bluuebunny/crossref_metadata_2025_split huggingface dataset:
Disentangling the thermofield-double state
Authors: Dadras Pouria 
Published: January 2022

Abstract
In this paper, we consider the evolution of the thermofield-double state under the double-traced operator that connects its both sides. We will compute the entanglement entropy of the resulting state using the replica trick for the large N field theory. To leading order, it can be computed from the two-point function of the theory, where, in CFTs, it is fixed by the symmetries. Due to the exponential decay of the interaction, the entanglement entropy saturates about the thermal time after the interaction is on. Next, we restrict ourselves to one dimension and assume that the theory at strong coupling is effectively described by the Schwarzian action. We then compute the coarse-grained entropy of the resulting state using the four-point function. The equality of the two entropies implies that the double-traced operators in our theory act coherently. In AdS/CFT correspondence where the thermofield-double state corresponds to a two-sided black hole, the action of a double-traced operator corresponds to shrinking or expanding the black hole in the bulk.
Non-asymptotic error estimates for the Laplace approximation in Bayesian inverse problems
Authors: Helin Tapio , Kretschmann Remo 
Published: January 2022

AbstractIn this paper we study properties of the Laplace approximation of the posterior distribution arising in nonlinear Bayesian inverse problems. Our work is motivated by Schillings et al. (Numer Math 145:915–971, 2020. 10.1007/s00211-020-01131-1), where it is shown that in such a setting the Laplace approximation error in Hellinger distance converges to zero in the order of the noise level. Here, we prove novel error estimates for a given noise level that also quantify the effect due to the nonlinearity of the forward mapping and the dimension of the problem. In particular, we are interested in settings in which a linear forward mapping is perturbed by a small nonlinear mapping. Our results indicate that in this case, the Laplace approximation error is of the size of the perturbation. The paper provides insight into Bayesian inference in nonlinear inverse problems, where linearization of the forward mapping has suitable approximation properties.
Bacterial profile and antimicrobial resistance patterns of common bacteria among pregnant women with bacteriuria in Ethiopia: a systematic review and meta-analysis
Authors: Chelkeba Legese , Fanta Korinan , Mulugeta Temesgen , Melaku Tsegaye 
Published: January 2022

AbstractBackgroundGlobally, antimicrobial resistance (AMR) restricted the armamentarium of the health care providers against infectious diseases, mainly due to the emergence of multidrug resistant. This review is aimed at providing contemporary bacterial profile and antimicrobial resistance pattern among pregnant women with significant bacteriuria.MethodsElectronic biomedical databases and indexing services such as PubMed/MEDLINE, Web of Science, EMBASE and Google Scholar were searched. Original records of research articles, available online from 2008 to 2021, addressing the prevalence of significant bacteriuria and AMR pattern among pregnant women and written in English were identified and screened. The relevant data were extracted from included studies using a format prepared in Microsoft Excel and exported to STATA 14.0 software for the outcome measure analyses and subgrouping.ResultsThe data of 5894 urine samples from 20 included studies conducted in 8 regions of the country were pooled. The overall pooled estimate of bacteriuria was 15% (95% CI 13–17%,I2 = 77.94%,p < 0.001) with substantial heterogeneity. The pooled estimate ofEscherichia colirecovered from isolates of 896 urine samples was 41% (95% CI 38–45%) followed by coagulase-negativeStaphylococci, 22% (95% CI 18–26%),Staphylococcus aureus, 15% (95% CI 12–18%),Staphylococcus saprophytic, 12% (95% CI 6–18%)Proteus mirabilis, 7% (95% CI 4–10%),Enterococcusspecies, 6% (0–12%),Pseudomonas aeruginosa, 4% (2–6%),Citrobacterspecies, 4% (95% CI 2–4%), Group B streptococcus, 3% (1–5%), andEnterobacterspecies, 2% (1–4%). Multidrug resistance proportions ofE. coli,Klebsiellaspecies,Staphylococcus aureusandCoagulase negative staphylococci, 83% (95% CI 76–91%), 78% (95% CI 66–90%), 89% (95% CI 83–96%), and 78% (95% CI 67–88%), respectively.ConclusionThe result of current review revealed the occurrence of substantial bacteriuria among pregnant women in Ethiopia. Resistance among common bacteria (E. coli,Klebsiellaspecies,Staphylococcispecies) causing UTIs in pregnant women is widespread to commonly used antibiotics. The high rate of drug resistance in turn warrants the need for regular epidemiological surveillance of antibiotic resistance and implementation of an efficient infection control and stewardship program.
What do we know about dynamic glucose-enhanced (DGE) MRI and how close is it to the clinics? Horizon 2020 GLINT consortium report
Authors: Kim Mina , Eleftheriou Afroditi , Ravotto Luca , Weber Bruno , Rivlin Michal , Navon Gil , Capozza Martina , Anemone Annasofia , Longo Dario Livio , Aime Silvio , Zaiss Moritz , Herz Kai , Deshmane Anagha , Lindig Tobias , Bender Benjamin , Golay Xavier ,   the GLINT consortium
Published: January 2022

