bluuebunny/crossref_metadata_2025 huggingface dataset:
The comprehensive impact of pityriasis rubra pilaris on physical symptoms, mental health, and activities of daily living: A mixed methods study
Authors: Velasco Rose C. , Cutler Brett , McCue William , Greiling Teri M.
Published: January 2023

Background

Pityriasis rubra pilaris (PRP) is a rare and often severe inflammatory skin disorder with major detriment to patients' quality of life. While past studies have described in detail the morphologic and histopathologic presentations of PRP, little attention has been given to the patient experience.

Objectives

To identify the physical, mental, and daily living impacts of patients living with PRP

Methods

Four focus groups involving 47 participants with PRP from six countries were conducted in English. Sessions were recorded and codified by themes, which were used to compose a 23‐question follow‐up survey.

Results

Common physical symptoms that impacted a majority of PRP patients included severe pruritus, pain (generalised in involved skin, localised to palmoplantar fissures, and arthralgias), poor sleep, fatigue, anhidrosis, body temperature dysregulation, joint pain, buildup of material in the ears, and rhinorrhea. Participants felt that PRP was associated with a strong negative mental impact that caused depression, anxiety, embarrassment, loneliness, loss of self‐esteem, and memory loss or brain fog. 38% endorsed passive suicidal ideation and 4% active suicidal ideation. Common daily activity impacts included loss of fine motor ability and difficulty walking from palmoplantar keratoderma, difficulty wearing normal clothing, difficulty working, and difficulty leaving the home. Participants reported a mean of six applications of topical creams or ointments daily.

Conclusions

This study illustrates the debilitating daily life impacts of PRP in a variety of domains. In addition to care by a dermatologist, patients should be evaluated for the need for referral to ophthalmology, otolaryngology, and podiatry. Patients with PRP felt strongly that the mental health impact of PRP was not given enough attention by providers. Given the high rate of depression, anxiety, and passive and active suicidal ideation, providers should evaluate patients' mental health and offer a referral to psychiatry and other mental health providers.
Glycyrrhizic acid protects against temporal lobe epilepsy in young rats by regulating neuronal ferroptosis through the miR‐194‐5p/PTGS2 axis
Authors: Yi Ting‐Ting , Zhang Li‐Mei , Huang Xiang‐Nan
Published: January 2023

Temporal lobe epilepsy (TLE) leads to extensive degradation of the quality of life of patients. Glycyrrhizic acid (GA) has been reported to exert neuroprotective effects on status epilepticus. Herein, the current study set out to explore the functional mechanism of GA in TLE young rats. Firstly, TLE young rat models were established using the lithium chloride and pilocarpine regimen and then subjected to treatment with different doses of GA, miR‐194‐5p‐antagomir, or/and sh‐prostaglandin‐endoperoxide synthase 2 (PTGS2) to observe changes in iron content, glutathione and malondialdehyde levels, and GPX4 (glutathione peroxidase 4) and PTGS2 protein levels in the hippocampus. Neuronal injury and apoptosis were assessed through HE, Nissl, and TUNEL staining. Additionally, the expression patterns of miR‐194‐5p were detected. The binding site of miR‐194‐5p and PTGS2 was verified with a dual‐luciferase assay. Briefly, different doses of GA (20, 40, and 60 mg/kg) reduced the epileptic score, frequency, and duration in TLE young rats, along with reductions in iron content, lipid peroxidation, neuronal injury, and apoptosis in the hippocampus. Silencing of miR‐194‐5p partly annulled the action of GA on inhibiting ferroptosis and attenuating neuronal injury in TLE young rats. Additionally, PTGS2 was validated as a target of miR‐194‐5p. GA inhibited ferroptosis and ameliorated neuronal injury in TLE young rats via the miR‐194‐5p/PTGS2 axis. Overall, our findings indicated that GA exerts protective effects on TLE young rats against neuronal injury by inhibiting ferroptosis through the miR‐194‐5p/PTGS2 axis.
The fractional porous medium equation on manifolds with conical singularities II
Authors: Roidos Nikolaos , Shao Yuanzhen
Published: January 2023

