bluuebunny/crossref_metadata_2025_split huggingface dataset:
Primary observables for indirect searches at colliders
Authors: Chang Spencer , Chen Miranda , Liu Da , Luty Markus A. 
Published: July 2023

Abstract
We consider the complete set of observables for collider searches for indirect effects of new heavy physics. They consist of SU(3)C × U(1)EM invariant interaction terms/operators that parameterize deviations from the Standard Model. We show that, under very general assumptions, the leading deviations from the Standard Model are given by a finite number of ‘primary’ operators, with the remaining operators given by ‘Mandelstam descendants’ whose effects are suppressed by powers of Mandelstam variables divided by the mass scale M of the heavy physics. We explicitly determine all 3 and 4-point primary operators relevant for Higgs signals at colliders by using the correspondence between on-shell amplitudes and independent operators. We give a detailed discussion of the methods used to obtain this result, including a new analytical method for determining the independent operators. The results are checked using the Hilbert series that counts independent operators. We also give a rough sketch of the phenomenology, including unitarity bounds on the interaction strengths and rough estimates of their importance for Higgs decays at the HL-LHC. These results motivate further exploration of Higgs decays to $$ Z\overline{f}f $$
Z

f
¯

f
, $$ W\overline{f}{f}^{\prime } $$
W

f
¯

f
′

, $$ \gamma \overline{f}f $$
γ

f
¯

f
, and Zγγ.
Late time behavior of n-point spectral form factors in Airy and JT gravities
Authors: Anegawa Takanori , Iizuka Norihiro , Okuyama Kazumi , Sakai Kazuhiro 
Published: July 2023

Abstract
We study the late time behavior of n-point spectral form factors (SFFs) in two-dimensional Witten-Kontsevich topological gravity, which includes both Airy and JT gravities as special cases. This is conducted in the small ħ expansion, where $$ \hbar \sim {e}^{-1/{G}_{\textrm{N}}} $$
ħ
∼

e

−
1
/

G
N

is the genus counting parameter and nonperturbative in Newton’s constant GN. For one-point SFF, we study its absolute square at two different late times. We show that it decays by power law at t ~ ħ−2/3 while it decays exponentially at t ~ ħ−1 due to the higher order corrections in ħ. We also study general n(≥2)-point SFFs at t ~ ħ−1 in the leading order of the ħ expansion. We find that they are characterized by a single function, which is essentially the connected two-point SFF and is determined by the classical eigenvalue density ρ0(E) of the dual matrix integral. These studies suggest that qualitative behaviors of n-point SFFs are similar in both Airy and JT gravities, where our analysis in the former case is based on exact results.
Holographic composite Higgs model building: soft breaking, maximal symmetry, and the Higgs mass
Authors: Blasi Simone , Bollig Julian , Goertz Florian 
Published: July 2023

Abstract
We study the emergence and phenomenological consequences of recently proposed new structures, namely soft breaking of the Higgs shift symmetry and ‘maximal symmetry’ of the composite sector, in holographic realizations of composite Higgs models. For the former, we show that soft breaking can also successfully be implemented in a full 5D warped model, where symmetry-restoring universal boundary conditions for the fermion fields allow to break the problematic connection between a realistically light Higgs and anomalously light top partners. For the latter, we demonstrate that the minimal incarnation of maximal symmetry in the holographic dual leads to a sharp prediction of mh≈ 197 GeV for f = 800 GeV. However, a viable implementation is possible with sizable negative gauge brane kinetic terms, allowing for the observed mh = 125 GeV. Overall, both approaches offer promising directions to improve the naturalness also of holographic realizations of composite Higgs models.
A duality in string theory on AdS3
Authors: Halder Indranil , Jafferis Daniel Louis , Kolchmeyer David K. 
Published: July 2023

