bluuebunny/crossref_metadata_2025 huggingface dataset:
OP-Bereich: Verbesserung der Kostentransparenz in der Materialversorgung durch ein Fallwagenkonzept
Authors: Moll Beate , Raida Andrea
Published: August 2023

Im Krankenhaus gewinnt eine transparente und fallbezogene Kostenverrechnung der genutzten Ressourcen zunehmend an Bedeutung. Insbesondere im OP-Bereich, der zu den kostspieligsten Bereichen eines Krankenhauses zählt, gibt es verschiedene Ansätze, um die Kostentransparenz zu erhöhen. Die fallbasierte Materialerfassung stellt einen Konzeptansatz zur Verbesserung der Transparenz des Materialverbrauchs dar.
Künstliche Intelligenz in Einkauf und Logistik
Authors: Eltzholtz Lennart
Published: August 2023

Mit künstlicher Intelligenz werden durch Computer/Maschinen intellektuelle Aufgaben bewältigt, die normalerweise Menschen erledigen würden.
Anwendungsbericht: Papierlos, transparent, kostensparend: elektronische Rechnungsbearbeitung
Authors: Adorf Frank
Published: August 2023

Was sich im Bereich Einkauf/Materialwirtschaft über Jahre bewährt hatte, wurde auch in allen relevanten Bereichen des Verbundes der Niels-Stensen-Kliniken implementiert. Mit Erfolg: Heute will man in Osnabrück die elektronische Rechnungsbearbeitung nicht mehr missen.
Fachgerechte Gebäudereinigung im Gesundheitssektor: Hygiene als Rückendeckung der medizinischen Versorgung
Authors: Tegeler Sven
Published: August 2023

Die professionelle Gebäudereinigung ist eine wichtige Voraussetzung zur Prävention nosokomialer Infektionen. Jedoch stellt die Steuerung nicht-medizinischer Prozesse viele Kliniken vor große Herausforderungen. Abhilfe können spezialisierte Dienstleister schaffen.
The Prognostic Value of the Age–D-Dimer–Albumin Score in Patients with Acute Myocardial Infarction Undergoing Percutaneous Coronary Intervention
Authors: He Hao-ming , Chen Yi-nong , Zeng Ji-lang , Zheng Shu-wen , Zhu Long-yang , Wang Zhe , Jiao Si-qi , Yang Fu-rong , Sun Yi-hong
Published: August 2023

Background The Age–D-dimer–Albumin (ADA), the CREDO-Kyoto, and the PARIS scores have been established to predict thrombotic events. However, the prognostic performance of these scores compared to the GRACE score in patients with acute myocardial infarction (AMI) undergoing percutaneous coronary intervention (PCI) has not been reported.

Methods Consecutive AMI patients treated with PCI were retrospectively enrolled at a teaching hospital in China from January 2016 to December 2019. The primary endpoint was all-cause mortality and the secondary endpoint was cardiac death. Harrell's C-index and net reclassification improvement (NRI) were used to compare the prognostic value of these scores with the GRACE score for mortality.

Results Of the 1,578 patients enrolled, the mean age was 62.5 years, and 23.5% were female. During a median follow-up of 3.8 years, 146 all-cause deaths and 80 cardiac deaths occurred. The ADA score showed a better prognostic performance than the GRACE (Harrell's C-index: 0.800 vs. 0.749; p = 0.003), the CREDO-Kyoto (Harrell's C-index: 0.800 vs. 0.765; NRI = 0.348, p < 0.001), and the PARIS scores (Harrell's C-index: 0.800 vs. 0.694; NRI = 0.556, p < 0.001). In the multivariable Cox regression analysis, the ADA score was independently associated with all-cause mortality (hazard ratio [HR] = 1.641 per 10-point increment, 95% confidence interval [CI]: 1.397–1.929) and cardiac death (HR = 1.636 per 10-point increment, 95% CI: 1.325–2.020). The risk of all-cause mortality and cardiac death increased with the rising of the ADA score.

Conclusion The ADA score showed a better prognostic performance than the GRACE, the CREDO-Kyoto, and the PARIS scores in patients with AMI undergoing PCI, which was a potential predictive tool for mortality.
Flow-based assembly of nucleic acid-loaded polymer nanoparticles
Authors: Xu Zeyan , McCarrol Joshua , Stenzel Martina H.
Published: August 2023

Since the development of messenger RNA (mRNA)-based SARS-CoV-2 (COVID-19) vaccines, there is increased public awareness of the importance of nanoparticles, in this case lipid nanoparticles, to ensure safe delivery of an active compound. To ensure the formation of high-quality nanoparticles with reproducible results, these lipid nanoparticles are assembled with the nucleic acid drug using flow-based devices. Although flow assembly using lipid nanoparticles for nucleic acid delivery is well described in the literature, only a few examples use polymers. This is surprising because the field of polymers for nucleic acid delivery is substantial as hundreds of polymers for nucleic acid delivery have been reported in the literature. In this review, we discuss several aspects of flow-based assembly of nucleic acid-loaded polymer nanoparticles. Initially, we introduce the concept of chip-based or capillary-based systems that can be either used as single-phase or multiphase systems. Initially, researchers have to choose the type of mixing, which can be active or passive. The type of flow, laminar or turbulent, also significantly affects the quality of the nanoparticles. We then present the type of polymers that have so far been assembled with mRNA, small interfering RNA (siRNA) or plasmid DNA (pDNA) using flow devices. We discuss effects such as flow rate, concentration and polymer lengths on the outcome. To conclude, we highlight how flow assembly is an excellent way to generate well-defined nanoparticles including polyplexes in a reproducible manner.
A new approach in top-of-line corrosion studies in CO2/H2S environment
Authors: Neshati Jaber , Saremi Mohsen , Mashhadi Golnoush
Published: August 2023

