bluuebunny/crossref_metadata_2025_split huggingface dataset:
Resurgence and 1/N Expansion in Integrable Field Theories
Authors: Di Pietro Lorenzo , Mariño Marcos , Sberveglieri Giacomo , Serone Marco 
Published: October 2021

Abstract
In theories with renormalons the perturbative series is factorially divergent even after restricting to a given order in 1/N, making the 1/N expansion a natural testing ground for the theory of resurgence. We study in detail the interplay between resurgent properties and the 1/N expansion in various integrable field theories with renormalons. We focus on the free energy in the presence of a chemical potential coupled to a conserved charge, which can be computed exactly with the thermodynamic Bethe ansatz (TBA). In some examples, like the first 1/N correction to the free energy in the non-linear sigma model, the terms in the 1/N expansion can be fully decoded in terms of a resurgent trans-series in the coupling constant. In the principal chiral field we find a new, explicit solution for the large N free energy which can be written as the median resummation of a trans-series with infinitely many, analytically computable IR renormalon corrections. However, in other examples, like the Gross-Neveu model, each term in the 1/N expansion includes non-perturbative corrections which can not be predicted by a resurgent analysis of the corresponding perturbative series. We also study the properties of the series in 1/N. In the Gross-Neveu model, where this is convergent, we analytically continue the series beyond its radius of convergence and show how the continuation matches with known dualities with sine-Gordon theories.
Empiricism in the foundations of cognition
Authors: Childers Timothy , Hvorecký Juraj , Majer Ondrej 
Published: October 2021

AbstractThis paper traces the empiricist program from early debates between nativism and behaviorism within philosophy, through debates about early connectionist approaches within the cognitive sciences, and up to their recent iterations within the domain of deep learning. We demonstrate how current debates on the nature of cognition via deep network architecture echo some of the core issues from the Chomsky/Quine debate and investigate the strength of support offered by these various lines of research to the empiricist standpoint. Referencing literature from both computer science and philosophy, we conclude that the current state of deep learning does not offer strong encouragement to the empiricist side despite some arguments to the contrary.
Global and regional aggregate damages associated with global warming of 1.5 to 4 °C above pre-industrial levels
Authors: Warren R. , Hope C. , Gernaat D. E. H. J. , Van Vuuren D. P. , Jenkins K. 
Published: October 2021

AbstractWe quantify global and regional aggregate damages from global warming of 1.5 to 4 °C above pre-industrial levels using a well-established integrated assessment model, PAGE09. We find mean global aggregate damages in 2100 of 0.29% of GDP if global warming is limited to about 1.5 °C (90% confidence interval 0.09–0.60%) and 0.40% for 2 °C (range 0.12–0.91%). These are, respectively, 92% and 89% lower than mean losses of 3.67% of GDP (range 0.64–10.77%) associated with global warming of 4 °C. The net present value of global aggregate damages for the 2008–2200 period is estimated at $48.7 trillion for ~ 1.5 °C global warming (range $13–108 trillion) and $60.7 trillion for 2 °C (range $15–140 trillion). These are, respectively, 92% and 90% lower than the mean NPV of $591.7 trillion of GDP for 4 °C warming (range $70–1920 trillion). This leads to a mean social cost of CO2 emitted in 2020 of ~ $150 for 4 °C warming as compared to $30 at ~ 1.5 °C warming. The benefits of limiting warming to 1.5 °C rather than 2 °C might be underestimated since PAGE09 is not recalibrated to reflect the recent understanding of the full range of risks at 1.5 °C warming.
Multiscale matrix-fracture transfer functions for naturally fractured reservoirs using an analytical, infinite conductivity, discrete fracture model
Authors: Hazlett R. D. , Younis R. 
Published: October 2021

