bluuebunny/crossref_metadata_2025_split huggingface dataset:
From the Privacy Calculus to Crossing the Rubicon: An Introduction to Theoretical Models of User Privacy Behavior
Authors: Gerber Nina , Stöver Alina 
Published: August 2023

AbstractSeveral theories and behavioral models aiming to explain user privacy behavior, including the privacy paradox, have been proposed in the literature. In this chapter, we give an introduction to the behavioral models that are most frequently used in privacy research, as well as those that originate in other contexts but nevertheless have the potential to make a meaningful contribution to explaining user privacy behavior. We further discuss to what extent the behavioral models help us to explain and predict privacy behaviors. The renowned privacy calculus model, for example, falls short in this respect since it remains unclear which consequences are evaluated by the user, whereas other models such as the theory of planned behavior can offer novel insights when combined with models such as HAPA or COM-B that are so far unfathomed in the context of privacy research.
Privacy Nudges and Informed Consent? Challenges for Privacy Nudge Design
Authors: Zimmermann Verena 
Published: August 2023

AbstractPrivacy nudges aim to support the “wise” choice concerning digital privacy decisions. Examples include nudges to encourage privacy-friendly app choices or to discourage unintended location disclosure. Yet, a general nudge criticism concerns the potential manipulation of users by targeting automatic and perhaps unaware cognitive processes. This calls for guidance in designing ethically favorable and transparent nudges. Therefore, this chapter first reviews and presents guidelines for designing ethical privacy nudges. Second, encouraging users to make the “wise” privacy choice is not easy. Initially, the more privacy-friendly choice for the user appears to be clear in many cases. However, with regard to privacy, the choice is less clear when considering legal requirements. Current EU regulations depart from generally favoring the more privacy-friendly option and instead suggest enabling users to make an informed decision. This is not necessarily the most privacy-preserving option but for some users might be a trade-off considering convenience or other factors. Apart from “privacy-preserving” nudges, this chapter thus discusses options for and challenges associated with designing privacy nudges that can support users in making informed privacy decisions. This includes nudges that target reflective thinking, interventions based on the users’ preferences, or a combination of nudges with other approaches.
The Hows and Whys of Dark Patterns: Categorizations and Privacy
Authors: Kitkowska Agnieszka 
Published: August 2023

AbstractWhen people interact with digital technologies, their choices are often driven in a specific direction, mainly through user interface designs—e.g., specific layout or content. Such guiding practices might be useful. They may help find desired information quicker or proceed with a given task more efficiently. Ultimately, they may contribute to improved usability and satisfaction that users experience during the interaction. However, some of such designs can mislead, manipulate, or trick users into choices that are beneficial to service providers but not necessarily to users. These designs are known as dark patterns, and their success relies on psychological characteristics, particularly exploiting decision-making processes’ weaknesses. The applicability of dark patterns is traditionally associated with e-commerce or marketing strategies aiming to increase sales. However, research shows that dark patterns also extend to online privacy, resulting in harms reaching beyond economic loss and exploiting the vulnerabilities of individuals. This chapter reviews research on dark patterns and explains some of the psychological bases that dark patterns rely on. The chapter focuses on privacy issues and discusses possible ways of preventing the detrimental effects of dark patterns, including their effects on business.
Generalized Linear Models
Authors: Salinas Ruíz Josafhat , Montesinos López Osval Antonio , Hernández Ramírez Gabriela , Crossa Hiriart Jose 
Published: August 2023

AbstractIn the generalized linear model (GLM) (which is not highly general) y = Xβ + ϵ, the response variables are normally distributed, with constant variance across the values of all the predictor variables, and are linear functions of the predictor variables. Transformations of data are used to try to force the data into a normal linear regression model or to find a non-normal-type response variable transformation (discrete, categorical, positive continuous scale, etc.) that is linearly related to the predictor variables; however, this is no longer necessary. Instead of using a normal distribution, a positively skewed distribution with values that are positive real numbers can be selected. Generalized linear models (GLMs) go beyond linear mixed models, taking into account that the response variables are not of continuous scale (not normally distributed), GLMs are heteroscedastic, and there is a linear relationship between the mean of the response variable and the predictor or explanatory variables.
Generalized Linear Mixed Models for Non-normal Responses
Authors: Salinas Ruíz Josafhat , Montesinos López Osval Antonio , Hernández Ramírez Gabriela , Crossa Hiriart Jose 
Published: August 2023