This is the second of a series of two papers that studies the fractional porous medium equation, with and , posed on a Riemannian manifold with isolated conical singularities. The first aim of the article is to derive some useful properties for the Mellin–Sobolev spaces including the Rellich–Kondrachov theorem and Sobolev–Poincaré, Nash and Super Poincaré type inequalities. The second part of the article is devoted to the study the Markovian extensions of the conical Laplacian operator and its fractional powers. Then based on the obtained results, we establish existence and uniqueness of a global strong solution for initial data and all . We further investigate a number of properties of the solutions, including comparison principle, contraction and conservation of mass. Our approach is quite general and thus is applicable to a variety of similar problems on manifolds with more general singularities.
On the trace embedding and its applications to evolution equations
Authors: Agresti Antonio , Lindemulder Nick , Veraar Mark
Published: January 2023

In this paper, we consider traces at initial times for functions with mixed time‐space smoothness. Such results are often needed in the theory of evolution equations. Our result extends and unifies many previous results. Our main improvement is that we can allow general interpolation couples. The abstract results are applied to regularity problems for fractional evolution equations and stochastic evolution equations, where uniform trace estimates on the half‐line are shown.
Biological mass spectrometry enables spatiotemporal ‘omics: From tissues to cells to organelles
Authors: Pade Leena R. , Stepler Kaitlyn E. , Portero Erika P. , DeLaney Kellen , Nemes Peter
Published: January 2023

Biological processes unfold across broad spatial and temporal dimensions, and measurement of the underlying molecular world is essential to their understanding. Interdisciplinary efforts advanced mass spectrometry (MS) into a tour de force for assessing virtually all levels of the molecular architecture, some in exquisite detection sensitivity and scalability in space‐time. In this review, we offer vignettes of milestones in technology innovations that ushered sample collection and processing, chemical separation, ionization, and 'omics analyses to progressively finer resolutions in the realms of tissue biopsies and limited cell populations, single cells, and subcellular organelles. Also highlighted are methodologies that empowered the acquisition and analysis of multidimensional MS data sets to reveal proteomes, peptidomes, and metabolomes in ever‐deepening coverage in these limited and dynamic specimens. In pursuit of richer knowledge of biological processes, we discuss efforts pioneering the integration of orthogonal approaches from molecular and functional studies, both within and beyond MS. With established and emerging community‐wide efforts ensuring scientific rigor and reproducibility, spatiotemporal MS emerged as an exciting and powerful resource to study biological systems in space‐time.
Plane problems of multiple interactions of rigid punches and bodies with complex multilayer coatings
Authors: Kazakov Kirill E. , Kurdina Svetlana P.
Published: January 2023

The article deals with the most general formulation of the problem of the interaction of a system of rigid punches and a viscoelastic aging foundation covered by several different nonuniform thin layers of variable thickness. It is shown that the mathematical model of such a problem is a system of mixed integral equations with additional integral conditions. On the basis of a special approach described in present article, an analytical solution is obtained in series for various versions of the problem statement. It is indicated that the obtained solution representation is effective even in the case when the properties of the coating layers and the shape of the contacting surfaces are described by complex functions.
Detector shifting and deep learning based ring artifact correction method for low‐dose CT
Authors: Liu Yuedong , Wei Cunfeng , Xu Qiong
Published: January 2023

Background

In x‐ray computed tomography (CT), the gain inconsistency of detector units leads to ring artifacts in the reconstructed images, seriously destroys the image structure, and is not conducive to image recognition. In addition, to reduce radiation dose and scanning time, especially photon counting CT, low‐dose CT is required, so it is important to reduce the noise and suppress ring artifacts in low‐dose CT images simultaneously.

Purpose

Deep learning is an effective method to suppress ring artifacts, but there are still residual artifacts in corrected images. And the feature recognition ability of the network for ring artifacts decreases due to the effect of noise in the low‐dose CT images. In this paper, a method is proposed to achieve noise reduction and ring artifact removal simultaneously.

Methods

To solve these problems, we propose a ring artifact correction method for low‐dose CT based on detector shifting and deep learning in this paper. Firstly, at the CT scanning stage, the detector horizontally shifts randomly at each projection to alleviate the ring artifacts as front processing. Thus, the ring artifacts are transformed into dispersed noise in front processed images. Secondly, deep learning is used for dispersed noise and statistical noise reduction.

Results

Both simulation and real data experiments are conducted to evaluate the proposed method. Compared to other methods, the results show that the proposed method in this paper has better effect on removing ring artifacts in the low‐dose CT images. Specifically, the RMSEs and SSIMs of the two sets of simulated and experiment data are better compared to the raw images significantly.

