bluuebunny/crossref_metadata_2025 huggingface dataset:
Clustering protein functional families at large scale with hierarchical approaches
Authors: Bordin Nicola , Scholes Harry , Rauer Clemens , Roca‐Martínez Joel , Sillitoe Ian , Orengo Christine
Published: August 2024

Proteins, fundamental to cellular activities, reveal their function and evolution through their structure and sequence. CATH functional families (FunFams) are coherent clusters of protein domain sequences in which the function is conserved across their members. The increasing volume and complexity of protein data enabled by large‐scale repositories like MGnify or AlphaFold Database requires more powerful approaches that can scale to the size of these new resources. In this work, we introduce MARC and FRAN, two algorithms developed to build upon and address limitations of GeMMA/FunFHMMER, our original methods developed to classify proteins with related functions using a hierarchical approach. We also present CATH‐eMMA, which uses embeddings or Foldseek distances to form relationship trees from distance matrices, reducing computational demands and handling various data types effectively. CATH‐eMMA offers a highly robust and much faster tool for clustering protein functions on a large scale, providing a new tool for future studies in protein function and evolution.
A novel block‐coordinate gradient descent algorithm for simultaneous grouped selection of fixed and random effects in joint modeling
Authors: Chen Shuyan , Fang Zhiqing , Li Zhong , Liu Xin
Published: August 2024

Joint models for longitudinal and time‐to‐event data are receiving increasing attention owing to its capability of capturing the possible association between these two types of data. Typically, a joint model consists of a longitudinal submodel for longitudinal processes and a survival submodel for the time‐to‐event response, and links two submodels by common covariates that may carry both fixed and random effects. However, research gaps still remain on how to simultaneously select fixed and random effects from the two submodels under the joint modeling framework efficiently and effectively. In this article, we propose a novel block‐coordinate gradient descent (BCGD) algorithm to simultaneously select multiple longitudinal covariates that may carry fixed and random effects in the joint model. Specifically, for the multiple longitudinal processes, a linear mixed effect model is adopted where random intercepts and slopes serve as essential covariates of the trajectories, and for the survival submodel, the popular proportional hazard model is employed. A penalized likelihood estimation is used to control the dimensionality of covariates in the joint model and estimate the unknown parameters, especially when estimating the covariance matrix of random effects. The proposed BCGD method can successfully capture the useful covariates of both fixed and random effects with excellent selection power, and efficiently provide a relatively accurate estimate of fixed and random effects empirically. The simulation results show excellent performance of the proposed method and support its effectiveness. The proposed BCGD method is further applied on two real data sets, and we examine the risk factors for the effects of different heart valves, differing on type of tissue, implanted in the aortic position and the risk factors for the diagnosis of primary biliary cholangitis.
Comparing methods for assessing the reliability of health care quality measures
Authors: Nieser Kenneth J. , Harris Alex H. S.
Published: August 2024

Quality measurement plays an increasing role in U.S. health care. Measures inform quality improvement efforts, public reporting of variations in quality of care across providers and hospitals, and high‐stakes financial decisions. To be meaningful in these contexts, measures should be reliable and not heavily impacted by chance variations in sampling or measurement. Several different methods are used in practice by measure developers and endorsers to evaluate reliability; however, there is uncertainty and debate over differences between these methods and their interpretations. We review methods currently used in practice, pointing out differences that can lead to disparate reliability estimates. We compare estimates from 14 different methods in the case of two sets of mental health quality measures within a large health system. We find that estimates can differ substantially and that these discrepancies widen when sample size is reduced.
Three-loop corrections to Higgs boson pair production: reducible contribution
Authors: Davies Joshua , Schönwald Kay , Steinhauser Matthias , Vitti Marco
Published: August 2024

Abstract

We compute three-loop corrections to the process gg → HH originating from one-particle reducible diagrams. This requires the computation of two-loop corrections to the gluon-gluon-Higgs vertex with an off-shell gluon. We describe in detail our approach to obtain semi-analytic results for the vertex form factors and present results for the two form factors contributing to Higgs boson pair production.
Erratum to: Localization and resummation of unstable instantons in 2d Yang-Mills
Authors: Griguolo Luca , Panerai Rodolfo , Papalini Jacopo , Seminara Domenico , Yaakov Itamar
Published: August 2024

A correction to this paper has been published: https://doi.org/10.1007/JHEP06(2024)188
Large N universality of 4d $$ \mathcal{N} $$ = 1 superconformal index and AdS black holes
Authors: Choi Sunjin , Kim Seunggyu , Song Jaewon
Published: August 2024

Abstract

We study the large N limit of the matrix models associated with the superconformal indices of four-dimensional $$ \mathcal{N} $$
N
= 1 superconformal field theories. We find that for a large class of $$ \mathcal{N} $$
N
= 1 superconformal gauge theories, the superconformal indices in the large N limit of such theories are dominated by the ‘parallelogram’ saddle, providing O(N2) free energy for the generic value of chemical potentials. This saddle corresponds to BPS black holes in AdS5 whenever a holographic dual description is available. Our saddle applies to a large class of gauge theories, including ADE quiver gauge theories, and the theories with rank-2 tensor matters. Our analysis works for most $$ \mathcal{N} $$
N
= 1 superconformal gauge theories that admit a suitable large N limit while keeping the flavor symmetry fixed. We also find ‘multi-cut’ saddle points, which correspond to the orbifolded Euclidean black holes in AdS5.
Expansions for semiclassical conformal blocks
Authors: Carneiro da Cunha Bruno , Cavalcante João Paulo
Published: August 2024