AbstractCancer is one of the most devastating diseases that the world is currently facing, accounting for 10 million deaths in 2020 (WHO). In the last two decades, advanced medical imaging has played an ever more important role in the early detection of the disease, as it increases the chances of survival and the potential for full recovery. To date, dynamic glucose-enhanced (DGE) MRI using glucose-based chemical exchange saturation transfer (glucoCEST) has demonstrated the sensitivity to detect both d-glucose and glucose analogs, such as 3-oxy-methyl-d-glucose (3OMG) uptake in tumors. As one of the recent international efforts aiming at pushing the boundaries of translation of the DGE MRI technique into clinical practice, a multidisciplinary team of eight partners came together to form the “glucoCEST Imaging of Neoplastic Tumors (GLINT)” consortium, funded by the Horizon 2020 European Commission. This paper summarizes the progress made to date both by these groups and others in increasing our knowledge of the underlying mechanisms related to this technique as well as translating it into clinical practice.
The Cost-Effectiveness of HIV/STI Prevention in High-Income Countries with Concentrated Epidemic Settings: A Scoping Review
Authors: Brunner Palmo , Brunner Karma , Kübler Daniel 
Published: January 2022

AbstractThe purpose of this scoping review is to establish the state of the art on economic evaluations in the field of HIV/STI prevention in high-income countries with concentrated epidemic settings and to assess what we know about the cost-effectiveness of different measures. We reviewed economic evaluations of HIV/STI prevention measures published in the Web of Science and Cost-Effectiveness Registry databases. We included a total of 157 studies focusing on structural, behavioural, and biomedical interventions, covering a variety of contexts, target populations and approaches. The majority of studies are based on mathematical modelling and demonstrate that the preventive measures under scrutiny are cost-effective. Interventions targeted at high-risk populations yield the most favourable results. The generalisability and transferability of the study results are limited due to the heterogeneity of the populations, settings and methods involved. Furthermore, the results depend heavily on modelling assumptions. Since evidence is unequally distributed, we discuss implications for future research.
A novelty-based multi-objective evolutionary algorithm for identifying functional dependencies in complex technical infrastructures from alarm data
Authors: Antonello Federico , Baraldi Piero , Zio Enrico , Serio Luigi 
Published: January 2022

