bluuebunny/crossref_metadata_2025_split huggingface dataset:
Psychological Themes in Blaustein’s Philosophy
Authors: Płotka Witold 
Published: September 2024

AbstractIn his works, Blaustein used a complex analytical method to describe psychic life. He explicitly called this approach “descriptive psychology” (psychologia deskryptywna), and he noted on many occasions that he did research “on the borderline of psychology.” This should come as no surprise, as he was trained in philosophy by Twardowski, a direct student of Brentano. The presence of Brentano’s thought in the school of Twardowski is well described by, for instance, Liliana Albertazzi, Arianna Betti, Jan Woleński, and others. Indeed, after his arrival in Lvov in 1895, in his early writings, Twardowski developed—as I attempt to show in this chapter—a Brentanian notion of philosophy based on psychology and focused on “mental phenomena.” By claiming that philosophy examines mental phenomena, Twardowski set the psychological trend of the Lvov–Warsaw School, which included, in addition to Blaustein, Władysław Witwicki (1878–1948), Bronisław Bandrowski (1879–1914), Ludwik Jaxa-Bykowski (1881–1948), Stefan Baley (1885–1952), Stefan Błachowski (1889–1962), Salomon Igel (1889–1942), Mieczysław Kreutz (1893–1971), and Walter Auerbach (1900–1942 [?]). In this chapter, I discuss Teresa Rzepa’s idea that Blaustein can be considered a part of this group of scholars. Psychology was still a popular field of research in Lvov during Blaustein’s studies in the 1920s. Following Twardowski, Blaustein indeed used a variety of descriptive-psychological tools in his investigations. Nonetheless, his view of psychology cannot be reduced only to the Brentano–Twardowski legacy. After all, he referred to Gestalt psychology or to the conception of psychology put forward by Dilthey, not to mention Husserl’s phenomenological psychology. Whereas I will discuss Blaustein’s polemic against Husserl’s method in Chap. 5, here I attempt to show that he combined a variety of detailed ideas and procedures that had been developed by, for instance, Brentano, Twardowski, Stumpf or Dilthey. By claiming this, I will argue against Krzysztof Wieczorek, who holds that Blaustein overcame Brentano’s heritage by adapting Husserl’s phenomenology. If Wieczorek was right, Blaustein’s descriptive psychology was a mere introduction to his phenomenology. Accordingly, the latter can be understood in Blaustein’s writings without the former, which—as I will show in this chapter—is false. In this regard, I will argue that philosophical psychology is one of the cornerstones of Blaustein’s method; as such, it cannot be excluded from Blaustein’s writings or reduced to his account of phenomenology.
The Basics of Blaustein’s Descriptive Psychology in the Context of Twardowski’s Theory of Presentations
Authors: Płotka Witold 
Published: September 2024

AbstractBlaustein’s project of philosophical psychology, for which he used the term “descriptive psychology” (psychologia deskryptywna), was—as already stated in Chap. 3—deeply rooted in the nineteenth- and twentieth-century heritage of psychology; however, Blaustein was a critical reader of this rich legacy. He elaborated different approaches and sought efficient tools to analyze psychic life. Psychology was, for him, a descriptive method which accounted for mental phenomena as wholes that ought to be analyzed or described as a combination of the simplest parts. The general purpose of this discipline was to classify mental phenomena. Nonetheless, whereas Brentano or Twardowski attempted to address a unified and complete taxonomy of mental phenomena, including presentations, judgments, emotions and (eventually defined as a separate class) will, Blaustein instead focused solely on presentations. Of course, in his writings, one finds some clues that he preferred Twardowski’s four-class taxonomy over Brentano’s three-part division; however, again, there is no in-depth discussion of this categorization. Instead, Blaustein formulated an interesting and original analysis of different classes of presentations. With these ideas in mind, the present chapter aims to introduce the basics of Blaustein’s descriptive psychology by discussing the sources, main ideas, arguments, and development of his theory of presentations. By doing so, I will explore the theoretical background of his philosophy, but a few remarks are necessary here.
A Reappraisal of Blaustein’s Exposition of Husserl’s Theory of Content
Authors: Płotka Witold 
Published: September 2024

