cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Deontic Paradoxes in ASP with Weak Constraints
Creators: name: Hatschka, Christian
name: Ciabattoni, Agata
name: Eiter, Thomas
Publisher: name: arXiv
Year: 2023
Subjects: subject: Logic in Computer Science (cs.LO)
subject: Artificial Intelligence (cs.AI)
subject: Computers and Society (cs.CY)
subject: Multiagent Systems (cs.MA)
subject: FOS: Computer and information sciences

description: The rise of powerful AI technology for a range of applications that are sensitive to legal, social, and ethical norms demands decision-making support in presence of norms and regulations. Normative reasoning is the realm of deontic logics, that are challenged by well-known benchmark problems (deontic paradoxes), and lack efficient computational tools. In this paper, we use Answer Set Programming (ASP) for addressing these shortcomings and showcase how to encode and resolve several well-known deontic paradoxes utilizing weak constraints. By abstracting and generalizing this encoding, we present a methodology for translating normative systems in ASP with weak constraints. This methodology is applied to "ethical" versions of Pac-man, where we obtain a comparable performance with related works, but ethically preferable results.
description: In Proceedings ICLP 2023, arXiv:2308.14898
The role of annexin A1 in the regulation of amyloid beta clearance, neuroinflammation, and blood-brain barrier functionality in Alzheimer’s disease
Creators: name: Ries, Miriam
Publisher: name: Imperial College London
Year: 2017

description: The main pathological hallmarks of Alzheimer’s disease (AD) are amyloid β (Aβ) plaques and neurofibrillary tangles in the brain. Neuroinflammation is strongly implicated in the progression of the disease, supported by the presence of clusters of activated glial cells surrounding Aβ plaques in AD patients and in animal models of AD. An increase in inflammatory mediators released by these glial cells is thought to contribute to the toxicity of Aβ in AD, leading to neuronal dysfunction and cell death. In addition, neurovascular dysfunction and blood-brain barrier (BBB) deficits have been described in AD, potentially as a consequence of both Aβ deposition and neuroinflammation. Annexin A1 (ANXA1) is an anti-inflammatory mediator, which has recently been shown to suppress microglial activation by acting on the formyl peptide receptor 2 (FPR2), and has also been shown to reduce BBB permeability. We hypothesised that ANXA1 has neuroprotective properties in AD, and our aim was to investigate the effects of ANXA1 treatment on Aβ deposition, neuroinflammation, BBB permeability, and memory using in vitro and in vivo models of AD. We show that ANXA1 reduces Aβ load in models of AD by increasing the expression of Aβ degrading enzymes and by stimulating microglial phagocytosis of Aβ. We also show that these effects are mediated by the activation of FPR2. In addition, ANXA1 had anti-inflammatory properties by reversing the Aβ-mediated increase of pro-inflammatory cytokines in vitro and in vivo in the 5xFAD mouse model of amyloidosis. We also found that ANXA1 treatment increases microglial clustering around Aβ plaques and induces the secretion of anti-inflammatory markers, including transforming growth factor β and arginase. These effects were paralleled by increased synaptic density in the hippocampus and reduced memory deficits. Furthermore, we show that administration of ANXA1 is able to reverse BBB leakage and vascular disruption in 5xFAD mice at 12 weeks of age. These data suggest that ANXA1 plays a pivotal role in Aβ clearance, modulating inflammation, and maintaining BBB integrity in AD, and support the further investigation of ANXA1 as a potential pharmacological tool for AD therapeutics.
ABA Learning via ASP
Creators: name: De Angelis, Emanuele
name: Proietti, Maurizio
name: Toni, Francesca
Publisher: name: arXiv
Year: 2023
Subjects: subject: Artificial Intelligence (cs.AI)
subject: Logic in Computer Science (cs.LO)
subject: FOS: Computer and information sciences

description: Recently, ABA Learning has been proposed as a form of symbolic machine learning for drawing Assumption-Based Argumentation frameworks from background knowledge and positive and negative examples. We propose a novel method for implementing ABA Learning using Answer Set Programming as a way to help guide Rote Learning and generalisation in ABA Learning.
description: In Proceedings ICLP 2023, arXiv:2308.14898
Supramenable groups and partial actions
Creators: name: Scarparo, Eduardo P.
Publisher: name: arXiv
Year: 2015
Subjects: subject: Operator Algebras (math.OA)
subject: FOS: Mathematics

description: We characterize supramenable groups in terms of existence of invariant probability measures for partial actions on compact Hausdorff spaces and existence of tracial states on partial crossed products. These characterizations show that, in general, one cannot decompose a partial crossed product of a C*-algebra by a semi-direct product of groups as two iterated partial crossed products. We give conditions which ensure that such decomposition is possible.
description: 17 pages. Corrected typos. To appear in Ergodic Theory and Dynamical Systems
What Does the Pipeline Promise about Upcoming Biosimilar Antibodies in Oncology?
Creators: name: Busse, Antonia
name: Lüftner, Diana
Publisher: name: Charité - Universitätsmedizin Berlin
Year: 2019
Subjects: subject: Biosimilar
subject: Trastuzumab
subject: Rituximab
subject: Bevacizumab
subject: Cetuximab
subject: 600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und Gesundheit

