bluuebunny/crossref_metadata_2025 huggingface dataset:
Temporal, spatial and spectroscopic study of plasma emission on Cu target in bipolar HiPIMS
Authors: Klein P , Hnilica J , Lundin D , Dvořák P , Zanáška M , Helmersson U , Vašina P
Published: July 2023

Bipolar high power impulse magnetron sputtering introduces new possibilities to affect positive ions created during the negative discharge pulse in order to tailor thin films with specific parameters. This paper studies plasma emission in different experimental conditions during different phases of the positive pulse with spectral, spatial and temporal resolution. It is found that predominantly the working gas gives rise to plasma emission during the positive pulse. The plasma emission is observed only in regions of low magnetic confinement, forming a ‘mushroom-like’ shape in the middle of the target or a ‘dome-like’ shape on the outer parts of the target. An explanation of the discharge kinetics is proposed based on the acquired data.
Amplitude-controllable microwave pulse generator using single-flux-quantum pulse pairs for qubit control
Authors: Shen Hongxiang , Takeuchi Naoki , Yamanashi Yuki , Yoshikawa Nobuyuki
Published: July 2023

To achieve large-scale quantum processors, cryogenic quantum-bit (qubit) interface circuits that can control qubits inside a dilution refrigerator are indispensable. Superconducting single-flux quantum (SFQ) circuits are a promising building block for qubit interface circuits because SFQ circuits can operate with high clock frequencies and low power dissipation. In the present study, we developed an SFQ-based qubit interface circuit that we refer to as a pulse-pair microwave pulse generator (PP-MPG). The PP-MPG can generate microwave pulses for qubit control, with the microwave amplitude controlled based on the delay between paired SFQ pulses. By finely adjusting the delay with delay controlling circuits, the microwave amplitude can be controlled over a wide range. We fabricated a PP-MPG chip and tested it at 4.2 K, showing that the microwave amplitude can be controlled over a range of approximately 30 dB. Our results show that the PP-MPG has the potential for use in future large-scale quantum processors.
Numerical analysis of the mechanical and electrical properties of (RE)BCO tapes with multiple edge cracks
Authors: Ma Jintao , Gao Yuanwen
Published: July 2023

One of the leading causes of critical current degradation in rare-earth barium–copper-oxide tapes is the micro-cracks produced by mechanical slitting. These cracks are scattered near the edge of the tape and vary in length and angle. In this work, a tape model with multiple edge cracks is established. Under tensile loading, the effects of the Poisson ratio, crack length, crack angle, crack spacing, and geometric mutation between cracks on the stress intensity factor are investigated using the extended finite element method (XFEM). Tensile experiments were conducted at room temperature to investigate the crack propagation behavior of tapes with multiple edge cracks. The results show that the stress intensity factor obtained using XFEM is more informative than the analytical solution, which ignores the Poisson effect. The stress intensity factor is sensitive to crack length and angle variations and exhibits an evident jump characteristic when a geometric mutation occurs. The jump level strongly depends on the geometric difference. The jump location is the initiation site for crack propagation, which is consistent with the experiment results. The strain analysis of the tape implies that high-strain regions exist at the crack tip before the tensile strain reaches the irreversible strain limit. The critical strain of crack propagation is closely related to the form of crack distribution. It dominates the irreversible strain limit of critical current degradation, which facilitates understanding the early degradation of critical current. Finally, some engineering suggestions are given.
Structural distortion induced Dzyaloshinskii–Moriya interaction in monolayer CrI3 at heterostructures
Authors: Li Hongxing , Zhang Wei-Bing , Zhou Guanghui
Published: July 2023

The magnetic heterostructures provide flexible ways to realize particular magnetic properties that possess both scientific and practical significance. Here, by first-principles calculation, we predict strong Dzyaloshinskii–Moriya interactions (DMIs) by constructing CrI3/Metal heterostructures. The underlaying mechanisms are ascribed to the large spin-orbital coupling (SOC) of the I atom and the structural distortion in CrI3 layer caused by substrates. This is different from the traditional way that deposit magnetic films on substrate to generate DMI, wherein DMI is dominated by interlayer hybridization and large SOC of substrates. In addition, both Heisenberg exchange and magnetic anisotropy are modulated dramatically, such as Heisenberg exchange is nearly doubled on Au(111), and the out-of-plane magnetism is enhanced by 88% on Ir(111). Our work may provide a experimentally accessible strategy to induce DMI in layered magnetic materials, which will be helpful to the design of spintronics devices.
Analysis of soliton interactions of modified Korteweg-de Vries equation using conserved quantities
Authors: You Xiangcheng , Xu Hang , Sun Qiang
Published: July 2023

In this paper, the conservative quantities are used to develop an approximate method to calculate the merged waveform shape of the solitary waves described by modified Korteweg–de Vries (mKdV) equation. With this method, we can efficiently and effectively capture the physics of the complicated merging phenomena when two solitary waves described by the nonlinear evolution partial differential equation merge at the maximum without the need to solve the equation in detail. This offers a simple and robust tool to analyse the interactions between solitons and to benchmark the results obtained by the asymptotic and numerical methods. It is expected that the approximate analysis demonstrated in this paper can be applied to a series of nonlinear evolution equations to simulate various solitary wave interaction problems. In future, our goal is to extend this simple method to other nonlinear wave evolution phenomena.
A comparative study of structural, electronic, magnetic, and pressure-dependent properties of Full-Heusler Fe2XSi (X=Mn and Co): first-principles calculation and Monte Carlo Simulation
Authors: Aladerah Bilal , Gharaibeh Maen , Obeidat Abdalla , Aledealat Khaled
Published: July 2023