AbstractBlaustein’s analyses contained in Husserlowska nauka… [Husserl’s Theory...] took a wide perspective on the problems discussed in the book. This enabled Blaustein to clearly define the value of Husserl’s theories compared to the traditions of Bolzano as well as Brentano and Twardowski. However, rather than stopping at the presentation and discussion of the theory of content, Blaustein raises interesting objections to it. As I have stressed in the preceding chapter, these objections resulted in part from his original findings that he later used in other object-oriented and systematic research. In the present chapter, I want to ask to what extent his critique of the theory of content in Husserl may be considered valid. I want to define the elements in Blaustein’s interpretation that seem to diverge from Husserl’s position. What comes to the fore in this context is the issue of psychologism and the related problem of understanding reduction. I want to address these two problems at the beginning of the chapter. Next, I will try to formulate a phenomenological, i.e., metaphysically neutral, interpretation of the phenomenal world to which Blaustein referred, as he analyzed the theory of content in Husserl. Finally, I will assess the interpretative proposal made by Blaustein, identifying its strong and weak points.
Temporal Evaluation of Uncertainty Quantification Under Distribution Shift
Authors: Svensson Emma , Friesacher Hannah Rosa , Arany Adam , Mervin Lewis , Engkvist Ola 
Published: September 2024

AbstractUncertainty quantification is emerging as a critical tool in high-stakes decision-making processes, where trust in automated predictions that lack accuracy and precision can be time-consuming and costly. In drug discovery, such high-stakes decisions are based on modeling the properties of potential drug compounds on biological assays. So far, existing uncertainty quantification methods have primarily been evaluated using public datasets that lack the temporal context necessary to understand their performance over time. In this work, we address the pressing need for a comprehensive, large-scale temporal evaluation of uncertainty quantification methodologies in the context of assay-based molecular property prediction. Our novel framework benchmarks three ensemble-based approaches to uncertainty quantification and explores the effect of adding lower-quality data during training in the form of censored labels. We investigate the robustness of the predictive performance and the calibration and reliability of predictive uncertainty by the models as time evolves. Moreover, we explore how the predictive uncertainty behaves in response to varying degrees of distribution shift. By doing so, our analysis not only advances the field but also provides practical implications for real-world pharmaceutical applications.
Latent-Conditioned Equivariant Diffusion for Structure-Based De Novo Ligand Generation
Authors: Cremer Julian , Le Tuan , Clevert Djork-Arné , Schütt Kristof T. 
Published: September 2024

AbstractWe propose PoLiGenX for de novo ligand design using latent-conditioned, target-aware equivariant diffusion. Our model leverages the conditioning of the generation process on reference molecules within a protein pocket to produce shape-similar de novo ligands that can be used for target-aware hit expansion and hit optimization. The results of our study showcase the efficacy of PoLiGenX in ligand design. Docking scores indicate that the generated ligands exhibit superior binding affinity compared to the reference molecule while preserving the shape. At the same time, our model maintains chemical diversity, ensuring the exploration of diverse chemical space. The evaluation of Lipinski’s rule of five suggests that the sampled molecules possess a higher drug-likeness than the reference data. This constitutes an important step towards the controlled generation of therapeutically relevant de novo ligands tailored to specific protein targets.
Leveraging Quantum Mechanical Properties to Predict Solvent Effects on Large Drug-Like Molecules
Authors: Hilfiker Mathias , Sandonas Leonardo Medrano , Klähn Marco , Engkvist Ola , Tkatchenko Alexandre 
Published: September 2024