The most common way to control Top of line Corrosion (TLC) is to use corrosion inhibitors. A setup was designed to simulate the TLC conditions and measure the corrosion rate in the presence of an Imidazoline-based commercial inhibitor. The base solution was at temperature 70°C and the samples X65 steel were at 5°C and 20°C. Experiments were carried out in atmospheric conditions by purging a mixture of CO2 and H2S gases in proportions of 21% and 79%, respectively. An increase in the TLC rate was measured when the sample temperature increased. The difference between the average corrosion rate measured by weight loss and the instantaneous resulting from Tafel and linear polarisation resistance was significant in this study. Results showed that the surface temperature of the sample has a significant effect on TLC. Although the condensation rate on X65 steel sample with surface temperature of 5°C was about ten times more at 20°C, the corrosion rate was more at higher temperatures.
Dissolution of gold in the presence of copper ion and diethylenetriamine (DETA)
Authors: Agorhom Eric Aminartey , Owusu Clement , Gyedu Lilian
Published: August 2023

Cyanidation is the most widely used technique for gold extraction worldwide. However, its efficiency in gold extraction has decreased due to gold association with base metals such as copper. Copper is known to form different complexes with cyanide depending on the pulp pH. These Cu-CN complexes deplete the pulp of free cyanide, thereby decreasing gold leaching. The study examined the application of diethylenetriamine (DETA) in cyanidation to minimise copper ions effect on gold cyanidation. Leaching tests performed in the presence of copper ions reduced gold recovery from 93% to 15% at a copper sulphate concentration of 1% and increased cyanide consumption by 10%. The introduction of DETA (between 0.2% and 1%) however restored gold recovery back to normal as the baseline without copper ions and also enabled gold extraction at a reduced cyanide strength. Based on the study, DETA could be used during gold–copper cyanide leaching to minimise the copper ion effect and enhance gold extraction.
Solution of lepton g − 2 anomalies with nonlocal QED
Authors: Li Hang , Wang P
Published: August 2023

An explanation using nonlocal quantum electrodynamics (QED) for lepton g − 2 anomalies is provided that is a simple extension of the standard model. This solution is based on the same gauge symmetry as QED without introducing any new particles and interactions. The correlation functions in the nonlocal strength tension and lepton–photon interaction make it possible to explain the discrepancies of both Δa

μ
and Δa

e
. With the same approach, the discrepancy of the anomalous magnetic moment of τ leptons from the standard model is estimated in the range from 1.19 × 10−5 to 3.21 × 10−3, which is covered by the current experimental uncertainty.
A piezoelectric energy harvester with a hybrid nonlinearity of bluff body and magnet repulsion in low threshold wind speed for power supply
Authors: He Lipeng , Hou Yi , Liu Xuejin , Liu Renwen , Yu Baojun , Huang Hu , Lin Jieqiong
Published: August 2023

The environment contains several substantial energies, such as low-speed wind, which can be harvested to power sensors for environment monitoring, data collection, etc. As a promising solution, a piezoelectric energy harvester with hybrid nonlinearity for low threshold wind speed and practical wind speed range is introduced in this paper. Because of the hybrid nonlinearity of bluff body and magnet, the symmetrically shaped bluff body can induce a greater cantilever deformation, and a stronger repulsion generates a higher swing frequency of the cantilever. Moreover, the dual lead zirconate titanate plate enhances the utilization efficiency of the magnet repulsion. The hybrid nonlinearity is studied in theoretical models, numerical simulations, and experiments. The harvester outputs a noticeable voltage at 2.5 m s−1. The highest output peak-to-peak voltage and power came to 33.72 VP–P, 0.346 mW in 5.5 m s−1, 800 kΩ. The application experiments also demonstrate the feasibility and stability of the harvester by powering LEDs and sensors, which enable sensors to be placed in a wider range with high stability for environment monitoring.
Research on the influence of an adhesive layer on the monitoring signal of piezoelectric sensors
Authors: Yu Hui , Guo Chenguang , Yue Haitao , Li Qiang , Dai Weibing , Wang Hui
Published: August 2023