This study investigates the structural, electronic, magnetic, and pressure-dependent properties of Fe2XSi (X=Mn and Co) full-Heusler alloy through a comprehensive computational approach. The structural stability of these alloys confirmed L21 and XA prototypes as favorable structures for Fe2MnSi and Fe2CoSi, respectively. In addition, Fe2MnSi exhibits 100% spin polarization suggesting its potential suitability for spintronics applications. Conversely, Fe2CoSi does not exhibit similar behavior. The calculated magnetic moments of these alloys revealed an increase due to Coulomb interaction (U). The magnetic moments satisfy the Slater-Pauling relation, with calculated values of 3

μ

B

for Fe2MnSi and 5

μ

B

for Fe2CoSi. Heisenberg exchange interaction parameters are calculated to illustrate distinct magnetic interactions within the alloys. The study further explores thermomagnetic properties through Monte Carlo simulations, including thermal magnetization, thermal magnetic susceptibility, and Curie temperature

T

C

.

The calculated

T

C

were found to be 294 K for Fe2MnSi and 1029 K for Fe2CoSi, showing close agreement with experimental data. We additionally investigate the pressure-dependent properties of these alloys, revealing a non-linear dependence of the band gap on pressure for Fe2MnSi, with values decreasing from 0.668 eV to 0.259 eV as pressure increased from −15.917 to 23.712 GPa. For Fe2CoSi, the band gap remained zero across varying pressure conditions, indicating its metallic conducting behavior.
Estimates for negative eigenvalues of Schrödinger operators on unbounded fractal spaces
Authors: Tang Wei , Wang Zhiyong
Published: July 2023

We study an asymptotic formula for the number of negative eigenvalues of Schrödinger operators on unbounded fractal spaces, which admit a cellular decomposition. We first give some sufficient conditions for Weyl-type asymptotic formula to hold. Second, we verify these conditions for the infinite blowup of Sierpiński gasket and unbounded generalized Sierpiński carpets. Finally, we demonstrate how the result can be applied to the infinite blowup of certain fractals associated with iterated function systems with overlaps, including those defining the classical infinite Bernoulli convolution with golden ratio.
Are good leaders truly good?
Authors: Cato Susumu , Inoue Akira
Published: July 2023

This paper offers a new insight on the Condorcet Jury Theorem (CJT) in the theory of epistemic democracy. This theorem states that democratic decision-making leads us to correct outcomes under certain assumptions. One key assumption is the ‘independence condition’, which requires that voters form their beliefs independently when they vote. This paper examines the role of an opinion leader as an informational source, which potentially violates independence. We demonstrate that voters’ beliefs may be correlated in the presence of the leader, and that the CJT can fail if the leader’s opinions are reliable. This leads us to the following paradoxical observation: for epistemic democracy, good leaders may be bad, while bad leaders may be good.
Daptomycin Exposure as a Risk Factor for Daptomycin-Induced Eosinophilic Pneumonia and Muscular Toxicity
Authors: Garreau Romain , Pham Truong-Thanh , Bourguignon Laurent , Millet Aurélien , Parant François , Bussy David , Desevre Marine , Franchi Victor , Ferry Tristan , Goutelle Sylvain
Published: July 2023

Background

High-dose daptomycin is increasingly used in patients with bone and joint infection (BJI). This raises concerns about a higher risk of adverse events (AEs), including daptomycin-induced eosinophilic pneumonia (DIEP) and myotoxicity. We aimed to examine pharmacokinetic and other potential determinants of DIEP and myotoxicity in patients with BJI receiving daptomycin.

Methods

All patients receiving daptomycin for BJI were identified in a prospective cohort study. Cases were matched at a 1:3 ratio, with controls randomly selected from the same cohort. Bayesian estimation of the daptomycin daily area under the concentration-time curve over 24 hours (AUC24h) was performed with the Monolix software based on therapeutic drug monitoring (TDM) data. Demographic and biological data were also collected. Risk factors of AEs were analyzed using Cox proportional hazards model.

Results

From 1130 patients followed over 7 years, 9 with DIEP, 26 with myotoxicity, and 106 controls were included in the final analysis. Daptomycin AUC24h, C-reactive protein, and serum protein levels were associated with the risk of AEs. The adjusted hazard ratio of DIEP or myotoxicity was 3.1 (95% confidence interval [CI], 1.48–6.5; P < .001) for daptomycin AUC24h > 939 mg/h/L, 9.8 (95% CI, 3.94–24.5; P < .001) for C-reactive protein > 21.6 mg/L, and 2.4 (95% CI, 1.02–5.65; P = .04) for serum protein <72 g/L.