description: The introduction of biosimilars of biological agents for which the patents and exclusivity periods have expired is an attractive way of reducing healthcare spending through price competition with the reference product. In oncology, biosimilars of growth factors for supportive therapy were the pioneers; now, monoclonal antibody biosimilars are conquering the market. In Europe, this is currently limited to biosimilars of the monoclonal antibodies trastuzumab and rituximab. However, the pipeline is full and several monoclonal antibody biosimilars in oncology are now in late-stage development. We are expecting not only more biosimilar versions of the top 3 blockbuster monoclonal antibodies, trastuzumab, rituximab and bevacizumab, to enter the market; as patent expiration of multiple other cancer biologicals will occur in the next few years, the biosimilar landscape will become much more diversified. Several biosimilars of monoclonal antibodies used in targeted therapy such as cetuximab, pertuzumab, or denosumab are in early development.
Yoneda Completeness
Creators: name: Bice, Tristan
Publisher: name: arXiv
Year: 2015
Subjects: subject: General Topology (math.GN)
subject: Functional Analysis (math.FA)
subject: FOS: Mathematics
subject: 06A06, 18A35, 54E50, 54E55

description: We characterize Yoneda completeness for non-symmetric distances by combinations of metric and directed completeness. One of these generalizes the Kostanek-Waszkiewicz theorem on formal balls.
description: This consists of the relevant parts of sections 4 and 5 of the previous version (the other material will be developed separately)
Benchmarking for Integrating Logic Rules with Everything Else
Creators: name: Liu, Yanhong A.
name: Stoller, Scott D.
name: Tong, Yi
name: Tekle, K. Tuncay
Publisher: name: arXiv
Year: 2023
Subjects: subject: Programming Languages (cs.PL)
subject: Logic in Computer Science (cs.LO)
subject: Performance (cs.PF)
subject: FOS: Computer and information sciences

description: Integrating logic rules with other language features is increasingly sought after for advanced applications that require knowledge-base capabilities. To address this demand, increasingly more languages and extensions for such integration have been developed. How to evaluate such languages? This paper describes a set of programming and performance benchmarks for evaluating languages supporting integrated use of rules and other features, and the results of evaluating such an integrated language together with logic languages and languages not supporting logic rules.
description: In Proceedings ICLP 2023, arXiv:2308.14898. arXiv admin note: substantial text overlap with arXiv:2205.15204
Explanations for Answer Set Programming
Creators: name: Alviano, Mario
name: Trieu, Ly Ly
name: Son, Tran Cao
name: Balduccini, Marcello
Publisher: name: arXiv
Year: 2023
Subjects: subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: The paper presents an enhancement of xASP, a system that generates explanation graphs for Answer Set Programming (ASP). Different from xASP, the new system, xASP2, supports different clingo constructs like the choice rules, the constraints, and the aggregates such as #sum, #min. This work formalizes and presents an explainable artificial intelligence system for a broad fragment of ASP, capable of shrinking as much as possible the set of assumptions and presenting explanations in terms of directed acyclic graphs.
description: In Proceedings ICLP 2023, arXiv:2308.14898
Vectorial capacity across an environmental gradient
Creators: name: Gregory, Nichar
Publisher: name: Imperial College London
Year: 2019

description: Disease transmitted by mosquitoes present some of the most pressing challenges facing human health today. Land-use change is a key driver of disease emergence, however the mechanisms linking environmental covariates of change, such as temperature, to the transmission potential of mosquitoes is poorly understood. Studies exploring these relationships have largely been correlative in nature, and thus have limited capacity to predict dynamics through space and time. Mechanistic approaches provide a valuable framework for understanding the processes underlying transmission, however they suffer from a dearth of field data on fundamental mosquito ecology. In both approaches, the environmental data used is typically coarse in scale and interpolated from weather stations located in open areas. In reality, local climatic conditions can vary considerably over fine spatial and temporal scales, particularly in dynamic working landscapes. Wild mosquitoes experience and respond to this highly dynamic environment, and failing to account for this variation may have significant implications for the accuracy of epidemiological models. This thesis uses an established epidemiological framework to explore the effects of tropical forest conversion to oil palm plantation on the potential for Ae. albopictus mosquitoes to transmit disease. Using field-derived microclimate data and published thermal responses of mosquito traits, I first examine how the scale of environmental data affects predictions of mosquito demography under land-use change. Next, I conduct field experiments to investigate whether microclimate heterogeneity across a land-use gradient drives variation in the rates of larval development. By pairing fine-scale microclimate data with temperature-dependent trait estimates, I find that forest conversion significantly increases the potential of Ae. albopictus to transmit disease. Together, these findings advance our understanding of Ae. albopictus ecology, and highlight the importance of incorporating fine-scale environmental and mosquito data into epidemiological frameworks to better understand disease risk in changing landscapes.
Knight shift vs hole concentration in Hg1201 and Hg1212
Creators: name: Itoh, Y.
Publisher: name: arXiv
Year: 2015
Subjects: subject: Superconductivity (cond-mat.supr-con)
subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: We studied the hole concentration dependences of 63Cu Knight shifts in single-CuO2-layer high-Tc cuprate superconductors HgBa2CuO4+d and double-layer HgBa2CaCu2O6+d. We found that the spin Knight shift at room temperature as a function of the hole concentration in the single-layer superconductor is different from that in the double-layer superconductor. Two type relations between the spin Knight shift and the hole doping level serve to estimate the individual hole concentrations of the non-equivalent CuO2 planes in a unit cell.
description: 4 pages, 4 figures, submitted to Physics Procedia, ISS2014 (27th International Symposium on Superconductivity, Tokyo)
A Dataflow Analysis for Comparing and Reordering Predicate Arguments
Creators: name: Yernaux, Gonzague
name: Vanhoof, Wim
Publisher: name: arXiv
Year: 2023
Subjects: subject: Logic in Computer Science (cs.LO)
subject: FOS: Computer and information sciences
subject: F.3.2; D.1.6