AbstractIn this work, a Multi-Objective Evolutionary Algorithm (MOEA) is developed to identify Functional Dependencies (FDEPs) in Complex Technical Infrastructures (CTIs) from alarm data. The objectives of the search are the maximization of a measure of novelty, which drives the exploration of the solution space avoiding to get trapped in local optima, and of a measure of dependency among alarms, which drives the uncovering of functional dependencies. The main contribution of the work is the direct identification of patterns of dependent alarms; this avoids going through the preliminary step of mining association rules, as typically done by state-of-the-art methods which, however, fail to identify rare functional dependencies due to the need of setting a balanced minimum occurrence threshold. The proposed framework for FDEPs identification is applied to a synthetic alarm database generated by a simulated CTI model and to a real large-scale database of alarms collected at the CTI of CERN (European Organization for Nuclear Research). The obtained results show that the framework enables the thorough exploration of the solution space and captures also rare functional dependencies.
Explicit solvation thermodynamics in ionic solution: extending grid inhomogeneous solvation theory to solvation free energy of salt–water mixtures
Authors: Waibl Franz , Kraml Johannes , Fernández-Quintero Monica L. , Loeffler Johannes R. , Liedl Klaus R. 
Published: January 2022

AbstractHydration thermodynamics play a fundamental role in fields ranging from the pharmaceutical industry to environmental research. Numerous methods exist to predict solvation thermodynamics of compounds ranging from small molecules to large biomolecules. Arguably the most precise methods are those based on molecular dynamics (MD) simulations in explicit solvent. One theory that has seen increased use is inhomogeneous solvation theory (IST). However, while many applications require accurate description of salt–water mixtures, no implementation of IST is currently able to estimate solvation properties involving more than one solvent species. Here, we present an extension to grid inhomogeneous solvation theory (GIST) that can take salt contributions into account. At the example of carbazole in 1 M NaCl solution, we compute the solvation energy as well as first and second order entropies. While the effect of the first order ion entropy is small, both the water–water and water–ion entropies contribute strongly. We show that the water–ion entropies are efficiently approximated using the Kirkwood superposition approximation. However, this approach cannot be applied to the water–water entropy. Furthermore, we test the quantitative validity of our method by computing salting-out coefficients and comparing them to experimental data. We find a good correlation to experimental salting-out constants, while the absolute values are overpredicted due to the approximate second order entropy. Since ions are frequently used in MD, either to neutralize the system or as a part of the investigated process, our method greatly extends the applicability of GIST. The use-cases range from biopharmaceuticals, where many assays require high salt concentrations, to environmental research, where solubility in sea water is important to model the fate of organic substances.
Hopes Woven in Smoke: Reimagining Virgil’s Aeneid in Irene Vallejo’s El silbido del arquero
Authors: Nisa Cáceres Daniel , Moreno Soldevila Rosario 
Published: January 2022

AbstractThis article investigates Irene Vallejo’s 2015 novel El silbido del arquero, a narrative in the Virgilian tradition mostly inspired by Book IV of the Aeneid. We show how Vallejo reinterprets Dido and Aeneas’s tragic love story by foregrounding minor characters, developing the setting, integrating popular subgenres and exploring communicative anxieties and gender issues. It is argued that patterns of dissatisfaction, self-delusion and disillusionment with human affairs ultimately collide with a message of hope voiced by the fictionalised Virgil.
The financial and prudential performance of Chinese banks and Fintech lenders in the era of digitalization
Authors: Katsiampa Paraskevi , McGuinness Paul B. , Serbera Jean-Philippe , Zhao Kun 
Published: January 2022

AbstractThe years 2013 to 2019 marked an explosion in Fintech in China. We analyze thefinancialandprudentialperformance of 40 exchange-traded banksand25 listed Fintech lenders in China during this watershed period. Among other things, traditional banks experienced rising operating costs, declining profit margins and softening loan quality. Consistent with a process of adaptation, traditional bank performance stabilized in the latter part of the study period (2018-19) after an initial period of decline. Study findings also highlight rising business and regulatory costs for Fintech providers over the course of the study frame. A marked deterioration in online lenders’ Special Mention and Non-Performing Loan (SML & NPL) positions arose during the period. Within the traditional bank group, smaller entities with fewer growth options and greater foreign ownership fared worst in prudential terms. Traditional banks’ financial and prudential performance also declines with time since IPO. Relative to joint stock commercial, city and rural banks, state-owned lenders registered more resilient performance, especially in relation to asset quality. In a final area, we construct a categorical Fintech proficiency variable for China's established banks. Our preliminary evidence suggests such proficiencies help stabilize SML and NPL rates and support financial returns. Overall, we offer major contribution to the banking literature by analyzing thefinancialandprudentialperformance of both incumbent and emerging lenders in one of the world’s most dynamic Fintech settings.
A method of linking functional and structural connectivity analysis in urban green infrastructure network construction
Authors: Liu Yang , Huang Ting-Ting , Zheng Xi 
Published: January 2022

