bluuebunny/crossref_metadata_2025 huggingface dataset:
Scalable Cryptography
Authors: Hofheinz Dennis , Kiltz Eike
Published: January 2023

In our modern digital society, cryptography is vital to protect the secrecy and integrity of transmitted and stored information. Settings like digital commerce, electronic banking, or simply private email communication already rely on encryption and signature schemes.

However, today’s cryptographic schemes do not scale well, and thus are not suited for the increasingly large sets of data they are used on. For instance, the security guarantees currently known for RSA encryption—one of the most commonly used type of public-key encryption scheme—degrade linearly in the number of users and ciphertexts. Hence, larger settings (such as cloud computing, or simply the scenario of encrypting all existing email traffic) may enable new and more efficient attacks. To maintain a reasonable level of security in larger scenarios, RSA keylengths must be chosen significantly larger, and the scheme becomes very inefficient. Besides, a switch in RSA keylengths requires an update of the whole public key infrastructure, an impossibility in truly large scenarios. Even worse, when the scenario grows beyond an initially anticipated size, we may lose all security guarantees.

This problematic is the motivation for our project “Scalable Cryptography”, which aims at offering a toolbox of cryptographic schemes that are suitable for huge sets of data. In this overview, we summarize the approach, and the main findings of our project. We give a number of settings in which it is possible to indeed provide scalable cryptographic building blocks. For instance, we survey our work on the construction of scalable public-key encryption schemes (a central cryptographic building block that helps secure communication), but also briefly mention other settings such as “reconfigurable cryptography”. We also provide first results on scalable quantum-resistant cryptography, i.e., scalable cryptographic schemes that remain secure even in the presence of a quantum computer.
Root of unity asymptotics for Schur indices of 4d Lagrangian theories
Authors: Eleftheriou Giorgos
Published: January 2023

Abstract

The Schur index of a 4 dimensional $$ \mathcal{N} $$
N
= 2 superconformal field theory counts (with sign) bosonic and fermionic states that preserve 4 supercharges. We consider the Schur indices of 4d $$ \mathcal{N} $$
N
= 4 super Yang-Mills and $$ \mathcal{N} $$
N
= 2 circular quiver gauge theories with gauge groups U(N) or SU(N). We calculate the exponentially dominant part of their asymptotic expansions as the index parameter q approaches any root of unity. We find that some of the indices exhibit “small” ($$ \mathcal{O} $$
O
(N0) as N → ∞) exponential growth, which is much smaller than an $$ \mathcal{O} $$
O
(N2) exponential growth of states that is indicative of a black hole. This implies that the indices do not capture a growth of states that would correspond to a supersymmetric black hole that preserves 4 supercharges in the holographic dual AdS theory. Interestingly, the exponentially dominant part in the Schur asymptotics we consider, depends on the parity of the rank N.
Opposing USP19 splice variants in TGF-β signaling and TGF-β-induced epithelial–mesenchymal transition of breast cancer cells
Authors: Zhang Jing , van Dinther Maarten , Thorikay Midory , Gourabi Babak Mousavi , Kruithof Boudewijn P. T. , ten Dijke Peter
Published: January 2023

Ubiquitin-specific protease (USP)19 is a deubiquitinating enzyme that regulates the stability and function of multiple proteins, thereby controlling various biological responses. The alternative splicing of USP19 results in the expression of two major encoded variants that are localized to the endoplasmic reticulum (ER) (USP19-ER) and cytoplasm (USP19-CY). The importance of alternative splicing for the function of USP19 remains unclear. Here, we demonstrated that USP19-CY promotes TGF-β signaling by directly interacting with TGF-β type I receptor (TβRI) and protecting it from degradation at the plasma membrane. In contrast, USP19-ER binds to and sequesters TβRI in the ER. By decreasing cell surface TβRI levels, USP19-ER inhibits TGF-β/SMAD signaling in a deubiquitination-independent manner. Moreover, USP19-ER inhibits TGF-β-induced epithelial–mesenchymal transition (EMT), whereas USP19-CY enhances EMT, as well as the migration and extravasation of breast cancer cells. Furthermore, USP19-CY expression is correlated with poor prognosis and is higher in breast cancer tissues than in adjacent normal tissues. Notably, the splicing modulator herboxidiene inhibits USP19-CY, increases USP19-ER expression and suppresses breast cancer cell migration. Targeting USP19 splicing or its deubiquitinating activity may have potential therapeutic effects on breast cancer.
Schutz der Rechte und Freiheiten von Personen bei der Datenverarbeitung im Gesundheitsbereich: Der Risikoansatz der EU-Datenschutz-Grundverordnung (DGSVO)
Authors: Molnár-Gábor Fruzsina
Published: January 2023

Die Zusammenführung von sensiblen Daten und die Rückführung ihrer Analyseergebnisse zu den betroffenen Personen ist ein wesentlicher Bestandteil der Datenverarbeitung im Gesundheitsbereich. Dies stellt eine besondere Herausforderung für den Datenschutz und damit für dessen wahren Zweck, den Schutz der Betroffenen, dar. Der Grund ist, dass die wissenschaftlichen und gesundheitlichen Erkenntnisse oft auf bestimmten Merkmalen in den Datensätzen fußen, die in ihrer Eigenschaft als personenbezogen beibehalten werden sollten, um die Ergebnisse der Datenanalyse fruchtbar werden zu lassen. Die Datenschutz-Grundverordnung (DSGVO) der Europäischen Union (EU) legt einen risikobasierten Ansatz fest, der sowohl die Frage des Personenbezugs von Daten als auch die Verhältnismäßigkeit ihrer Verarbeitung bestimmt.