Electromechanical impedance (EMI) technology, as one of the important methods for analyzing and studying the interaction between sensors and structures, has the characteristics of clear physical meaning and high computational efficiency. However, for complex structures, it is difficult to quantitatively combine the measured impedance signal with the physical parameters of the tested structure. Therefore, establishing an appropriate EMI model is crucial to facilitate the quantitative analysis of structural health monitoring. The impedance models developed so far assume perfect adhesion between PZT and the structure, with displacement compatibility, and ignore the shear lag effect of the adhesive layer. Therefore, this research focuses on analyzing how surface-bonded PZT couples with the structure through the adhesives and conducting a shear layer analysis on two-dimensional (2-D) circular PZT to derive a closed-form solution for shear lag distribution. The shear lag effect is integrated into the 2D impedance formula. The influence of the adhesive layer on bolt loosening monitoring is studied, and it is proven that the modified EMI model can effectively predict the shear lag effect of the adhesive layer. The result of relative error analysis proves that conventional adhesive PZT also exhibits the shear lag phenomenon. The influence of different thicknesses of adhesive layers on sensor sensitivity is studied. The experimental results show that as the thickness of the adhesive layer decreases, the monitoring sensitivity of the sensor increases. Moreover, for slight bolt loosening, the thickness of the adhesive layer can affect the monitoring frequency.
Construction of a quantum Stirling engine cycle tuned by dynamic-angle spinning
Authors: Çakmak Selçuk , Rastegar Sedehi H R
Published: August 2023

In this contribution, we investigate two coupled spins as a working substance of the quantum Stirling heat engine cycle. We propose an experimentally implementable scheme in which the cycle is driven by tuning the dipole-dipole interaction angle via a dynamic-angle spinning technique under a magnetic field. Realistic parameters are chosen for the proposed heat engine cycle. In addition, our goal is to calculate the power of the engine. To this end, we focus on the microdynamics of the quantum isothermal process to predict the required-time per engine cycle. The obtained results show that the engine has high efficiency. Furthermore, the engine attains maximum power at the same point where the maximum efficiency is satisfied.
Gravitational instability of dark-baryonic matter systems in f (R) gravity
Authors: Shu Chun-Hua , Zhang Ke-Xin , He Ke-Rong , Chen Hui , Liu San-Qiu
Published: August 2023

The gravitational instability of dark-baryonic matter systems is investigated by adopting Boltzmann-Vlasov equation in the background of f(R) gravity, the dispersion relation considering the κ-deformed Kaniadakis distribution is derived by exploiting the kinetic theory. The cases of high and low frequency perturbations are analyzed, respectively. In the high-frequency regime, as κ increases, the normalized frequency experiences a corresponding increase. Conversely, in the low-frequency regime, an increase in κ leads to a simultaneous decrease in both the growth rate and the critical wave number. Furthermore, Jeans mass limit of dark-baryonic matter systems in

f

R

gravity with κ-deformed Kaniadakis distribution is studied, it is found that the increase of T

eff
with the enlargement of κ, which leads to the increase of Jeans mass M
*. In additional, the influence of dispersion velocity ratio and density ratio of dark to baryonic matter is investigated, it is indicated that the amplification of the dispersion velocity ratio leads to the decrease of Jeans mass. It is worth emphasizing that the dark-bayonic matter system have a higher limitation of instability in f(R) gravity than that in the classical Newtonian gravity.
Exposing minimal composition of Kohn–Sham theory and its extendability
Authors: Nakada H
Published: August 2023

Reducing the many-fermion problem to a set of single-particle (s.p.) equations, the Kohn–Sham (KS) theory has provided a practical tool to implement ab initio calculations of ground-state energies and densities in many-electron systems. There have been attempts to extend the KS theory so that it could describe other physical quantities, or it could be applied to other many-fermion systems. By generalizing and reformulating the KS theory in terms of the 1-body density matrix, we expose the minimal composition of the theory that enables the reduction of the many-fermion problem to the s.p. equations. Based on the reformulation, several basic issues are reconsidered. The v- and N-representabilities for the KS theory are distinguished from those for the Hohenberg-Kohn theorem. Criteria for the extendability of the KS theory are addressed.
On a dynamical system linked to the BKL scenario
Authors: Conte Robert
Published: August 2023

We consider the six-dimensional dynamical system in three components introduced by Ryan to describe the scenario of Belinskii, Khalatnikov and Lifshitz to the cosmological singularity when the spatial metric tensor is not diagonal. Despite its nonintegrability, recently proven by Goldstein and Piechocki, the three four-dimensional systems defined by canceling one of the three components happen to be integrable. We express their general solution as a rational function of, respectively, two exponential functions, a third Painlevé function, two exponential functions.
Squeezed bispectrum and one-loop corrections in transient constant-roll inflation
Authors: Motohashi Hayato , Tada Yuichiro
Published: August 2023

In canonical single-field inflation, the production of primordial black holes (PBH) requires a transient violation of the slow-roll condition. The transient ultra slow-roll inflation is an example of such scenarios, and more generally, one can consider the transient constant-roll inflation. We investigate the squeezed bispectrum in the transient constant-roll inflation and find that Maldacena's consistency relation holds for a sufficiently long-wavelength mode, whereas it is violated for modes around the peak scale for the non-attractor case. We also demonstrate how the one-loop corrections are modified compared to the case of the transient ultra slow-roll inflation, focusing on representative one-loop terms originating from a time derivative of the second slow-roll parameter in the cubic action. We find that the perturbativity requirement on those terms does not rule out the production of PBH from the transient constant-roll inflation. Therefore, it is a simple counterexample of the recently claimed no-go theorem of PBH production from single-field inflation.
MeV to multi-TeV thermal WIMPs: most conservative limits
Authors: Dutta Koushik , Ghosh Avirup , Kar Arpan , Mukhopadhyaya Biswarup
Published: August 2023