AbstractUnderstanding how solvation affects structure-property and property-property relationships of drug-like molecules is crucial for de novo design, as most relevant reactions occur in aqueous environments. We have thus performed an exhaustive analysis of the recently proposed Aquamarine dataset to gain insights into the effect of solvent-molecule interaction on the quantum-mechanical (QM) properties of large drug-like molecules. Our results show that the inclusion of an implicit solvent model of water changes the values of (extensive and intensive) QM properties but it does not alter the correlations among them. Moreover, we have found that solvation can limit the identification of unique molecular conformations, with variations in specific properties being rationalized by the extent of structural changes. $$\varDelta $$
Δ
-learning approach was used to predict solvent effects on the dipole moment $$\mu $$
μ
and the many-body dispersion energy $$E_\textrm{MBD}$$

E
MBD

, resulting in more accurate and scalable predictive models compared to these directly trained on solvated properties. Hence, our work provides valuable insights into the effect of solvent-molecule interaction on physicochemical properties, which could assist in the development of machine-learning models for designing solvated molecules of pharmaceutical and biological relevance.
Towards Interpretable Models of Chemist Preferences for Human-in-the-Loop Assisted Drug Discovery
Authors: Nahal Yasmine , Heinonen Markus , Kabeshov Mikhail , Janet Jon Paul , Nittinger Eva , Engkvist Ola , Kaski Samuel 
Published: September 2024

AbstractIn recent years, there has been growing interest in leveraging human preferences for drug discovery to build models that capture chemists’ intuition for de novo molecular design, lead optimization, and prioritization for experimental validation. However, existing models derived from human preferences in chemistry are often black-boxes, lacking interpretability regarding how humans form their preferences. Enhancing transparency in human-in-the-loop learning is crucial to ensure that such approaches in drug discovery are not unduly affected by subjective bias, noise or inconsistency. Moreover, interpretability can promote the development and use of multi-user models in drug design projects, integrating multiple expert perspectives and insights into multi-objective optimization frameworks for de novo molecular design. This also allows for assigning more or less weight to experts based on their knowledge of specific properties. In this paper, we present a methodology for decomposing human preferences based on binary responses (like/dislike) to molecules essentially proposed by generative chemistry models, and inferring interpretable preference models that represent human reasoning. Our approach aims to bridge the gap between human-in-the-loop learning and user model interpretability in drug discovery applications, providing a transparent framework that elucidates how human judgments can shape molecular design outcomes.
Registries in Machine Learning-Based Drug Discovery: A Shortcut to Code Reuse
Authors: Hartog Peter B. R. , Svensson Emma , Mervin Lewis , Genheden Samuel , Engkvist Ola , Tetko Igor V. 
Published: September 2024

AbstractComputer-aided drug discovery gradually builds on previous work and requires reusable code to advance research. Currently, research code is mainly used to provide further insights into the original research whilst code reuse has a lower priority. Modularity, the segmentation of code for independent modules, promotes good coding practices and code reuse. The registry pattern has been proposed as a way to call functionalities dynamically, but it is currently overlooked as a shortcut to promote code reuse. In this work, we expand the registry pattern to better suit computer-aided drug discovery and achieve a unified, reusable, and interchangeable interface with optional meta information. Our reformulated pattern is particularly suitable for collaborative research with standardized frameworks where multiple internal and external modules are used interchangeably and coding is more focused on fast iteration over low-debt technical code, such as in machine learning-based research for drug discovery. In a workflow, we exemplify the usage of the design patterns. Additionally, we provide two case studies where we 1) showcase the effectiveness of registration in a larger collaborative research group, and 2) overview the potential of registration in currently available open-source tools. Finally, we empirically evaluate the registry pattern through previous implementations and indicate where additional functionality can improve its use.
Introduction
Authors: Xu Bin , Pang Rui 
Published: September 2024