In diesem Beitrag wird analysiert, wie der risikobasierte Ansatz den Anwendungsbereich der DSGVO eröffnet und mit den Risiken für die Rechte und Freiheiten der betroffenen Personen in Verbindung steht, die durch die Verarbeitung personenbezogener Daten entstehen. Darüber hinaus wird der Frage nachgegangen, inwieweit der risikobasierte Ansatz der DSGVO die Regeln für den internationalen Datentransfer beeinflusst, und erklärt, wie die internationale Datenverarbeitung im Gesundheitssektor auf seiner Grundlage zurzeit organisiert wird.

Insgesamt gibt die vorliegende Analyse Aufschluss darüber, wie die technischen Maßnahmen der Datenverarbeitung und die organisatorischen Maßnahmen zu deren Handhabung dazu beitragen können, die Verhältnismäßigkeit der Datenverarbeitung nach der DSGVO zu wahren, die im Wesentlichen als risikobasiert bestimmt werden kann, um zugleich der Spezifität der Datenverarbeitung im Gesundheitsbereich Rechnung zu tragen.
Künstliche Intelligenz und Ethik im Gesundheitswesen – Spagat oder Symbiose?
Authors: Küster Dennis , Schultz Tanja
Published: January 2023

Künstliche Intelligenz (KI) gewinnt auch im Gesundheitswesen immer mehr an Bedeutung. Diese Entwicklung löst ernst zu nehmende Sorgen aus, die sich anhand von sechs großen „Worst-Case-Szenarien“ zusammenfassen lassen. Von einer KI-basierten Verbreitung von Desinformationen und Propaganda über einen möglichen militärischen Wettlauf zwischen den Großmächten bis hin zu einer möglichen Herrschaft der Algorithmen („Algokratie“) auf Basis einer voreingenommenen Torwächterintelligenz: Die realen Gefahren einer unkontrollierten weiteren Entwicklung von KI sind insbesondere im Gesundheitsbereich keinesfalls zu unterschätzen. Allerdings könnte der Menschheit aus Angst vor KI jedoch die Möglichkeit entgehen, die Entwicklung unserer Gesellschaft gemeinsam mit uns freundlich gesinnter KI positiv zu gestalten.

Anwendungsfälle im Gesundheitswesen spielen in diesem Diskussionsbeitrag eine vorrangige Rolle, da hier sowohl die Risiken als auch die Chancen neuer KI-basierter Systeme besonders deutlich werden. Dürfen z. B. ältere Menschen mit Demenz (MmD) Teile ihrer Autonomie KI-basierten Assistenzsystemen anvertrauen, damit sie andere Aspekte ihres Alltagslebens weiterhin selbstständig meistern können? In diesem Beitrag argumentieren wir, dass sich der Spagat zwischen Ethik und KI sowie den Gefahren und Chancen von KI im Gesundheitswesen zumindest teilweise durch einen langfristig angelegten ethischen Ansatz in Richtung einer Symbiose zwischen Mensch und KI überwinden lässt. Wir illustrieren diesen Ansatz beispielhaft anhand unseres „I-CARE“-Systems, eines KI-basierten Empfehlungssystems zur tertiären Prävention von Demenz. Dieses System wurde seit 2015 im gleichnamigen Projekt „I-CARE“ an der Universität Bremen entwickelt und wird dort bis heute erforscht..
An Analysis of Hydromorphological Index for Rivers (HIR) Model Components, Based on a Hydromorphological Assessment of Watercourses in the Central European Plain
Authors: Garbowski Tomasz , Brysiewicz Adam , Nosek Justyna , Bar-Michalczyk Dominika , Czerniejewski Przemysław
Published: January 2023

Assessing the hydromorphological conditions of watercourses is a requirement of the Water Framework Directive (WFD) and national river status monitors (e.g., in Poland,the State Environmental Monitoring, and Water Monitoring coordinated by Chief Inspectorate of Environmental Protection). This paper evaluates the hydromorphological status of 10 watercourses (30 measurement sections) in Poland based on the multimetric Hydromorphological Index for Rivers (HIR). A new approach to the delineation of the river valley (small watercourses) is proposed. An analysis of the influence of river valley management on the value of HIR and its components was carried out using statistical methods (basic statistics, Mann–Whitney U Test and Ward’s cluster analysis). In addition, the relationship between the components of the HDS (Hydromorphological Diversity Score) and HMS (Hydromorphological Modification Score) was analyzed (Spearman’s Rank Correlation Coefficient). HIR values for the watercourse sections ranged from 0.553 to 0.825. HDS values ranged from 27.5 to 75.5 and HMS from 2.0 to 17.5. The results of the basic statistical analyses showed slight differences between the two river valley delineation methods. The Mann–Whitney U Test showed a significant difference in the test significance level of the HDS, HMS and HIR for the river valley delineation methods. Spearman’s rank correlation analysis showed that most of the HDS and HMS parameters components had a low degree of correlation. The juxtaposition of the two methods for delineating a river valley and its influence on the HIR allows for a better understanding of the interdependence between its parameters.
Robustness of precipitation Emergent Constraints in CMIP6 models
Authors: Ferguglia Olivia , von Hardenberg Jost , Palazzi Elisa
Published: January 2023