Conclusions

We identified common determinants of DIEP and myotoxicity in patients with BJI. Because the risk of AEs was associated with daptomycin exposure, daptomycin TDM and model-informed precision dosing may help optimize the efficacy and safety of daptomycin treatment in this setting. A target AUC24h range of 666 to 939 mg/h/L is suggested.
Using artificial intelligence to learn optimal regimen plan for Alzheimer’s disease
Authors: Bhattarai Kritib , Rajaganapathy Sivaraman , Das Trisha , Kim Yejin , Chen Yongbin ,   The Alzheimer’s Disease Neuroimaging Initiative,   The Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing, Dai Qiying , Li Xiaoyang , Jiang Xiaoqian , Zong Nansu
Published: July 2023

Background

Alzheimer’s disease (AD) is a progressive neurological disorder with no specific curative medications. Sophisticated clinical skills are crucial to optimize treatment regimens given the multiple coexisting comorbidities in the patient population.

Objective

Here, we propose a study to leverage reinforcement learning (RL) to learn the clinicians’ decisions for AD patients based on the longitude data from electronic health records.

Methods

In this study, we selected 1736 patients from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. We focused on the two most frequent concomitant diseases—depression, and hypertension, thus creating 5 data cohorts (ie, Whole Data, AD, AD-Hypertension, AD-Depression, and AD-Depression-Hypertension). We modeled the treatment learning into an RL problem by defining states, actions, and rewards. We built a regression model and decision tree to generate multiple states, used six combinations of medications (ie, cholinesterase inhibitors, memantine, memantine-cholinesterase inhibitors, hypertension drugs, supplements, or no drugs) as actions, and Mini-Mental State Exam (MMSE) scores as rewards.

Results

Given the proper dataset, the RL model can generate an optimal policy (regimen plan) that outperforms the clinician’s treatment regimen. Optimal policies (ie, policy iteration and Q-learning) had lower rewards than the clinician’s policy (mean −3.03 and −2.93 vs. −2.93, respectively) for smaller datasets but had higher rewards for larger datasets (mean −4.68 and −2.82 vs. −4.57, respectively).

Conclusions

Our results highlight the potential of using RL to generate the optimal treatment based on the patients’ longitude records. Our work can lead the path towards developing RL-based decision support systems that could help manage AD with comorbidities.
Quantile autoregressive conditional heteroscedasticity
Authors: Zhu Qianqian , Tan Songhua , Zheng Yao , Li Guodong
Published: July 2023

This article proposes a novel conditional heteroscedastic time series model by applying the framework of quantile regression processes to the ARCH(∞) form of the GARCH model. This model can provide varying structures for conditional quantiles of the time series across different quantile levels, while including the commonly used GARCH model as a special case. The strict stationarity of the model is discussed. For robustness against heavy-tailed distributions, a self-weighted quantile regression (QR) estimator is proposed. While QR performs satisfactorily at intermediate quantile levels, its accuracy deteriorates at high quantile levels due to data scarcity. As a remedy, a self-weighted composite quantile regression estimator is further introduced and, based on an approximate GARCH model with a flexible Tukey-lambda distribution for the innovations, we can extrapolate the high quantile levels by borrowing information from intermediate ones. Asymptotic properties for the proposed estimators are established. Simulation experiments are carried out to access the finite sample performance of the proposed methods, and an empirical example is presented to illustrate the usefulness of the new model.
Endoreduplication in plant organogenesis: a means to boost fruit growth
Authors: Tourdot Edouard , Mauxion Jean-Philippe , Gonzalez Nathalie , Chevalier Christian
Published: July 2023

Endoreduplication is the major source of somatic endopolyploidy in higher plants, and leads to variation in cell ploidy levels due to iterative rounds of DNA synthesis in the absence of mitosis. Despite its ubiquitous occurrence in many plant organs, tissues, and cells, the physiological meaning of endoreduplication is not fully understood, although several roles during plant development have been proposed, mostly related to cell growth, differentiation, and specialization via transcriptional and metabolic reprogramming. Here, we review recent advances in our knowledge of the molecular mechanisms and cellular characteristics of endoreduplicated cells, and provide an overview of the multi-scale effects of endoreduplication on supporting growth in plant development. In addition, the effects of endoreduplication in fruit development are discussed, since it is highly prominent during fruit organogenesis where it acts as a morphogenetic factor supporting rapid fruit growth, as illustrated by case of the model fleshy fruit, tomato (Solanum lycopersicum).
Galactic coronae in Milky Way-like galaxies: the role of stellar feedback in gas accretion
Authors: Barbani Filippo , Pascale Raffaele , Marinacci Federico , Sales Laura V , Vogelsberger Mark , Torrey Paul , Li Hui
Published: July 2023