Abstract

We propose a relation the expansions of regular and irregular semiclassical conformal blocks at different branch points making use of the connection between the accessory parameters of the BPZ decoupling equations to the logarithm derivative of isomonodromic tau functions. We give support for these relations by considering two eigenvalue problems for the confluent Heun equations obtained from the linearized perturbation theory of black holes. We first derive the large frequency expansion of the spheroidal equations, and then compare numerically the excited quasi-normal mode spectrum for the Schwarzschild case obtained from the large frequency expansion to the one obtained from the low frequency expansion and with the literature, indicating that the relations hold generically in the complex modulus plane.
Matter asymmetries in the ZN dark matter-companion models
Authors: Zhang Peng , Chen Shao-Long , Kang Zhaofeng , Liu Ze-Kun
Published: August 2024

Abstract

A class of ZN≥3-symmetric WIMP dark matter models that are characterized by the semi-annihilation into the companion of dark matter has been proposed in ref. [1], providing a mechanism to evade the stringent direct detection constraint. In this work, we point out that such models naturally provide the three Sakharov elements necessary for dark matter asymmetry, and moreover this asymmetry can be transferred to the visible sector with a proper link to the leptonic or quark sector. In our minimal Z3 example, the migration to the leptonic sector is via the asymmetric companion decay into neutrinos, and the lepton asymmetry can be further transferred to the quark sector. The CP violation parameter is restrained in this model. Thus, we explore the thermal motion effect of dark matter and find that it gives an enhancement to the CP violation parameter, which is studied for the first time. A preliminary numerical analysis based on the Boltzmann equations shows that both correct relic density of dark matter and baryon asymmetry can be accommodated.
Exponential quintessence: curved, steep and stringy?
Authors: Andriot David , Parameswaran Susha , Tsimpis Dimitrios , Wrase Timm , Zavala Ivonne
Published: August 2024

Abstract

We explore the possibility that our universe’s current accelerated expansion is explained by a quintessence model with an exponential scalar potential, V = V0e−λ ϕ, keeping an eye towards λ ≥ $$ \sqrt{2} $$

2

and an open universe, favorable to a string theory realisation and with no cosmological horizon. We work out the full cosmology of the model, including matter, radiation, and optionally negative spatial curvature, for all λ > 0, performing an extensive analysis of the dynamical system and its phase space. The minimal physical requirements of a past epoch of radiation domination and an accelerated expansion today lead to an upper bound λ ≲ $$ \sqrt{3} $$

3

, which is driven slightly up in the presence of observationally allowed spatial curvature. Cosmological solutions start universally in a kination epoch, go through radiation and matter dominated phases and enter an epoch of acceleration, which is only transient for λ > $$ \sqrt{2} $$

2

. Field distances traversed between BBN and today are sub-Planckian. We discuss possible string theory origins and phenomenological challenges, such as time variation of fundamental constants. We provide theoretical predictions for the model parameters to be fitted to data, most notably the varying dark energy equation of state parameter, in light of recent results from DES-Y5 and DESI.
Ultrafast spallation dynamics of a thin gold film characterized by imaging pump-probe interferometry
Authors: Pflug Theo , Olbrich Markus , Loheit Henry , Horn and Alexander
Published: August 2024

Interferometry allows to measure microscopic displacements in the nanometer scale. This work introduces an imaging pump-probe interferometer that enables to detect the spatially resolved phase shift of the probe radiation being reflected on a sample surface after ultrashort pulsed laser excitation with a temporal resolution of 40 fs and a maximum temporal delay of 3 ns. The capability of the pump-probe interferometer is demonstrated on the spallation of a thin gold film upon femtosecond laser irradiation. The pump-probe interferometer enables to measure a minimum phase change of $$\Delta \varphi <\pi /10$$

Δ
φ
<
π
/
10

which corresponds to a displacement of $$\Delta h<$$

Δ
h
<

12.5 nm for the applied probe wavelength of 500 nm. Upon irradiation, two distinct phase changes are observable: First, an abrupt minor phase shift has been measured in the femtosecond range, which is attributed to the changed optical properties of the sample surface after excitation. Second, a more pronounced continuing phase shift increase is detectable after a few tens of picoseconds resulting from the onset of spallation. Based on the measured spatially resolved phase shift, the transient surface topography during the spallation is reconstructed. The determined velocity of the ablated material reaches a maximum of a few 1000 m/s at ten picosecond after irradiation and decreases to 250 m/s afterwards. Consequently, the introduced imaging pump-probe interferometer provides important insights into the physical processes during laser excitation as well as the subsequent laser-induced ablation, and will enable to validate theoretical models quantitatively in following studies.
Evaluating the diet in Germany with two indices focusing on healthy eating and planetary healthy eating using nationwide cross-sectional food intake data from DEGS1 (2008–2011)
Authors: Richter Almut , Loss Julika , Kuhn Daria-Alina , Moosburger Ramona , Mensink Gert B. M.
Published: August 2024

Purpose

To improve sustainability, adjustments to current diets are necessary. Therefore, limited planetary resources are considered within the healthy reference diet proposed by the EAT-Lancet Commission. The agreement with nationwide food intake was evaluated with two indices which reflect this reference and German food intake recommendations.