description: In this work, which is done in the context of a (moded) logic programming language, we devise a data-flow analysis dedicated to computing what we call argument profiles. Such a profile essentially describes, for each argument of a predicate, its functionality, i.e. the operations in which the argument can be involved during an evaluation of the predicate, as well as how the argument contributes to the consumption and/or construction of data values. While the computed argument profiles can be useful for applications in the context of program understanding (as each profile essentially provides a way to better understand the role of the argument), they more importantly provide a way to discern between arguments in a manner that is more fine-grained than what can be done with other abstract characterizations such as types and modes. This is important for applications where one needs to identify correspondences between the arguments of two or more different predicates that need to be compared, such as during clone detection. Moreover, since a total order can be defined on the abstract domain of profiles, our analysis can be used for rearranging predicate arguments and order them according to their functionality, constituting as such an essential ingredient for predicate normalization techniques.
description: In Proceedings ICLP 2023, arXiv:2308.14898
The role of mitochondria in the cell-to-cell interactions that regulate fitness during early mouse embryonic development
Creators: name: De Lima, Ana Raquel Abrunhosa Carvalho
Publisher: name: Imperial College London
Year: 2019

description: The early stages of embryonic development involve a rewiring of transcriptional, epigenetic, signalling and metabolic pathways that define cell identity. The substantial nature of the changes taking place creates a large potential for the emergence of defective cells, that need to be eliminated to prevent them from contributing to the future foetus. One quality control that ensures this elimination is cell competition, a fitness sensing mechanism that eliminates cells that, although viable, are less fit than their neighbours. Here we investigated the nature of competitive interactions to understand what are the key features of unfit cells that are recognised as a read-out of cell fitness. First, we studied mouse embryonic stem cells (mESCs) with defective BMP signalling (Bmpr1a-/-), that are eliminated by their wild-type neighbours, and found these have metabolic defects, including loss of mitochondrial membrane potential and decreased mitochondrial respiration. Second, we tested if the direct manipulation of mitochondrial biology can trigger cell competition. We found that mESCs with deletion of mitofusin 2 (Mfn2-/-) or dynamin-related protein 1 (Drp1-/-), which are genes important for mitochondrial morphology and dynamics, are eliminated by wild-type cells. This led us to test if more subtle changes in the mitochondria of mESCs could impact on their relative fitness. By analysing mESCs on the same nuclear background, but with different mitochondrial DNA (mtDNA), we demonstrate that even changes in mtDNA sequences can trigger cell selection by cell competition. Finally, using single cell RNA sequencing and analysis of mitochondrial activity, we identify that mitochondrial defects are key signature of the cells eliminated from the early mouse embryo. Together, our results suggest that cell competition acts during early development to select cells with the fittest mitochondria to give rise to the embryo, preventing the propagation of deleterious defects to the adult organism and future generations.
"Would life be more interesting if I were in AI?" Answering Counterfactuals based on Probabilistic Inductive Logic Programming
Creators: name: Rückschloß, Kilian
name: Weitkämper, Felix
Publisher: name: arXiv
Year: 2023
Subjects: subject: Logic in Computer Science (cs.LO)
subject: Artificial Intelligence (cs.AI)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: Probabilistic logic programs are logic programs where some facts hold with a specified probability. Here, we investigate these programs with a causal framework that allows counterfactual queries. Learning the program structure from observational data is usually done through heuristic search relying on statistical tests. However, these statistical tests lack information about the causal mechanism generating the data, which makes it unfeasible to use the resulting programs for counterfactual reasoning. To address this, we propose a language fragment that allows reconstructing a program from its induced distribution. This further enables us to learn programs supporting counterfactual queries.
description: In Proceedings ICLP 2023, arXiv:2308.14898
Direct collapse black hole formation via high-velocity collisions of protogalaxies
Creators: name: Inayoshi, Kohei
name: Visbal, Eli
name: Kashiyama, Kazumi
Publisher: name: arXiv
Year: 2015
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: FOS: Physical sciences

description: We propose high-velocity collisions of protogalaxies as a new pathway to form supermassive stars (SMSs) with masses of ~ 10^5 Msun at high redshift (z > 10). When protogalaxies hosted by dark matter halos with a virial temperature of ~ 10^4 K collide with a relative velocity > 200 km/s, the gas is shock-heated to ~ 10^6 K and subsequently cools isobarically via free-free emission and He^+, He, and H line emission. Since the gas density (> 10^4 cm^{-3}) is high enough to destroy H_2 molecules by collisional dissociation, the shocked gas never cools below ~ 10^4 K. Once a gas cloud of ~ 10^5 Msun reaches this temperature, it becomes gravitationally unstable and forms a SMS which will rapidly collapse into a super massive black hole (SMBH) via general relativistic instability. We perform a simple analytic estimate of the number density of direct-collapse black holes (DCBHs) formed through this scenario (calibrated with cosmological N-body simulations) and find n_{DCBH} ~ 10^{-9} Mpc^{-3} (comoving) by z = 10. This could potentially explain the abundance of bright high-z quasars.
description: 9 pages, 5 figures, accepted for publication in MNRAS
Exploring dynamic cognitive states using magnetic resonance imaging
Creators: name: Soreq, Eyal
Publisher: name: Imperial College London
Year: 2019