Conclusions

The method proposed in this paper combines detector shifting and deep learning to remove ring artifacts and statistical noise simultaneously. The results show that the proposed method is able to get better performance.
A numerical model for hydrothermal transport in unsaturated freezing soils considering thermodynamics equilibrium
Authors: Fu Hao , Song Erxiang , Tong Rui
Published: January 2023

The analysis of frost heave in unsaturated subgrade soils should consider the coupled movement of liquid water, vapor, and heat, accompanied by phase transition of water, vapor, and ice. In this paper, the equilibrium relationship of the three phases of water in soils was comprehensively considered, and the water head and vapor density were determined under frozen and unfrozen conditions from the perspective of thermodynamics. Based on that, the governing equations of mass and energy conservation were then derived and a new transient finite element model was developed, considering the behavior of the phase change and coupled hydrothermal transport under frozen as well as unfrozen conditions. Since the discontinuities between the frozen and the unfrozen zones may bring difficulties to the numerical solution, two kinds of smoothing techniques were proposed to solve the discontinuities at the phase transition interface, which guaranteed robust convergence and enhanced computational efficiency. The model proposed was verified by comparing with some available test results and applied to analyze the frost heave process of unsaturated subgrade under impermeable road pavements, demonstrating the model's accuracy and applicative prospect. It is revealed that the movement of liquid water and vapor in the frozen zones may still exist, and its mechanism and performance are different from that in unfrozen zones. The significance of vapor migration on the subgrade frost heave is also emphasized.
Fiscal decentralization, intergovernmental mobility, and the innovativeness of local governments' policy response in COVID‐19: Evidence from China
Authors: Huang Biao , Wu Jiebing , Ye Li
Published: January 2023

Policy innovation is an essential approach for local governments to deal with external challenges, which is also the case in response to the COVID‐19 pandemic. This article discusses the effects of fiscal decentralization and leaders' intergovernmental mobility on the innovativeness of local governments in pandemic response. By investigating the economic relief policy of local governments in China, we find that both fiscal decentralization and local leaders' intergovernmental mobility in their previous careers facilitate the innovativeness of local governments' economic relief policy for pandemic recovery, and the business experience of local leaders enhances the positive influence of fiscal decentralization on the innovativeness of local policy. The results indicate that fiscal decentralization and the intergovernmental connection based on leaders' political mobility are likely to be two predominant factors for local governments to enable horizontal mutual learning and central‐local policy coordination, and as a result foster policy innovativeness in response to the pandemic.
All‐in‐one whole exome sequencing strategy with simultaneous copy number variant, single nucleotide variant and absence‐of‐heterozygosity analysis in fetuses with structural ultrasound anomalies: A 1‐year experience
Authors: Faas Brigitte H. W. , Westra Dineke , de Munnik Sonja A. , van Rij Maartje , Marcelis Carlo , Joosten Sara , Krapels Ingrid , Vernimmen Vivian , Heijligers Malou , Willemsen Marjolein H. , de Leeuw Nicole , Rinne Tuula , Pfundt Rolph , Smeekens Sanne P. , Stegmann Sander P. A. , Macville Merryn , Sikkel Esther , Coumans Audrey , Wijnberger Lia , Derks Irma , van Lent‐Albrechts Josefa , Hofste Tom , Timmermans Raoul , van den End Janneke , Stevens Servi J. C. , Feenstra Ilse
Published: January 2023

Objective

We performed a 1‐year evaluation of a novel strategy of simultaneously analyzing single nucleotide variants (SNVs), copy number variants (CNVs) and copy‐number‐neutral Absence‐of‐Heterozygosity from Whole Exome Sequencing (WES) data for prenatal diagnosis of fetuses with ultrasound (US) anomalies and a non‐causative QF‐PCR result.

Methods

After invasive diagnostics, whole exome parent‐offspring trio‐sequencing with exome‐wide CNV analysis was performed in pregnancies with fetal US anomalies and a non‐causative QF‐PCR result (WES‐CNV). On request, additional SNV‐analysis, restricted to (the) requested gene panel(s) only (with the option of whole exome SNV‐analysis afterward) was performed simultaneously (WES‐CNV/SNV) or as rapid SNV‐re‐analysis, following a normal CNV analysis.

Results

In total, 415 prenatal samples were included. Following a non‐causative QF‐PCR result, WES‐CNV analysis was initially requested for 74.3% of the chorionic villus (CV) samples and 45% of the amniotic fluid (AF) samples. In case WES‐CNV analysis did not reveal a causative aberration, SNV‐re‐analysis was requested in 41.7% of the CV samples and 17.5% of the AF samples. All initial analyses could be finished within 2 weeks after sampling. For SNV‐re‐analysis during pregnancy, turn‐around‐times (TATs) varied between one and 8 days.