Methods

A healthy eating index (HEI-MON) reflecting the dietary guidelines of the German nutrition society and a planetary healthy eating index (PHEI-MON) reflecting the healthy reference diet were developed, with scores from 0 to 100. Both indices were applied to data from a nationally representative sample of the German population aged 18–79 years for which data from a 53-item food frequency questionnaire are available.

Results

Mean scores for the indices were 53 for HEI-MON and 39 for PHEI-MON. A better adherence to either guideline could be found among women, persons of older age as well as persons with higher education level. The sub-scores for HEI-MON showed high agreement with the recommendations for side dishes, fruit/nuts, (processed) meat and cereals, but low agreement with the recommendations for free sugar and vegetables/legumes. PHEI-MON sub-scores were highest for poultry, fruits and potatoes, and lowest for nuts, red meat and legumes. High scores in one index do not necessarily correspond to high scores in the other index. Individuals with more plantbased diets had higher scores in both indices, while high sugar and meat consumption led to lower scores.

Conclusions

More plant-based diets are crucial for individual and planetary health. Both indices reflect such diets which consider already health and sustainability aspects. At an individual level, the scores for both indices may differ considerably, but overall there is a huge potential in the population to adapt to a diet more in line with both guidelines.
Impact of surface conductivity on the zeta potential determination of concentrated aqueous polymer dispersions using electroacoustics and electrokinetic standard models
Authors: Frangenberg Matthias , Schmidt Annette M. , Wilkens Jan
Published: August 2024

Surface conductivity can have a significant impact on the determination of the zeta potential, but it is normally not accounted for when applying the Helmholtz-Smoluchowski or Henry models. In this study, we investigate concentrated polymer dispersions using electroacoustics and both standard models. We also pay particular attention to the influence of surface conductivity, which is characterized by conductivity measurements of the dispersion and dispersion medium. The Dukhin number as a measure of surface conductivity is calculated according to Maxwell–Wagner-O’Konski theory. Zeta potentials were determined by means of colloid vibration current (CVI) and electrophoretic light scattering (ELS) methods. It has been found that neglecting surface conductivity in standard electrokinetic models can lead to large measurement errors of up to 100% with increasing particle volume fraction. In this study, the surface conductivity is now correctly taken into account by using the conductivities of the dispersion and the dispersion medium. Alternatively, this influence can also be considered using the Dukhin number. The zeta potentials resulting from the CVI measurement are then in excellent agreement with ELS reference measurements over a wide volume fraction range.

Graphical Abstract
A Discrete Element Method Calibration Approach for Large Ore-flow Applications
Authors: Koch Lukas Alexander
Published: August 2024

The major constraint for large discrete element method (DEM) simulations is the high demand for computation power. To keep the model in a feasible range of simulation time and to conduct the numerical calculations efficiently, the implemented material can be simplified and upscaled. After this, a calibration of the material is inevitable and sets the link between the simulation model and reality. Therefore, an alternative calibration approach is established in this contribution to mimic the flow behaviour of the original material with multi-spherical DEM particles. The calibration approach utilises flow zone dimensions, which were observed in block-caving operations. Additionally, a passive draw-point is used to calibrate the angle of repose. Applying the calibration approach for Kiruna iron ore showed that, with the help of the calibration approach, the material in the simulation could successfully reproduce the targeted flow zone and angle of repose.
Regularization-based methods for ordinal quantification
Authors: Bunse Mirko , Moreo Alejandro , Sebastiani Fabrizio , Senz Martin
Published: August 2024

Quantification, i.e., the task of predicting the class prevalence values in bags of unlabeled data items, has received increased attention in recent years. However, most quantification research has concentrated on developing algorithms for binary and multi-class problems in which the classes are not ordered. Here, we study the ordinal case, i.e., the case in which a total order is defined on the set of $$n>2$$

n
>
2

classes. We give three main contributions to this field. First, we create and make available two datasets for ordinal quantification (OQ) research that overcome the inadequacies of the previously available ones. Second, we experimentally compare the most important OQ algorithms proposed in the literature so far. To this end, we bring together algorithms proposed by authors from very different research fields, such as data mining and astrophysics, who were unaware of each others’ developments. Third, we propose a novel class of regularized OQ algorithms, which outperforms existing algorithms in our experiments. The key to this gain in performance is that our regularization prevents ordinally implausible estimates, assuming that ordinal distributions tend to be smooth in practice. We informally verify this assumption for several real-world applications.
Smartphone GPS-Based Exposure to Greenspace and Walkability and Accelerometer-Assessed Physical Activity During Pregnancy and Early Postpartum—Evidence from the MADRES Cohort
Authors: Yi Li , Habre Rima , Mason Tyler B. , Xu Yan , Cabison Jane , Rosales Marisela , Chu Daniel , Chavez Thomas A. , Johnson Mark , Eckel Sandrah P. , Bastain Theresa M. , Breton Carrie V. , Wilson John P. , Dunton Genevieve F.
Published: August 2024

