bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Free Trade Fantasy
Authors: Lopes Carlos 
Published: July 2024

AbstractFree trade is fêted as a cornerstone of a competitive economy, essential to build prosperous nations and create socioeconomic benefits. But in Africa, this has not been a universal experience. Far from integrating African economies into the world economy, free trade appears to have cemented Africa’s marginalisation. This is largely because trade agreements have been systematically used to impose norms, standards, and preferences that perpetuate extractive colonial structures and create a dependency on external trade partners for processed products.This chapter provides a background to and overview of the trade agreements that have shaped African trade, including a deep dive on EPAs, which brought about a sea change in how Africa engaged with its largest trading partner, the EU. We also highlight the EU’s conflicting involvement with the AfCFTA process and how this is influencing Africa’s positioning on trade issues as the AU attempts to redefine its trade relationships in a way that prioritises African interests, aligns with continental goals, and contributes to sustainable development.
Collaborative Workshop for Women in Mathematical Biology: Mathematical Modeling for Women’s Health
Authors: Ford Versypt Ashlee N. , Segal Rebecca A. , Sindi Suzanne S. 
Published: July 2024

AbstractDespite advances in health care, women continue to have disparate outcomes. Women experience higher morbidity and mortality especially with regard to cancer, cardiovascular disease, and recently COVID-19. Reproductive health and maternity are also a continued source of health risk. Collaborative teams were formed during a workshop to study topics relevant to women’s health using mathematical modeling. Here, the workshop is described, and research topics are introduced.
Introduction: Europarties—Ubiquitous Yet Rarely Noticed
Authors: Johansson Karl Magnus , Raunio Tapio 
Published: July 2024

AbstractEuroparties, parties operating at the European level, are ever-present in EU governance, yet their impact is often indirect and difficult to measure. This chapter reviews existing literature on Europarties and explains their relevance in EU policymaking. The starting point of this book is that European integration cannot be understood without accounting for the impact of the Europarties. It identifies Europarties as transnational partisan actors that operate both at intergovernmental and supranational levels of EU decision-making. Europarties have consolidated their own organizational structures and have over the decades built their own networks and coalitions that enable them to wield influence in ways not captured by previous studies.
Extending the Comparative Argumentative Machine: Multilingualism and Stance Detection
Authors: Nikishina Irina , Bondarenko Alexander , Zaczek Sebastian , Haag Onno Lander , Hagen Matthias , Biemann Chris 
Published: July 2024

AbstractThe comparative argumentative machine CAM can retrieve arguments that answer comparative questions—questions that ask which of several to-be-compared options should be favored in some scenario. In this paper, we describe how we equipped CAM with a better answer stance detection (i.e., a better detection of which option “wins” a comparison) and with system variants to support non-English requests. As for the improved answer stance detection, we develop RoBERTa-based approaches and experimentally show them to be more effective than previous feature-based and LLM-based stance detectors. As for the multilingualism, in a proof of concept, we compare two approaches to support Russian requests and answers: (1) translating the original English CAM data and (2) using an existing replica of CAM on native Russian data. Comparing the translation-based and the replica-based CAM variants in a user study shows that combining their answers seems to be the most promising. For individual questions, the retrieved arguments of the two variants are often different and of quite diverse relevance and quality. As a demonstrator, we deploy a first multilingual CAM version that combines translation-based and replica-based outputs for English and Russian and that can easily be extended to further languages.
Objective Argument Summarization in Search
Authors: Ziegenbein Timon , Syed Shahbaz , Potthast Martin , Wachsmuth Henning 
Published: July 2024