AbstractFracture matrix transfer functions have long been recognized as tools in modelling naturally fractured reservoirs. If a significant degree of fracturing is present, models involving single matrix blocks and matrix block distributions become relevant. However, this captures only the largest fracture sets and treats the matrix blocks as homogeneous, though possibly anisotropic. Herein, we produce the steady and transient baseline solutions for depletion for such models. Multiscale models pass below grid scale information to the larger scale system with some numerical cost. Instead, for below block scale information, we take the analytic solution to the Diffusivity Equation for transient inflow performance of wells of arbitrary trajectory, originally developed for Neumann boundary conditions, and recast it for Dirichlet boundaries with possible internal fractures of variable density, length, and orientation. As such, it represents the analytical solution for a heterogeneous matrix block surrounded by a constant pressure sink, we take to be the primary fracture system. Instead of using a constant rate internal boundary condition on a fracture surrounded by matrix, we segment the fracture and, through imposed material balance, force the internal complex fracture feature to be a constant pressure element with net zero flux. In doing so, we create a representative matrix block with infinite conductivity subscale fractures that impact the overall drainage into the surrounding fracture system. We vary the internal fracture structure and delineate sensitivity to fracture spacing and extent of fracturing. We generate the complete transient solution, enabling new well test interpretation for such systems in characterization of block size distributions or extent of below block-scale fracturing. The initial model for fully-penetrating fractures can be extended to 3D, generalized floating fractures of arbitrary inclination, and internal complex fracture networks.
Decline in Mast Cell Density During Diffuse Alveolar Damage in Idiopathic Pulmonary Fibrosis
Authors: Salonen Johanna , Kreus Mervi , Lehtonen Siri , Vähänikkilä Hannu , Purokivi Minna , Kaarteenaho Riitta 
Published: October 2021

Abstract
Mast cells (MCs) are known to be involved in the pathogenesis of idiopathic pulmonary fibrosis (IPF), although their role in acute exacerbations of IPF has not been investigated. The aims of the study were to evaluate the numbers of MCs in fibrotic and non-fibrotic areas of lung tissue specimens of idiopathic pulmonary fibrosis (IPF) patients with or without an acute exacerbation of IPF, and to correlate the MC density with clinical parameters. MCs of IPF patients were quantified from surgical lung biopsy (SLB) specimens (n = 47) and lung tissue specimens taken at autopsy (n = 7). MC density was higher in the fibrotic areas of lung tissue compared with spared alveolar areas or in controls. Female gender, low diffusion capacity for carbon monoxide, diffuse alveolar damage, and smoking were associated with a low MC density. MC densities of fibrotic areas had declined significantly in five subjects in whom both SLB in the stable phase and autopsy after an acute exacerbation of IPF had been performed. There were no correlations of MC densities with survival time or future acute exacerbations. The MC density in fibrotic areas was associated with several clinical parameters. An acute exacerbation of IPF was associated with a significant decline in MC counts. Further investigations will be needed to clarify the role of these cells in IPF and in the pathogenesis of acute exacerbation as this may help to identify some potential targets for medical treatment for this serious disease.
Pilot Randomized Controlled Trial of the WHO Caregiver Skills Training in Public Health Services in Italy
Authors: Salomone Erica , Settanni Michele , McConachie Helen , Suma Katharine , Ferrara Federica , Foletti Giulia , Salandin Arianna ,   WHO CST Team, Brown Felicity L. , Pacione Laura , Shire Stephanie , Servili Chiara , Adamson Lauren B. 
Published: October 2021

AbstractParents of children with ASD (N = 86; mean age 44.8 months; 67 boys) were randomized to either WHO Caregiver Skills Training (CST) delivered in public health settings in Italy or enhanced treatment-as-usual. Primary blinded outcomes were 3-months post-intervention change scores of autism severity and engagement during caregiver-child interaction. CST was highly acceptable to caregivers and feasibly delivered by trained local clinicians. Intention-to-treat analysis showed a large and significant effect on parent skills supporting joint engagement and a smaller significant effect on flow of interaction. Expected changes in child autism severity and joint engagement did not meet statistical significance. Analysis of secondary outcomes showed a significant effect on parenting stress, self-efficacy, and child gestures. Strategies to improve the effectiveness of CST are discussed.
A review of flexible multibody dynamics for gradient-based design optimization
Authors: Gufler Veit , Wehrle Erich , Zwölfer Andreas 
Published: October 2021

AbstractDesign optimization of flexible multibody dynamics is critical to reducing weight and therefore increasing efficiency and lowering costs of mechanical systems. Simulation of flexible multibody systems, though, typically requires high computational effort which limits the usage of design optimization, especially when gradient-free methods are used and thousands of system evaluations are required. Efficient design optimization of flexible multibody dynamics is enabled by gradient-based optimization methods in concert with analytical sensitivity analysis. The present study summarizes different formulations of the equations of motion of flexible multibody dynamics. Design optimization techniques are introduced, and applications to flexible multibody dynamics are categorized. Efficient sensitivity analysis is the centerpiece of gradient-based design optimization, and sensitivity methods are introduced. The increased implementation effort of analytical sensitivity analysis is rewarded with high computational efficiency. An exemplary solution strategy for system and sensitivity evaluations is shown with the analytical direct differentiation method. Extensive literature sources are shown related to recent research activities.
Response to “Limitations in the Hilbert Transform Approach to Locating Solar Cycle Terminators” by R. Booth
Authors: Leamon Robert J. , McIntosh Scott W. , Chapman Sandra C. , Watkins Nicholas W. 
Published: October 2021