An Emergent Constraint (EC) is a physically-explainable relationship between model simulations of a past climate variable (predictor) and projections of a future climate variable (predictand). If a significant correlation exists between the predictand and the predictor, observations of the latter can be used to constrain model projections of the former and to narrow their uncertainties. In the present study, the EC technique has been applied to the analysis of precipitation, one of the variables most affected by model uncertainties and still insufficiently analysed in the context of ECs, particularly for the recent CMIP6 model ensemble. The main challenge in determining an EC is establishing if the relationship found is physically meaningful and robust to the composition of the model ensemble. Four precipitation ECs already documented in the literature and so far tested only with CMIP3/CMIP5, three of them involving the analysis of extreme precipitation, have been reconsidered in this paper. Their existence and robustness are evaluated using different subsets of CMIP5 and CMIP6 models, verifying if the EC is still present in the most recent ensemble and assessing its sensitivity to the detailed ensemble composition. Most ECs considered do not pass this test: we found one EC not to be robust in both CMIP5 and CMIP6, other two exist and are robust in CMIP5 but not in CMIP6, and only one is verified and is robust in both model ensembles.
Exploring the limits of the Jenkinson–Collison weather types classification scheme: a global assessment based on various reanalyses
Authors: Fernández-Granja Juan A. , Brands Swen , Bedia Joaquín , Casanueva Ana , Fernández Jesús
Published: January 2023

The Jenkinson–Collison weather typing scheme (JC-WT) is an automated method used to classify regional sea-level pressure into a reduced number of typical recurrent patterns. Originally developed for the British Isles in the early 1970’s on the basis of expert knowledge, the method since then has seen many applications. Encouraged by the premise that the JC-WT approach can in principle be applied to any mid-to-high latitude region, the present study explores its global extra-tropical applicability, including the Southern Hemisphere. To this aim, JC-WT is applied at each grid-box of a global 2.5$$^{\circ }$$

∘

regular grid excluding the inner tropics (± 5$$^{\circ }$$

∘

band). Thereby, 6-hourly JC-WT catalogues are obtained for 5 distinct reanalyses, covering the period 1979–2005, which are then applied to explore (1) the limits of method applicability and (2) observational uncertainties inherent to the reanalysis datasets. Using evaluation criteria, such as the diversity of occurring circulation types and the frequency of unclassified situations, we extract empirically derived applicability thresholds which suggest that JC-WT can be generally used anywhere polewards of 23.5$$^{\circ }$$

∘

, with some exceptions. Seasonal fluctuations compromise this finding along the equatorward limits of the domain. Furthermore, unreliable reanalysis sea-level pressure estimates in elevated areas with complex orography (such as the Tibetan Plateau, the Andes, Greenland and Antarctica) prevent the application of the method in these regions. In some other regions, the JC-WT classifications obtained from the distinct reanalyses substantially differ from each other, which may bring additional uncertainties when the method is used in model evaluation experiments.
Intralabyrinthine schwannomas: a two-case series and literature review with a focus on hearing rehabilitation
Authors: Curatoli Luigi , Pontillo Vito , Quaranta Nicola
Published: January 2023

Purpose

Intralabyrinthine schwannomas (ILSs) are an uncommon finding. Diagnosis is challenging and no gold standard treatment exists yet. In this article, we present a two-cases series and review the latest available literature to assess the best diagnostic and therapeutic scheme.

Methods

We reviewed the latest available literature assessing most frequent and relevant sets of symptoms, clinical features of the disease, diagnostic tests and imaging, possible treatments and after-surgery hearing rehabilitation techniques. We then compared literature data to our own series ones.

Results

ILSs clinical presentation and development may overlap with other, more common otological conditions. Full audiometric battery test, electrophysiological study of VEMPS and MRI with contrast enhancement all appear to be critical to correctly diagnose these tumors. Several treatments exist: radiological follow-up, radiation therapy, full or partial surgical excision. Hearing rehabilitation is mostly accomplished through simultaneous cochlear implantation.

Conclusions

Our case-series data matches the available literature. ILSs are a rare type of vestibular schwannomas. Diagnosis in challenging and delayed in time as all the diagnostic tests, yet sensitive, are not specific for ILSs. The most suitable treatment seems to be surgical excision of these tumors followed by simultaneous cochlear implantation to restore hearing.
Systematic literature review of immunoglobulin trends for anti-CD20 monoclonal antibodies in multiple sclerosis
Authors: Saidha Shiv , Bell Judith , Harold Sydney , Belisario Jose Marcano , Hawe Emma , Shao Qiujun , Wyse Kerri , Maiese Eric M.
Published: January 2023

Objective

To exp lore changes in immunoglobulin (Ig) levels for people with relapsing-multiple sclerosis (RMS) treated with ocrelizumab or ofatumumab and the relationship between Ig levels and infections.