AbstractThis paper provides a complete probabilistic analysis method and a performance-based seismic safety evaluation for high concrete faced rockfill dam (CFRD). Combined with random sample generation and reliability analysis methods, the dynamic response characteristics and reliability level of CFRD under various random factors are comprehensively described. In Chapter 2, a random ground motion model based on spectral representation-random function and a high-dimensional random variable generation method based on GF-discrepancy are established. Combined with probability density evolution method (PDEM) and the random sample generation methods to verify its effectiveness and reliability for nonlinear complex geotechnical engineering. In Chapter 3, the dynamic response and probabilistic characteristics of high CFRD under random ground motion are revealed based on the elastoplastic analysis. A performance-based seismic safety evaluation method is established. In Chapter 4, the influence of material parameter randomness on dynamic response and seismic safety of high CFRD is studied from the perspective of stochastic dynamics and probability. In Chapter 5, the stochastic dynamic response and probability distribution of high CFRD under the coupled random action of ground motion and material parameters are systematically studied, and the performance-based seismic safety evaluation framework is improved. In Chapter 6, The stochastic dynamic response of 3D high CFRD is studied, and the failure performance index and performance level based on overstress volume ratio combined with overstress accumulation time are discussed. The performance-based seismic safety evaluation framework is further improved. In Chapter 7, combined with the finite element dynamic time-history analysis method considering the softening effect of rockfill, a performance-based seismic safety evaluation framework for dam slope stability of high CFRD under multiple random factors is systematically explored from the perspective of stochastic dynamics and probability. In Chapter 8, The performance indexes of seismic safety evaluation for high CFRDs are suggested and the corresponding performance level with probability assurance is put forward. The multi-seismic intensity—multi-performance target—failure probability performance relationship is established, and a performance-based seismic safety evaluation framework is initially formed. This book can be used as a reference for scholars studying random vibration and reliability analysis, as well as for scholars studying dam safety evaluation.
Stochastic Dynamic Analysis for High CFRD Considering Uncertainties of Material Parameters
Authors: Xu Bin , Pang Rui 
Published: September 2024

AbstractDue to the uncertainty of the source of dam construction materials for CFRD, the material model parameters should be uncertain values, so the traditional deterministic seismic safety evaluation method is difficult to objectively evaluate the CFRD, especially difficult to analyze from the perspective of the probability of performance, and there are only a small number of studies that consider the effect of uncertainty in the dam construction materials, and there is virtually no literature to consider the effect of the randomness of elasticity-plasticity parameters of the dam construction materials on the seismic There are only a few studies considering the effect of uncertainty of dam construction materials, and almost no literature considering the effect of randomness of elastic–plastic parameters of dam construction materials on the seismic response, while the effect of parameter uncertainty on the seismic response of CFRD cannot be ignored.
The distribution amplitude of the ηc-meson at leading twist from lattice QCD
Authors: Blossier B. , Mangin-Brinet M. , Morgado Chávez J. M. , San José T. 
Published: September 2024

Abstract
Distribution amplitudes are functions of non-perturbative matrix elements describing the hadronization of quarks and gluons. Thanks to factorization theorems, they can be used to compute the scattering amplitude of high-energy processes. Recently, new ideas have allowed their computation using lattice QCD, which should provide us with a general, fully relativistic determination. We present the first lattice calculation of the ηc-meson distribution amplitude at leading twist. Starting from the relevant matrix element in discrete Euclidean space on a set of Nf = 2 CLS ensembles, we explain the method to connect to continuum Minkowski spacetime. After addressing several sources of systematic uncertainty, we compare to Dyson-Schwinger and non-relativistic QCD determinations of this quantity. We find significant deviations between the latter and our result even at small Ioffe times.
Time-dependent microstrata in AdS3
Authors: Houppe Anthony 
Published: September 2024

Abstract
We use perturbation theory to construct a family of time-dependent microstrata: a set of non-extremal solutions of IIB supergravity asymptotic to AdS3 × S3 × T4. Our construction shows that the “special locus” constraints of [1] can be broken by allowing the solutions to depend on time. We study the secular terms appearing in the perturbation theory. Some of them can be resummed into frequency shifts, with the same interpretation as for the previously-studied microstrata solutions. Other secular terms appear harder to resum, questioning the long-term stability of the solutions.
Tensor renormalization group study of (1 + 1)-dimensional U(1) gauge-Higgs model at θ = π with Lüscher’s admissibility condition
Authors: Akiyama Shinichiro , Kuramashi Yoshinobu 
Published: September 2024