AbstractGeneralized linear mixed models (GLMMs) have been recognized as one of the major methodological developments in recent years, which is evidenced by the increased use of such sophisticated statistical tools with broader applicability and flexibility. This family of models can be applied to a wide range of different data types (continuous, categorical (nominal or ordinal), percentages, and counts), and each is appropriate for a specific type of data. This modern methodology allows data to be described through a distribution of the exponential family that best fits the response variable. These complex models were not computationally possible up until recently when advances in statistical software have allowed users to apply GLMMs (Zuur et al. 2009; Stroup 2012; Zuur et al. 2013). Researchers in fields other than statistical science are also interested in modeling the structure of data. For example, in the social sciences there have been applications in the field of education when several tests are applied to students; in longitudinal personality studies when the occurrence of an emotion is repeatedly observed over time over a set of people; and in surveys to investigate the political preference of a population, among others.
Generalized Linear Mixed Models for Proportions and Percentages
Authors: Salinas Ruíz Josafhat , Montesinos López Osval Antonio , Hernández Ramírez Gabriela , Crossa Hiriart Jose 
Published: August 2023

AbstractIn this chapter, we will review generalized linear mixed models (GLMMs) whose response can be either a proportion or a percentage. For proportion and percentage data, we refer to data whose expected value is between 0 and 1 or between 0 and 100. For the remainder of this book, we will refer to this type of data only in terms of proportion, knowing that it is possible to change it to a percentage scale only when multiplying it by 100. Proportions can be classified into two types: discrete and continuous. Discrete proportions arise when the unit of observation consists of N distinct entities, of which individuals have the attribute of interest “y. ”N must be a nonnegative integer and “y” must be a positive integer; here, y ≤ N. Therefore, the observed proportion must be a discrete fraction, which can take values $$ \frac{0}{N},\frac{1}{N},\cdots, \frac{N}{N} $$

0
N

,

1
N

,
⋯
,

N
N

. A binomial distribution is the sum of a series of m independent binary trials (i.e., trials with only two possible outcomes: success or failure), where all trials have the same probability of success. For binary and binomial distributions, the target of inference is the value of the parameter such that $$ 0\le E\left(\frac{y}{N}\right)=\pi \le 1 $$
0
≤
E

y
N

=
π
≤
1
. Continuous proportions (ratios) arise when the researcher measures responses such as the fraction of the area of a leaf infested with a fungus, the proportion of damaged cloth in a square meter, the fraction of a contaminated area, and so on. As with the binomial parameter π, the continuous rates (fractions) take values between 0 and 1, but, unlike the binomial, the continuous proportions do not result from a set of Bernoulli tests. Instead, the beta distribution is most often used when the response variable is in continuous proportions. In the following sections, we will first address issues in modeling when we have binary and binomial data. When the response variable is binomial, we have the option of using a linearization method (pseudo-likelihood (PL)) or the Laplace or quadrature integral approximation (Stroup 2012).
Time of Occurrence of an Event of Interest
Authors: Salinas Ruíz Josafhat , Montesinos López Osval Antonio , Hernández Ramírez Gabriela , Crossa Hiriart Jose 
Published: August 2023

AbstractIn studies such as biological sciences, animal science, and agronomy, a common outcome of interest is the time at which an event of interest occurs. The main characteristic of these data is that the subjects/experimental units are usually observed for different periods of time until the event of interest occurs. These events of interest may be adverse events such as the death of an experimental unit and the cessation of lactation, or positive events such as the conception of a female’s offspring from a particular treatment and the onset of estrus in a female undergoing hormone treatment, among others. Because of the characteristics of these response variables, a “normal” distribution is often a poor choice for modeling the time at which the event of interest occurs. Exponential, log-normal, gamma, Weibull, and other more complex distributions that tend to be more common and are better choices for modeling these phenomena.
Generalized Linear Mixed Models for Categorical and Ordinal Responses
Authors: Salinas Ruíz Josafhat , Montesinos López Osval Antonio , Hernández Ramírez Gabriela , Crossa Hiriart Jose 
Published: August 2023