Abstract
We consider bosonic string theory on AdS3 supported by Kalb-Ramond flux. It is well known that the α′ exact worldsheet theory is described by the SL(2,R) WZW model. In this note we perform checks of an α′ exact dual description proposed in [arXiv:2104.07233] involving a winding condensate on a free theory background. We give the explicit map of vertex operators for normalizable states on both sides of the duality and demonstrate the equivalence of their two and three point functions by direct computation. The duality is of strong-weak nature in α′.
Non-Alcoholic Fatty Liver Disease (NAFLD) and risk of new-onset heart failure: a retrospective analysis of 173,966 patients
Authors: Roderburg Christoph , Krieg Sarah , Krieg Andreas , Vaghiri Sascha , Mohr Raphael , Konrad Marcel , Luedde Mark , Luedde Tom , Kostev Karel , Loosen Sven H. 
Published: July 2023

Abstract
Background
Non-alcoholic fatty liver disease (NAFLD) represents the leading cause of chronic liver disease. Its high mortality and morbidity are mainly caused by non-hepatic comorbidities and their clinical complications. Accumulating evidence suggests an association between NAFLD and heart failure (HF), but large-scale data analyses from Germany are scarce.

Methods
Using the Disease Analyzer database (IQVIA), this analysis retrospectively evaluated two cohorts of outpatients with and without NAFLD with respect to the cumulative incidence of HF as the primary outcome between January 2005 and December 2020. Cohorts were propensity score matched for sex, age, index year, yearly consultation frequency, and known risk factors for HF.

Results
A total of 173,966 patients were included in the analysis. Within 10 years of the index date, 13.2% vs. 10.0% of patients with and without NAFLD were newly diagnosed with HF (p < 0.001). This finding was supported by univariate Cox regression analysis in which NAFLD was found to be significantly associated with subsequent HF (Hazard Ratio (HR) 1.34, 95% Confidence Interval (CI) 1.28–1.39, p < 0.001). The association between NAFLD and HF was observed across all analysed age groups and as comparable between both men (HR 1.30, 95% CI 1.23–1.38; p < 0.001) and women (HR: 1.37, 95% CI 1.29–1.45; p < 0.001).

Conclusion
NAFLD is significantly associated with an increased cumulative incidence of HF, which, given its rapidly increasing global prevalence, could be crucial to further reduce its high mortality and morbidity. We recommend risk stratification within a multidisciplinary approach for NAFLD patients, including systematic prevention or early detection strategies for HF.
Correction to: Beating the market? A mathematical puzzle for market efficiency
Authors: Baumann Michael Heinrich 
Published: July 2023

AbstractIn this note, we point out a missing assumption for ‘Michael Heinrich Baumann, Beating the market? A mathematical puzzle for market efficiency, Decis Econ Finance 45: 279–325, 2022.’ In detail, we have to assume the (almost sure) survival of the controllers. Further, we discuss this assumption concerning relevance for theory and implementations and how it may alter the results and we give directions for future research.
Do Barn Swallow nestlings incur an oxidative cost of begging?
Authors: Fuertes-Recuero Manuel , Cantarero Alejandro , Redondo Alberto J. , Sánchez-Sánchez Nuria , Redondo Tomás 
Published: July 2023

AbstractSome theoretical models predict that nestling begging must be a costly activity to transmit reliable information to parents about offspring hunger. One candidate cost is oxidative stress, which could impair growth or immune function. This hypothesis predicts that nestlings in a poor oxidative status should pay higher costs for a given amount of begging, hence beg at lower rates for a similar degree of hunger. To test this prediction, we experimentally induced a transient alteration of the oxidative status of Barn Swallow (Hirundo rustica) nestlings by administering them either a single dose of a pro-oxidant substance (BSO) or an antioxidant (vitamin E), and recorded their begging behaviour. Chicks treated with vitamin E increased their begging rates in the hours following treatment. However, and contrary to prediction, BSO nestlings did not decrease begging compared to controls. These inconsistent results are difficult to explain by the hypothesis that begging performance is mediated by the oxidative status of nestlings because chicks with an impaired oxidative status (the BSO group) begged the same as controls. Alternatively, vitamin E may alleviate the inhibitory effects on begging of stress responses mediated by glucocorticoids. This study suggests that oxidative costs of begging are minor or absent in this species. Future studies should consider alternative explanations for an association between oxidative status, antioxidant supplementation and begging behaviour, particularly those involving glucocorticoids.
3D-Ultrasound Based Mechanical and Geometrical Analysis of Abdominal Aortic Aneurysms and Relationship to Growth
Authors: Maas Esther Jorien , Nievergeld Arjet Helena Margaretha , Fonken Judith Helena Cornelia , Thirugnanasambandam Mirunalini , van Sambeek Marc Rodolph Henricus Maria , Lopata Richard Godfried Paulus 
Published: July 2023