description: The path to make sense of the puzzling nature of human cognitive behaviour requires an intimate understanding of the general systems in the brain and how they work in concert to manifest such behaviour. As a multi-disciplinary approach, it is at the forefront of adapting, integrating and applying recent developments in data science, and machine learning to further our understanding of the many facets of the brain. These advancements led to a paradigm shift perceiving the brain as a biological system composed of multi-scaled intertwined communities of functional networks. This perspective gained immense popularity in recent years providing new insight into the brain fundamental organisation and the neuronal mechanisms associated with cognitive behaviour. However, while highly promising, the application of these new techniques to cognitive neurosciences is still a challenge. It requires neuroscientists to be able to reformat the accumulated knowledge in the field, its big questions, theories and prior knowledge within the confines imposed by these approaches. It also calls for adapting, challenging and changing the interrogative capabilities of these methods from their applied nature. In this thesis, I use an advanced suite of machine-learning methods and data science approaches to investigate how multivariate patterns of brain activity and connectivity dynamically vary with manipulation of behaviourally distinct aspects of cognition. Specifically, I demonstrate that inspection of dynamic macro connectomic provides additional insight to transcend our understanding of intelligence and working memory. The multivariate inspection provided here was able to validate classic localist findings in the field and tie them to the modern network perspective. Additionally, this thesis develops a framework and tools to apply data science methodologies to new and exciting research questions within cognitive neuroscience.
Random-field Ising model: Insight from zero-temperature simulations
Creators: name: Theodorakis, P. E.
name: Fytas, N. G.
Publisher: name: arXiv
Year: 2015
Subjects: subject: Disordered Systems and Neural Networks (cond-mat.dis-nn)
subject: FOS: Physical sciences

description: We enlighten some critical aspects of the three-dimensional ($d=3$) random-field Ising model from simulations performed at zero temperature. We consider two different, in terms of the field distribution, versions of model, namely a Gaussian random-field Ising model and an equal-weight trimodal random-field Ising model. By implementing a computational approach that maps the ground-state of the system to the maximum-flow optimization problem of a network, we employ the most up-to-date version of the push-relabel algorithm and simulate large ensembles of disorder realizations of both models for a broad range of random-field values and systems sizes $\mathcal{V}=L\times L\times L$, where $L$ denotes linear lattice size and $L_{\rm max}=156$. Using as finite-size measures the sample-to-sample fluctuations of various quantities of physical and technical origin, and the primitive operations of the push-relabel algorithm, we propose, for both types of distributions, estimates of the critical field $h_{\rm c}$ and the critical exponent $ν$ of the correlation length, the latter clearly suggesting that both models share the same universality class. Additional simulations of the Gaussian random-field Ising model at the best-known value of the critical field provide the magnetic exponent ratio $β/ν$ with high accuracy and clear out the controversial issue of the critical exponent $α$ of the specific heat. Finally, we discuss the infinite-limit size extrapolation of energy- and order-parameter-based noise to signal ratios related to the self-averaging properties of the model, as well as the critical slowing down aspects of the algorithm.
description: 14 pages, 8 figures
Towards One-Shot Learning for Text Classification using Inductive Logic Programming
Creators: name: Milani, Ghazal Afroozi
name: Cyrus, Daniel
name: Tamaddoni-Nezhad, Alireza
Publisher: name: arXiv
Year: 2023
Subjects: subject: Machine Learning (cs.LG)
subject: Computation and Language (cs.CL)
subject: Logic in Computer Science (cs.LO)
subject: FOS: Computer and information sciences

description: With the ever-increasing potential of AI to perform personalised tasks, it is becoming essential to develop new machine learning techniques which are data-efficient and do not require hundreds or thousands of training data. In this paper, we explore an Inductive Logic Programming approach for one-shot text classification. In particular, we explore the framework of Meta-Interpretive Learning (MIL), along with using common-sense background knowledge extracted from ConceptNet. Results indicate that MIL can learn text classification rules from a small number of training examples. Moreover, the higher complexity of chosen examples, the higher accuracy of the outcome.
description: In Proceedings ICLP 2023, arXiv:2308.14898
The resilience of tropical forest invertebrates to microclimate change
Creators: name: Boyle, Michael
Publisher: name: Imperial College London
Year: 2019