Conclusion

We show a highly efficient all‐in‐one WES‐based strategy, with short TATs, and the option of rapid SNV‐re‐analysis after a normal CNV result.
Prediction of quasi‐static elastic modulus for polyethylene‐terephthalate‐glycol prepared from fused deposition modeling
Authors: Cui Xinrui , Jar P.‐Y. Ben
Published: January 2023

This article is concerned about change of elastic modulus as a function of raster angle used in the fused deposition modeling and applicability of laminate theory to prediction of the elastic modulus. Polyethylene terephthalate glycol (PETG) was used for the experimental testing. In view that PETG shows viscous deformation which was not considered in the laminate theory, quasi‐static (QS) component of the elastic modulus was used to examine the applicability of laminate theory, which was achieved by extraction of the QS stress response to deformation through stress relaxation and then finite element modeling of the slope for the load–displacement curve before the relaxation. Two analytical approaches were used to examine the laminate theory. One was known as the mechanics of materials approach that considers matrix properties from the intralayer regions, and the other the elasticity model approach that also considers the interlayer regions. The study found that both approaches provided reasonable estimation of the QS elastic modulus but their values were slightly over the measured values. We provide evidence to suggest that the prediction accuracy could be improved by considering the change of interlayer filament contact with the change of raster angle.
Modeling the risk of acetone emission from a storage tank in summer and winter
Authors: Li Xi , Li Jian , Ji Wenjing , Ou Yangcui , He Ranran , Xu Xiaoguang , Wang Boliang
Published: January 2023

The leakage of acetone from damaged tanks can threaten workers, surrounding facilities, and the environment. The safe storage of acetone is of vital importance for emergency planning and response. This paper focused on the effects and consequences of acetone leaks from a 200 m3 storage tank in the summer and winter seasons by the employment of Areal Locations of Hazardous Atmospheres. The hazard zones classified as red threat zone, orange threat zone, and yellow threat zone were determined and analyzed. Results showed that the risk distribution of the toxic acetone vapor cloud in summer was greater than those in winter. The summer and winter seasons have no significant effect on the thermal radiation intensities from pool fire and the Boiling Liquid Expanding Vapor Explosion (BLEVE) scenario. The maximum distance of toxicity, flammability, and thermal radiation from the pool fire and BLEVE scenario for the acetone leakage were 547, 111, 16, and 1100 m, respectively. The results would provide guidance for decision‐makers in safety management and emergency response to reduce hazards.
A “middle‐out approach” for the prediction of human drug disposition from preclinical data using simplified physiologically based pharmacokinetic (PBPK) models
Authors: Yau Estelle , Gertz Michael , Ogungbenro Kayode , Aarons Leon , Olivares‐Morales Andrés
Published: January 2023

Simplified physiologically based pharmacokinetic (PBPK) models using estimated tissue‐to‐unbound plasma partition coefficients (Kpus) were previously investigated by fitting them to in vivo pharmacokinetic (PK) data. After optimization with preclinical data, the performance of these models for extrapolation of distribution kinetics to human were evaluated to determine the best approach for the prediction of human drug disposition and volume of distribution (Vss) using PBPK modeling. Three lipophilic bases were tested (diazepam, midazolam, and basmisanil) for which intravenous PK data were available in rat, monkey, and human. The models with Kpu scalars using k‐means clustering were generally the best for fitting data in the preclinical species and gave plausible Kpu values. Extrapolations of plasma concentrations for diazepam and midazolam using these models and parameters obtained were consistent with the observed clinical data. For diazepam and midazolam, the human predictions of Vss after optimization in rats and monkeys were better compared with the Vss estimated from the traditional PBPK modeling approach (varying from 1.1 to 3.1 vs. 3.7‐fold error). For basmisanil, the sparse preclinical data available could have affected the model performance for fitting and the subsequent extrapolation to human. Overall, this work provides a rational strategy to predict human drug distribution using preclinical PK data within the PBPK modeling strategy.
Risk assessment validation in patients with pulmonary arterial hypertension: Data from a Southern Brazil registry (RESPHIRAR study)
Authors: Spilimbergo Fernanda Brum , Pirath Rodrigues Roger , Credidio Dias‐Pinto Marcelo , Blanco Daniela Cavalet , Barbieri Gláucia Maria , Andrade‐Lima Marina , Leal Fagundes Ariovaldo , Gazzana Marcelo Basso , Roncato Gabriela , Mello Marcelo Martins , Watte Guilherme , Assmann Taís Silveira , Caurio Cássia Ferreira Braz , Souza Rogerio , Meyer Gisela Martina Bohns
Published: January 2023