A growing number of studies have associated walkability and greenspace exposure with greater physical activity (PA) in women during pregnancy. However, most studies have focused on examining women’s residential environments and neglected exposure in locations outside the home neighborhood. Using 350 person-days (N = 55 participants) of smartphone global positioning system (GPS) location and accelerometer data collected during the first and third trimesters and 4–6 months postpartum from 55 Hispanic pregnant women from the Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) study, we examined the day-level effect of women’s exposure to walkability and greenspace on their PA outcomes during pregnancy and in the early postpartum period. Moderate-to-vigorous physical activity [MVPA] minutes per day was assessed using accelerometers. Walkability and greenspace were measured using geographic information systems (GIS) within women’s daily activity spaces (i.e., places visited and routes taken) recorded using a smartphone GPS and weighted by time spent. We used a generalized linear mixed-effects model to estimate the effects of daily GPS-derived environmental exposures on day-level MVPA minutes. Results showed that women engaged in 23% more MVPA minutes on days when they had some versus no exposure to parks and open spaces in activity spaces (b = 1.23; 95%CI: 1.02–1.48). In addition, protective effects of daily greenspace and walkability exposure on MVPA were stronger in the first and third trimesters, among first-time mothers, and among women who had high pre-pregnancy body mass index (BMI) and lived in least-safe neighborhoods. Our results suggest that daily greenspace and walkability exposure are important for women’s PA and associated health outcomes during pregnancy and early postpartum.
An Integrated Embodiment Concept Combines Neuroethics and AI Ethics – Relational Perspectives on Artificial Intelligence, Emerging Neurotechnologies and the Future of Work
Authors: Weh Ludwig
Published: August 2024

Applications of artificial intelligence (AI) bear great transformative potential in the economic, technological and social sectors, impacting especially future work environments. Ethical regulation of AI requires a relational understanding of the technology by relevant stakeholder groups such as researchers, developers, politicians, civil servants, affected workers or other users applying AI in their work processes. The purpose of this paper is to support relational AI discourse for an improved ethical framing and regulation of the technology. The argumentation emphasizes a widespread reembodied understanding of AI technology as critical requirement for capable ethical and regulatory frameworks. A sociotechnical perspective encourages the material interpretation of AI as reembodied adaptation of biological intelligence. Reviewing Cartesian dualism as motivating the disembodiment of human intelligence for its transfer to machines, the argumentation develops an integrated embodiment concept of AI in its mechanistic, naturalistic, combined AI and neuroethical, and relational contexts. This concept is discussed in relation to basic phenomenological and postphenomenological assumptions, and is applied to the example of AI-based neurotechnology potentially disrupting future work processes. Strengthening a human-centered approach, the presented concept for a reembodied understanding of AI technology enables better integrated ethical and regulatory debates, and improves social discourse and human agency in developing and regulating AI technology.
Dissemination of the 2022 ASMBS and IFSO Guidelines for Bariatric Surgery: What Has Reached Primary Care Providers?
Authors: Hulse John , Slay Richard , Bryant Mary Kate , Byrne T. Karl , Pullatt Rana
Published: August 2024

Background

Only 1% of Americans eligible for metabolic and bariatric surgery (MBS) receive MBS. Prior studies have analyzed primary care provider (PCP) referral patterns and perceptions of MBS as a potential barrier to increasing MBS. However, less data exists regarding PCP knowledge of MBS indications and outcomes. Following the 2022 update to the indications for MBS by the ASMBS and IFSO, the number of eligible patients is only expected to increase. We evaluated PCP knowledge regarding the existence of the 2022 ASMBS and IFSO updated guidelines, MBS indications, and MBS outcomes.

Methods

An 11-question survey was emailed to primary care residents, advanced practice providers, and faculty at a single institution.

Results

Of 151 surveys distributed, 39.7% responded (n = 60). 95% were unaware of the 2022 updated guidelines. On multiple choice questions, 16.3% correctly identified the average weight loss from MBS, and 46.8% correctly answered the diabetes remission rate following MBS. Trainee answers were not statistically significant from practicing PCPs. Fifteen respondents had referred a patient for MBS, but this subgroup did not perform significantly better on the assessment. A total of 72.3% of respondents reported inadequate MBS education during their training, and 85.1% were interested in additional education.