Methods

A systematic literature review (SLR) was conducted to identify clinical trials and real-world evidence (RWE) studies on Ig levels over time and studies on associations with infections for ocrelizumab and ofatumumab for people with RMS through 10 September 2021. Searches were conducted in Embase, MEDLINE, Cochrane Library, trial registries, and recent conference abstracts.

Results

Of 1,580 articles identified, 30 reporting on 11 trials and 5 RWE studies were included. Ocrelizumab trials (n = 4) had 24–336 weeks of follow-up and reported decreasing Ig G (IgG) levels, while RWE (n = 5) had 52–78 weeks of follow-up and reported IgG to be stable or decrease only slightly. IgG levels were stable in ofatumumab trials (n = 5; 104–168 weeks of follow-up), but no RWE or longer-term studies were identified. No apparent association between decreased Ig levels and infections was observed during ofatumumab treatment (ASCLEPIOS I/II), while for ocrelizumab, the only data on apparent associations between decreased IgG levels and serious infection rates were for a pooled population of people with RMS or primary progressive MS.

Conclusion

Decreasing IgG levels have been correlated with increased infection risk over time. IgG levels appeared to decrease over time in ocrelizumab trials but remained relatively stable over time in ofatumumab trials. Additional research is needed to understand differences between ocrelizumab and ofatumumab and identify people at risk of decreasing IgG levels and infection.
Construction and demolition waste management in Kosovo: a survey of challenges and opportunities on the road to circular economy
Authors: Alite Martin , Abu-Omar Heba , Agurcia Maria Teresa , Jácome Myriam , Kenney Jolina , Tapia Andrea , Siebel Maarten
Published: January 2023

Managing Construction and demolition waste (CDW) is a severe and growing urban challenge, particularly in post-conflict countries. Though Kosovo has significantly rebuilt and developed after the Liberation War, these initiatives have accompanied suboptimal waste management. This research evaluates CDW management in Kosovo by assessing current practices and operations vis-a-vis the legal framework and EU requirements. It identifies instruments and policies capable of ameliorating gaps and proposes a more sustainable and circular CDW management system for Kosovo. Information was primarily collected during on-site visits to Pristina and the surroundings by a cohort of Urban Management Students from the Technische Universität Berlin, students from Kosovo, and the local office of the Gesellschaft für Internationale Zusammenarbeit, GIZ. The analysis identified gaps in Kosovo's CDW management and its observance and enforcement of existing CDW legislation, including an ambiguous licensing system impeding sustainable demolition, storage, and transport; the absence of approved CDW storage options leading to uncontrolled disposal; and an underdeveloped market for recycling and reuse, deterring stakeholders from further pursuit of circular practices. These gaps were compounded by poor recordkeeping, obscuring precise information on CDW streams. Possible instruments and incentives to support Kosovo's transition to a more sustainable CDW management system were then identified.
A graph-based framework for model-driven optimization facilitating impact analysis of mutation operator properties
Authors: John Stefan , Kosiol Jens , Lambers Leen , Taentzer Gabriele
Published: January 2023

Optimization problems in software engineering typically deal with structures as they occur in the design and maintenance of software systems. In model-driven optimization (MDO), domain-specific models are used to represent these structures while evolutionary algorithms are often used to solve optimization problems. However, designing appropriate models and evolutionary algorithms to represent and evolve structures is not always straightforward. Domain experts often need deep knowledge of how to configure an evolutionary algorithm. This makes the use of model-driven meta-heuristic search difficult and expensive. We present a graph-based framework for MDO that identifies and clarifies core concepts and relies on mutation operators to specify evolutionary change. This framework is intended to help domain experts develop and study evolutionary algorithms based on domain-specific models and operators. In addition, it can help in clarifying the critical factors for conducting reproducible experiments in MDO. Based on the framework, we are able to take a first step toward identifying and studying important properties of evolutionary operators in the context of MDO. As a showcase, we investigate the impact of soundness and completeness at the level of mutation operator sets on the effectiveness and efficiency of evolutionary algorithms.
Uncertainty in firm valuation and a cross-sectional misvaluation measure
Authors: Bottazzi Giulio , Cordoni Francesco , Livieri Giulia , Marmi Stefano
Published: January 2023

The degree of uncertainty associated with the value of a company plays a relevant role in valuation analysis. We propose an original and robust methodology for company market valuation, which replaces the traditional point estimate of the conventional Discounted Cash Flow model with a probability distribution of fair values that convey information about both the expected value of the company and its intrinsic uncertainty. Our methodology depends on two main ingredients: an econometric model for company revenues and a set of firm-specific balance sheet relations that are estimated using historical data. We explore the effectiveness and scope of our methodology through a series of statistical exercises on publicly traded U.S. companies. At the firm level, we show that the fair value distribution derived with our methodology constitutes a reliable predictor of the company’s future abnormal returns. At the market level, we show that a long-short valuation (LSV) factor, built using buy-sell recommendations based on the fair value distribution, contains information not accessible through the traditional market factors. The LSV factor significantly increases the explanatory and the predictive power of factor models estimated on portfolios and individual stock returns.
A survey of Bayesian Network structure learning
Authors: Kitson Neville Kenneth , Constantinou Anthony C. , Guo Zhigao , Liu Yang , Chobtham Kiattikun
Published: January 2023