Pulmonary arterial hypertension (PAH) is a severe and progressive disease characterized by increased pulmonary vascular resistance, ultimately leading to right heart failure and death. Registries are a valuable tool in the research of rare conditions such as PAH. Moreover, the risk assessment strategy has been validated in European and North American registries and has been reported to provide an accurate prediction of mortality and the clinical advantage of reaching low‐risk status. However, there is no available data from Brazil. Thus, the aim of the present study was to describe the characteristics of a sample of PAH from Southern Brazil and to retrospectively validate the risk assessment at our population. The RESPHIRAR is a retrospective and multicentric registry on pulmonary hypertension. With a join collaboration from nine centers in Southern Brazil, demographics, clinical presentation, and hemodynamics data of PAH were collected between 2007 and 2017. Moreover, the REVEAL 2.0 and REVEAL 2.0 Lite risk assessments were validated in our population. Overall, 370 PAH patients were included in the present study. Patients were predominantly female (78.5%) and had a mean age of 41.8 ± 18.8 years. Most patients (33.4%) had idiopathic PAH, 30.2% had PAH associated with congenital heart disease, and 23.5% had PAH associated with connective tissue disease. The low‐risk group showed significantly lower mortality than the intermediated‐ or high‐risk group at diagnosis (p < 0.05). In conclusion, our data suggest that REVEAL 2.0 and REVEAL 2.0 Lite risk assessments can predict mortality risk in PAH patients in Southern Brazil.
Replacing cutting guides with an augmented reality‐based navigation system: A feasibility study in the maxillofacial region
Authors: Pietruski Piotr , Majak Marcin , Świątek‐Najwer Ewelina , Żuk Magdalena , Popek Michał , Świecka Marta , Jaworowski Janusz , Mazurek Maciej
Published: January 2023

Purpose

The work presents outcomes of simulated maxillofacial skeleton osteotomies supported with cutting guides or one of two AR‐based intraoperative navigation systems.

Material and Methods

The series of osteotomies supported with a cutting guide, simple AR (sAR) or navigated AR (nAR) module were carried out on 15 (five per each method) skull models according to the virtual surgical plan (VSP). Each method was used to support 40 osteotomies involving the upper jaw and 40 involving the orbital region (16 osteotomies on each model). Postoperative computed tomography scans were fused with the VSP to analyse angular deviations from the planned cutting trajectory (°) and the deviations of labelled control points (mm).

Results

Guides provided the highest accuracy, with a mean osteotomy angular deviation of 3.73 ± 2.94° and a mean control point deviation of 1.30 ± 0.73 mm. Mean angular deviations for the sAR‐ and nAR‐assisted osteotomies were 5.93 ± 5.12° and 6.75 ± 5.33°, and mean control point deviations amounted to 1.86 ± 0.88 mm and 1.97 ± 0.70 mm.
The role of renewable energy investment in tackling climate change concerns: Environmental policies for achieving SDG‐13
Authors: He Xiuzhi , Khan Samiha , Ozturk Ilhan , Murshed Muntasir
Published: January 2023

In the contemporary era, tackling climate change‐related problems has become a vital environmental policy agenda, especially for realizing the targets related to SDG‐13. Therefore, this study aims to check the efficacy of scaling public investments in research and development for renewable energy development in countering the causes and effects of climate change in leading renewable energy‐investing countries. Overall, the findings verify the climate change‐inhibiting impact of such investments. By contrast, consumption of natural resources and urbanization are identified as factors responsible for piling up climate change‐related concerns in the long run while no impact of net exports, in this regard, is evidenced. Moreover, the long‐run results affirm that public investment in renewable energy development projects also exerts moderating effects for partially neutralizing the adverse climate change concerns associated with natural resource consumption and urbanization. Furthermore, such investments are also evidenced to mediate the repercussions of net exports on the causes and effects of climate change in the long run. Based on these key findings, it is recommended to scale budgetary allocations for financing renewable energy technology development‐oriented initiatives, enhancing the efficiency rate of natural resource utilization, and deploying environmentally sustainable urbanization policies for achieving the targets concerning objectives of SDG‐13.
Tourism poverty alleviation hotspots in China: Topic evolution and sustainable development
Authors: Wang Jinli , Lv Wanqing
Published: January 2023