Conclusions

We present the first assessment of PCP MBS knowledge since the release of the 2022 updated ASMBS and IFSO guidelines. This study indicates a gap in PCPs’ knowledge regarding the updated guidelines and represents an opportunity for collaboration with our primary care colleagues to provide further MBS education.
Antecedents of researchers’ behavioral intentions to use crowdsourcing in science: a multilevel approach
Authors: Lenart-Gansiniec Regina , Czakon Wojciech , Meyer Natanya
Published: August 2024

Crowdsourcing in science is a collaborative online process through which scientists involve a group of self-selected individuals of varying, diverse knowledge and skills via an open call on the Internet and/or online platforms to undertake a specified research task or set of tasks. It is a response to the call for more inclusive, responsive and transparent research in science. Despite the growing importance of crowdsourcing in science, little is known about which factors influence researchers’ behavioural intentions to use crowdsourcing in science. This study aims to identify factors that influence researchers’ behavioural intentions to use crowdsourcing in science, as well as to develop and test a theoretical multilevel model of researchers’ behavioural intentions to use crowdsourcing in science. We use a sequential mixed method: (1) focus group interviews with 36 researchers from six fields of science, in line with the OECD classification; and (2) partial least squares structural equation modelling (PLS-SEM), using a survey of 552 management researchers to test the model. Managerial and theoretical results show that the antecedents to perceived usefulness and perceived organizational support positively impact the intention to use crowdsourcing in science. Our study offers a new conceptual framework that presents antecedents relevant to scholars’ intention to use crowdsourcing in science. The results bring implications for researchers, managerial staff of institutions of higher education and decision-makers that can encourage researchers of crowdsourcing in science to further develop scientific knowledge in the field.
60 Jahre Freiwilliges Soziales Jahr
Authors: Jakob Gisela
Published: August 2024

Das Freiwillige Soziale Jahr (FSJ) stellt ein passgenaues Angebot für Jugendliche und junge Erwachsene im Übergang Schule/Ausbildung dar. Seine Geschichte ist durch eine stetige Zunahme der Teilnehmer_innen und eine Ausdifferenzierung des Formats gekennzeichnet. Dies kam allerdings nicht allen Gruppen gleichermaßen zugute, sondern vor allem junge Menschen mit Beeinträchtigungen blieben weitgehend ausgeschlossen. Neben Anforderungen zur Öffnung für bislang vernachlässigte Zielgruppen kommen für Trägerorganisationen und Einrichtungen weitere Herausforderungen hinzu: der Umgang mit Tendenzen einer Indienstnahme für politische Zwecke sowie die derzeitige Auseinandersetzung mit Forderungen nach einer verpflichtenden Dienstzeit.
Effect of deep learning reconstruction on the assessment of pancreatic cystic lesions using computed tomography
Authors: Kanzawa Jun , Yasaka Koichiro , Ohizumi Yuji , Morita Yuichi , Kurokawa Mariko , Abe Osamu
Published: August 2024

This study aimed to compare the image quality and detection performance of pancreatic cystic lesions between computed tomography (CT) images reconstructed by deep learning reconstruction (DLR) and filtered back projection (FBP). This retrospective study included 54 patients (mean age: 67.7 ± 13.1) who underwent contrast-enhanced CT from May 2023 to August 2023. Among eligible patients, 30 and 24 were positive and negative for pancreatic cystic lesions, respectively. DLR and FBP were used to reconstruct portal venous phase images. Objective image quality analyses calculated quantitative image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) using regions of interest on the abdominal aorta, pancreatic lesion, and pancreatic parenchyma. Three blinded radiologists performed subjective image quality assessment and lesion detection tests. Lesion depiction, normal structure illustration, subjective image noise, and overall image quality were utilized as subjective image quality indicators. DLR significantly reduced quantitative image noise compared with FBP (p < 0.001). SNR and CNR were significantly improved in DLR compared with FBP (p < 0.001). Three radiologists rated significantly higher scores for DLR in all subjective image quality indicators (p ≤ 0.029). Performance of DLR and FBP were comparable in lesion detection, with no statistically significant differences in the area under the receiver operating characteristic curve, sensitivity, specificity and accuracy. DLR reduced image noise and improved image quality with a clearer depiction of pancreatic structures. These improvements may have a positive effect on evaluating pancreatic cystic lesions, which can contribute to appropriate management of these lesions.
Afrothismia ugandensis nom. nov. (Afrothismiaceae), Critically Endangered and endemic to Budongo Central Forest Reserve, Uganda
Authors: Cheek Martin , Gereau Roy E. , Kalema James
Published: August 2024

The fully mycotrophic (or mycoheterophic) Afrothismia ugandensis Cheek nom. nov. (Afrothismiaceae), formerly described as A. winkleri (Engl.) Schltr. var. budongensis Cowley from the Budongo Forest in Western Uganda, is renamed, redescribed and illustrated. This change in status is supported by eight newly elucidated, qualitative, morphological, diagnostic characters despite the overall similarity with A. winkleri, a species restricted to Cameroon and Gabon. Afrothismia ugandensis is remarkable in the genus for occurring in semi-deciduous (not evergreen) forest and for having ellipsoid or ovoid (vs globose) root bulbils. It has only been recorded twice, first in August 1940, and most recently in June 1998, despite targeted searches in recent years. In both 1940 and 1998, only single individuals appear to have been detected. A single site for the species is known with certainty. It is here assessed as Critically Endangered [CR B2ab(iii); D1] using the IUCN categories and criteria. A. ugandensis is threatened by forest degradation and clearance due to illegal, selective, small-holder logging for firewood and charcoal, timber and limited agriculture.
Technology and Interspecies Musical Practice
Authors: Kass Susanne
Published: August 2024