Abstract
The heterogeneity of progression of abdominal aortic aneurysms (AAAs) is not well understood. This study investigates which geometrical and mechanical factors, determined using time-resolved 3D ultrasound (3D + t US), correlate with increased growth of the aneurysm. The AAA diameter, volume, wall curvature, distensibility, and compliance in the maximal diameter region were determined automatically from 3D + t echograms of 167 patients. Due to limitations in the field-of-view and visibility of aortic pulsation, measurements of the volume, compliance of a 60 mm long region and the distensibility were possible for 78, 67, and 122 patients, respectively. Validation of the geometrical parameters with CT showed high similarity, with a median similarity index of 0.92 and root-mean-square error (RMSE) of diameters of 3.5 mm. Investigation of Spearman correlation between parameters showed that the elasticity of the aneurysms decreases slightly with diameter (p = 0.034) and decreases significantly with mean arterial pressure (p < 0.0001). The growth of a AAA is significantly related to its diameter, volume, compliance, and surface curvature (p < 0.002). Investigation of a linear growth model showed that compliance is the best predictor for upcoming AAA growth (RMSE 1.70 mm/year). To conclude, mechanical and geometrical parameters of the maximally dilated region of AAAs can automatically and accurately be determined from 3D + t echograms. With this, a prediction can be made about the upcoming AAA growth. This is a step towards more patient-specific characterization of AAAs, leading to better predictability of the progression of the disease and, eventually, improved clinical decision making about the treatment of AAAs.
Feature engineering of EEG applied to mental disorders: a systematic mapping study
Authors: García-Ponsoda Sandra , García-Carrasco Jorge , Teruel Miguel A. , Maté Alejandro , Trujillo Juan 
Published: July 2023

AbstractAround a third of the total population of Europe suffers from mental disorders. The use of electroencephalography (EEG) together with Machine Learning (ML) algorithms to diagnose mental disorders has recently been shown to be a prominent research area, as exposed by several reviews focused on the field. Nevertheless, previous to the application of ML algorithms, EEG data should be correctly preprocessed and prepared via Feature Engineering (FE). In fact, the choice of FE techniques can make the difference between an unusable ML model and a simple, effective model. In other words, it can be said that FE is crucial, especially when using complex, non-stationary data such as EEG. To this aim, in this paper we present a Systematic Mapping Study (SMS) focused on FE from EEG data used to identify mental disorders. Our SMS covers more than 900 papers, making it one of the most comprehensive to date, to the best of our knowledge. We gathered the mental disorder addressed, all the FE techniques used, and the Artificial Intelligence (AI) algorithm applied for classification from each paper. Our main contributions are: (i) we offer a starting point for new researchers on these topics, (ii) we extract the most used FE techniques to classify mental disorders, (iii) we show several graphical distributions of all used techniques, and (iv) we provide critical conclusions for detecting mental disorders. To provide a better overview of existing techniques, the FE process is divided into three parts: (i) signal transformation, (ii) feature extraction, and (iii) feature selection. Moreover, we classify and analyze the distribution of existing papers according to the mental disorder they treat, the FE processes used, and the ML techniques applied. As a result, we provide a valuable reference for the scientific community to identify which techniques have been proven and tested and where the gaps are located in the current state of the art.Graphical Abstract
Integrating short-term stochastic production planning updating with mining fleet management in industrial mining complexes: an actor-critic reinforcement learning approach
Authors: de Carvalho Joao Pedro , Dimitrakopoulos Roussos 
Published: July 2023