AbstractAccording to Agresti (2013), a multinomial distribution is a generalization of a binomial distribution in cases with more than two possible ordered (ordinal) or unordered (nominal) outcomes. Given a response with more than two possible outcomes and independent trials with probabilities of similar category for each trial, the distribution of counts across categories follows a multinomial distribution. Quinn and Keough (2002) believe that several methods exist for multinomial data analysis. The most common form of categorical data analysis in biological sciences, which results in frequency counts, is creating cross-tabulations or contingency tables and chi-squared tests to examine associations between two or more categorical variables. However, such an approach is ill suited for a study aimed at estimating the response when there is a change in the explanatory variable(s), as contingency tables are used to analyze the association between variables without considering a predictor or response variable. In this analysis, the results are valid as long as less than 20% of the cells have an expected count less than five and none are less than one (Logan 2010). Fisher’s exact test extends the chi-squared test in studies involving small sample sizes.
Vulnerable Households in the Energy Transition
Authors: Bardazzi Rossella , Pazienza Maria Grazia 
Published: August 2023

AbstractEnergy transitions are multi-dimensional and multi-actor processes involving technical systems, social networks and societal institutions and regimes (Sovacool and Geels, Energy Research & Social Science 22:232–237, 2016). Interactions between firms, households, policymakers and social bodies are at the core of the shift from one energy system to another. This nexus of interactions is even more important to be analysed when considering the current energy transition towards decarbonization, which is mainly policy-driven rather than social- or technology-driven.
Exact large charge in $$ \mathcal{N} $$ = 4 SYM and semiclassical string theory
Authors: Paul Hynek , Perlmutter Eric , Raj Himanshu 
Published: August 2023

Abstract
In four-dimensional $$ \mathcal{N} $$
N
= 4 super Yang-Mills theory with gauge group SU(N), we present a closed-form solution for a family of integrated four-point functions involving stress tensor multiplet composites of arbitrary R-charge. These integrated correlators are shown to be equivalent to a one-dimensional semi-infinite lattice of harmonic oscillators with nearest-neighbor interactions, evolving over the fundamental domain of SL(2, ℤ). The solution, exceptionally simple in an SL(2, ℤ)-invariant eigenbasis, is exact in the R-charge p, rank N, and complexified gauge coupling τ. This permits a systematic and non-perturbative large charge expansion for any N and τ. Especially novel is a double-scaled “gravity regime” in which p ~ N2 ≫ 1, holographically dual to a large charge regime of semiclassical type IIB string theory in AdS5 × S5. Our results in this limit provide a holographic computation of integrated semiclassical string amplitudes at arbitrary string coupling, including an emergent string scale with a large charge dressing factor. We compare to extremal correlators in superconformal QCD, for which we predict new genus expansions at large charge scaling with N.
Holography from lattice $$ \mathcal{N} $$ = 4 super Yang-Mills
Authors: Catterall Simon , Giedt Joel , Toga Goksu Can 
Published: August 2023

Abstract
In this paper we use lattice simulation to study four dimensional $$ \mathcal{N} $$
N
= 4 super Yang-Mills (SYM) theory. We have focused on the three color theory on lattices of size 124 and for ’t Hooft couplings up to λ = 40.0. Our lattice action is based on a discretization of the Marcus or GL twist of $$ \mathcal{N} $$
N
= 4 SYM and retains one exact supersymmetry for non-zero lattice spacing. We show that lattice theory exists in a single non-Abelian Coulomb phase for all ’t Hooft couplings. Furthermore the static potential we obtain from correlators of Polyakov lines is in good agreement with that obtained from holography — specifically the potential has a Coulombic form with a coefficent that varies as the square root of the ’t Hooft coupling.
A multi-channel U-Matrix model of hadron interaction at high energy
Authors: Oueslati Rami 
Published: August 2023