Understanding the hotspots and patterns of tourism poverty alleviation is of great significance to stakeholders. This study aims to comprehensively and scientifically understand the research hotspots, characteristics, trends, and future research directions in the field of tourism poverty alleviation, provide decision support for tourism stakeholders, improve the level of management and service quality of tourism, balance the distribution of tourism resources and interests, and promote high‐quality and sustainable development of tourism. First, we propose a dynamic nonnegative matrix factorization (DNMF) method to analyze the tourism poverty alleviation literature from 2012 to 2021, extract hot topics and topic words. Then, we propose a topic evaluation criteria to evaluate the effect of the extracted topics. Third, we propose a topic intensity model to calculate the intensity of hot topics that can track the evolution trend of hot topics in the past 10 years, and explore the future development trends of the tourism poverty alleviation. Finally, we put forward the countermeasures and suggestions for sustainable tourism poverty alleviation under the guidance of sustainable development theory. The experimental results show that DNMF has a good effect in topic extraction. The evolution process based on topic intensity reflects the evolution trend of China's tourism poverty alleviation. This study provides a theoretical foundations and technical support for the sustainable development of China's tourism poverty alleviation.
Group testing regression analysis with covariates and specimens subject to missingness
Authors: Delaigle Aurore , Tan Ruoxu
Published: January 2023

We develop parametric estimators of a conditional prevalence in the group testing context. Group testing is applied when a binary outcome variable, often a disease indicator, is assessed by testing a specimen for the presence of the disease. Instead of testing all individual specimens separately, these are pooled in groups and the grouped specimens are tested for the disease, which permits to significantly reduce the number of tests to be performed. Various techniques have been developed in the literature for estimating a conditional prevalence from group testing data, but most of them are not valid when the data are subject to missingness. We consider this problem in the case where the specimen and the covariates are subject to nonmonotone missingness. We propose parametric estimators of the conditional prevalence, establish identifiability conditions for a logistic missing not at random model, and introduce an ignorable missing at random model. In theory, our estimators could be applied with multiple covariates missing, but in practice, they face numerical challenges when more than one covariate is missing for given individuals. We illustrate the method on simulated data and on a dataset from the Demographics and Health Survey.
Personalized online ensemble machine learning with applications for dynamic data streams
Authors: Malenica Ivana , Phillips Rachael V. , Chambaz Antoine , Hubbard Alan E. , Pirracchio Romain , van der Laan Mark J.
Published: January 2023

In this work we introduce the personalized online super learner (POSL), an online personalizable ensemble machine learning algorithm for streaming data. POSL optimizes predictions with respect to baseline covariates, so personalization can vary from completely individualized, that is, optimization with respect to subject ID, to many individuals, that is, optimization with respect to common baseline covariates. As an online algorithm, POSL learns in real time. As a super learner, POSL is grounded in statistical optimality theory and can leverage a diversity of candidate algorithms, including online algorithms with different training and update times, fixed/offline algorithms that are not updated during POSL's fitting procedure, pooled algorithms that learn from many individuals' time series, and individualized algorithms that learn from within a single time series. POSL's ensembling of the candidates can depend on the amount of data collected, the stationarity of the time series, and the mutual characteristics of a group of time series. Depending on the underlying data‐generating process and the information available in the data, POSL is able to adapt to learning across samples, through time, or both. For a range of simulations that reflect realistic forecasting scenarios and in a medical application, we examine the performance of POSL relative to other current ensembling and online learning methods. We show that POSL is able to provide reliable predictions for both short and long time series, and it's able to adjust to changing data‐generating environments. We further cultivate POSL's practicality by extending it to settings where time series dynamically enter and exit.
Sulfur polymerization strategy based on the intrinsic properties of polymers for advanced binder‐free and high‐sulfur‐content Li–S batteries
Authors: Song Zihui , Zhang Tianpeng , Liu Siyang , Shao Wenlong , Jiang Wanyuan , Mao Runyue , Jian Xigao , Hu Fangyuan
Published: January 2023