AbstractDecision-making and opinion formation are influenced by arguments from various online sources, including social media, web publishers, and, not least, the search engines used to retrieve them. However, many, if not most, arguments on the web are informal, especially in online discussions or on personal pages. They can be long and unstructured, subjective and emotional, and contain inappropriate language. This makes it difficult to find relevant arguments efficiently. We hypothesize that, on search engine results pages, “objective snippets” of arguments are better suited than the commonly used extractive snippets and develop corresponding methods for two important tasks:snippet generationandneutralization. For each of these tasks, we investigate two approaches based on (1) prompt engineering for large language models (LLMs), and (2) supervised models trained on existing datasets. We find that a supervised summarization model outperforms zero-shot summarization with LLMs for snippet generation. For neutralization, using reinforcement learning to align an LLM with human preferences for suitable arguments leads to the best results. Both tasks are complementary, and their combination leads to the best snippets of arguments according to automatic and human evaluation.
On the D5-brane description of $$ \frac{1}{4} $$-BPS Wilson loops in $$ \mathcal{N} $$ = 4 super Yang-Mills theory
Authors: Faraggi Alberto , Moreno Cristóbal 
Published: July 2024

Abstract
We construct the probe D5-brane solution in AdS5 × S5 dual to the $$ \frac{1}{4} $$

1
4

-BPS latitude Wilson loop in $$ \mathcal{N} $$
N
= 4 super Yang-Mills theory in the k-antisymmetric representation of SU(N). The solution is exact in the latitude parameter θ0 and correctly reproduces the $$ \frac{1}{2} $$

1
2

-BPS limit. We compute the string charge k and the renormalized on-shell action perturbatively to order $$ \mathcal{O}\left({\theta}_0^{10}\right) $$
O

θ
0
10

and find full agreement with the expectation value of the Wilson loop predicted by the Gaussian matrix model in the limit N ∼ k → ∞, λ → ∞.
Celestial leaf amplitudes
Authors: Melton Walker , Sharma Atul , Strominger Andrew 
Published: July 2024

Abstract
Celestial amplitudes may be decomposed as weighted integrals of AdS3-Witten diagrams associated to each leaf of a hyperbolic foliation of spacetime. We show, for the Kleinian three-point MHV amplitude, that each leaf subamplitude is smooth except for the expected light-cone singularities. Moreover, we find that the full translationally-invariant celestial amplitude is simply the residue of the pole in the leaf amplitude at the point where the total conformal weights of the gluons equals three. This full celestial amplitude vanishes up to light-cone contact terms, as required by spacetime translation invariance, and reduces to the expression previously derived by Mellin transformation of the Parke-Taylor formula.
Searching for axion forces with spin precession in atoms and molecules
Authors: Agrawal Prateek , Hutzler Nicholas R. , Kaplan David E. , Rajendran Surjeet , Reig Mario 
Published: July 2024

Abstract
We propose to use atoms and molecules as quantum sensors of axion-mediated monopole-dipole forces. We show that electron spin precession experiments using atomic and molecular beams are well-suited for axion searches thanks to the presence of co-magnetometer states and single-shot temporal resolution. Experimental strategies to detect axion gradients from localised sources and the earth are presented, taking ACME III as a prototype example. Other possibilities including atomic beams, and laser-cooled atoms and molecules are discussed.
Variety Evasive Subspace Families
Authors: Guo Zeyu 
Published: July 2024

AbstractWe introduce the problem of constructing explicit variety evasive subspace families.
Given a family $$\mathcal{F}$$
F
of subvarieties of a projective or affine space, a collection $$\mathcal{H}$$
H
of projective or affine $$k$$
k
-subspaces is $$(\mathcal{F},\epsilon)$$

(
F
,
ϵ
)

-evasive if
for every $$\mathcal{V}\in\mathcal{F}$$

V
∈
F

, all but at most $$\epsilon$$
ϵ
-fraction of $$W\in\mathcal{H}$$

W
∈
H

intersect every irreducible component of $$\mathcal{V}$$
V
with (at most) the expected dimension.
The problem of constructing such an explicit subspace family generalizes both deterministic black-box polynomial identity testing (PIT) and the problem of constructing explicit (weak) lossless rank condensers.Using Chow forms, we construct explicit $$k$$
k
-subspace families of polynomial size that are evasive for all varieties of bounded degree in a projective or affine $$n$$
n
-space. As one application, we obtain a complete derandomization of Noether’s normalization lemma for varieties of low degree in a projective or affine $$n$$
n
-space. In another application, we obtain a simple polynomial-time black-box PIT algorithm for depth-4 arithmetic circuits with bounded top fan-in and bottom fan-in that are not in the Sylvester–Gallai configuration, improving and simplifying a result of Gupta (ECCC TR 14-130).As a complement of our explicit construction, we prove a tight lower bound for the size of $$k$$
k
-subspace families that are evasive for degree-$$d$$
d
varieties in a projective $$n$$
n
-space. When $$n-k=n^{\Omega(1)}$$

n
-
k
=

n

Ω
(
1
)