We consider a weakly interacting massive
particle (WIMP) dark matter (DM) annihilating into
all possible Standard Model (SM) particle pairs,
including the SM neutrinos, via s-wave processes and
derive the branching ratio independent upper limit
on the total annihilation cross-section
 〈σv〉 using the data of
CMB, gamma-ray, cosmic-ray and several neutrino
observations. For conservative choices of all relevant
astrophysical parameters, we obtain upper limits
of 10-23–10-25 cm3 s-1 
on the total 〈σv〉 for the WIMP mass
range 10 MeV–100 TeV, thus making the
entire mass range consistent with the observed relic density.
An important input that goes into our analysis
is the assumption that thermal WIMPs can
have significant coupling to the SM neutrinos.
Forbidden dark matter annihilation into leptons with full collision terms
Authors: Aboubrahim Amin , Klasen Michael , Wiggering Luca Paolo
Published: August 2023

The standard approach of calculating the relic density of thermally produced dark matter
based on the assumption of kinetic equilibrium is known to fail for forbidden dark matter models
since only the high momentum tail of the dark matter phase space distribution function contributes
significantly to dark matter annihilations. Furthermore, it is known that the computationally less
expensive Fokker-Planck approximation for the collision term describing elastic scattering
processes between non-relativistic dark matter particles and the Standard Model thermal bath
breaks down if both scattering partners are close in mass. This, however, is the defining feature
of the forbidden dark matter paradigm. In this paper, we therefore include the full elastic
collision term in the full momentum-dependent Boltzmann equation as well as in a set of fluid
equations that couple the evolution of the number density and dark matter temperature for a
simplified model featuring forbidden dark matter annihilations into muon or tau leptons through a
scalar mediator. On the technical side, we perform all angular integrals in the full collision
term analytically and take into account the effect of dark matter self-interactions on the relic
density. The overall phenomenological outcome is that the updated relic density calculation
results in a significant reduction of the experimentally allowed parameter space compared to the
traditional approach, which solves only for the abundance. In addition, almost the entire
currently viable parameter space can be probed with CMB-S4, next-generation beam-dump experiments
or at a future high-luminosity electron-position collider, except for the resonant region where
the mediator corresponds to approximately twice the muon or tau mass.
First results from BRASS-p broadband searches for hidden photon dark matter
Authors: Bajjali Fayez , Dornbusch Sven , Ekmedžić Marko , Horns Dieter , Kasemann Christoph , Lobanov Andrei , Mkrtchyan Artak , Nguyen Le Hoang , Tluczykont Martin , Tuccari Gino , Ulrichs Johannes , Wieching Gundolf , Zensus Anton
Published: August 2023

We discuss first results from hidden photon dark matter searches made with a prototype of the Broadband Radiometric Axion/ALPs Search Setup (BRASS-p) in the range of particle mass of 49.63 μeV to 74.44 μeV
(frequency range of 12 GHz to 18 GHz). The conceptual design of BRASS and a detailed description of its present prototype, BRASS-p, are given, with a view of the potential application of such setups to hidden photon, axion, and axion-like particle (ALP) dark matter searches using heterodyne detectors in the range of particle mass from
40 μeV to 4000 μeV (10 GHz to 1 THz). Pioneering measurements made with BRASS-p achieve the record sensitivity of (0.3-1.0) × 10-13 to the kinetic mixing between the normal and hidden photons, assuming the dark matter is made entirely of unpolarized hidden photons. Based on these results, a discussion of further prospects for dark matter searches using the BRASS-p apparatus is presented.
Intrinsic symmetry of nonlocal nonlinear optical susceptibility tensor in degenerate multi-wave mixing
Authors: Ryzhikov P S , Makarov V A
Published: August 2023

Using energy and momentum conservation laws, we obtained the intrinsic symmetry relations for the nonlocal nonlinear optical susceptibility tensor in lossless nth order nonlinear medium of arbitrary symmetry class for the case when less than n + 1 electromagnetic waves with different frequencies interact. Particular attention is devoted to the relations of the components of this tensor, which cannot be obtained as limiting case from the symmetry relations for the nonlocal nonlinear susceptibility tensor describing interaction of exactly n + 1 waves with different frequencies. The examples of these symmetry relations for degenerate second- and third-order processes often considered are given.
Simple model for cluster radioactivity half-lives in trans-lead nuclei*
Authors: Zhu 朱 Xiao-Yan 小彦 , Luo 骆 Song 松 , Qi 亓 Lin-Jing 林静 , Zhang 张 Dong-Meng 冬萌 , Li 李 Xiao-Hua 小华 , Lin 林 Wen-Bin 文斌
Published: August 2023

In this study, considering the modified preformation probability

to be

, where

and

are the α-particle preformation probability and an adjustable parameter proposed by Wang et al. [Chin. Phys. C 45, 044111 (2021)], respectively, we extend a new simple model put forward by Bayrak [J. Phys. G 47, 025102 (2020)] to systematically study the cluster radioactivity half-lives of 28 trans-lead nuclei ranging from

to

, which is based on the Wentzel-Kramers-Brillouin approximation and Bohr–Sommerfeld quantization condition. For comparison, a universal decay law proposed by Qi et al. [Phys. Rev. C 80, 044326 (2009)], a three-parameter model-independent formula put forward by Balasubramaniam et al. [Phys. Rev. C 70, 017301 (2004)], and the semi-empirical model proposed by Tavares et al. [Eur. Phys. J. A 49, 1 (2013)] are used. Our calculated results reproduce the experimental data well, with a standard deviation of 0.818. Furthermore, we use this model to predict the cluster radioactivity half-lives of 51 possible cluster radioactive candidates whose cluster radioactivities are energetically allowed or observed but not yet quantified in NUBASE2020.
Machine learning approach to percolation transitions: global information
Authors: Oh Soo Min , Choi Kwangjong , Kahng B
Published: August 2023