description: Tropical forests are key terrestrial biomes in terms of carbon sequestration, water cycle regulation and biodiversity insurance. They are under threat from a host of anthropogenic factors including logging, poaching, cash-cropping and grazing. Climate change is also a major threat to tropical systems, and it is expected that tropical forests will soon experience conditions that have not existed on earth for millions of years. Structural changes brought about by logging and fragmentation also cause changes to local microclimates, so organisms and ecological processes in logged forests may face combined thermal stresses. Invertebrates make up the majority of animal biodiversity in tropical forests and drive many ecological processes. As ectotherms they are also expected to be sensitive to changes to environmental temperature. In this thesis I studied ants across a gradient of habitat disturbance in Sabah, Malaysian Borneo. I found that interactions between environmental temperature and physiology defined the abundance and functional activity of ants in human-modified tropical landscapes. I also found that temperatures in logged forests exceed the functional tolerances of ants, but that intact forests exhibit remarkable buffering capacity against climate warming. Finally, I described a mechanistic pathway outlining how microclimate change, arising because of human disturbance, led to a reduction in ecosystem functioning via correlations between species’ functional ‘response’ and ‘effect’ traits. These findings suggest that tropical forest invertebrates and the functions they perform are already significantly affected by elevated temperatures in the most heavily logged forests and oil palm plantations. This effect is likely to be exacerbated by future climate warming, with potential implications for the ability of logged forests to maintain current levels of biodiversity. Intact forests, however, may be able to buffer against even the most extreme climate change scenarios, and may be unique in their ability to conserve tropical biodiversity in a warmer future.
On the Potential of CLIP for Compositional Logical Reasoning
Creators: name: Brody, Justin
Publisher: name: arXiv
Year: 2023
Subjects: subject: Artificial Intelligence (cs.AI)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: Logic in Computer Science (cs.LO)
subject: FOS: Computer and information sciences

description: In this paper we explore the possibility of using OpenAI's CLIP to perform logically coherent grounded visual reasoning. To that end, we formalize our terms and give a geometric analysis of how embeddings in CLIP's latent space would need to be configured in order for the system to be logically coherent. Our main conclusion is that, as usually configured, CLIP cannot perform such reasoning.
description: In Proceedings ICLP 2023, arXiv:2308.14898
A Bayesian framework for verification and recalibration of ensemble forecasts: How uncertain is NAO predictability?
Creators: name: Siegert, Stefan
name: Stephenson, David B.
name: Sansom, Philip G.
name: Scaife, Adam A.
name: Eade, Rosie
name: Arribas, Alberto
Publisher: name: arXiv
Year: 2015
Subjects: subject: Applications (stat.AP)
subject: FOS: Computer and information sciences

description: Predictability estimates of ensemble prediction systems are uncertain due to limited numbers of past forecasts and observations. To account for such uncertainty, this paper proposes a Bayesian inferential framework that provides a simple 6-parameter representation of ensemble forecasting systems and the corresponding observations. The framework is probabilistic, and thus allows for quantifying uncertainty in predictability measures such as correlation skill and signal-to-noise ratios. It also provides a natural way to produce recalibrated probabilistic predictions from uncalibrated ensembles forecasts. The framework is used to address important questions concerning the skill of winter hindcasts of the North Atlantic Oscillation for 1992-2011 issued by the Met Office GloSea5 climate prediction system. Although there is much uncertainty in the correlation between ensemble mean and observations, there is strong evidence of skill: the 95% credible interval of the correlation coefficient of [0.19,0.68] does not overlap zero. There is also strong evidence that the forecasts are not exchangeable with the observations: With over 99% certainty, the signal-to-noise ratio of the forecasts is smaller than the signal-to-noise ratio of the observations, which suggests that raw forecasts should not be taken as representative scenarios of the observations. Forecast recalibration is thus required, which can be coherently addressed within the proposed framework.
description: 36 pages, 10 figures
Leaflets on open access discounts and vouchers for Charles University´s authors
Creators: name: Simandlová, Tereza
name: Grofová, Šárka
Publisher: name: Zenodo
Year: 2020
Subjects: open access
article processing charge
scholarly communication
scholarly publishing
open access fee

description: A set of informative leaflets promoting discounts and vouchers on open access fees (article processing charges, APCs) for authors from Charles University.
Analytical Energy Gradients in Range-Separated Hybrid Density Functional Theory with Random Phase Approximation
Creators: name: Mussard, Bastien
name: Szalay, Peter G.
name: Ángyán, János G.
Publisher: name: arXiv
Year: 2015
Subjects: subject: Chemical Physics (physics.chem-ph)
subject: FOS: Physical sciences

description: Analytical forces have been derived in the Lagrangian framework for several random phase approximation (RPA) correlated total energy methods based on the range separated hybrid (RSH) approach, which combines a short-range density functional approximation for the short-range exchange-correlation energy with a Hartree-Fock-type long-range exchange and RPA long-range correlation. The RPA correlation energy has been expressed as a ring coupled cluster doubles (rCCD) theory. The resulting analytical gradients have been implemented and tested for geometry optimization of simple molecules and intermolecular charge transfer complexes, where intermolecular interactions are expected to have a non-negligible effect even on geometrical parameters of the monomers.
description: 18 two-column pages + 4 tables and 6 figures
Generalizing Level Ranking Constraints for Monotone and Convex Aggregates
Creators: name: Janhunen, Tomi
Publisher: name: arXiv
Year: 2023
Subjects: subject: Logic in Computer Science (cs.LO)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences
subject: D.1.6; F.4.1; I.2.3