Star-forming galaxies like the Milky Way are surrounded by a hot gaseous halo at the virial temperature – the so-called galactic corona – that plays a fundamental role in their evolution. The interaction between the disc and the corona has been shown to have a direct impact on accretion of coronal gas onto the disc with major implications for galaxy evolution. In this work, we study the gas circulation between the disc and the corona of star-forming galaxies like the Milky Way. We use high-resolution hydrodynamical N-body simulations of a Milky Way-like galaxy with the inclusion of an observationally motivated galactic corona. In doing so, we use SMUGGLE, an explicit interstellar medium (ISM), and stellar feedback model coupled with the moving-mesh code arepo. We find that the reservoir of gas in the galactic corona is sustaining star formation: the gas accreted from the corona is the primary fuel for the formation of new stars, helping in maintaining a nearly constant level of cold gas mass in the galactic disc. Stellar feedback generates a gas circulation between the disc and the corona (the so-called galactic fountain) by ejecting different gas phases that are eventually re-accreted onto the disc. The accretion of coronal gas is promoted by its mixing with the galactic fountains at the disc–corona interface, causing the formation of intermediate temperature gas that enhances the cooling of the hot corona. We find that this process acts as a positive feedback mechanism, increasing the accretion rate of coronal gas onto the galaxy.
3D hydrodynamic simulations of massive main-sequence stars – I. Dynamics and mixing of convection and internal gravity waves
Authors: Herwig Falk , Woodward Paul R , Mao Huaqing , Thompson William R , Denissenkov Pavel , Lau Josh , Blouin Simon , Andrassy Robert , Paul Adam
Published: July 2023

We performed 3D hydrodynamic simulations of the inner $\approx 50{{\ \rm per\ cent}}$ radial extent of a $25\,\,\mathrm{\mathrm{M}_\odot }$ star in the early phase of the main sequence and investigate core convection and internal gravity waves in the core-envelope boundary region. Simulations for different grid resolutions and driving luminosities establish scaling relations to constrain models of mixing for 1D applications. As in previous works, the turbulent mass entrainment rate extrapolated to nominal heating is unrealistically high ($1.58\times 10^{-4}\,\,\mathrm{\mathrm{M}_\odot \, {\mathrm{yr}}^{-1}}$), which is discussed in terms of the non-equilibrium response of the simulations to the initial stratification. We measure quantitatively the effect of mixing due to internal gravity waves excited by core convection interacting with the boundary in our simulations. The wave power spectral density as a function of frequency and wavelength agrees well with the GYRE eigenmode predictions based on the 1D spherically averaged radial profile. A diffusion coefficient profile that reproduces the spherically averaged abundance distribution evolution is determined for each simulation. Through a combination of eigenmode analysis and scaling relations it is shown that in the N2-peak region, mixing is due to internal gravity waves and follows the scaling relation DIGW-hydro ∝ L4/3 over a $\gtrapprox 2\,\,\mathrm{\mathrm{dex}}$ range of heating factors. Different extrapolations of the mixing efficiency down to nominal heating are discussed. If internal gravity wave mixing is due to thermally enhanced shear mixing, an upper limit is $D_\mathrm{IGW}\lessapprox 2$ to $3\times 10^{4}\,\,\mathrm{cm^2\, s^{-1}}$ at nominal heating in the N2-peak region above the convective core.
Sums of singular series with large sets and the tail of the distribution of primes
Authors: Kuperberg Vivian
Published: July 2023

In 1976, Gallagher showed that the Hardy–Littlewood conjectures on prime k-tuples imply that the distribution of primes in log-size intervals is Poissonian. He did so by computing average values of the singular series constants over different sets of a fixed size k contained in an interval $[1,h]$ as $h \to \infty$, and then using this average to compute moments of the distribution of primes. In this paper, we study averages where k is relatively large with respect to h. We then apply these averages to the tail of the distribution. For example, we show, assuming appropriate Hardy–Littlewood conjectures and in certain ranges of the parameters, the number of intervals $[n,n +\lambda \log x]$ with $n\le x$ containing at least k primes is $\ll x\exp(-k/(\lambda {\rm e}))$.
Autoimmune diseases exhibit shared alterations in the gut microbiota
Authors: Wang Tianjiao , Sternes Peter R , Guo Xue-Kun , Zhao Huiying , Xu Congmin , Xu Huji
Published: July 2023

Objective

Accumulating evidence from microbial studies have highlighted the modulatory roles of intestinal microbes in numerous human diseases, however, the shared microbial signatures across different diseases remain relatively unclear.

Methods

To consolidate existing knowledge across multiple studies, we performed meta-analyses of 17 disease types, covering 34 case–control datasets of 16S rRNA sequencing data, to identify shared alterations among different diseases. Furthermore, the impact of a microbial species, Lactobacillus salivarius, was established in a dextran sodium sulphate–induced colitis model and a collagen type II–induced arthritis mouse model.

Results

Microbial alterations among autoimmune diseases were substantially more consistent compared with that of other diseases (cancer, metabolic disease and nervous system disease), with microbial signatures exhibiting notable discriminative power for disease prediction. Autoimmune diseases were characterized by the enrichment of Enterococcus, Veillonella, Streptococcus and Lactobacillus and the depletion of Ruminococcus, Gemmiger, Oscillibacter, Faecalibacterium, Lachnospiracea incertae sedis, Anaerostipes, Coprococcus, Alistipes, Roseburia, Bilophila, Barnesiella, Dorea, Ruminococcus2, Butyricicoccus, Phascolarctobacterium, Parabacteroides and Odoribacter, among others. Functional investigation of L. salivarius, whose genus was commonly enriched in numerous autoimmune diseases, demonstrated protective roles in two separate inflammatory mouse models.