Recently, a machine learning (ML) approach has been proposed to determine the percolation threshold and critical behaviors of percolation transitions (PTs), based on the ML algorithm used for the phase transition in thermal equilibrium systems. However, we have observed that the conventional ML approach used for thermal systems does not accurately provide the percolation threshold, in particular when the training regions for ML are asymmetrical with respect to its known value. Here, we remark that percolation is a geometric phase transition, and thus global information, rather than the local configurations used in thermal systems, is needed to determine the percolation threshold. To address this, we assign a parent node index to each node, which is updated during cluster merging, capturing global information on the ancestor of each node. Utilizing this quantity as input data for the convolutional neural network in the ML algorithm, we successfully obtain the correct percolation threshold regardless of whether the training regions are symmetric or asymmetric with respect to the known value. This validity holds independently of the PT type: continuous, hybrid, or discontinuous. As the concept of percolation is applied to various phenomena, this ML algorithm could be used ubiquitously.
Breast Cancer Classification using Random Forest Algorithm
Authors: Batool Amreen , Byun Yung-Cheol
Published: August 2023

This study uses detect breast cancer based on Random Forest (RF). It is crucial to diagnose the illness to identify treatment solutions closely linked to patient safety. Breast cancer is diagnosed using past medical records and various classification methods used in data mining fields today. Each technique performs differently depending on the input feature types and model parameters. Neutral Networks have been proven to be more effective in data analysis and pre-diagnosis without requiring medical knowledge. The study reduces diagnostic variance and increases diagnostic accuracy by overcoming the limitation of individual models. The Random Forest model had a training and validation accuracy of 90% and 91%.
Wired-Wireless Hierarchical Sensor Network using Zero power Sensor Node
Authors: Yamawaki Akira , Miyauchi Makoto , Serikawa Seiichi
Published: August 2023

The wireless sensor network, WSN, is a promising technology to make our social life better. However, the maintenance of the battery attached to each sensor node avoids WSN widely be used. The zero standby-power sensor node (ZSSN) extends battery life by eliminating standby power, but they impose high cost and maintenance burdens because each node has its own battery and wireless module. This paper proposes a wired-wireless hierarchical sensor network consisting of a small network group of ZPSNs (Zero power sensor node) with large capacitor as power supply that are wired together, and the parent node has a wireless module and an energy harvester. The proposed WSN can suppress the number of energy harvesters and wireless modules to that of groups. There are no batteries by replaced to the capacitors. That is, our WSN can reduce the maintenance and cost caused by which there is no battery, and each only parent node has wireless module and energy harvester. The experimental result shows that the standby ZPSN can keep enough voltage 48 days on the large capacitor to operate in active mode correctly.
Arctic coastal hazard assessment considering permafrost thaw subsidence, coastal erosion, and flooding
Authors: Wang Ziyi , Xiao Ming , Nicolsky Dmitry , Romanovsky Vladimir , McComb Christopher , Farquharson Louise
Published: August 2023

The thawing of permafrost in the Arctic has led to an increase in coastal land loss, flooding, and ground subsidence, seriously threatening civil infrastructure and coastal communities. However, a lack of tools for synthetic hazard assessment of the Arctic coast has hindered effective response measures. We developed a holistic framework, the Arctic Coastal Hazard Index (ACHI), to assess the vulnerability of Arctic coasts to permafrost thawing, coastal erosion, and coastal flooding. We quantified the coastal permafrost thaw potential (PTP) through regional assessment of thaw subsidence using ground settlement index. The calculations of the ground settlement index involve utilizing projections of permafrost conditions, including future regional mean annual ground temperature, active layer thickness, and talik thickness. The predicted thaw subsidence was validated through a comparison with observed long-term subsidence data. The ACHI incorporates the PTP into seven physical and ecological variables for coastal hazard assessment: shoreline type, habitat, relief, wind exposure, wave exposure, surge potential, and sea-level rise. The coastal hazard assessment was conducted for each 1 km2 coastline of North Slope Borough, Alaska in the 2060s under the Representative Concentration Pathway 4.5 and 8.5 forcing scenarios. The areas that are prone to coastal hazards were identified by mapping the distribution pattern of the ACHI. The calculated coastal hazards potential was subjected to validation by comparing it with the observed and historical long-term coastal erosion mean rates. This framework for Arctic coastal assessment may assist policy and decision-making for adaptation, mitigation strategies, and civil infrastructure planning.
Duality of averaging of quantum states over arbitrary symmetry groups revealing Schur–Weyl duality
Authors: Markiewicz Marcin , Przewocki Janusz
Published: August 2023