description: In answer set programming (ASP), answer sets capture solutions to search problems of interest and thus the efficient computation of answer sets is of utmost importance. One viable implementation strategy is provided by translation-based ASP where logic programs are translated into other KR formalisms such as Boolean satisfiability (SAT), SAT modulo theories (SMT), and mixed-integer programming (MIP). Consequently, existing solvers can be harnessed for the computation of answer sets. Many of the existing translations rely on program completion and level rankings to capture the minimality of answer sets and default negation properly. In this work, we take level ranking constraints into reconsideration, aiming at their generalizations to cover aggregate-based extensions of ASP in more systematic way. By applying a number of program transformations, ranking constraints can be rewritten in a general form that preserves the structure of monotone and convex aggregates and thus offers a uniform basis for their incorporation into translation-based ASP. The results open up new possibilities for the implementation of translators and solver pipelines in practice.
description: In Proceedings ICLP 2023, arXiv:2308.14898
ПРАВОВЫЕ АСПЕКТЫ РЕШЕНИЯ НАЦИОНАЛЬНЫХ КОНФЛИКТОВ В РОССИИ
Creators: name: Абасян Ферик Ордиханович
Publisher: name: Вестник Науки и Творчества
Year: 2022
Subjects: национальный вопрос
национальный (межэтнический) конфликт
национальная безопасность
национальная политика

description: Данная статья посвящена проблемам возникновения национальных конфликтов в России, ее правовым аспектам. На основе приведенных примеров рассмотрены основные причины таких конфликтов, предлагаются пути самосовершенствования национальных вопросов.
Sorting Strategies for Interactive Conflict Resolution in ASP
Creators: name: Thevapalan, Andre
name: Kern-Isberner, Gabriele
Publisher: name: arXiv
Year: 2023
Subjects: subject: Logic in Computer Science (cs.LO)
subject: FOS: Computer and information sciences
subject: D.1.6

description: Answer set programs in practice are often subject to change. This can lead to inconsistencies in the modified program due to conflicts between rules which are the results of the derivation of strongly complementary literals. To facilitate the maintenance of consistency in answer set programs, in this paper we continue work on a recently presented framework that implements interactive conflict resolution by extending the bodies of conflicting rules by suitable literals, so-called $λ$-extensions. More precisely, we present strategies to choose $λ$-extensions that allow for resolving several conflicts at a time in an order that aims at minimizing (cognitive) efforts. In particular, we present a graphical representation of connections between conflicts and their possible solutions. Such a representation can be utilized to efficiently guide the user through the conflict resolution process by displaying conflicts and suggesting solutions in a suitable order.
description: In Proceedings ICLP 2023, arXiv:2308.14898
title: Διερεύνηση σκυροδεμάτων τριών κατηγοριών C20/25, C30/35, C35/45 κατά τους ελέγχους μηχανικών ιδιοτήτων
title: Investigation of the mechanical purposes of reinforced concrete C20/25, C30/35, C35/45
titleType: AlternativeTitle
Creators: name: Σεΐζη, Αθανασία Μαρία
Publisher: name: Πανεπιστήμιο Δυτικής Αττικής
Year: 2023
Subjects: Σκυρόδεμα
Οπλισμένο σκυρόδεμα
Αντοχή σκυροδέματος
Ινοπλισμένο σκυρόδεμα
Μηχανικές ιδιότητες

description: Με σκοπό τη διερεύνηση των μηχανικών ιδιοτήτων του οπλισμένου σκυροδέματος, που είναι και ο τίτλος της συγκεκριμένης διπλωματικής εργασίας, επιλέχθηκαν τρεις κατηγορίες σκυροδέματος και συγκεκριμένα οι C20/25, C25/30 και C35/45, οι οποίες αφού εξετάστηκαν σε τέσσερα πειράματα στο εργαστήριο έδωσαν ορισμένα αποτελέσματα διευκρινίζοντας τις διαφορές που υπάρχουν στις μηχανικές ιδιότητες κάθε κατηγορίας. Σε θεωρητικό επίπεδο, έγινε εμβάθυνση σε πολλές λεπτομέρειες που αφορούν την τεράστια επιστήμη του σκυροδέματος, χωρίς να μπορούν να καλυφθούν όλες οι δυνατότητες που περιλαμβάνει και δίνει το συγκεκριμένο υλικό, πράγματα τα οποία ήταν αδύνατον να περιγραφούν σε μία μόνο εργασία. Συγκεκριμένα, έγινε έρευνα για το σκυρόδεμα σαν γενική έννοια, για τις κατηγορίες σκυροδέματος, τις δυνατότητες που παρέχει η κάθε μία, τη χρήση τους, έγινε μια θεωρητική αναφορά στις μηχανικές ιδιότητες τους. Τέλος, αναφέρθηκε συνοπτικά πως είναι δυνατόν η σωστή χρήση και ανακύκλωση σκυροδέματος να λειτουργήσει ευεργετικά για το περιβάλλον μειώνοντας τη ρύπανση του. Στο πειραματικό στάδιο, εφαρμόστηκαν τέσσερις πειραματικές μέθοδοι για τον προσδιορισμό των μηχανικών ιδιοτήτων του σκυροδέματος σε πρακτικό επίπεδο, μέσω της δοκιμής προσδιορισμού καθίζησης και ωρίμανσης σκυροδέματος, της δοκιμής άμεσου προσδιορισμού αντοχής σκυροδέματος, της δοκιμής προσδιορισμού αντοχών ινοπλισμένου σκυροδέματος και, τέλος, του υπολογισμού της οριακής ροπής δοκού οπλισμένου σκυροδέματος, οι οποίες μέθοδοι αναλύονται στη συνέχεια λεπτομερώς.
The electronic properties of doped single walled carbon nanotubes and carbon nanotube sensors
Creators: name: Tetik, E.
Publisher: name: arXiv
Year: 2015
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: We present ab initio calculations on the band structure and density of states of single wall semiconducting carbon nanotubes with high degrees (up to 25%) of B, Si and N substitution. The doping process consists of two phases: different carbon nanotubes (CNTs) for a constant doping rate and different doping rates for the zigzag (8, 0) carbon nanotube. We analyze the doping dependence of nanotubes on the doping rate and the nanotube type. Using these results, we select the zigzag (8, 0) carbon nanotube for toxic gas sensor calculation and obtain the total and partial densities of states for CNT (8, 0). We have demonstrated that the CNT (8, 0) can be used as toxic gas sensors for CO and NO molecules, and it can partially detect Cl$_2$ toxic molecules but cannot detect H$_2$S. To overcome these restrictions, we created the B and N doped CNT (8, 0) and obtained the total and partial density of states for these structures. We also showed that B and N doped CNT (8, 0) can be used as toxic gas sensors for such molecules as CO, NO, Cl$_2$ and H$_2$S.
description: 12 pages, 13 figures
Doctoral thesis recital (collaborative piano)
Creators: name: Ahn, Giyong
Publisher: name: The University of Texas at Austin
Year: 2023
Subjects: Viola and piano music
Flute and piano music
Violin and piano music
Chamber music