Bayesian Networks (BNs) have become increasingly popular over the last few decades as a tool for reasoning under uncertainty in fields as diverse as medicine, biology, epidemiology, economics and the social sciences. This is especially true in real-world areas where we seek to answer complex questions based on hypothetical evidence to determine actions for intervention. However, determining the graphical structure of a BN remains a major challenge, especially when modelling a problem under causal assumptions. Solutions to this problem include the automated discovery of BN graphs from data, constructing them based on expert knowledge, or a combination of the two. This paper provides a comprehensive review of combinatoric algorithms proposed for learning BN structure from data, describing 74 algorithms including prototypical, well-established and state-of-the-art approaches. The basic approach of each algorithm is described in consistent terms, and the similarities and differences between them highlighted. Methods of evaluating algorithms and their comparative performance are discussed including the consistency of claims made in the literature. Approaches for dealing with data noise in real-world datasets and incorporating expert knowledge into the learning process are also covered.
Descent for internal multicategory functors
Authors: Prezado Rui , Nunes Fernando Lucatelli
Published: January 2023

We give sufficient conditions for effective descent in categories of (generalized) internal multicategories. Two approaches to study effective descent morphisms are pursued. The first one relies on establishing the category of internal multicategories as an equalizer of categories of diagrams. The second approach extends the techniques developed by Ivan Le Creurer in his study of descent for internal essentially algebraic structures.
Insecticidal activity of Bacillus thuringiensis strains isolated from tropical greenhouses towards Cydia pomonella and Spodoptera exigua larvae
Authors: Baranek Jakub , Pluskota Mateusz , Rusin Monika , Konecka Edyta , Kaznowski Adam , Wiland-Szymańska Justyna
Published: January 2023

Three Bacillus thuringiensis strains were isolated from a specific habitat of tropical greenhouses located in the Botanical Garden of Adam Mickiewicz University in Poznań, Poland. The BG11, BG12 and BG15 strains harbour genes encoding a specific set of insecticidal proteins (cry1Ba, cry1Ia, cry2Ab, vip3Aa)—entirely different from those found in commercial isolates, currently used as bioinsecticides. Despite high genetic similarity of the new strains, each of them produces unique Cry1Ba toxin as a main component of the parasporal crystals. Moreover, the tested entomopathogens contain genetic determinants encoding two types of chitinolytic enzymes ChiA and ChiB. The tested strains display insecticidal activity against two distinct, economically important pest insects, Cydia pomonella L. (Lepidoptera: Tortricidae) and Spodoptera exigua Hübner (Lepidoptera: Noctuidae). However, BG12 and BG15 strains are significantly more active than BG11 towards both pests. The BG12 and BG15 strains can be considered as candidates for the production of new lepidopteran-active bioinsecticides with high potential to augment the existing biocontrol strategies.
Short attribute-based signatures for arbitrary Turing machines from standard assumptions
Authors: Datta Pratish , Dutta Ratna , Mukhopadhyay Sourav
Published: January 2023

This paper presents the first attribute-based signature () scheme supporting signing policies representable by Turing machines (), based on well-studied computational assumptions. Our work supports arbitrarys as signing policies in the sense that the s can accept signing attribute strings of unbounded polynomial length and there is no limit on their running time, description size, or space complexity. Moreover, we are able to achieve input-specific running time for the signing algorithm. All other known expressive schemes could at most support signing policies realizable by either arbitrary polynomial-size circuits or s having a pre-determined upper bound on the running time. Consequently, those schemes can only deal with signing attribute strings whose lengths are a priori bounded, as well as suffers from the worst-case running time problem. On a more positive note, for the first time in the literature, the signature size of our scheme only depends on the size of the signed message and is completely independent of the size of the signing policy under which the signature is generated. This is a significant achievement from the point of view of communication efficiency. Our construction makes use of indistinguishability obfuscation () for polynomial-size circuits and certain -compatible cryptographic tools. Note that, all of these building blocks including for polynomial-size circuits are currently known to be realizable under well-studied computational assumptions.
Large Isotropic Elastic Deformations: On a Comprehensive Model to Correlate the Theory and Experiments for Incompressible Rubber-Like Materials
Authors: Anssari-Benam Afshin
Published: January 2023

A comprehensive model, i.e., a model that: (i) suitably captures the mechanical behaviour of various types of rubber-like materials; (ii) describes the constitutive behaviour of a subject rubber-like specimen under different deformation modes via a single set of model parameter values, and (iii) is parent to many of the existing models of distinct types, is presented in this paper for application to the finite deformation of incompressible isotropic rubber-like materials. The model breaks away from Rivlin’s principal invariants $I_{i}$

I
i

and Valanis-Landel’s separable function of principal stretches $\lambda _{i}$

λ
i

representations, and instead adopts a general non-separable functional form $W( \lambda _{1}, \lambda _{2}, \lambda _{3} )$
W
(

λ
1

,

λ
2

,

λ
3

)
, subject to the incompressibility constraint. By way of example, the application of the model to extant datasets from four types of rubber-like materials that exhibit discernible mechanical behaviours, namely natural unfilled and filled rubbers, hydrogels and (extremely) soft tissue specimens, will be considered. The favourable correlation between the model predictions and the considered experimental datasets, obtained via simultaneous fitting of the model to the data of various deformations, will be demonstrated. It will be shown that most of the landmark models in the literature including the $W( I_{1}, I_{2} )$
W
(