Conclusion

Our study highlights a strong link between autoimmune diseases and the gut microbiota, with notably consistent microbial alterations compared with that of other diseases, indicating that therapeutic strategies that target the gut microbiome may be transferable across different autoimmune diseases. Functional validation of L. salivarius highlighted that bacterial genera associated with disease may not always be antagonistic, but may represent protective or adaptive responses to disease.
Perceptions of the Availability of Personal Protective Equipment and Its Association With Burnout Among US Healthcare Personnel During the SARS-CoV-2 Pandemic, 2020–2021
Authors: Green-McKenzie Judith , Shofer Frances S. , Lappin Maura , Cohen Erik , O’Connor Daniel , Kuter Barbara J.
Published: July 2023

Objective

The aim of the study is to explore associations among personal protective equipment (PPE) availability, workplace environment, and burnout among US healthcare personnel during the COVID-19 pandemic.

Methods

The study used an online healthcare provider (HCP) survey (December 2020–February 2021) regarding PPE confidence, availability, burnout, and workplace environment.

Results

Lack of appropriate PPE was reported by 27% of 799 US HCP surveyed. Burnout, reported by 77% of HCP, was more likely among females, those with fewer years of professional experience, and those with a higher desire to quit, and less likely for those who perceived PPE was adequate or their employer took all steps to minimize workplace risks.

Conclusions

This study suggests that lack of adequate PPE can lead to HCP burnout, which may result in employees quitting. A pandemic preparedness plan that includes adequate PPE is essential for HCP well-being, patient health, and employer fiscal health.
Labour's Politics of Anti‐Neoliberalism from Corbyn to Starmer
Authors: Webb Niles
Published: July 2023

Many see the Labour leader, Keir Starmer, as a new Tony Blair, taking the party rightward to gain electability. However, Labour under Starmer has advanced a politics of anti‐neoliberalism like that of Jeremy Corbyn and John McDonnell. As Shadow Chancellor, McDonnell developed a critique of neoliberalism which he holds responsible for widening inequality, the 2008 financial crash and its aftermath. Key members of Starmer's Shadow Cabinet agree with this diagnosis and have advanced similar ideas to reform neoliberalism, embracing a decentralised, communitarian socialism which involves large‐scale structural reform. Whilst Shadow ministers’ politics of anti‐neoliberalism has been rendered more culturally conservative by recent populist victories, it reveals fundamental continuities between Corbyn's and Starmer's Labour in a shared scepticism of globalisation. Labour under Starmer is best understood as a party aspiring to restructure an economic model perceived to have failed. In that sense, it differs markedly from New Labour.
Social Security Disability Insurance and intergenerational economic mobility
Authors: Jajtner Katie , Messel Matt , Fletcher Jason
Published: July 2023

Economic opportunity in the United States is shaped by parental health and disability. We hypothesize that Disability Insurance (DI) may mitigate the observed pattern. Using linked survey and administrative data, we find children of work‐limited parents have 4.1 percentiles less upward economic mobility and 4.3 percentiles more downward mobility relative to children of non‐limited parents. Despite poorer health, children of parents initially awarded DI experience a negligible mobility gap relative to peers whose parents never apply to DI and 3.6 percentiles more upward mobility than peers of parents who are initially denied benefits—suggesting DI may moderate economic mobility.
Nomogram predicting overall survival of stage IIIB non‐small‐cell lung cancer patients based on the SEER database
Authors: Li Ziye , Shi Pingfan , Qin Chenge , Zhang Wen , Lin Shumeng , Zheng Tiansheng , Li Ming , Fan Lihong
Published: July 2023

Purpose

We aimed to evaluate the prognostic value of stage IIIB non‐small‐cell (NSCLC) lung cancer patients and to construct a nomogram to effectively predict their overall survival (OS).

Methods

In total, 4323 patients with stage IIIB NSCLC diagnosed between 1975 and 2018 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Multiple prognostic factors were combined to construct a nomogram for predicting OS of patients with stage IIIB NSCLC. The discrimination and calibration of the nomogram were evaluated by C‐indexes and calibration curves. The nomogram was evaluated for predictive ability using receiver operating characteristic (ROC) curves, decision curve analysis curve (DCA), and clinical impact curve (CIC).

Results

The nomogram was built on data of 4323 patients with stage IIIB NSCLC and consisted of the following prognostic factors: age, race, sex, primary labeled, pathology, T stage, whether to receive surgery, whether to receive radiotherapy, and whether to receive chemotherapy. The C‐index in the training and validation sets for the nomogram was 0.672 (95% CI: 0.661–0.683) and 0.675 (95% CI: 0.656–0.694), respectively. According to scores of the nomogram, patients in the complete set, validation set, and training set were classified into two risk groups, low risk and high risk.