This case study on the work of interspecies musician David Rothenberg explores how engaging with the songs and rhythms of other species continues to challenge his musical practice and aesthetic. Technology, science and art come together in an artistic and research practice, which is grounded in the belief that technologies can bring us closer to nature. The article outlines how Umwelt theory, enactive music cognition, biosemiotics and the phenomenology of human-technology relations are engaged in the perception and creation of musical experiences. It also looks at how interdisciplinary research practices that traverse zoomusicology, the visual and performing arts, and data visualisation contribute to interspecies music theory and practice. The article concludes by presenting four interspecies auditory dispositives as a guide to how knowledge, tools and practice are entangled in concrete examples from Rothenberg’s musical collaborations with nightingales, humpback whales, periodical cicadas and pond life.
Pattern Theory of Selflessness: How Meditation May Transform the Self-Pattern
Authors: Berkovich-Ohana Aviva , Brown Kirk Warren , Gallagher Shaun , Barendregt Henk , Bauer Prisca , Giommi Fabio , Nyklíček Ivan , Ostafin Brian , Raffone Antonino , Slagter Heleen A. , Trautwein Fynn-Mathis , Vago David , Amaro Ajahn
Published: August 2024

For many centuries, scholars and philosophers from wisdom traditions in different cultures have reported and discussed non-self states of consciousness. These states can be both short-term (state, transitory) and long-term (trait, lasting) conditions. However, in psychology, the importance of a healthy self is usually emphasized, and some theorists have dismissed the idea of “selfless” modes of functioning. This disagreement hinders further empirical progress in the study of self and the way it might be affected by meditation. This paper addresses this issue by providing an interdisciplinary conceptual discussion, grounded in the pattern theory of self (PTS). According to PTS, what we call “self” is a complex pattern of dynamically related constituent processes, which include embodied, experiential (prereflective), affective, psychological/cognitive, reflective, narrative, intersubjective, ecological, and normative processes. We propose that Buddhist and secular meditative practices induce a reorganization of the self-pattern, allowing individuals to experience a “selfless” state, both temporarily and persistently. We then put forward a heuristic model, the pattern theory of selflessness (PTSL), possibly experienced through meditation practices. The proposed PTSL model consists of six transformations that contribute to self-pattern reorganization in a nonlinear and iterative manner: consolidating and integrating the self-pattern; cultivating concentration and present-moment awareness; cultivating mindful awareness; self-deconstruction (non-self) states; self-flexibility; and self-liberation as a trait. This conceptual analysis and integrative view contributes to the growing field of consciousness and contemplative research by advancing the contemporary understanding of non-self experience and its relation to Buddhist and secular meditation. The proposed model serves as a basis for interdisciplinary efforts to guide empirical research in this area.
Self-Deception: A Case Study in Folk Conceptual Structure
Authors: Isern-Mas Carme , Hannikainen Ivar R.
Published: August 2024

Theoretical debates around the concept of self-deception revolve around identifying the conditions for a behavior to qualify as self-deception. Experiments 1 and 2 revealed that various candidate features—such as intent, belief change, and motive—are treated as sufficient, but non-necessary, conditions according to the lay concept of self-deception. This led us to ask whether there are multiple lay concepts, such that different participants endorse competing theories (the disagreement view), or whether individual participants assign partial weight to various features and consequently waver in cases of middling similarity (the conflict view). In Experiment 3, by-participant regression models uncovered that most participants additively consider multiple characteristics of the prototype of self-deception, while only a minority of participants treat a characteristic (or a combination thereof) as necessary and sufficient. In sum, by disambiguating interpersonal disagreement and intrapersonal conflict in a within-subjects design, the present experiments indicate that the lay concept may primarily exhibit a prototype structure. In closing, we suggest that future research deploying this method may help to explain why experimental research on philosophical concepts often engenders partial support for competing theories.
Centering Equity in the Implementation of Exposure and Response Prevention for Pediatric OCD: Current Evidence and Future Directions
Authors: Rudrabhatla Asha , Flowers Sasha , Becker-Haimes Emily M. , Sanchez Amanda L.
Published: August 2024

Purpose of Review

Exposure and Response Prevention (ERP), the gold standard psychosocial treatment for pediatric OCD, is severely underutilized in routine practice. The majority of youth in need do not receive ERP, with minoritized youth being even less likely to receive and benefit from ERP. Improving the equitable implementation of ERP is pivotal to improving outcomes for youth with OCD. This article examines determinants of equitable implementation and the efforts to date to improve ERP access and response across multiple levels of implementation context (e.g., clinician, innovation, societal).

Recent Findings

Determinants exist across contextual levels that inhibit or promote ERP access and response including lack of ERP cultural responsiveness, clinician training and attitudes, client stigma, therapeutic alliance, organizational supports, and workforce shortages. Most efforts have been focused on improving access through clinician training. Emerging work has also attempted to address both access and response through expanding the workforce capacity and improving the cultural responsiveness of ERP.