Abstract
The present phenomenological study investigates a multi-channel model of high-energy hadron interactions by considering a full parton configurations space and the U-matrix unitarisation scheme of the elastic amplitude, comparing it to the two-channel model, and examining the consequences of up-to-date high-energy collider data on the best fits to various hadronic observables in pp and $$ p\overline{p} $$
p

p
¯

collisions. The findings of this study reveal that the data are well-fitted with the multi-channel model and that the difference compared to the two-channel one is negligible. Of particular significance is the observation that the U-matrix unitarisation is likely incompatible with uncorrelated pomeron exchange, as suggested by the equivalence between the U-matrix multi-channel and eikonal two-channel descriptions. Based on our best fit, predictions for the ρ parameter, the double diffractive cross-section, and the elastic differential cross-section are provided. We shed light on the effect of taking into account a multi-channel model on present and future cosmic ray data.
Dual-tracer PET/CT protocol with [18F]FDG and [68Ga]Ga-FAPI-46 outperforms single-tracer PET/CT with [18F]FDG in different cancer types, resulting in larger functional and gross tumor volume
Authors: Wegen Simone , Weindler Jasmin , Voltin Conrad-Amadeus , van Heek Lutz , Schomäcker Klaus , Fischer Thomas , Marnitz Simone , Kobe Carsten , Drzezga Alexander , Roth Katrin S. 
Published: August 2023

Abstract
Purpose
Fibroblast activation protein (FAP) detected by positron-emission tomography (PET) using fibroblast activation protein inhibitor (FAPI) appears to be a promising target for cancer imaging, staging, and therapy, providing added value and strength as a complement to [18F]fluorodeoxyglucose (FDG) in cancer imaging. We recently introduced a combined single-session/dual-tracer protocol with [18F]FDG and [68Ga]Ga-FAPI for cancer imaging and staging. Malignant tissue visualization and target-to-background uptake ratios (TBRs) as well as functional tumor volume (FTV) and gross tumor volume (GTV) were assessed in the present study with single-tracer [18F]FDG PET/computed tomography (CT) and with dual-tracer [18F]FDG&[68Ga]Ga-FAPI-46 PET/CT.

Methods
A total of 19 patients with head and neck and gastrointestinal cancers received initial [18F]FDG-PET/CT followed by dual-tracer PET/CT after additional injection of [68Ga]Ga-FAPI-46 during the same medical appointment (on average 13.9 ± 12.3 min after injection of [18F]FDG). Two readers visually compared detection rate of malignant tissue, TBR, FTV, and GTV for tumor and metastatic tissue in single- and dual-tracer PET/CT.

Results
The diagnostic performance of dual-tracer compared to single-tracer PET/CT was equal in 13 patients and superior in 6 patients. The mean TBRs of tumors and metastases in dual-tracer PET/CTs were mostly higher compared to single-tracer PET/CT using maximal count rates (CRmax). GTV and FTV were significantly larger when measured on dual-tracer compared to single-tracer PET/CT.

Conclusion
Dual-tracer PET/CT with [18F]FDG and [68Ga]Ga-FAPI-46 showed better visualization due to a generally higher TBR and larger FTV and GTV compared to [18F]FDG-PET/CT in several tumor entities, suggesting that [68Ga]Ga-FAPI-46 provides added value in pretherapeutic staging.
A generalisation of the aggregate association index (AAI): incorporating a linear transformation of the cells of a 2 × 2 table
Authors: Beh Eric J. , Tran Duy , Hudson Irene L. 
Published: August 2023

AbstractThe analysis of aggregate, or marginal, data for contingency tables is an increasingly important area of statistics, applied sciences and the social sciences. This is largely due to confidentiality issues arising from the imposition of government and corporate protection and data collection methods. The availability of only aggregate data makes it difficult to draw conclusions about the association between categorical variables at the individual level. For data analysts, this issue is of growing concern, especially for those dealing with the aggregate analysis of a single 2 × 2 table or stratified 2 × 2 tables and lies in the field of ecological inference. As an alternative to ecological inference techniques, one may consider the aggregate association index (AAI) to obtain valuable information about the magnitude and direction of the association between two categorical variables of a single 2 × 2 table or stratified 2 × 2 tables given only the marginal totals. Conventionally, the AAI has been examined by considering $${\mathrm{p}}_{11}$$