description: Drei Romanzen / Clara Schumann -- Sonata for flute and piano / Brian Nabors -- Romance for violin and piano op.23 / Amy Beach
Natlog: Embedding Logic Programming into the Python Deep-Learning Ecosystem
Creators: name: Tarau, Paul
Publisher: name: arXiv
Year: 2023
Subjects: subject: Artificial Intelligence (cs.AI)
subject: Programming Languages (cs.PL)
subject: FOS: Computer and information sciences

description: Driven by expressiveness commonalities of Python and our Python-based embedded logic-based language Natlog, we design high-level interaction patterns between equivalent language constructs and data types on the two sides. By directly connecting generators and backtracking, nested tuples and terms, coroutines and first-class logic engines, reflection and meta-interpretation, we enable logic-based language constructs to access the full power of the Python ecosystem. We show the effectiveness of our design via Natlog apps working as orchestrators for JAX and Pytorch pipelines and as DCG-driven GPT3 and DALL.E prompt generators. Keyphrases: embedding of logic programming in the Python ecosystem, high-level inter-paradigm data exchanges, coroutining with logic engines, logic-based neuro-symbolic computing, logic grammars as prompt-generators for Large Language Models, logic-based neural network configuration and training.
description: In Proceedings ICLP 2023, arXiv:2308.14898
Active-Region Tilt Angles: Magnetic Versus White-Light Determinations of Joy's Law
Creators: name: Wang, Y. -M.
name: Colaninno, R. C.
name: Baranyi, T.
name: Li, J.
Publisher: name: arXiv
Year: 2014
Subjects: subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences

description: The axes of solar active regions are inclined relative to the east--west direction, with the tilt angle tending to increase with latitude ("Joy's law"). Observational determinations of Joy's law have been based either on white-light images of sunspot groups or on magnetograms, where the latter have the advantage of measuring directly the physically relevant quantity (the photospheric field), but the disadvantage of having been recorded routinely only since the mid-1960s. White-light studies employing the historical Mount Wilson (MW) database have yielded tilt angles that are smaller and that increase less steeply with latitude than those obtained from magnetic data. We confirm this effect by comparing sunspot-group tilt angles from the Debrecen Photoheliographic Database with measurements made by Li and Ulrich using MW magnetograms taken during cycles 21--23. Whether white-light or magnetic data are employed, the median tilt angles significantly exceed the mean values, and provide a better characterization of the observed distributions. The discrepancy between the white-light and magnetic results is found to have two main sources. First, a substantial fraction of the white-light "tilt angles" refer to sunspots of the same polarity. Of greater physical significance is that the magnetograph measurements include the contribution of plage areas, which are invisible in white-light images but tend to have greater axial inclinations than the adjacent sunspots. Given the large uncertainties inherent in both the white-light and the magnetic measurements, it remains unclear whether any systematic relationship exists between tilt angle and cycle amplitude during cycles 16--23.
description: 35 pages, 13 figures, Accepted in ApJ
Understanding ProbLog as Probabilistic Argumentation
Creators: name: Toni, Francesca
name: Potyka, Nico
name: Ulbricht, Markus
name: Totis, Pietro
Publisher: name: arXiv
Year: 2023
Subjects: subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences
subject: I.2.4