AbstractBooth (Solar Phys.296, 108, 2021; hereafter B21) is essentially a critique of the Hilbert transform techniques used in our paper (Leamon et al., Solar Phys.295, 36, 2020; hereafter L20) to predict the termination of solar cycles. Here we respond to his arguments; our methodology and parameter choices do extract a mathematically robust signature of terminators from the historical sunspot record. We agree that the attempt in L20 to extrapolate beyond the sunspot record gives a failed prediction for the next terminator of May 2020, and we identify both a possible cause and remedy here. However, we disagree with the B21 assessment that the likely termination of Solar Cycle 24 is two years after the date predicted in L20, and we show why.
Inert agricultural spray adjuvants may increase the adverse effects of selected insecticides on honey bees (Apis mellifera L.) under laboratory conditions
Authors: Wernecke Anna , Eckert Jakob H. , Forster Rolf , Kurlemann Nils , Odemer Richard 
Published: October 2021

AbstractCurrently, more than 360 spray adjuvants are registered in Germany (September 2021). Unlike plant protection products (PPPs), adjuvants are not subjected to regulatory risk assessment. In practice, numerous combinations of PPPs and adjuvants are therefore possible. Thus, tank mixtures containing insecticides that are classified as non-hazardous to bees up to the highest approved application rate or concentration may raise pollinator safety concerns when mixed with efficacy increasing adjuvants and applied in bee-attractive crops. This study analyzes whether selected “PPP–adjuvant” combinations result in increased contact mortality and pose an elevated risk to honey bees. To answer this question, we chose six common spray adjuvants of different classes for laboratory screening. These were then tested in a total of 30 tank mixtures, each with a neonicotinoid (acetamiprid), pyrethroid (lambda-cyhalothrin), diamide (chlorantraniliprole), carbamate (pirimicarb), and butenolide (flupyradifurone) formulation. We adapted an acute contact test (OECD Test Guideline 214) to our needs, e.g., by using a professional spray chamber for more realistic exposures. Our results showed that, in total, 50% of all combinations significantly increased the mortality of caged honey bees in comparison with individual application of insecticides. In contrast, none of the adjuvants alone affected bee mortality (Cox proportional hazard model, p > 0.05). With four of the five insecticide formulations, the organosilicone surfactant Break-Thru® S 301 significantly increased bee mortality within 72 h (for all insecticides except chlorantraniliprole). Furthermore, acetamiprid yielded the highest and second highest mortality increases from a tank mixture with the crop oil surfactant LI 700® (hazard ratio = 28.84, p < 0.05) and the organosilicone Break-Thru® S 301 (hazard ratio = 14.66, p < 0.05), respectively. To assess risk in a more field-realistic setting, field trials should be performed to provide a more realistic exposure scenario under colony conditions.
Künstliche Intelligenz und Arbeit: Betrachtungen zwischen Prognose und betrieblicher Realität
Authors: Giering Oliver 
Published: October 2021