It is a well-established fact in quantum information theory, that uniform averaging over the collective action of a unitary group on a multipartite quantum state projects the state to a form equivalent to a permutation operator of the subsystems. Hence states equivalent to permutation operators are untouched by collective unitary noise. A trivial observation shows that uniform averaging over permutation operators projects the state into a form with block-diagonal structure equivalent to the one of the collective action of the unitary group. We introduce a name for this property: duality of averaging. The mathematical reason behind this duality is the fact that the collective action of the unitary group on the tensor product state space of a multipartite quantum system and the action of the permutation operations are mutual commutants when treated as matrix algebras. Such pairs of matrix algebras are known as dual reductive pairs. In this work we show, that in the case of finite dimensional quantum systems such duality of averaging holds for any pairs of symmetry groups being dual reductive pairs, regardless of whether they are compact or not, as long as the averaging operation is defined via iterated integral over the Cartan decomposition of the group action. Although our result is very general, we focus much attention on the concrete example of a dual reductive pair consisting of collective action of special linear matrices and permutation operations, which physically corresponds to averaging multipartite quantum states over non-unitary SLOCC-type (Stochastic Local Operations and Classical Communication) operations. In this context we show, that noiseless subsystems known from collective unitary averaging persist in the case of SLOCC averaging in a conditional way: upon postselection to specific invariant subspaces.
Chimera dynamics of generalized Kuramoto–Sakaguchi oscillators in two-population networks
Authors: Lee Seungjae , Krischer Katharina
Published: August 2023

Chimera dynamics, an intriguing phenomenon of coupled oscillators, is characterized by the coexistence of coherence and incoherence, arising from a symmetry-breaking mechanism. Extensive research has been performed in various systems, focusing on a system of Kuramoto–Sakaguchi (KS) phase oscillators. In recent developments, the system has been extended to the so-called generalized Kuramoto model, wherein an oscillator is situated on the surface of an M-dimensional unit sphere, rather than being confined to a unit circle. In this paper, we exploit the model introduced in Tanaka (2014 New. J. Phys.
16 023016) where the macroscopic dynamics of the system was studied using the extended Watanabe–Strogatz transformation both for real and complex spaces. Considering two-population networks of the generalized KS oscillators in 2D complex spaces, we demonstrate the existence of chimera states and elucidate different motions of the order parameter vectors depending on the strength of intra-population coupling. Similar to the KS model on the unit circle, stationary and breathing chimeras are observed for comparatively strong intra-population coupling. Here, the breathing chimera changes their motion upon decreasing intra-population coupling strength via a global bifurcation involving the completely incoherent state. Beyond that, the system exhibits periodic alternation of the two order parameters with weaker coupling strength. Moreover, we observe that the chimera state transitions into a componentwise aperiodic dynamics when the coupling strength weakens even further. The aperiodic chimera dynamics emerges due to the breaking of conserved quantities that are preserved in the stationary, breathing and alternating chimera states. We provide a detailed explanation of this scenario in both the thermodynamic limit and for finite-sized ensembles. Furthermore, we note that an ensemble in 4D real spaces demonstrates similar behavior.
Current-climate sea ice amount and seasonality as constraints for future Arctic amplification
Authors: Linke Olivia , Feldl Nicole , Quaas Johannes
Published: August 2023

The recent Arctic sea ice loss is a key driver of the amplified surface warming in the northern high latitudes, and simultaneously a major source of uncertainty in model projections of Arctic climate change. Previous work has shown that the spread in model predictions of future Arctic amplification (AA) can be traced back to the inter-model spread in simulated long-term sea ice loss. We demonstrate that the strength of future AA is further linked to the current climate’s, observable sea ice state across the multi-model ensemble of the 6th Coupled Model Intercomparison Project (CMIP6). The implication is that the sea-ice climatology sets the stage for long-term changes through the 21st century, which mediate the degree by which Arctic warming is amplified with respect to global warming. We determine that a lower base-climate sea ice extent and sea ice concentration (SIC) in CMIP6 models enable stronger ice melt in both future climate and during the seasonal cycle. In particular, models with lower Arctic-mean SIC project stronger future ice loss and a more intense seasonal cycle in ice melt and growth. Both processes systemically link to a larger future AA across climate models. These results are manifested by the role of climate feedbacks that have been widely identified as major drivers of AA. We show in particular that models with low base-climate SIC predict a systematically stronger warming contribution through both sea-ice albedo feedback and temperature feedbacks in the future, as compared to models with high SIC. From our derived linear regressions in conjunction with observations, we estimate a 21st-century AA over sea ice of 2.47–3.34 with respect to global warming. Lastly, from the tight relationship between base-climate SIC and the projected timing of an ice-free September, we predict a seasonally ice-free Arctic by mid-century under a high-emission scenario.
Evolutionary history of Castanea sativa in the Caucasus driven by Middle and Late Pleistocene paleoenvironmental changes
Authors: Beridze Berika , Sękiewicz Katarzyna , Walas Łukasz , Thomas Peter A , Danelia Irina , Kvartskhava Giorgi , Farzaliyev Vahid , Bruch Angela A , Dering Monika
Published: August 2023