The review highlights the complex, multifactorial efforts required to achieve equitable access and treatment outcomes for youth with OCD. Our review suggests that there has been a disproportionate effort to date to improve ERP access and response by targeting clinicians directly; however, sustained change is unlikely unless policy and structural factors are addressed.
Depressive Symptoms Affect Cognitive Functioning from Middle to Late Adulthood: Ethnoracial Minorities Experience Greater Repercussions
Authors: Persin Michael J. , Payen Ameanté , Bateman James R. , Alessi Maria G. , Price Brittany C. , Bennett Jeanette M.
Published: August 2024

Cognitive deficits, a diagnostic criterion for depressive disorders, may precede or follow the development of depressive symptoms and major depressive disorder. However, an individual can report an increase in depressive symptoms without any change in cognitive functioning. While ethnoracial minority group differences exist, little is known to date about how the relationship between depressive symptoms and cognitive function may differ by ethnoracial minority status. Utilizing data from the Midlife in the United States (MIDUS) study waves II (M2) and III (M3), this study examines the relationship between depressive symptoms and cognitive functioning concurrently and longitudinally in community-dwelling adults, as well as whether the results differed by ethnoracial minority status. Our participants included 910 adults (43.8% male, 80.8% White, 54.4 ± 11.5 years old at M2). Cross-sectionally, depressive symptoms, ethnoracial minority status, and their interaction had significant effects on cognitive function, consistent with previous investigations. Longitudinally, higher M2 depressive symptoms predicted poorer cognitive function at M3 over and above M2 cognitive functioning, but only within the ethnoracial minority sample. Our finding suggests that depressive symptoms predict cognitive functioning both concurrently and across time, and this relationship is moderated by ethnoracial identity, resulting in greater cognitive deficits among ethnoracial minority groups compared to their non-Hispanic White counterparts.
SAM-driven MAE pre-training and background-aware meta-learning for unsupervised vehicle re-identification
Authors: Wang Dong , Wang Qi , Min Weidong , Gai Di , Han Qing , Li Longfei , Geng Yuhan
Published: August 2024

Distinguishing identity-unrelated background information from discriminative identity information poses a challenge in unsupervised vehicle re-identification (Re-ID). Re-ID models suffer from varying degrees of background interference caused by continuous scene variations. The recently proposed segment anything model (SAM) has demonstrated exceptional performance in zero-shot segmentation tasks. The combination of SAM and vehicle Re-ID models can achieve efficient separation of vehicle identity and background information. This paper proposes a method that combines SAM-driven mask autoencoder (MAE) pre-training and background-aware meta-learning for unsupervised vehicle Re-ID. The method consists of three sub-modules. First, the segmentation capacity of SAM is utilized to separate the vehicle identity region from the background. SAM cannot be robustly employed in exceptional situations, such as those with ambiguity or occlusion. Thus, in vehicle Re-ID downstream tasks, a spatially-constrained vehicle background segmentation method is presented to obtain accurate background segmentation results. Second, SAM-driven MAE pre-training utilizes the aforementioned segmentation results to select patches belonging to the vehicle and to mask other patches, allowing MAE to learn identity-sensitive features in a self-supervised manner. Finally, we present a background-aware meta-learning method to fit varying degrees of background interference in different scenarios by combining different background region ratios. Our experiments demonstrate that the proposed method has state-of-the-art performance in reducing background interference variations.
HDAC2 promotes autophagy-associated HCC malignant progression by transcriptionally activating LAPTM4B
Authors: Wang Meifeng , Liao Jianping , Wang Jie , Xu Meifang , Cheng Ye , Wei Lixin , Huang Aimin
Published: August 2024

Hepatocellular carcinoma (HCC) is a significant global health challenge. The activation of autophagy plays an essential role in promoting the proliferation and survival of cancer cells. However, the upstream regulatory network and mechanisms governing autophagy in HCC remain unclear. This study demonstrated that histone deacetylase 2 (HDAC2) regulates autophagy in HCC. Its expression was elevated in HCC tissues, and high HDAC2 expression was strongly associated with poor prognosis in individuals with HCC. Integrated in vitro and in vivo investigations confirmed that HDAC2 promotes autophagy and autophagy-related malignant progression in HCC. Mechanistically, HDAC2 bound specifically to the lysosome-associated protein transmembrane 4-β (LAPTM4B) promoter at four distinct binding sites, enhancing its transcriptional activation and driving autophagy-related malignant progression in HCC. These findings establish LAPTM4B as a direct target gene of HDAC2. Furthermore, the selective inhibitor of HDAC2 effectively alleviated the malignant development of HCC. In addition, multivariate Cox regression analysis of 105 human HCC samples revealed that HDAC2 expression is an independent predictor of HCC prognosis. This study underscores the crucial role of the HDAC2-LAPTM4B axis in regulating autophagy in the malignant evolution of HCC and highlights the potential of targeting HDAC2 to prevent and halt the malignant progression of HCC.
C5aR1 antagonism suppresses inflammatory glial responses and alters cellular signaling in an Alzheimer’s disease mouse model
Authors: Schartz Nicole D. , Liang Heidi Y. , Carvalho Klebea , Chu Shu-Hui , Mendoza-Arvilla Adrian , Petrisko Tiffany J. , Gomez-Arboledas Angela , Mortazavi Ali , Tenner Andrea J.
Published: August 2024