Lithium–sulfur (Li–S) batteries are the promising next‐generation secondary energy storage systems, because of their advantages of high energy density and environmental friendliness. Among numerous cathode materials, organosulfur polymer materials have received extensive attentions because of their controllable structure and uniform sulfur distribution. However, the sulfur content of most organosulfur polymer cathodes is limited (S content <60%) due to the addition of large amounts of conductive agents and binders, which adversely affects the energy density of Li–S batteries. Herein, a hyperbranched sulfur‐rich polymer based on modified polyethyleneimine (Ath‐PEI) named carbon nanotube‐entangled poly (allyl‐terminated hyperbranched ethyleneimine‐random‐sulfur) (CNT/Ath‐PEI@S) was prepared by sulfur polymerization and used as a Li–S battery cathode. The high intrinsic viscosity of Ath‐PEI provided considerable adhesion and avoided the addition of PVDF binder, thereby increasing the sulfur content of cathodes to 75%. Moreover, considering the uniform distribution of elemental sulfur by the polymer, the utilization of sulfur was successfully improved, thus improving the rate capability and discharge capacity of the battery. The binder‐free, sulfur‐rich polymer cathode exhibited ultra‐high initial discharge capacity (1520.7 mAh g−1 at 0.1 C), and high rate capability (804 mAh g−1 at 2.0 C). And cell‐level calculations show that the electrode exhibits an initial capacity of 942.3 mAh g−1electrode, which is much higher than those of conventional sulfur‐polymer electrodes reported in the literature.
Prevalence of adenomyosis in women with subfertility: systematic review and meta‐analysis
Authors: Mishra I. , Melo P. , Easter C. , Sephton V. , Dhillon‐Smith R. , Coomarasamy A.
Published: January 2023

Objective

To determine the prevalence of adenomyosis in women with subfertility.

Methods

A systematic search was conducted in MEDLINE, EMBASE, CINAHL Plus, Google Scholar, PsycINFO and Web of Science Core Collection from database inception to October 2022. The included studies evaluated the prevalence of adenomyosis in women with subfertility, with or without endometriosis and/or uterine fibroids. Secondary analyses were conducted to identify variation in the prevalence of isolated adenomyosis according to geographical location, diagnostic modality, diagnostic criteria, type of ultrasound, ultrasound features of adenomyosis and the use of assisted reproductive technology.

Results

Among 21 longitudinal studies evaluating 25 600 women, the overall pooled prevalence of isolated adenomyosis was 10% (95% CI, 6–15%) (I2 = 99.1%; tau2 = 0.12). The pooled prevalence was 1% (95% CI, 0–4%) for adenomyosis with concurrent fibroids (eight studies; I2 = 95.8%; tau2 = 0.03), 6% (95% CI, 3–11%) for adenomyosis with concurrent endometriosis (18 studies; I2 = 98.6%; tau2 = 0.12) and 7% (95% CI, 2–13%) for adenomyosis with concurrent endometriosis and/or fibroids (nine studies; I2 = 98.3%; tau2 = 0.09). The prevalence of isolated adenomyosis varied substantially according to geographical location, with Australia exhibiting the highest pooled prevalence of adenomyosis (19% (95% CI, 12–27%)), which was significantly higher compared with that in Asia (5% (95% CI, 1–12%)). The pooled prevalence of isolated adenomyosis diagnosed using a combination of direct and indirect ultrasound features was 11% (95% CI, 7–16%), whereas it was 0.45% (95% CI, 0–1%) in the study in which only an indirect feature was used as the diagnostic criterion.

Conclusion

One in 10 women with subfertility have a diagnosis of isolated adenomyosis. The prevalence of adenomyosis varies according to the presence of concurrent endometriosis and/or fibroids. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
Predicting spontaneous preterm birth in asymptomatic high‐risk women with cervical cerclage
Authors: Ridout A. E. , Ross G. , Seed P. T. , Hezelgrave N. L. , Tribe R. M. , Shennan A. H.
Published: January 2023

Objective

To determine the performance of the predictive markers of spontaneous preterm birth, cervicovaginal quantitative fetal fibronectin (fFN) and cervical length, in asymptomatic high‐risk women with transabdominal, history‐indicated or ultrasound‐indicated cervical cerclage.

Methods

This was a secondary analysis of a prospective cohort of asymptomatic high‐risk women with cervical cerclage and no other prophylactic intervention (including progesterone), who attended the preterm birth clinic at a central London teaching hospital between October 2010 and September 2016. Women had either transabdominal cerclage, placed prior to conception, history‐indicated cerclage, placed before 14 weeks' gestation, or ultrasound‐indicated cerclage for a short cervix (< 25 mm), placed before 24 weeks. All women underwent serial cervical length assessment on transvaginal ultrasound in the second trimester (16–28 weeks), and quantitative fFN testing from 18 weeks onward. Test performance was analyzed for the prediction of spontaneous preterm birth before 30 weeks (cerclage failure), 34 weeks and 37 weeks, using receiver‐operating‐characteristics (ROC)‐curve analysis.