ZusammenfassungKünstliche Intelligenz avanciert zu einem zentralen Thema der Debatten um eine übergreifende Digitalisierung der Arbeitswelt. Insgesamt zeigt sich dabei eine Dominanz wirtschaftlicher Perspektiven auf KI: so wird KI oft anhand ökonomischer Prognosen in Bezug auf Beschäftigung diskutiert. Andererseits finden sich auch Annahmen zu Auswirkungen auf Tätigkeiten im konkreten Arbeitsprozess. Einigkeit herrscht scheinbar darüber, dass KI umfangreiche Veränderungen in den Betrieben bewirken wird. Der Beitrag widmet sich im Sinne eines Positionspapiers diesem Spannungsfeld zwischen dominanten, diskursiven Erwartungen und empirischer, betrieblicher Realität von KI in Deutschland. Hierfür werden zentrale Perspektiven auf KI in Bezug auf Beschäftigung und Tätigkeiten vorgestellt und mit der vorhandenen Empirie zum Thema abgeglichen. Dadurch lassen sich die vorherrschenden Leitbilder und Spekulationen der KI Debatte besser einordnen. Die Sammlung der Empirie offenbart eklatante Forschungslücken hinsichtlich quantitativer als auch qualitativer Forschung zur Nutzung, als auch zum Einfluss von KI auf Arbeit. Zudem zeigen sich Schwierigkeiten bezüglich der Operationalisierung des Begriffs. Der Artikel bietet abschließend Überlegungen zu einem detaillierteren Verständnis von KI und zeigt Anknüpfungspunkte für künftige Forschung auf.Praktische Relevanz: Der Artikel illustriert das Phänomen KI, indem er eine Übersicht über zentrale Perspektiven in Bezug auf Beschäftigung und Tätigkeiten vorstellt und die vorhandene Empirie zum Thema KI und Arbeit in Deutschland sammelt. Dadurch ermöglicht er es, die vielfältigen Prognosen und Spekulationen über KI insgesamt besser einzuordnen.
Diversity Forests: Using Split Sampling to Enable Innovative Complex Split Procedures in Random Forests
Authors: Hornung Roman 
Published: October 2021

AbstractThe diversity forest algorithm is an alternative candidate node split sampling scheme that makes innovative complex split procedures in random forests possible. While conventional univariable, binary splitting suffices for obtaining strong predictive performance, new complex split procedures can help tackling practically important issues. For example, interactions between features can be exploited effectively by bivariable splitting. With diversity forests, each split is selected from a candidate split set that is sampled in the following way: for $$l = 1, \dots , {nsplits}$$

l
=
1
,
⋯
,

nsplits

: (1) sample one split problem; (2) sample a single or few splits from the split problem sampled in (1) and add this or these splits to the candidate split set. The split problems are specifically structured collections of splits that depend on the respective split procedure considered. This sampling scheme makes innovative complex split procedures computationally tangible while avoiding overfitting. Important general properties of the diversity forest algorithm are evaluated empirically using univariable, binary splitting. Based on 220 data sets with binary outcomes, diversity forests are compared with conventional random forests and random forests using extremely randomized trees. It is seen that the split sampling scheme of diversity forests does not impair the predictive performance of random forests and that the performance is quite robust with regard to the specified nsplits value. The recently developed interaction forests are the first diversity forest method that uses a complex split procedure. Interaction forests allow modeling and detecting interactions between features effectively. Further potential complex split procedures are discussed as an outlook.
Comparing risk changes of needlestick injuries between countries adopted and not adopted the needlestick safety and prevention act: A meta-analysis
Authors: Ou Y.S. , Wu H.C. , Guo Y.L. , Shiao J.S.C. 
Published: October 2021

AbstractObjectives:To determine whether countries that adopted the Needlestick Safety and Prevention Act (NSPA) achieved a reduced risk of needlestick injuries (NSIs).Method:In this meta-analysis, 3 international databases (Embase, PubMed, and MEDLINE EBSCO) and 1 Chinese database (Airiti Library) were searched using appropriate keywords to retrieve relevant articles, including multiyear NSI incidences that were published after 2010. The Joanna Briggs Institute Critical Appraisal Checklist for Prevalence Studies was used to evaluate article prevalence. A binary random-effects model was used to estimate risk ratio as summary effect. A log scale was used to evaluate differences in risk ratios of NSIs between countries that adopted versus those that did not adopt the NSPA.Results:In total, 11 articles were included in the meta-analysis from 9 countries, and NSI incidence rates were surveyed between 1993 and 2016. The risk ratios of NSIs in countries with and without the NSPA were 0.78 (95% CI, 0.67–0.91) and 0.98 (95% CI, 0.85–1.12), respectively, and the ratio of risk ratios was 0.79 (95% CI, 0.65–0.98). Reduction in NSI incidence was more prominent in nurses than in physicians.Conclusions:Our findings suggest that the mandatory use of safety-engineered medical devices in countries that adopted the NSPA had lower NSI incidence in healthcare workers compared with countries without needlestick safety and prevention regulatory policies. Further studies are needed to develop preventive strategies to protect against NSIs in physicians, which should be incorporated into the standards of care established by national regulatory agencies.
Mitochondrial, exosomal miR137-COX6A2 and gamma synchrony as biomarkers of parvalbumin interneurons, psychopathology, and neurocognition in schizophrenia
Authors: Khadimallah Ines , Jenni Raoul , Cabungcal Jan-Harry , Cleusix Martine , Fournier Margot , Beard Elidie , Klauser Paul , Knebel Jean-François , Murray Micah M. , Retsa Chrysa , Siciliano Milena , Spencer Kevin M. , Steullet Pascal , Cuenod Michel , Conus Philippe , Do Kim Q. 
Published: October 2021

