuki , Kawata Yasushi , Kumamoto Shiho , Tokui Noritaka , Takei Toshiki , Shimizu Kuniyoshi , Inoue Akio , Yamamoto Naoki , Unoki Motoko , Tanabe Kenichi , Nakashima Kinichi , Sasaki Hiroyuki , Hojo Hironobu , Nagata Yasuo , Suetake Isao 
Published: August 2024

ABSTRACT
Amyloid fibril formation is associated with various amyloidoses, including neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. Despite the numerous studies on the inhibition of amyloid formation, the prevention and treatment of a majority of amyloid-related disorders are still challenging. In this study, we investigated the effects of various plant extracts on amyloid formation of α-synuclein. We found that the extracts from Eucalyptus gunnii are able to inhibit amyloid formation, and to disaggregate preformed fibrils, in vitro. The extract itself did not lead to cell damage. In the extract, miquelianin, which is a glycosylated form of quercetin and has been detected in the plasma and the brain, was identified and assessed to have a moderate inhibitory activity, compared to the effects of ellagic acid and quercetin, which are strong inhibitors for amyloid formation. The properties of miquelianin provide insights into the mechanisms controlling the assembly of α-synuclein in the brain.
GR-pKa: a message-passing neural network with retention mechanism for pKa prediction
Authors: Miao Runyu , Liu Danlin , Mao Liyun , Chen Xingyu , Zhang Leihao , Yuan Zhen , Shi Shanshan , Li Honglin , Li Shiliang 
Published: August 2024

Abstract
During the drug discovery and design process, the acid–base dissociation constant (pKa) of a molecule is critically emphasized due to its crucial role in influencing the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties and biological activity. However, the experimental determination of pKa values is often laborious and complex. Moreover, existing prediction methods exhibit limitations in both the quantity and quality of the training data, as well as in their capacity to handle the complex structural and physicochemical properties of compounds, consequently impeding accuracy and generalization. Therefore, developing a method that can quickly and accurately predict molecular pKa values will to some extent help the structural modification of molecules, and thus assist the development process of new drugs. In this study, we developed a cutting-edge pKa prediction model named GR-pKa (Graph Retention pKa), leveraging a message-passing neural network and employing a multi-fidelity learning strategy to accurately predict molecular pKa values. The GR-pKa model incorporates five quantum mechanical properties related to molecular thermodynamics and dynamics as key features to characterize molecules. Notably, we originally introduced the novel retention mechanism into the message-passing phase, which significantly improves the model’s ability to capture and update molecular information. Our GR-pKa model outperforms several state-of-the-art models in predicting macro-pKa values, achieving impressive results with a low mean absolute error of 0.490 and root mean square error of 0.588, and a high R2 of 0.937 on the SAMPL7 dataset.