AbstractShort-term production planning in industrial mining complexes involves defining daily, weekly or monthly decisions that aim to achieve production targets established by long-term planning. Operational requirements must be considered when defining fleet allocation and production scheduling decisions. Thus, this paper presents an actor-critic reinforcement learning (RL) method to make mining equipment allocation and production scheduling decisions that maximize the profitability of a mining operation. Two RL agents are proposed. The first agent allocates shovels to mining fronts by considering some operational requirements. The second agent defines the processing destination and the number of trucks required for transportation. A simulator of mining complex operations is proposed to forecast the material flow from the mining fronts to the destinations. This simulator provides new states and rewards to the RL agents, so shovel allocation and production scheduling decisions can be improved. Additionally, as the mining complex operates, sensors collect ore quality data, which are used to update the uncertainty associated with the orebody models. The improvement in material supply characterization allows the RL agents to make more informed decisions. A case study applied at a copper mining complex highlights the method’s ability to make informed decisions while collecting new data. The results show a 47% improvement in cash flow by adapting the shovel and truck allocation and material destination compared to a base case with predefined fleet assignments.
Comprehensive analysis of mitochondrial dysfunction and necroptosis in intracranial aneurysms from the perspective of predictive, preventative, and personalized medicine
Authors: Chen Bo , Xie Kang , Zhang Jianzhong , Yang Liting , Zhou Hongshu , Zhang Liyang , Peng Renjun 
Published: July 2023

AbstractMitochondrial dysfunction and necroptosis are closely associated, and play vital roles in the medical strategy of multiple cardiovascular diseases. However, their implications in intracranial aneurysms (IAs) remain unclear. In this study, we aimed to explore whether mitochondrial dysfunction and necroptosis could be identified as valuable starting points for predictive, preventive, and personalized medicine for IAs. The transcriptional profiles of 75 IAs and 37 control samples were collected from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs), weighted gene co-expression network analysis, and least absolute shrinkage and selection operator (LASSO) regression were used to screen key genes. The ssGSEA algorithm was performed to establish phenotype scores. The correlation between mitochondrial dysfunction and necroptosis was evaluated using functional enrichment crossover, phenotype score correlation, immune infiltration, and interaction network construction. The IA diagnostic values of key genes were identified using machine learning. Finally, we performed the single-cell sequencing (scRNA-seq) analysis to explore mitochondrial dysfunction and necroptosis at the cellular level. In total, 42 IA-mitochondrial DEGs and 15 IA-necroptosis DEGs were identified. Screening revealed seven key genes invovled in mitochondrial dysfunction (KMO, HADH, BAX, AADAT, SDSL, PYCR1, and MAOA) and five genes involved in necroptosis (IL1B, CAMK2G, STAT1, NLRP3, and BAX). Machine learning confirmed the high diagnostic value of these key genes for IA. The IA samples showed higher expression of mitochondrial dysfunction and necroptosis. Mitochondrial dysfunction and necroptosis exhibited a close association. Furthermore, scRNA-seq indicated that mitochondrial dysfunction and necroptosis were preferentially up-regulated in monocytes/macrophages and vascular smooth muscle cells (VSMCs) within IA lesions. In conclusion, mitochondria-induced necroptosis was involved in IA formation, and was mainly up-regulated in monocytes/macrophages and VSMCs within IA lesions. Mitochondria-induced necroptosis may be a novel potential target for diagnosis, prevention, and treatment of IA.
Inverse reinforcement learning for autonomous navigation via differentiable semantic mapping and planning
Authors: Wang Tianyu , Dhiman Vikas , Atanasov Nikolay 
Published: July 2023