description: ProbLog is a popular probabilistic logic programming language/tool, widely used for applications requiring to deal with inherent uncertainties in structured domains. In this paper we study connections between ProbLog and a variant of another well-known formalism combining symbolic reasoning and reasoning under uncertainty, i.e. probabilistic argumentation. Specifically, we show that ProbLog is an instance of a form of Probabilistic Abstract Argumentation (PAA) that builds upon Assumption-Based Argumentation (ABA). The connections pave the way towards equipping ProbLog with alternative semantics, inherited from PAA/PABA, as well as obtaining novel argumentation semantics for PAA/PABA, leveraging on prior connections between ProbLog and argumentation. Further, the connections pave the way towards novel forms of argumentative explanations for ProbLog's outputs.
description: In Proceedings ICLP 2023, arXiv:2308.14898
Thermodynamic structure of field equations near apparent horizon for radiating black holes
Creators: name: Papnoi, Uma
name: Govender, Megan
name: Ghosh, Sushant G
Publisher: name: arXiv
Year: 2014
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: We study the intriguing analogy between gravitational dynamics of the horizon and thermodynamics for the case of nonstationary radiating spherically symmetric black holes both in four dimensions and higher dimensions. By defining all kinematical parameters of nonstationary radiating black holes in terms of null vectors, we demonstrate that it is possible to interpret the Einstein field equations near the apparent horizon in the form of a thermodynamical identity $TdS=dE+PdV$.
Looking for new physics: Search for anomalous gauge couplings in WW and WZ production in lepton + jet events in proton-proton collisions at 13 TeV with the CMS experiment
Creators: name: Iqbal, Muhammad Ansar
Publisher: name: Karlsruhe
Year: 2020

description: The LHC Run 2, with a centre-of-mass energy of 13 TeV, has opened new avenues for searching possible effects of physics beyond the standard model. Such new physics can be parametrised by adding additional operators to the standard model Lagrangian in a model-independent effective field theory approach. In this thesis, a search is presented for three operators that would lead to anomalous WWgamma or WWZ couplings. They are constrained by studying proton-proton collision events, recorded by the CMS experiment, in which two vector bosons are produced; a W boson which decays into a charged lepton and the corresponding neutrino, and a W or Z boson which decays into hadrons that are reconstructed as a single, large-radius jet. Using reconstructed kinematic variable distributions, one- and two-dimensional 95% confidence intervals are obtained for the anomalous coupling parameters. The obtained limits, $-1.58 < c_\rm{WWW}/\Lambda^2 < 1.59~\TeV^{-2}$, $-2.00 < c_\rm{W}/\Lambda^2 < 2.65~ \TeV^{-2}$, and $-8.78 < c_\rm{B}/\Lambda^2 < 8.54~\TeV^{-2}$, are the strictest bounds on these parameters to date.
Golgi α-mannosidase: opposing structures of Drosophila melanogaster and novel human model using molecular dynamics simulations and docking at different pHs
Creators: name: Drogalin, Artem
name: Monteiro, Luís S.
name: Alves, Maria José
name: Castro, Tarsila G.
Publisher: name: Taylor & Francis
Year: 2023
Subjects: subject: Biophysics
subject: Biochemistry
subject: Medicine
subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Neuroscience
subject: 39999 Chemical Sciences not elsewhere classified
subject: FOS: Chemical sciences
subject: 69999 Biological Sciences not elsewhere classified
subject: 80699 Information Systems not elsewhere classified
subject: FOS: Computer and information sciences
subject: Cancer

description: The search for Golgi α-mannosidase II (GMII) potent and specific inhibitors has been a focus of many studies for the past three decades since this enzyme is a key target for cancer treatment. α-Mannosidases, such as those from Drosophila melanogaster or Jack bean, have been used as functional models of the human Golgi α-mannosidase II (hGMII) because mammalian mannosidases are difficult to purify and characterize experimentally. Meanwhile, computational studies have been seen as privileged tools able to explore assertive solutions to specific enzymes, providing molecular details of these macromolecules, their protonation states and their interactions. Thus, modelling techniques can successfully predict hGMII 3D structure with high confidence, speeding up the development of new hits. In this study, Drosophila melanogaster Golgi mannosidase II (dGMII) and a novel human model, developed in silico and equilibrated via molecular dynamics simulations, were both opposed for docking. Our findings highlight that the design of novel inhibitors should be carried out considering the human model’s characteristics and the enzyme operating pH. A reliable model is evidenced, showing a good correlation between Ki/IC50 experimental data and theoretical ΔGbinding estimations in GMII, opening the possibility of optimizing the rational drug design of new derivatives. Communicated by Ramaswamy H. Sarma
Complex synchronization patterns in the human connectome network
Creators: name: Villegas, Pablo
name: Hidalgo, Jorge
name: Moretti, Paolo
name: Muñoz, Miguel A.
Publisher: name: arXiv
Year: 2015
Subjects: subject: Neurons and Cognition (q-bio.NC)
subject: Disordered Systems and Neural Networks (cond-mat.dis-nn)
subject: Adaptation and Self-Organizing Systems (nlin.AO)
subject: FOS: Biological sciences
subject: FOS: Physical sciences

description: A major challenge in neuroscience is posed by the need for relating the emerging dynamical features of brain activity with the underlying modular structure of neural connections, hierarchically organized throughout several scales. The spontaneous emergence of coherence and synchronization across such scales is crucial to neural function, while its anomalies often relate to pathological conditions. Here we provide a numerical study of synchronization dynamics in the human connectome network. Our purpose is to provide a detailed characterization of the recently uncovered broad dynamic regime, interposed between order and disorder, which stems from the hierarchical modular organization of the human connectome. In this regime -similar in essence to a Griffiths phase- synchronization dynamics are trapped within metastable attractors of local coherence. Here we explore the role of noise, as an effective description of external perturbations, and discuss how its presence accounts for the ability of the system to escape intermittently from such attractors and explore complex dynamic repertoires of locally coherent states, in analogy with experimentally recorded patterns of cerebral activity.
description: 12pages, 6 Figures