, the lower bound is superpolynomial unless $$d$$
d
is bounded.
The proof uses a dimension counting argument on Chow varieties that parametrize projective subvarieties.
Prediction model for leaflet thrombosis in patients undergoing transcatheter aortic valve implantation: the EFFORT study
Authors: Steiner-Gager Gloria M. , Rogozarski Jovan , Kronberger Christina , Dizdarevic Al Medina , Quehenberger Peter , Schernthaner Ruediger , Loewe Christian , Reider Lukas , Strassl Andreas , Kovacevic Miljevic Katarina , Jilma Bernd , Ay Cihan , Königsbrügge Oliver , Postula Marek , Hengstenberg Christian , Siller-Matula Jolanta M. 
Published: July 2024

Abstract
Background
Leaflet thrombosis (LT) is a multifaceted and underexplored condition that can manifest following transcatheter aortic valve implantation (TAVI). The objective of this study was to formulate a prediction model based on laboratory assessments and clinical parameters, providing additional guidance and insight into this relatively unexplored aspect of post-TAVI complications.

Methods
The present study was an observational prospective hypothesis-generating study, including 101 patients who underwent TAVI and a screening for LT (the primary endpoint) by multidetector computed tomography (MDCT). All images were acquired on a third-generation dual-source CT system. Levels of von Willebrand factor (vWF) activity, hemoglobin (Hb), and lactate dehydrogenase (LDH) were measured among other parameters. A predictive score utilizing binary logistic regression, Kaplan–Meier time-to-event analysis, and receiver operating characteristics (ROC) analysis was established.

Results
LT (11 subclinical and 2 clinical) was detected in 13 of 101 patients (13%) after a median time to screening by MDCT of 105 days (IQR, 98–129 days). Elevated levels of vWF activity (> 188%) pre-TAVI, decreased Hb values (< 11.9 g/dL), as well as increased levels of LDH (> 312 U/L) post-TAVI and absence of oral anticoagulation (OAC) were found in patients with subsequent LT formation as compared to patients without LT. The established EFFORT score ranged from − 1 to 3 points, with an increased probability for LT development in patients with ≥ 2 points (85.7% of LT cases) vs < 2 points (14.3% of LT cases; p < 0.001). Achieving an EFFORT score of ≥ 2 points was found to be significantly associated with a 10.8 times higher likelihood of developing an LT (p = 0.001). The EFFORT score has an excellent c-statistic (area under the curve (AUC) = 0.89; 95% CI 0.74–1.00; p = 0.001) and a high negative predictive value (98%).

Conclusion
An EFFORT score might be a helpful tool to predict LT development and could be used in risk assessment, if validated in confirmatory studies. Therefore, the score has the potential to guide the stratification of individuals for the planning of subsequent MDCT screenings.

Graphical abstract
Central illustration. Created with BioRender.com
TRF1 and TRF2: pioneering targets in telomere-based cancer therapy
Authors: Kallingal Anoop , Krzemieniecki Radosław , Maciejewska Natalia , Brankiewicz-Kopcińska Wioletta , Baginski Maciej 
Published: July 2024

AbstractThis article presents an in-depth exploration of the roles of Telomere Repeat-binding Factors 1 and 2 (TRF1 and TRF2), and the shelterin complex, in the context of cancer biology. It emphasizes their emerging significance as potential biomarkers and targets for therapeutic intervention. Central to the shelterin complex, TRF1 and TRF2 are crucial in maintaining telomere integrity and genomic stability, their dysregulation often being a hallmark of cancerous cells. The article delves into the diagnostic and prognostic capabilities of TRF1 and TRF2 across various cancer types, highlighting their sensitivity and specificity. Furthermore, it reviews current strides in drug discovery targeting the shelterin complex, detailing specific compounds and their modes of action. The review candidly addresses the challenges in developing therapies aimed at the shelterin complex, including drug resistance, off-target effects, and issues in drug delivery. By synthesizing recent research findings, the article sheds light on the intricate relationship between telomere biology and cancer development. It underscores the urgency for continued research to navigate the existing challenges and fully leverage the therapeutic potential of TRF1, TRF2, and the shelterin complex in the realm of cancer treatment.
Consequences of age and education correction of cognitive screening tests – A simulation study of the MoCA test in Italy
Authors: Wischmann Hans-Aloys , Logroscino Giancarlo , Kurth Tobias , Piccininni Marco 
Published: July 2024