Conclusions

We developed the first validated nomogram to estimate the OS of patients with stage IIIB NSCLC. The nomogram was based on nine prognostic factors and provided an individualized risk estimate of 3‐year and 5‐year OS survival in patients with stage IIIB NSCLC.
Why look at dead animals?
Authors: Coughlin Maura
Published: July 2023

Lion Attacking a Dromedary was a sensational object for its first viewers at the Paris Universal Exposition in 1867. As an entity or thing, it provoked a powerfully visceral response and, as the current essay explores, it remains a difficult object to view or display today. As we now know, the Verreaux brothers embedded human remains in the figure of the rider that had formerly been assumed to be just a clothed mannequin. (I have elected to exclude any image of this controversial diorama containing human and other animal remains because it is not necessary for this theoretical inquiry). This essay suggests that theoretical tools derived from Material Ecocriticism and Monster Theory that may help us to think about, or alongside, the affective power of this disturbing taxidermy assemblage, ever aware that this piece draws its power from the theatrical, colonial violence of extraction and extinction.
…And the pursuit of happiness: International migratory flows and countries' subjective well‐being
Authors: Navarro‐Azorín José Miguel , Ramos‐Parreño José María
Published: July 2023

This research considers observed migratory flows as a source of information for the preferences of individuals. Using data on global migration flows from 2005 onwards, the extent to which the structure of the international migration system is consistent with an implicit ranking of countries is examined. Moreover, by assuming that migrants' decision‐making is guided by utility maximization, we interpret the scores of the ranking as a measure of subjective well‐being or happiness. After this, the estimated scores are associated with a set of factors usually considered key drivers of happiness. Empirical results suggest that income is the most relevant predictor of happiness and this relationship is non‐linear.
Cross‐Border Knowledge Transfer in the Digital Age: The Final Curtain Call for Long‐Term International Assignments?
Authors: Bucher Jana , Bader Benjamin , Deller Jürgen
Published: July 2023

Digital technology has altered how multinational companies (MNCs) transfer knowledge across borders. With digital communication media (DCM), knowledge exchange can become more cost‐effective, thereby reducing the need for face‐to‐face exchange. DCM's influence on long‐term international assignment management for cross‐border knowledge transfer remains unclear. Based on 71 interviews with German human resource (HR) managers and subsidiary HR counterparts, we investigated the use of DCM to exchange knowledge across country borders. Exploring these conditions alongside HR managers’ unique perspective on global mobility management prior to and during the global COVID‐19 pandemic, we present two major findings. First, 12 facilitating conditions are necessary for digital knowledge transfer across borders to be accepted as a valuable alternative to long‐term international assignments. Second, we identified individual connections between facilitating conditions and found that five conditions decreased in relevance, while the remaining seven became core aspects of successful digital knowledge transfer during COVID‐19 and possibly beyond.
Cognitive and executive impairments in Parkinson’s disease psychosis: a Bayesian meta-analysis
Authors: Pisani Sara , Gosse Luca , Wieretilo Rita , Ffytche Dominic , Velayudhan Latha , Bhattacharyya Sagnik
Published: July 2023

Background

Cognitive and executive deficits lead to worsening of quality of life and are a risk factor for developing dementia in people with Parkinson’s disease (PD) with psychosis (PDP). However, which key cognitive domains are differentially affected in PDP compared with those without (PDnP), remains unclear. Here, we examined this using a Bayesian meta-analytical approach.

Methods

Searches were conducted on PubMed, Web of Science, SCOPUS, Medline and PsycINFO. Hedges’ g effect-size estimates were extracted from eligible studies as a measure of standard mean differences between PDP and PDnP participants. Meta-analyses were conducted separately for each cognitive domain and subdomain, we examined the effect of age, PD medications, PD duration and severity, depression and psychosis severity for all major domains with meta-regressions.

Results

Effect-size estimates suggest worse performance on all major domains (k=105 studies) in PDP compared with PDnP participants, with global cognition (k=103 studies, g=−0.57), processing speed (k=29 studies, g=−0.58), executive functions (k=33, g=−0.56), episodic memory (k=30 studies, g=−0.58) and perception (k=34 studies, g=−0.55) as the most likely affected domains. Age, depression and PD duration had moderating effects on task-related performance across most of the major nine domains.

Conclusions

We report extensive deficits across nine domains as well as subdomains in PD psychosis, with global cognition, processing speed and executive functions as the most likely impaired. The presence of depression may influence task-related performance in PDP, alongside age and PD duration, but not dose of dopamine replacement treatments.
Analysis of complex chemotaxis models
Authors: Tao Youshan , Winkler Michael
Published: July 2023

This preface describes motivational aspects related to a special issue focusing on “analysis of complex chemotaxis models”, and briefly discusses the contributions provided by the six papers contained therein.
Stone Knives and Bear Skins
Authors: Neville-Neil George V.
Published: July 2023

If you look at the software tooling landscape, you see that the majority of developers work with either open-source tools; or tools from the recently reformed home of proprietary software, Microsoft, which has figured out that its Visual Studio Code system is a good way to sucker people into working with its platforms; or finally Apple, whose tools are meant only for its platform. In specialized markets, such as deeply embedded, military, and aerospace, there are proprietary tools that are often far worse than their open-source cousins, because the market for such tools is small but lucrative.
Syntactic-Informed Graph Networks for Sentence Matching
Authors: Xu Chen , Xu Jun , Dong Zhenhua , Wen Ji-Rong
Published: July 2023