AbstractAccelerated urbanization and population growth lead to the fragmentation of urban green space and loss of biodiversity. There are few studies on the integration of structural and functional connectivity to solve this problem. Our study aims to draw up a methodology to synthesize two methods of connectivity evaluation, accordingly, to construct an urban green infrastructure (UGI) network which is of great significance to maintain the stability of the urban ecosystem. Taking Beijing as a study area, we first used Morphological Spatial Pattern Analysis (MSPA) to identify the source patches, then combined with the graph theory-based landscape metrics to discuss the effect of different diffusion distances on the regional landscape connectivity and classify the importance level of the source patches. Finally, we used both least-cost path (LCP) and circuit theory to construct network and identify pinch areas in corridors for network optimization. The results show that (1) the landscape connectivity of the study area is obviously polarized. Source patches in mountain and hilly areas have good ecological bases and large areas, and the density of corridors is relatively high, which makes a large contribution to the overall landscape connectivity; Source patches in plain areas are severely fragmented, and there are only a small number of potential corridors connecting urban areas and suburban areas. (2) The UGI network is composed of 70 source patches and 148 potential corridors. The diffusion distance that is most beneficial to improve landscape connectivity is 20–25 km. (3) 6 pinch areas that are of great significance for improving the connectivity of the landscape present the coexistence of high migration resistance and large optimization potential, and urgently need to be restored first. This study provides a method to combine the structural and the functional analysis to construct a UGI network and formulate more scientifical protection strategies for planning departments.
Metal-Dielectric-Graphene Hybrid Heterostructures with Enhanced Surface Plasmon Resonance Sensitivity Based on Amplitude and Phase Measurements
Authors: Kravets Vasyl G. , Wu Fan , Yu Tongcheng , Grigorenko Alexander N. 
Published: January 2022

AbstractMetal-dielectric-graphene hybrid heterostructures based on oxides Al2O3, HfO2, and ZrO2 as well as on complementary metal–oxide–semiconductor compatible dielectric Si3N4 covering plasmonic metals Cu and Ag have been fabricated and studied. We show that the characteristics of these heterostructures are important for surface plasmon resonance biosensing (such as minimum reflectivity, sharp phase changes, resonance full width at half minimum and resonance sensitivity to refractive index unit (RIU) changes) can be significantly improved by adding dielectric/graphene layers. We demonstrate maximum plasmon resonance spectral sensitivity of more than 30,000 nm/RIU for Cu/Al2O3 (ZrO2, Si3N4), Ag/Si3N4 bilayers and Cu/dielectric/graphene three-layers for near-infrared wavelengths. The sensitivities of the fabricated heterostructures were ~ 5–8 times higher than those of bare Cu or Ag thin films. We also found that the width of the plasmon resonance reflectivity curves can be reduced by adding dielectric/graphene layers. An unexpected blueshift of the plasmon resonance spectral position was observed after covering noble metals with high-index dielectric/graphene heterostructures. We suggest that the observed blueshift and a large enhancement of surface plasmon resonance sensitivity in metal-dielectric-graphene hybrid heterostructures are produced by stationary surface dipoles which generate a strong electric field concentrated at the very thin top dielectric/graphene layer.
Market power and food loss at the producer-retailer interface of fruit and vegetable supply chains in Germany
Authors: Herzberg Ronja , Schmidt Thomas , Keck Markus 
Published: January 2022