Due to global climate cooling and aridification since the Paleogene, members of the Neogene flora were extirpated from the Northern Hemisphere or were confined to a few refugial areas. For some species, the final reduction/extinction came in the Pleistocene, but some others have survived climatic transformations up to the present. This has occurred in Castanea sativa, a species of high commercial value in Europe and a significant component of the Caucasian forests’ biodiversity. In contrast to the European range, neither the historical biogeography nor the population genetic structure of the species in its isolated Caucasian range has been clarified. Here, based on a survey of 21 natural populations from the Caucasus and a single one from Europe, we provide a likely biogeographic reconstruction and genetic diversity details. By applying Bayesian inference, species distribution modelling and fossil pollen data, we estimated (i) the time of the Caucasian—European divergence during the Middle Pleistocene, (ii) the time of divergence among Caucasian lineages and (iii) outlined the glacial refugia for species. The climate changes related to the Early–Middle Pleistocene Transition are proposed as the major drivers of the intraspecific divergence and European–Caucasian disjunction for the species, while the impact of the last glacial cycle was of marginal importance.
Prediction of drug–protein interaction based on dual channel neural networks with attention mechanism
Authors: Tan Dayu , Jiang Haijun , Li Haitao , Xie Ying , Su Yansen
Published: August 2023

The precise identification of drug–protein inter action (DPI) can significantly speed up the drug discovery process. Bioassay methods are time-consuming and expensive to screen for each pair of drug proteins. Machine-learning-based methods cannot accurately predict a large number of DPIs. Compared with traditional computing methods, deep learning methods need less domain knowledge and have strong data learning ability. In this study, we construct a DPI prediction model based on dual channel neural networks with an efficient path attention mechanism, called DCA-DPI. The drug molecular graph and protein sequence are used as the data input of the model, and the residual graph neural network and the residual convolution network are used to learn the feature representation of the drug and protein, respectively, to obtain the feature vector of the drug and the hidden vector of protein. To get a more accurate protein feature vector, the weighted sum of the hidden vector of protein is applied using the neural attention mechanism. In the end, drug and protein vectors are concatenated and input into the full connection layer for classification. In order to evaluate the performance of DCA-DPI, three widely used public data, Human, C.elegans and DUD-E, are used in the experiment. The evaluation metrics values in the experiment are superior to other relevant methods. Experiments show that our model is efficient for DPI prediction.
A comparison of behavioral paradigms assessing spatial memory in tree shrews
Authors: Li Cheng-Ji , Hui Yi-Qing , Zhang Rong , Zhou Hai-Yang , Cai Xing , Lu Li
Published: August 2023

Impairments in spatial navigation in humans can be preclinical signs of Alzheimer's disease. Therefore, cognitive tests that monitor deficits in spatial memory play a crucial role in evaluating animal models with early stage Alzheimer's disease. While Chinese tree shrews (Tupaia belangeri) possess many features suitable for Alzheimer's disease modeling, behavioral tests for assessing spatial cognition in this species are lacking. Here, we established reward-based paradigms using the radial-arm maze and cheeseboard maze for tree shrews, and tested spatial memory in a group of 12 adult males in both tasks, along with a control water maze test, before and after bilateral lesions to the hippocampus, the brain region essential for spatial navigation. Tree shrews memorized target positions during training, and task performance improved gradually until reaching a plateau in all 3 mazes. However, spatial learning was compromised post-lesion in the 2 newly developed tasks, whereas memory retrieval was impaired in the water maze task. These results indicate that the cheeseboard task effectively detects impairments in spatial memory and holds potential for monitoring progressive cognitive decline in aged or genetically modified tree shrews that develop Alzheimer's disease-like symptoms. This study may facilitate the utilization of tree shrew models in Alzheimer's disease research.
Effects of long-term feeding by spotted lanternfly (Hemiptera: Fulgoridae) on ecophysiology of common hardwood host trees
Authors: Hoover Kelli , Iavorivska Lidiia , Lavely Emily K , Uyi Osariyekemwen , Walsh Brian , Swackhamer Emelie , Johnson Anne , Eissenstat David M
Published: August 2023

While the invasive spotted lanternfly, Lycorma delicatula (White) [Hemiptera: Fulgoridae], continues to expand its range in the United States, there remains a knowledge gap regarding the economic threat that this pest presents to forest ecosystems and production nurseries. L. delicatula uses several common hardwood trees as hosts and a previous study found that short-term feeding can reduce growth of young maple saplings. Herein, long-term feeding over 4 consecutive seasons significantly reduced diameter growth and below-ground starch storage in roots of young silver maples (Acer saccharinum L.), weeping willows (Salix babylonica L.), river birches (Betula nigra L.), and trees of heaven (Ailanthus altissima [Mill.] Swingle) in response to L. delicatula feeding pressure in a density-dependent manner. In Year 3 when feeding pressure was the lowest, silver maple and willow recovered with greater diameter growth than in Year 2. Nutrients essential for photosynthesis and growth (iron, sulfur, and phosphorus) were reduced in leaves of all tree species compared to controls in the second year. This 4-yr study represents a worst-case scenario in which L. delicatula fed on the same trees for 4 consecutive growing seasons. In the wild, population numbers can vary greatly from year to year on individual trees and they move frequently among hosts (until autumn when they settle on A. altissima or other late-season hosts that have not yet senesced). Thus, we would not expect negative impacts of unconfined L. delicatula in natural settings on forest or ornamental trees to be as marked as reported here.
Periodontal outcomes associated with impacted maxillary central incisor and canine teeth following surgical exposure and orthodontic alignment: a systematic review and meta-analysis
Authors: Seehra Jadbinder , Alshammari Aminah , Wazwaz Fidaa , Papageorgiou Spyridon N , Newton Jonathon T , Cobourne Martyn T
Published: August 2023

Background

Maxillary incisor and canine teeth are commonly impacted and require multidisciplinary treatment to accommodate them in the dental arch.