Abstract
We investigate the phase structure of the (1+1)-dimensional U(1) gauge-Higgs model with a θ term, where the U(1) gauge action is constructed with Lüscher’s admissibility condition. Using the tensor renormalization group, both the complex action problem and topological freezing problem in the standard Monte Carlo simulation are avoided. We find the first-order phase transition with sufficiently large Higgs mass at θ = π, where the ℤ2 charge conjugation symmetry is spontaneously broken. On the other hand, the symmetry is restored with a sufficiently small mass. We determine the critical endpoint as a function of the Higgs mass parameter and show the critical behavior is in the two-dimensional Ising universality class.
LO, NLO, and NNLO parton distributions for LHC event generators
Authors: Cruz-Martinez Juan , Forte Stefano , Laurenti Niccolò , Rabemananjara Tanjona R. , Rojo Juan 
Published: September 2024

Abstract
We present NNPDF4.0MC, a variant of the NNPDF4.0 set of parton distributions (PDFs) at LO, NLO and NNLO, with and without inclusion of the photon PDF, suitable for use with Monte Carlo (MC) event generators, which require PDFs to satisfy additional constraints in comparison to standard PDF sets. These requirements include PDF positivity down to a low scale Q ~ 1 GeV, smooth extrapolation in the very small and large x regions, and numerically stable results even in extreme regions of phase space for all PDFs. We compare the NNPDF4.0MC PDFs to their baseline NNPDF4.0 counterparts, and to the NNPDF2.3LO set entering the Monash tune of the Pythia8 event generator. We briefly assess the phenomenological impact of these PDFs on the cross-sections for hard and soft QCD processes at the LHC.
Bjorken and threshold asymptotics of a space-like structure function in the 2D U(N) Gross-Neveu model
Authors: Liu Yizhuang 
Published: September 2024

Abstract
In this work, we investigate a coordinate space structure function $$ \mathcal{E} $$
E
(z2m2, λ) in the 2D U(N) Gross-Neveu model to the next-to-leading order in the large-N expansion. We analytically perform the twist expansion in the Bjorken limit through double Mellin representations. Hard and non-perturbative scaling functions are naturally generated in their Borel representations with detailed enumerations and explicit expressions provided to all powers. The renormalon cancellation at t = n between the hard functions at powers p and the non-perturbative functions at powers p + n are explicitly verified, and the issue of “scale-dependency” of the perturbative and non-perturbative functions is explained naturally. Simple expressions for the leading power non-perturbative functions are also provided both in the coordinate space and the momentum-fraction space (0 < α < 1) with “zero-mode-type” subtractions at α = 0 discussed in detail. In addition to the Bjorken limit, we also perform the threshold expansion of the structure function up to the next-to-next-to-leading threshold power exactly and investigate the resurgence relation between threshold and “Regge” asymptotics. We also prove that the twist expansion is absolutely convergent for any 0 < z2 < ∞ and any λ ∈ iR≥0.
Quantum vortices, M2-branes and black holes
Authors: Choi Sunjin , Hwang Chiung , Kim Seok 
Published: September 2024

Abstract
We study the partition functions of BPS vortices and magnetic monopole operators, in gauge theories describing N M2-branes. In particular, we explore two closely related methods to study the Cardy limit of the index on S2 × ℝ. The first method uses the factorization of this index to vortex partition functions, while the second one uses a continuum approximation for the monopole charge sums. Monopole condensation confines most of the N2 degrees of freedom except $$ {N}^{\frac{3}{2}} $$

N

3
2

of them, even in the high temperature deconfined phase. The resulting large N free energy statistically accounts for the Bekenstein-Hawking entropy of large BPS black holes in AdS4 × S7. Our Cardy free energy also suggests a finite N version of the $$ {N}^{\frac{3}{2}} $$

N

3
2

degrees of freedom.