I
1

,

I
2

)
form Mooney-Rivlin, the Gent-like limiting chain extensibility, the nonaffine tube and the separable principal stretches-based type Ogden models are all a special sub-set of the presented parent model, and are all recovered from this model. An important implication of the non-separable functional form of the model will be conferred, through a specific dataset, where the predictions of the separable functions prove inherently inadequate. The consequences of these improvements for a more accurate modelling of the finite deformation of incompressible isotropic rubber-like materials will also be discussed.
From Groups to Communities: A Resource Mobilization Theory Perspective on the Emergence of Communities
Authors: Angelopoulos Spyros , Canhilal Kubra S. , Hawkins Matthew A.
Published: January 2023

Groups and communities have been key topics in the information systems (IS) research agenda. While communities are assumed to emerge at the intersection of overlapping groups and their practices, prior research has mainly focused on their dynamics and evolution. This has resulted to limited empirical support regarding the emergence of communities. We address that lacuna by tracing the emergence of communities through the prism of resource mobilization theory. In doing so, we make use of a unique longitudinal dataset and incorporate Topic Modelling, Bipartite Network Analysis, and Community Detection. We show that new communities are formed at the intersection of overlapping groups and practices. In addition, we contribute to the IS literature by demonstrating that their emergence occurs due to resource mobilization that gives rise to a shared mindset. We also reveal that multiple resources are incorporated into the practices of an emerging community. By combining large datasets and innovative computational approaches, we help IS theory and practice to move away from traditional "what" questions towards the more insightful "how" ones. We discuss the theoretical and practical implications of our work and delineate an agenda for future research on the topic.
Learning Linearized Assignment Flows for Image Labeling
Authors: Zeilmann Alexander , Petra Stefania , Schnörr Christoph
Published: January 2023

We introduce a novel algorithm for estimating optimal parameters of linearized assignment flows for image labeling. An exact formula is derived for the parameter gradient of any loss function that is constrained by the linear system of ODEs determining the linearized assignment flow. We show how to efficiently evaluate this formula using a Krylov subspace and a low-rank approximation. This enables us to perform parameter learning by Riemannian gradient descent in the parameter space, without the need to backpropagate errors or to solve an adjoint equation. Experiments demonstrate that our method performs as good as highly-tuned machine learning software using automatic differentiation. Unlike methods employing automatic differentiation, our approach yields a low-dimensional representation of internal parameters and their dynamics which helps to understand how assignment flows and more generally neural networks work and perform.
How expressing one’s likes and dislikes affects enjoyment: a replication
Authors: Wittich Julia Sophia , Landwehr Jan R. , Wentzel Daniel
Published: January 2023

A recent article by He, Melumad, and Pham (Journal of Consumer Research 46(3):545–563, 2019) showed that consumers experienced greater enjoyment when they were asked to perform an evaluative task relative to a non-evaluative task. In this research, we intend to replicate this finding and to examine to what extent the strength of the effect is contingent on the sample employed. Using a sample from Amazon MTurk, study 1 replicates the indirect effect but not the total experimental effect. Study 2 draws on a sample that is unacquainted with the experimental paradigm and replicates the indirect as well as the total experimental effect. These findings suggest that the sampling population of MTurk may have become desensitized to the basic experimental paradigm.
Complete mitochondrial genome of the Spanish toothcarp, Aphanius iberus (Valenciennes, 1846) (Actinopterygii, Aphaniidae) and its phylogenetic position within the Cyprinodontiformes order
Authors: López-Solano Alfonso , Nester Tessa Lynn , Perea Silvia , Doadrio Ignacio
Published: January 2023

Background

The Spanish toothcarp (Aphanius iberus Valenciennes, 1846) is a small fish endemic to the eastern coastline of the Iberian Peninsula and is currently listed as “Endangered” (category IUCN: EN). It mainly inhabits brackish waters which can exhibit large fluctuations in temperature and salinity throughout the year. The genetics of A. iberus are not well-known since most studies have only evaluated the genetic structure of the species under a conservation framework in order to identify its potential conservation units. Different phylogenetic relationships of Aphanius have been published based on some particular genes. In the present study, the entire mitochondrial genome of A. iberus was obtained for the first time in the context of an A. iberus reference genome and a hypothesis regarding its phylogenetic position was considered.

Methods and results

The mitogenome (a circular doble-stranded DNA sequence of 16,708 bp) was reconstructed and aligned against 83 Cyprinodontiformes and two outgroup taxa to identify the phylogenetic position of A. iberus. PartitionFinder was first used to test for the best evolutionary model and the phylogenetic analyses were performed using two methods: Maximun-Likelihood Approximation (IQ-Tree) and Bayesian inference (MrBayes). Our results show that A. iberus forms a sister group with Orestias ascotanensis, a cyprinodontiform species native to South America.