Abstract
Background
Cognitive screening tools are widely used in clinical practice to screen for age-related cognitive impairment and dementia. These tools' test scores are known to be influenced by age and education, leading to routine correction of raw scores for these factors. Despite these corrections being common practice, there is evidence suggesting that corrected scores may perform worse in terms of discrimination than raw scores.

Objective
To address the ongoing debate in the field of dementia research, we assessed the impact of the corrections on discrimination, specificity, and sensitivity of the Montreal Cognitive Assessment test in Italy, both for the overall population and across age and education strata.

Methodology
We created a realistic model of the resident population in Italy in terms of age, education, cognitive impairment and test scores, and performed a simulation study.

Results
We confirmed that the discrimination performance was higher for raw scores than for corrected scores in discriminating patients with cognitive impairment from individuals without (areas under the curve of 0.947 and 0.923 respectively). With thresholds determined on the overall population, raw scores showed higher sensitivities for higher-risk age-education groups and higher specificities for lower-risk groups. Conversely, corrected scores showed uniform sensitivity and specificity across demographic strata, and thus better performance for certain age-education groups.

Conclusion
Raw and corrected scores show different performances due to the underlying causal relationships between the variables. Each approach has advantages and disadvantages, the optimal choice between raw and corrected scores depends on the aims and preferences of practitioners and policymakers.
Overview of microbial communities in the surface water of the Seine River to understand their response to climate change and human activities
Authors: Bagagnan Sadia , Guerin-Rechdaoui Sabrina , Marconi Anthony , Rocher Vincent , Giusti-Miller Stéphanie , Moilleron Régis , Jusselme My Dung 
Published: July 2024

AbstractDiverse microbial communities play a crucial role in maintaining the proper functioning of river ecosystems and are considered important indicators of river water quality. Although the Seine River being heavily impacted by human activities, little is known about the microbial communities in its surface waters. In order to monitor water quality and promote sustainable use, we studied its microbial diversity using high-throughput sequencing technology, and explored their relationships with physico-chemical properties. The dominant phyla identified were Proteobacteria, Actinobacteriota, Bacteriodota, and Cyanobacteria. The presence of the Alphaproteobacteria and Gammaproteobacteria indicates that the Seine River water nutrient profile is mainly determined by the recalcitrant organic compounds present in WWTP effluents. Bacterial diversity showed significant temporal variability with a highly significant difference in bacterial composition between 2020 and 2021, probably due to variations in water flow favoring Cyanobacteria growth. Summer displayed higher microbial activity and abundance than autumn, attributed to temperature and orthophosphate content. Spatial variation in bacterial composition was observed between sites upstream and downstream of Paris, as well as before and after of the Seine Valenton-WWTP, subject to an accumulation phenomenon and impacted by wastewater treatment. Further assessment of emerging contaminants and other pollutants is required to better understand these variations. These results provide a basic understanding of the microbial community in the Seine River, serving as a reference for assessing the impact of implementing new wastewater disinfection techniques in the near future.
Graphical abstract
A Pilot Randomized Control Trial of the Striving Towards EmPowerment and Medication Adherence (STEP-AD) Intervention for Black Women Living with HIV
Authors: Dale Sannisha K. , Wright Ian A. , Madhu Aarti , Reid Rachelle , Shahid Naysha N. , Wright Mya , Sanders Jasmyn , Phillips Arnetta , Rodriguez Allan , Safren Steven A. 
Published: July 2024