Alzheimer’s disease (AD) is the leading cause of dementia in older adults, and the need for effective, sustainable therapeutic targets is imperative. The complement pathway has been proposed as a therapeutic target. C5aR1 inhibition reduces plaque load, gliosis, and memory deficits in animal models, however, the cellular bases underlying this neuroprotection were unclear. Here, we show that the C5aR1 antagonist PMX205 improves outcomes in the Arctic48 mouse model of AD. A combination of single cell and single nucleus RNA-seq analysis of hippocampi derived from males and females identified neurotoxic disease-associated microglia clusters in Arctic mice that are C5aR1-dependent, while microglial genes associated with synapse organization and transmission and learning were overrepresented in PMX205-treated mice. PMX205 also reduced neurotoxic astrocyte gene expression, but clusters associated with protective responses to injury were unchanged. C5aR1 inhibition promoted mRNA-predicted signaling pathways between brain cell types associated with cell growth and repair, while suppressing inflammatory pathways. Finally, although hippocampal plaque load was unaffected, PMX205 prevented deficits in short-term memory in female Arctic mice. In conclusion, C5aR1 inhibition prevents cognitive loss, limits detrimental glial polarization while permitting neuroprotective responses, as well as leaving most protective functions of complement intact, making C5aR1 antagonism an attractive therapeutic strategy for AD.
Transporter-mediated depletion of extracellular proline directly contributes to plant pattern-triggered immunity against a bacterial pathogen
Authors: Rogan Conner J. , Pang Yin-Yuin , Mathews Sophie D. , Turner Sydney E. , Weisberg Alexandra J. , Lehmann Silke , Rentsch Doris , Anderson Jeffrey C.
Published: August 2024

Plants possess cell surface-localized immune receptors that detect microbe-associated molecular patterns (MAMPs) and initiate defenses that provide effective resistance against microbial pathogens. Many MAMP-induced signaling pathways and cellular responses are known, yet how pattern-triggered immunity (PTI) limits pathogen growth in plants is poorly understood. Through a combined metabolomics and genetics approach, we discovered that plant-exuded proline is a virulence-inducing signal and nutrient for the bacterial pathogen Pseudomonas syringae, and that MAMP-induced depletion of proline from the extracellular spaces of Arabidopsis leaves directly contributes to PTI against P. syringae. We further show that MAMP-induced depletion of extracellular proline requires the amino acid transporter Lysine Histidine Transporter 1 (LHT1). This study demonstrates that depletion of a single extracellular metabolite is an effective component of plant induced immunity. Given the important role for amino acids as nutrients for microbial growth, their depletion at sites of infection may be a broadly effective means for defense against many pathogens.
Future hydrogen economies imply environmental trade-offs and a supply-demand mismatch
Authors: Terlouw Tom , Rosa Lorenzo , Bauer Christian , McKenna Russell
Published: August 2024

Hydrogen will play a key role in decarbonizing economies. Here, we quantify the costs and environmental impacts of possible large-scale hydrogen economies, using four prospective hydrogen demand scenarios for 2050 ranging from 111–614 megatonne H2 year−1. Our findings confirm that renewable (solar photovoltaic and wind) electrolytic hydrogen production generates at least 50–90% fewer greenhouse gas emissions than fossil-fuel-based counterparts without carbon capture and storage. However, electrolytic hydrogen production could still result in considerable environmental burdens, which requires reassessing the concept of green hydrogen. Our global analysis highlights a few salient points: (i) a mismatch between economical hydrogen production and hydrogen demand across continents seems likely; (ii) region-specific limitations are inevitable since possibly more than 60% of large hydrogen production potentials are concentrated in water-scarce regions; and (iii) upscaling electrolytic hydrogen production could be limited by renewable power generation and natural resource potentials.
Drastic increase in the magnitude of very rare summer-mean vapor pressure deficit extremes
Authors: Hermann Mauro , Wernli Heini , Röthlisberger Matthias
Published: August 2024

Summers with extremely high vapor pressure deficit contribute to crop losses, ecosystem damages, and wildfires. Here, we identify very rare summer vapor pressure deficit extremes globally in reanalysis data and climate model simulations, and quantify the contributions of temperature and atmospheric moisture anomalies to their intensity. The simulations agree with reanalysis data regarding these physical characteristics of historic vapor pressure deficit extremes, and show a +33/+28% increase in their intensity in the northern/southern mid-latitudes over this century. About half of this drastic increase in the magnitude of extreme vapor pressure deficit anomalies is due to climate warming, since this quantity depends exponentially on temperature. Further contributing factors are increasing temperature variability (e.g., in Europe) and the expansion of soil moisture-limited regions. This study shows that to avoid amplified impacts of future vapor pressure deficit extremes, ecosystems and crops must become more resilient not only to an increasing mean vapor pressure deficit, but additionally also to larger seasonal anomalies of this quantity.