AbstractFood loss and waste are associated with an unnecessary consumption of natural resources and avoidable greenhouse gas emissions. The United Nations have thus set the reduction of food loss and waste on the political agenda by means of the Sustainable Development Goal Target 12.3. The German Federal Government committed itself to this goal by implementing the National Strategy for Food Waste Reduction in 2019. However, this policy approach relies heavily on voluntary action by involved actors and neglects the possible role of power imbalances along the food supply chain. While current research on food loss and waste in industrialised countries predominantly focuses on the consumer level, this study puts emphasis on the under-researched early stages of the food supply chain from the field to retailers’ warehouses. Based on 22 expert interviews with producers, producer organisations and retailers, this article identifies major inter-stage drivers of food loss in the supply chains for fresh fruit and vegetables in Germany. Its main novelty is to demonstrate how market power imbalances and risk shifting between powerful and subordinate actors can reinforce the tendency of food loss on the part of producers further up the supply chain. Results indicate that prevalent institutional settings, such as contractual terms and conditions, trading practices, ordering processes, product specifications, and communication privilege retailers and encourage food loss. The mechanisms in which these imbalances manifest, go beyond the European Commission’s current legislation on Unfair Trading Practices. This study suggests a research agenda that might help to formulate adjusted policy instruments for re-structuring the German fruit and vegetable markets so that less food is wasted.
Advancing video research methodology to capture the processes of social interaction and multimodality
Authors: Hannula Markku S. , Haataja Eeva , Löfström Erika , Garcia Moreno-Esteva Enrique , Salminen-Saari Jessica F. A. , Laine Anu 
Published: January 2022

AbstractIn this reflective methodological paper we focus on affordances and challenges of video data. We compare and analyze two research settings that use the latest video technology to capture classroom interactions in mathematics education, namely, The Social Unit of Learning (SUL) project of the University of Melbourne and the MathTrack project of the University of Helsinki. While using these two settings as examples, we have structured our reflections around themes pertinent to video research in general, namely, research methods, data management, and research ethics. SUL and MathTrack share an understanding of mathematics learning as social multimodal practice, and provide possibilities for zooming into the situational micro interactions that construct collaborative problem-solving learning. Both settings provide rich data for in-depth analyses of peer interactions and learning processes. The settings share special needs for technical support and data management, as well as attention to ethical aspects from the perspective of the participants’ security and discretion. SUL data are especially suitable for investigating interactions on a broad scope, addressing how multiple interactional processes intertwine. MathTrack, on the other hand, enables exploration of participants’ visual attention in detail and its role in learning. Both settings could provide tools for teachers’ professional development by showing them aspects of classroom interactions that would otherwise remain hidden.
Fingolimod Rescues Memory and Improves Pathological Hallmarks in the 3xTg-AD Model of Alzheimer’s Disease
Authors: Fagan Steven G. , Bechet Sibylle , Dev Kumlesh K. 
Published: January 2022

AbstractTherapeutic strategies for Alzheimer’s disease (AD) have largely focused on the regulation of amyloid pathology while those targeting tau pathology, and inflammatory mechanisms are less explored. In this regard, drugs with multimodal and concurrent targeting of Aβ, tau, and inflammatory processes may offer advantages. Here, we investigate one such candidate drug in the triple transgenic 3xTg-AD mouse model of AD, namely the disease-modifying oral neuroimmunomodulatory therapeutic used in patients with multiple sclerosis, called fingolimod. In this study, administration of fingolimod was initiated after behavioral symptoms are known to emerge, at 6 months of age. Treatment continued to 12 months when behavioral tests were performed and thereafter histological and biochemical analysis was conducted on postmortem tissue. The results demonstrate that fingolimod reverses deficits in spatial working memory at 8 and 12 months of age as measured by novel object location and Morris water maze tests. Inflammation in the brain is alleviated as demonstrated by reduced Iba1-positive and CD3-positive cell number, less ramified microglial morphology, and improved cytokine profile. Finally, treatment with fingolimod was shown to reduce phosphorylated tau and APP levels in the hippocampus and cortex. These results highlight the potential of fingolimod as a multimodal therapeutic for the treatment of AD.