AbstractBlack women living with HIV (BWLWH) face adversities associated with lower HIV medication adherence, viral non-suppression, and mental health symptoms (e.g., post-traumatic stress disorder) such as trauma/violence, racism, HIV-related discrimination/stigma, and gender-related stressors. We developed the first intervention based in cognitive behavioral therapy and culturally congruent coping for BWLWH to increase medication adherence and decrease PTSD symptoms by enhancing resilience, self-care, engagement in care, and coping for trauma, racism, HIV-related discrimination/stigma, and gender-related stressors. A pilot randomized control trial was conducted with BWLWH and histories of trauma who were at risk for their HIV viral load remaining or becoming detectable (i.e., below 80% medication adherence, detectable viral load in the past year, and/or missed HIV-related appointments). 119 BWLWH were assessed at baseline and 70 met inclusion criteria, completed one session of Life-Steps adherence counseling, and were randomized to either nine sessions of STEP-AD (Striving Towards EmPowerment and Medication Adherence) or ETAU (enhanced treatment as usual consisting of biweekly check-ins). Women completed a post intervention follow up assessment (3 months post baseline) and 3-month post intervention follow-up (6 months post baseline). Via STATA the difference-in-difference methodology with mixed models compared STEP-AD to ETAU on changes in outcomes over time. BWLWH in STEP-AD compared to E-TAU had significantly higher ART adherence (estimate = 9.36 p = 0.045) and lower likelihood of being clinically diagnosed with PTSD (OR = .07, estimate = − 2.66, p = 0.03) as well as borderline significance on higher CD4 count (estimate = 161.26, p = 0.05). Our findings suggest preliminary efficacy of STEP-AD in improving ART adherence, mental health, and immune function.
Federated learning for biometric recognition: a survey
Authors: Guo Jian , Mu Hengyu , Liu Xingli , Ren Hengyi , Han Chong 
Published: July 2024

AbstractRecently, deep learning (DL) has achieved great success in biometric recognition. The application of DL has also led to a high demand for biometric data. However, as people attach more importance to privacy protection, biometric data have become increasingly difficult to obtain and access, leading to significant limitations in the development and application of DL-based biometric recognition. Federated learning (FL), a distributed learning technique with privacy protection, provides a potential solution to this problem. Several researchers have attempted to integrate FL into biometric recognition. These studies have shown that the introduction of FL not only solves the conflict between privacy and accessibility of biometric data but also improves the accuracy and generalizability of local recognition systems. Therefore, the combination of FL and biometric recognition techniques has become a new research hotspot. In this survey, we comprehensively review the latest advances regarding the application of FL to biometric recognition, biometric presentation attack detection and the related fields to provide new researchers with a quick and systematic overview of this emerging cross-disciplinary field. This paper also summarizes the future opportunities and challenges of this field. To our knowledge, this is the first survey that systematically organizes and analyses federated biometric recognition and related fields to provide suggestions and references for future research.
Fire Identification Based on Novel Dense Generative Adversarial Networks
Authors: Shawly Tawfeeq , Alsheikhy Ahmed A. 
Published: July 2024

AbstractIncreasing death rates, damage to properties, and loss of trees can be caused by fires. In Australia and the United States of America, many fire incidents are reported annually. Due to that, both governments struggle from the devastation beyond plants, buildings, and infrastructure. A lot of people have lost their properties and land. Various innovations in fire detection technologies have been implemented to minimize the impacts of fires on the economy and lives. Some of these solutions are costly, while others lack accuracy. In this article, a novel deep-learning model to detect fires is presented. This model is based on new Novel Dense Generative Adversarial Networks (NDGANs) and image preprocessing technologies for fire detection through a continuous monitoring system. This system produces alarms if a fire or smoke is detected. The proposed approach was trained and tested on five datasets. This system was evaluated using four performance quantities, which are accuracy, sensitivity, dice, and F-score, and attained 98.87%, 97.64%, 98.82%, and 98.69% for the considered quantities, respectively. In addition, the proposed method was compared with other developed approaches and outperformed these methods. The presented New Dense Generative Adversarial Networks technology is useful in fire detection as shown from the conducted simulation experiments on MATLAB.