Conclusions

The results were congruent with the traditional morphometric reconstructed trees and with a geological vicariant hypothesis involving Cyprinodontiformes where Aphaniidae is shown as a monophyletic family separated from the family Cyprinodontidae. The information gathered from this study is not only valuable for improving our understanding of the evolutionary history of A. iberus, but for future genomic studies involving the species.
Reporting non-consensual pornography: clarity, efficiency and distress
Authors: De Angeli Antonella , Falduti Mattia , Menendez-Blanco Maria , Tessaris Sergio
Published: January 2023

According to recent legislative initiatives, non-consensual pornography is a crime in several countries and social media providers have a duty to provide their users easy to use mechanisms to report abuses. In this paper, we analyse the state of the art of the interfaces for reporting non-consensual pornography from the victim’s perspective. Firstly, we analysed 45 content sharing platforms where aggressors might post non-consensual pornography. The analysis identified three distinct interaction styles for reporting the crime: Scriptum (a text-field where the user verbally describes the abuse), Bonam (a multilayered menu that includes a correct option), and Malam (a multilayered menu that does not include a correct option). Secondly, we conducted a within-subject study to evaluate the experience elicited by these interaction styles. Participants (N = 39) were given a scenario and asked to report six blurred images as non-consensual pornography using a medium-fidelity prototype. The results exposed complex trade-offs between clarity, efficiency, and distress among the different interaction styles. These trade-offs open foundational research directions transcending boundaries between human-computer interaction and multimedia studies and interfacing computer science research with the law.
Population diversity and inheritance in genetic programming for symbolic regression
Authors: Burlacu Bogdan , Yang Kaifeng , Affenzeller Michael
Published: January 2023

In this work we aim to empirically characterize two important dynamical aspects of GP search: the evolution of diversity and the propagation of inheritance patterns. Diversity is calculated at the genotypic and phenotypic levels using efficient similarity metrics. Inheritance information is obtained via a full genealogical record of evolution as a directed acyclic graph and a set of methods for extracting relevant patterns. Advances in processing power enable our approach to handle previously infeasible graph sizes of millions of arcs and vertices. To enable a more comprehensive analysis we employ three closely-related but different evolutionary models: canonical GP, offspring selection and age-layered population structure. Our analysis reveals that a relatively small number of ancestors are responsible for producing the majority of descendants in later generations, leading to diversity loss. We show empirically across a selection of five benchmark problems that each configuration is characterized by different rates of diversity loss and different inheritance patterns, in support of the idea that each new problem may require a unique approach to solve optimally.
Sequences in overpartitions
Authors: Andrews George E. , Uncu Ali K.
Published: January 2023

This paper is devoted to the study of sequences in overpartitions and their relation to 2-color partitions. An extensive study of a general class of double series is required to achieve these ends.
Snake life history traits and their association with urban habitat use in a tropical city
Authors: Lettoof Damian Christopher , Parkin Tom , Jolly Chris James , de Laive Alana , von Takach Brenton
Published: January 2023

Urbanisation changes landscapes, often simplifying and homogenising natural ecosystems while introducing novel environments. Although this transformation often adversely impacts native wildlife, generalist species that exhibit broad dietary and habitat requirements can persist and take advantage of urban environments. To understand which life history traits most influence the occurrence of a diverse snake assemblage in an urban environment, we leveraged a dataset of 5102 detection records for 12 snake species in the tropical city of Darwin, Australia. By building ecological niche models, calculating urban niche hypervolume, and compiling life history data, we analysed the diversity of environments occupied by each species and determined which landscape components were most associated with occurrence data. In keeping with our hypothesis that generalist species would be more successful, we found that species with broader habitat and dietary preferences, as well as a penchant for arboreality, were associated with larger urban niche hypervolumes and more frequent human–snake interactions. Additionally, we found that colubrid snakes had significantly larger urban niche hypervolumes than elapid species. These findings contribute to understanding how life history traits aid wildlife persistence in, and adaptation to, urban ecosystems, and have implications for landscape design and conservation management.
Protective effect of quercetin on pulmonary dysfunction in streptozotocin-induced diabetic rats via inhibition of NLRP3 signaling pathway
Authors: El-Shaer Noha Osama , Hegazy Ahmed Medhat , Muhammad Marwa H.
Published: January 2023

Diabetes mellitus (DM) is a dysmetabolic disease characterized by chronic hyperglycemia. In the developed countries, DM is the commonest life style disease that affects both old and young age. Nod-like receptor protein-3 (NLRP3)-mediated pyroptosis may in fact aid in the development of diabetic complications. Quercetin is a natural flavonoid, can be present in natural foods and plants. Many studies have reported the antioxidant role of quercetin on different tissues, but its effects on NLRP3-mediated pyroptosis in diabetic lung are unclear. The current study aimed to assess quercetin’s protective effects on lung function, oxidative stress, and NLRP3-mediated pyroptosis in Wister rats exposed to streptozotocin (STZ)-induced DM. Forty male Wister rats were randomly allocated into four equal groups. The groups of rats were as follows: group 1 (G1) was kept under normal control conditions; G2 was injected I/P quercetin at a dose of 30 mg/kg b.wt., daily for 30 days; G3 and G4 were injected with a single dose of streptozotocin (STZ) 50 mg/kg b.wt. I/P to induce DM. After 72-h post diabetes induction, the rats of G4 were treated with quercetin as a manner in the second group. The results showed that quercetin ameliorates the pulmonary dysfunctions caused by DM through restoring the levels of glucose, insulin, and arterial blood gases, as well as the oxidative markers. Also, NLRP3-pyroptosis-mediated IL1β was inhibited. Quercetin also reduces the effect of DM on the lung by decreasing the pathological changes in the lung. In conclusion, NLRP3 inflammasome-induced pyroptosis may aggravate lung injury in diabetic rats. Quercetin has the potential to ameliorate diabetes induced pulmonary dysfunction by targeting NLRP3.
Cooling Off and the Effects of Mandatory Breaks in Online Gambling: A Large-Scale Real-World Study
Authors: Hopfgartner Niklas , Auer Michael , Santos Tiago , Helic Denis , Griffiths Mark D.
Published: January 2023