p
11

—the proportion of the sample that lies in the (1, 1)th cell of a given 2 × 2 table. However, the AAI can be expanded for other association indices. Therefore, a new generalisation of the original AAI is given here by reformulating and expanding the index so that it incorporates any linear transformation of $${\mathrm{p}}_{11}$$

p
11

. This study shall consider the consistency of the AAI under the transformation by examining four classic association indices, namely the independence ratio, Pearson’s ratio, standardised residual and adjusted standardised residual, although others may be incorporated into this general framework. We will show how these indices can be utilised to examine the strength and direction of association given only the marginal totals. Therefore, this work enhances our understanding of the AAI and establishes its links with common association indices.
Complications 8 weeks after an obstetric second-degree perineal laceration in relation to body mass index
Authors: Otterheim Maria , Hjertberg Linda , Pihl Sofia , Uustal Eva , Blomberg Marie 
Published: August 2023

Abstract
Introduction and hypothesis
How body mass index (BMI) affects pelvic floor function after a second-degree perineal laceration is unknown. The hypothesis of this study is that pelvic floor dysfunction and complications after an obstetric second-degree perineal laceration are more common in women with a higher BMI 8 weeks postpartum.

Methods
This register-based cohort study includes 10,876 primiparous women with an obstetric second-degree perineal laceration between 2014 and 2021. Data were retrieved from the Swedish Perineal Laceration Registry. Outcomes in relation to maternal BMI were urinary incontinence (UI), anal incontinence (AI) and common complications attributable to the laceration. Uni- and multivariate logistic regressions were used for comparison between normal weight (BMI < 24.9, reference), overweight (25.0–29.9) and obese (≥ 30) women.

Results
Multivariate analyses showed an increased risk for UI in both overweight and obese women compared to normal-weight women 8 weeks after a second-degree perineal laceration with an adjusted odds ratio (aOR) of 1.21 (CI 1.02–1.44) and 1.27 (CI 1.13–1.58) respectively. Overweight and obese women had a decreased risk for AI (aOR 0.81, CI 0.68–0.96; aOR 0.72, CI 0.57–0.90 respectively) compared with normal-weight women. No significant differences were found in the univariate analyses over BMI strata concerning complications after perineal laceration.

Conclusions
Primiparous overweight and obese women report less AI and more UI than normal-weight women 8 weeks after a second-degree perineal laceration. No differences were found regarding complications. These findings are new and merit further study to find potential preventive factors and interventions after a second-degree perineal laceration.
Continuous home cage monitoring of activity and sleep in mice during repeated paroxetine treatment and discontinuation
Authors: Collins Helen M. , Pinacho Raquel , Tam S. K. Eric , Sharp Trevor , Bannerman David M. , Peirson Stuart N. 
Published: August 2023

Abstract
Rationale
Non-invasive home cage monitoring is emerging as a valuable tool to assess the effects of experimental interventions on mouse behaviour. A field in which these techniques may prove useful is the study of repeated selective serotonin reuptake inhibitor (SSRI) treatment and discontinuation. SSRI discontinuation syndrome is an under-researched condition that includes the emergence of sleep disturbances following treatment cessation.

Objectives
We used passive infrared (PIR) monitoring to investigate changes in activity, sleep, and circadian rhythms during repeated treatment with the SSRI paroxetine and its discontinuation in mice.

Methods
Male mice received paroxetine (10 mg/kg/day, s.c.) for 12 days, then were swapped to saline injections for a 13 day discontinuation period and compared to mice that received saline injections throughout. Mice were continuously tracked using the Continuous Open Mouse Phenotyping of Activity and Sleep Status (COMPASS) system.

Results
Repeated paroxetine treatment reduced activity and increased behaviourally-defined sleep in the dark phase. These effects recovered to saline-control levels within 24 h of paroxetine cessation, yet there was also evidence of a lengthening of sleep bouts in the dark phase for up to a week following discontinuation.

Conclusions
This study provides the first example of how continuous non-invasive home cage monitoring can be used to detect objective behavioural changes in activity and sleep during and after drug treatment in mice. These data suggest that effects of paroxetine administration reversed soon after its discontinuation but identified an emergent change in sleep bout duration, which could be used as a biomarker in future preclinical studies to prevent or minimise SSRI discontinuation symptoms.