AbstractEarly detection and intervention in schizophrenia requires mechanism-based biomarkers that capture neural circuitry dysfunction, allowing better patient stratification, monitoring of disease progression and treatment. In prefrontal cortex and blood of redox dysregulated mice (Gclm-KO ± GBR), oxidative stress induces miR-137 upregulation, leading to decreased COX6A2 and mitophagy markers (NIX, Fundc1, and LC3B) and to accumulation of damaged mitochondria, further exacerbating oxidative stress and parvalbumin interneurons (PVI) impairment. MitoQ, a mitochondria-targeted antioxidant, rescued all these processes. Translating to early psychosis patients (EPP), blood exosomal miR-137 increases and COX6A2 decreases, combined with mitophagy markers alterations, suggest that observations made centrally and peripherally in animal model were reflected in patients’ blood. Higher exosomal miR-137 and lower COX6A2 levels were associated with a reduction of ASSR gamma oscillations in EEG. As ASSR requires proper PVI-related networks, alterations in miR-137/COX6A2 plasma exosome levels may represent a proxy marker of PVI cortical microcircuit impairment. EPP can be stratified in two subgroups: (a) a patients’ group with mitochondrial dysfunction “Psy-D”, having high miR-137 and low COX6A2 levels in exosomes, and (b) a “Psy-ND” subgroup with no/low mitochondrial impairment, including patients having miR-137 and COX6A2 levels in the range of controls. Psy-D patients exhibited more impaired ASSR responses in association with worse psychopathological status, neurocognitive performance, and global and social functioning, suggesting that impairment of PVI mitochondria leads to more severe disease profiles. This stratification would allow, with high selectivity and specificity, the selection of patients for treatments targeting brain mitochondria dysregulation and capture the clinical and functional efficacy of future clinical trials.
Role of RAGE in obesity-induced adipose tissue inflammation and insulin resistance
Authors: Feng Ziqian , Du Zuoqin , Shu Xin , Zhu Luochen , Wu Jiaqi , Gao Qian , Wang Liqun , Chen Ni , Li Yi , Luo Mao , Hill Michael A. , Wu Jianbo 
Published: October 2021

AbatractObesity is known to be associated with adipose tissue inflammation and insulin resistance. Importantly, in obesity, the accumulation of proinflammatory macrophages in adipose tissue correlates with insulin resistance. We hypothesized that the receptor for advanced glycation end products (RAGE) and associated ligands are involved in adipose tissue insulin resistance, and that the activation of the AGE–RAGE axis plays an important role in obesity-associated inflammation. C57BL/6J mice (WT) and RAGE deficient (RAGE−/−) mice were fed a high fat diet (HFD) and subjected to glucose and insulin tolerance tests. Epdidymal adipose tissue (eAT) was collected and adipose stromal vascular cells isolated using flow cytometry. Visceral adipose tissue macrophage polarization was assessed by quantitative real time PCR. Immunoblotting was performed to evaluate the insulin signaling in adipose tissues. In additional studies, cell trafficking was assessed by injecting labeled blood monocytes into recipient mice. RAGE−/− mice displayed improved insulin sensitivity and glucose tolerance, accompanied by decreased body weight and eAT mass. Exogenous methylglyoxal (MGO) impaired insulin-stimulated AKT signaling in adipose tissues from WT mice fed a normal chow diet, but not in RAGE−/− mice. In contrast, in obese mice, treatment with MGO did not reduce insulin-induced phosphorylation of AKT in WT-HFD mice. Moreover, insulin-induced AKT phosphorylation was found to be impaired in adipose tissue from RAGE−/−-HFD mice. RAGE−/− mice displayed improved inflammatory profiles and evidence for increased adipose tissue browning. This observation is consistent with the finding of reduced plasma levels of FFA, glycerol, IL-6, and leptin in RAGE−/− mice compared to WT mice. Collectively the data demonstrate that RAGE-mediated adipose tissue inflammation and insulin-signaling are potentially important mechanisms that contribute to the development of obesity-associated insulin resistance.