AbstractThis paper focuses on inverse reinforcement learning for autonomous navigation using distance and semantic category observations. The objective is to infer a cost function that explains demonstrated behavior while relying only on the expert’s observations and state-control trajectory. We develop a map encoder, that infers semantic category probabilities from the observation sequence, and a cost encoder, defined as a deep neural network over the semantic features. Since the expert cost is not directly observable, the model parameters can only be optimized by differentiating the error between demonstrated controls and a control policy computed from the cost estimate. We propose a new model of expert behavior that enables error minimization using a closed-form subgradient computed only over a subset of promising states via a motion planning algorithm. Our approach allows generalizing the learned behavior to new environments with new spatial configurations of the semantic categories. We analyze the different components of our model in a minigrid environment. We also demonstrate that our approach learns to follow traffic rules in the autonomous driving CARLA simulator by relying on semantic observations of buildings, sidewalks, and road lanes.
An updated assessment of the direct costs of invasive non-native species to the United Kingdom
Authors: Eschen René , Kadzamira Mariam , Stutz Sonja , Ogunmodede Adewale , Djeddour Djami , Shaw Richard , Pratt Corin , Varia Sonal , Constantine Kate , Williams Frances 
Published: July 2023

AbstractEstimates of the economic impact of invasive non-native species (INNS) are important to support informed decision-making and prioritise resources. A detailed estimate of the direct costs of INNS to Great Britain, covering many sectors of the economy and the impacts of many INNS in diverse habitats, was made in 2010 and extended to Northern Ireland in 2013. These estimates are increasingly out of date as a result of changes in distribution and impacts of species, new knowledge, changes in management and newly established INNS. We, therefore, updated the estimated costs for the United Kingdom (UK) for sectors where new information was available and applied an inflation factor to the remaining sectors and species. The results show changes in all sectors and species and the new estimated annual costs to the UK economy is £4014 m, with £3022 m, £499 m, £343 m and £150 m to England, Scotland, Wales and Northern Ireland, respectively. Overall, we found a 45% increase in comparable costs since 2010, with most estimated costs increased, often more than inflation, although in some cases the costs have decreased as a result of changes in the population size of INNS, such as was the case for rabbits. A comparison with the previously estimated costs revealed that the costliest species and sectors of 2010 remain the same, but the newly established, widely distributed and highly impactful ash dieback is now one of the most costly diseases caused by an INNS. We discuss reasons for these changes and the evolution of costs in comparison to other studies. Overall, these results confirm the enormous cost of INNS to the UK economy and highlight the need for continued efforts to mitigate the impacts of established INNS, whilst also supporting measures to limit the entry and establishment of new, potentially harmful non-native species.
On the Reliability of the EEG Microstate Approach
Authors: Kleinert Tobias , Koenig Thomas , Nash Kyle , Wascher Edmund 
Published: July 2023

AbstractEEG microstates represent functional brain networks observable in resting EEG recordings that remain stable for 40–120ms before rapidly switching into another network. It is assumed that microstate characteristics (i.e., durations, occurrences, percentage coverage, and transitions) may serve as neural markers of mental and neurological disorders and psychosocial traits. However, robust data on their retest-reliability are needed to provide the basis for this assumption. Furthermore, researchers currently use different methodological approaches that need to be compared regarding their consistency and suitability to produce reliable results. Based on an extensive dataset largely representative of western societies (2 days with two resting EEG measures each; day one: n = 583; day two: n = 542) we found good to excellent short-term retest-reliability of microstate durations, occurrences, and coverages (average ICCs = 0.874-0.920). There was good overall long-term retest-reliability of these microstate characteristics (average ICCs = 0.671-0.852), even when the interval between measures was longer than half a year, supporting the longstanding notion that microstate durations, occurrences, and coverages represent stable neural traits. Findings were robust across different EEG systems (64 vs. 30 electrodes), recording lengths (3 vs. 2 min), and cognitive states (before vs. after experiment). However, we found poor retest-reliability of transitions. There was good to excellent consistency of microstate characteristics across clustering procedures (except for transitions), and both procedures produced reliable results. Grand-mean fitting yielded more reliable results compared to individual fitting. Overall, these findings provide robust evidence for the reliability of the microstate approach.