The prevention of problematic online gambling behavior is a topic of major interest for regulators, the gambling industry, and researchers. Many gambling operators approach this issue by using responsible gambling tools. Among such tools, mandatory play breaks are used to interrupt long online gambling sessions, providing “cooling off” periods for players to take a reflective “time out”. The present study investigated the effects of mandatory play breaks in a large-scale experiment with 23,234 online gamblers engaging in more than 870,000,000 gambling transactions on Norsk Tipping’s gambling platform over a 1-month period. The gamblers were randomly assigned to several intervention groups with varying duration of mandatory play breaks and one control group with Norsk Tipping’s standard play break duration. More specifically, the study analyzed the relationship between the mandatory break received and the gambler’s acceptance of this tool, the interaction patterns with the tool, and how quickly they started to gamble again, as well as post-intervention effects on gambling behavior. Results showed that gamblers who were treated with longer mandatory breaks (i) tended to take longer voluntary breaks, and (ii) interacted more frequently with the tool (for instance, by clicking the “logout” button). Furthermore, gamblers appeared to accept longer mandatory play breaks. However, only a fraction of post-intervention effects remained, and mainly only for gamblers who received a substantial number of long mandatory play breaks. Overall, the present study provides actionable insights for both researchers and the gambling industry to improve the effectiveness of mandatory play breaks as a responsible gambling tool.
Small Acts With Big Impacts: Does Garbage Classification Improve Subjective Well-Being in Rural China?
Authors: Li Junpeng , Vatsa Puneet , Ma Wanglin
Published: January 2023

Solid waste has surged in rural China, home to more than 540 million people. To preserve the environment, the Chinese government has piloted garbage classification programs. However, little is known about whether and to what extent classifying garbage affects people's subjective well-being—should its effects be positive, people would be more amenable to classifying garbage, making it easier to entrench garbage classification practices and programs and ultimately improve the environment. Accordingly, we analyze the impact of garbage classification on subjective well-being using the 2020 China Land Economic Survey data. An endogenous treatment regression model is utilized to address self-selection into garbage classification programs. We find that this simple and somewhat mundane practice can significantly improve people's happiness and life satisfaction. These results reaffirm the compound benefits of allocating more public resources to accelerate the adoption of garbage classification in rural areas.
Systematic review of machine learning-based radiomics approach for predicting microsatellite instability status in colorectal cancer
Authors: Wang Qiang , Xu Jianhua , Wang Anrong , Chen Yi , Wang Tian , Chen Danyu , Zhang Jiaxing , Brismar Torkel B.
Published: January 2023

This study aimed to systematically summarize the performance of the machine learning-based radiomics models in the prediction of microsatellite instability (MSI) in patients with colorectal cancer (CRC). It was conducted according to the preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies (PRISMA-DTA) guideline and was registered at the PROSPERO website with an identifier CRD42022295787. Systematic literature searching was conducted in databases of PubMed, Embase, Web of Science, and Cochrane Library up to November 10, 2022. Research which applied radiomics analysis on preoperative CT/MRI/PET-CT images for predicting the MSI status in CRC patients with no history of anti-tumor therapies was eligible. The radiomics quality score (RQS) and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) were applied to evaluate the research quality (full score 100%). Twelve studies with 4,320 patients were included. All studies were retrospective, and only four had an external validation cohort. The median incidence of MSI was 19% (range 8–34%). The area under the receiver operator curve of the models ranged from 0.78 to 0.96 (median 0.83) in the external validation cohort. The median sensitivity was 0.76 (range 0.32–1.00), and the median specificity was 0.87 (range 0.69–1.00). The median RQS score was 38% (range 14–50%), and half of the studies showed high risk in patient selection as evaluated by QUADAS-2. In conclusion, while radiomics based on pretreatment imaging modalities had a high performance in the prediction of MSI status in CRC, so far it does not appear to be ready for clinical use due to insufficient methodological quality.
Policing Disobedient Demonstrations
Authors: Monaghan Jake
Published: January 2023

This article sketches a case for the importance of allowing and protecting civil disobedience in a democratic society. There are weighty reasons for non-enforcement of certain laws under certain circumstances, which undermines the legalistic claim that justice requires police to faithfully (try to) enforce all laws at all times. Furthermore, questions about how the police should respond to disobedient demonstrations are not settled by popular theoretical treatments of civil disobedience. Police responses to disobedient demonstrations should be guided by a principle of proportionality. This proportionality requirement is more stringent in cases of self-generated needs for self-defense. Common police tactics like “skirmish lines” predictably escalate interactions and create a need for further defensive force, thereby violating the proportionality requirement.