Matching two natural language sentences is a fundamental problem in both natural language processing and information retrieval. Preliminary studies have shown that the syntactic structures help improve the matching accuracy, and different syntactic structures in natural language are complementary to sentence semantic understanding. Ideally, a matching model would leverage all syntactic information. Existing models, however, are only able to combine limited (usually one) types of syntactic information due to the complex and heterogeneous nature of the syntactic information. To deal with the problem, we propose a novel matching model, which formulates sentence matching as a representation learning task on a syntactic-informed heterogeneous graph. The model, referred to as SIGN (Syntactic-Informed Graph Network), first constructs a heterogeneous matching graph based on the multiple syntactic structures of two input sentences. Then the graph attention network algorithm is applied to the matching graph to learn the high-level representations of the nodes. With the help of the graph learning framework, the multiple syntactic structures, as well as the word semantics, can be represented and interacted in the matching graph and therefore collectively enhance the matching accuracy. We conducted comprehensive experiments on three public datasets. The results demonstrate that SIGN outperforms the state of the art and also can discriminate the sentences in an interpretable way.
CLIP-guided StyleGAN Inversion for Text-driven Real Image Editing
Authors: Baykal Ahmet Canberk , Anees Abdul Basit , Ceylan Duygu , Erdem Erkut , Erdem Aykut , Yuret Deniz
Published: July 2023

Researchers have recently begun exploring the use of StyleGAN-based models for real image editing. One particularly interesting application is using natural language descriptions to guide the editing process. Existing approaches for editing images using language either resort to instance-level latent code optimization or map predefined text prompts to some editing directions in the latent space. However, these approaches have inherent limitations. The former is not very efficient, while the latter often struggles to effectively handle multi-attribute changes. To address these weaknesses, we present CLIPInverter, a new text-driven image editing approach that is able to efficiently and reliably perform multi-attribute changes. The core of our method is the use of novel, lightweight text-conditioned adapter layers integrated into pretrained GAN-inversion networks. We demonstrate that by conditioning the initial inversion step on the Contrastive Language-Image Pre-training (CLIP) embedding of the target description, we are able to obtain more successful edit directions. Additionally, we use a CLIP-guided refinement step to make corrections in the resulting residual latent codes, which further improves the alignment with the text prompt. Our method outperforms competing approaches in terms of manipulation accuracy and photo-realism on various domains including human faces, cats, and birds, as shown by our qualitative and quantitative results.
Genomic analysis of Enterococcus faecium strain RAOG174 associated with acute chorioamnionitis carried antibiotic resistance gene: is it time for precise microbiological identification for appropriate antibiotic use?
Authors: Pongchaikul Pisut , Romero Roberto , Mongkolsuk Paninee , Vivithanaporn Pornpun , Wongsurawat Thidathip , Jenjaroenpun Piroon , Nitayanon Perapon , Thaipisuttikul Iyarit , Kamlungkuea Threebhorn , Singsaneh Arunee , Santanirand Pitak , Chaemsaithong Piya
Published: July 2023

Background

Preterm labor syndrome is associated with high perinatal morbidity and mortality, and intra-amniotic infection is a cause of preterm labor. The standard identification of causative microorganisms is based on the use of biochemical phenotypes, together with broth dilution-based antibiotic susceptibility from organisms grown in culture. However, such methods could not provide an accurate epidemiological aspect and a genetic basis of antimicrobial resistance leading to an inappropriate antibiotic administration. Hybrid genome assembly is a combination of short- and long-read sequencing, which provides better genomic resolution and completeness for genotypic identification and characterization. Herein, we performed a hybrid whole genome assembly sequencing of a pathogen associated with acute histologic chorioamnionitis in women presenting with PPROM.

Results

We identified Enterococcus faecium, namely E. faecium strain RAOG174, with several antibiotic resistance genes, including vancomycin and aminoglycoside. Virulence-associated genes and potential bacteriophage were also identified in this genome.

Conclusion

We report herein the first study demonstrating the use of hybrid genome assembly and genomic analysis to identify E. faecium ST17 as a pathogen associated with acute histologic chorioamnionitis. The analysis provided several antibiotic resistance-associated genes/mutations and mobile genetic elements. The occurrence of E. faecium ST17 raised the awareness of the colonization of clinically relevant E. faecium and the carrying of antibiotic resistance. This finding has brought the advantages of genomic approach in the identification of the bacterial species and antibiotic resistance gene for E. faecium for appropriate antibiotic use to improve maternal and neonatal care.
Rhomboid intercostal block versus serratus block for postoperative analgesia after thoracoscopic sympathectomy for primary palmar hyperhidrosis: a randomized controlled trial
Authors: Elhouty Mohamed G. , Elbahrawy Khaled , Elawady Mostafa S.
Published: July 2023

Background

Although thoracoscopic sympathectomy is made via small incisions, it is associated with severe postoperative pain. Both Rhomboid intercostal block (RIB) and serratus anterior plane block (SABP) are recent techniques used for pain control after such procedures. Herein, we compared RIB and SAPB regarding pain control in patients undergoing thoracoscopic sympathectomy for palmar hyperhidrosis.