Objectives

To assess the periodontal outcomes of impacted maxillary central incisor and canine teeth, which have been successfully aligned in the arch following surgical exposure and orthodontic traction with fixed appliance therapy.

Search methods

Systematic literature searches without restrictions were undertaken in eight databases.

Selection criteria

Studies reporting surgical interventions in combination with orthodontic traction with fixed appliance therapy to align impacted maxillary incisors or canines published up to January 2023.

Data collection

Duplicate independent study selection, data extraction, and risk of bias assessment.

Analysis

Random-effects meta-analyses of aggregate data.

Results

Twenty-three studies (21 retrospective and 2 prospective) were included in the final analysis. Three studies reported outcomes for maxillary central incisors and 20 reported outcomes for maxillary canines. For maxillary central incisors, all three studies were rated as being at moderate risk of bias. For maxillary canines, 17 studies and 1 study were rated at moderate and high risk of bias, respectively. Both prospective studies were rated at a low risk of bias. Meta-analyses comparing aligned impacted maxillary canines to their non-impacted contralateral counterparts found the former had increased Plaque Index scores (mean difference [MD] 0.19; 95% confidence interval [CI] 0.03, 0.35﻿; P = 0.03), increased clinical attachment loss (MD 0.40 mm; 95% CI 0.17, 0.63﻿; P = 0.01), increased pocket probing depth (MD 0.18 mm; 95% CI 0.07, 0.28﻿; P = 0.001), increased bone loss (MD 0.51 mm; 95% CI 0.31, 0.72﻿; P < 0.001), and reduced keratinized gingival width (MD −0.31 mm; 95% CI −0.61, −0.01﻿; P = 0.04).

Conclusions

Limited evidence suggests that surgical exposure and orthodontic alignment of impacted maxillary central incisor or canine teeth, results in modest adverse effects in the periodontium. These findings should be viewed with caution as our certainty for these outcomes is very low to low due to the bias and heterogeneity. Further well-conducted studies reporting patient centred outcomes are required.

Registration

PROSPERO (CRD42020225639)
Past or Present; Which Exposures Predict Metabolomic Aging Better? The Doetinchem Cohort Study
Authors: Smit Annelot P , Herber Gerrie-Cor M , Kuiper Lieke M , Loef Bette , Picavet H Susan J , Verschuren W M Monique
Published: August 2023

People age differently. Differences in aging might be reflected by metabolites, also known as metabolomic aging. Predicting metabolomic aging is of interest in public health research. However, the added value of longitudinal over cross-sectional predictors of metabolomic aging is unknown. We studied exposome-related exposures as potential predictors of metabolomic aging, both cross-sectionally and longitudinally in men and women. We used data from 4 459 participants, aged 36–75 of Round 4 (2003–2008) of the long-running Doetinchem Cohort Study (DCS). Metabolomic age was calculated with the MetaboHealth algorithm. Cross-sectional exposures were demographic, biological, lifestyle, and environmental at Round 4. Longitudinal exposures were based on the average exposure over 15 years (Round 1 [1987–1991] to 4), and trend in these exposure over time. Random Forest was performed to identify model performance and important predictors. Prediction performances were similar for cross-sectional and longitudinal exposures in both men (R2 6.8 and 5.8, respectively) and women (R2 14.8 and 14.4, respectively). Biological and diet exposures were most predictive for metabolomic aging in both men and women. Other important predictors were smoking behavior for men and contraceptive use and menopausal status for women. Taking into account history of exposure levels (longitudinal) had no added value over cross-sectionally measured exposures in predicting metabolomic aging in the current study. However, the prediction performances of both models were rather low. The most important predictors for metabolomic aging were from the biological and lifestyle domain and differed slightly between men and women.
Study on the influence of digital financial inclusion on agricultural carbon emission efficiency in the Yangtze River Economic Belt
Authors: Jin Shengtian , Chen Zhuo , Bao Bingfei , Zhang Xinming
Published: August 2023

Improving the efficiency of agricultural carbon emission is an inevitable choice for high-quality sustainable development. As a new financial intermediary, what impact does the growth of digital financial inclusion have on the efficiency of agricultural carbon emissions? This paper uses the SBM-ML model to calculate the agricultural carbon emission efficiency of 110 prefecture-level cities in the Yangtze River Economic Belt from 2012 to 2020. Then, it analyzes its temporal and spatial evolution trend. Based on it, the panel regression model is used to analyze how the growth of digital financial inclusion affects agricultural carbon emission efficiency. Results show the following: (1) from the time dimension, the efficiency generally declined first and then rose with less fluctuations and stability, which is determined by technical efficiency and technological progress change, and from the spatial dimension, the number of cities with agricultural carbon emission efficiency greater than 1.0 is generally increasing, reflecting that the overall level is increasing; and (2) the growth of digital financial inclusion has a negative impact on agricultural carbon emission efficiency. The improvement of agricultural carbon emission efficiency has been hampered by the use depth and digitalization level of digital financial inclusion, but its coverage breadth can support this improvement. This paper aims to advance digital financial inclusive growth and low-carbon transformation of agriculture in China.