Patients and methods

Three groups were enrolled in this prospective randomized study (71 patients in each group); Group S received SAPB, Group R received RIB and Group C as controls. The block procedures were performed after general anesthesia and prior to the skin incision.

Results

The three groups showed comparable demographics and operative time (P ˃ 0.05). Pain scores showed a significant decline with the two block procedures compared to controls during the first day following surgery (both P ˂ 0.05), but Group R had better scores compared to Group S. Both block techniques were associated with a significant prolongation of the time to first rescue analgesic and less fentanyl consumption compared to controls (both P ˂ 0.05). However, both parameters were improved with RIB rather than SAPB (both P ˂ 0.05). Both blocks led to a significant improvement in patient satisfaction than in the control group (both P ˂ 0.05), but it was comparable between the two approaches (P ˃ 0.05).

Conclusion

Both RIB and SAPB are safe and effective in pain reduction after thoracoscopic sympathectomy procedures in patients with hyperhidrosis. Moreover, RIB is superior to SAPB as it is associated with better analgesic outcomes.

Trial registration

Pan African Trial Registry PACTR202203766891354. https://pactr.samrc.ac.za/Researcher/TrialRegister.aspx?TrialID=21522
Barriers and facilitators of adherence to awake prone positioning: a qualitative study using the COM-B model
Authors: Zhu Lingli , Ni Zijun , Zhang Yuping , Zhan Yang , Lan Meijuan , Zhao Ruiyi
Published: July 2023

Background

Awake prone positioning (APP) is a recommended therapy for non-intubated ARDS patients, but adherence can be challenging. Understanding the barriers and facilitators of adherence to APP is essential to increase the adherence of therapy and improve patient outcomes. The objective of this study was to explore the barriers and facilitators of adherence to awake prone ventilation using a qualitative approach and the Capability, Opportunity, Motivation-Behavior (COM-B) model.

Methods

Semi-structured, in-depth interviews were conducted with patients involved in awake prone ventilation. Data were analyzed using an adapted inductive thematical approach and mapped onto the COM-B model to identify barriers and facilitators to adherence of APP.

Results

Nineteen patients were interviewed (aged 55–92 years). Fifteen themes were identified and mapped directly on to the six COM-B constructs, with “physical challenges” related to physical capability being the primary barrier. These COM-B sub-items reflected five other barriers, including low self-efficacy(M), treatment environment(O), availability of time(O), misconceptions about the treatment(C), and insufficient knowledge(C). Key facilitators in adhering to APP were ability to identify and overcome obstacles(C), availability and affordability of treatment(O), family influences(O), beliefs and trust in treatment(M), fear about the disease(M), and perceived benefits(M). In addition, three factors played the role of both facilitator and barrier, such as media influences(O), healthcare influences(O), and behavioral habits(M).

Conclusion

The COM-B model was proved to be a useful framework for identifying the barriers and facilitators of adherence to awake prone ventilation. The findings suggest that adherence behavior is a dynamic and balanced process and interventions aimed at improving adherence to APP should address the barriers related to capability, opportunity, and motivation. Healthcare providers should focus on providing proper guidance and training, creating a comfortable environment, and offering social support to improve patients’ capability and opportunity. Additionally, promoting patients’ positive beliefs and attitudes towards the treatment and addressing misconceptions and fears can further enhance patients’ motivation to adhere to the treatment plan.
The effects of exercise training on knee repositioning sense in people with knee osteoarthritis: a systematic review and meta-analysis of clinical trials
Authors: Sheikhhoseini Rahman , Dadfar Mahdis , Shahrbanian Shahnaz , Piri Hashem , Salsali Mohammad
Published: July 2023

Objective

Osteoarthritis (OA) of the knee is one of the most common global joint disorders, especially in aging population, and is among leading health-related concerns of societies. Therefore, this systematic review and meta-analysis was done to investigate the results related to the effects of exercise interventions on knee repositioning sense in patients with knee OA.

Methods

An extensive search was independently performed in electronic databases including PubMed, MEDLINE, Web of Science, SCOPUS, and Google Scholar, to identify randomized clinical trials (RCTs) conducted on knee OA and to evaluate knee repositioning sense before and after different exercise interventions. After extracting relevant data from eligible studies, results of the studies were pooled using a random-effects model of meta-analysis. The Physiotherapy Evidence Database (PEDro) of clinical trials was used for quality assessment of eligible studies.

Results

Among 2702 studies identified in the initial search, 17 studies were eligible for final systematic review and meta-analysis. The results showed that the patients who participated in different exercise interventions had significantly less knee repositioning error (mean differences: -1.141 degrees (95%CI: -1.510, -0.772, P < .001) compared to those who did not undergo exercise interventions. The eligible studies exhibited publication bias (Intercept: -6.69, P = .002), and the data showed significant heterogeneity (I2 = 85.633%, Q = 153.125, P < .001). Moreover, meta regression showed more prolonged exercise duration might have more effects on knee repositioning error (Coefficient=-0.860, 95% CI=-1.705, -0.016, Z=-2.00, P = .045).

Conclusion

There is strong evidence that exercise interventions may effectively reduce knee repositioning error. Moreover, it seems that more prolonged exercise duration may be associated with the greater effect size.