Results

Overall, 181 women were included in the analysis. Cervical length and fFN were strong predictors of spontaneous preterm birth before 30 weeks in women with cerclage, with areas under the ROC curve (AUC) of 0.86 (95% CI, 0.79–0.94) and 0.84 (95% CI, 0.75–0.92), respectively. Cervical length was a better predictor of preterm birth before 30 weeks in women with history‐indicated compared to those with ultrasound‐indicated cerclage, although both showed clinical utility (AUC, 0.96 (95% CI, 0.91–1.00) vs 0.79 (95% CI, 0.66–0.91); P = 0.01). Quantitative fFN was a strong predictor of spontaneous preterm birth before 30 weeks in women with history‐indicated cerclage (AUC, 0.91 (95% CI, 0.75–1.00)) and retained clinical utility in those with ultrasound‐indicated cerclage (AUC, 0.76 (95% CI, 0.64–0.89)). There were no spontaneous deliveries before 34 weeks in women with a transabdominal cerclage, so AUC was not calculated. Delivery was delayed significantly in this group (P < 0.01).

Conclusions

Cervical length and quantitative fFN retain clinical utility for the prediction of spontaneous preterm birth in women with cervical cerclage, and prediction is best in women with a history‐indicated stitch. These tests can be relied upon to discriminate risk and have utility when planning clinical management with regard to treatment failure. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
Algorithms for Large-Scale Network Analysis and the NetworKit Toolkit
Authors: Angriman Eugenio , van der Grinten Alexander , Hamann Michael , Meyerhenke Henning , Penschuck Manuel
Published: January 2023

The abundance of massive network data in a plethora of applications makes scalable analysis algorithms and software tools necessary to generate knowledge from such data in reasonable time. Addressing scalability as well as other requirements such as good usability and a rich feature set, the open-source software NetworKit has established itself as a popular tool for large-scale network analysis. This chapter provides a brief overview of the contributions to NetworKit made by the SPP 1736. Algorithmic contributions in the areas of centrality computations, community detection, and sparsification are in the focus, but we also mention several other aspects – such as current software engineering principles of the project and ways to visualize network data within a NetworKit-based workflow.
Algorithms for Big Data Problems in de Novo Genome Assembly
Authors: Srivastav Anand , Wedemeyer Axel , Schielke Christian , Schiemann Jan
Published: January 2023

De novo genome assembly is a fundamental task in life sciences. It is mostly a typical big data problem with sometimes billions of reads, a big puzzle in which the genome is hidden. Memory and time efficient algorithms are sought, preferably to run even on desktops in labs. In this chapter we address some algorithmic problems related to genome assembly. We first present an algorithm which heavily reduces the size of input data, but with no essential compromize on the assembly quality. In such and many other algorithms in bioinformatics the counting of k-mers is a botleneck. We discuss counting in external memory. The construction of large parts of the genome, called contigs, can be modelled as the longest path problem or the Euler tour problem in some graphs build on reads or k-mers. We present a linear time streaming algorithm for constructing long paths in undirected graphs, and a streaming algorithm for the Euler tour problem with optimal one-pass complexity.
Kinetically stabilized inflation
Authors: Li Changhong , Gong Hao , Cheung Yeuk-kwan Edna
Published: January 2023

Abstract

In this work, we propose a string-inspired two fields inflation model to address the fine-tuning problem that the standard inflation model suffers. The fast-rolling tachyon $$ \mathcal{T} $$
T
originated from the D-brane and anti-D-brane pair annihilation locks the inflaton φ slowly rolling on a Higgs-like potential $$ V\left(\varphi \right)=-{m}_{\varphi}^2{\varphi}^2+\lambda {\varphi}^4 $$
V

φ

=
−

m
φ
2

φ
2

+
λ

φ
4

and drives a kinetically stabilized (KS) inflation. Our numerical simulation confirms such a solution is a dynamic attractor. In particular, for λ < 0.8 × 10−3, the e-folding number contributed by the KS inflation phase can be larger than 62 to solve the horizon and flatness problems of Big Bang theory. Notably, this KS inflation generates a nearly scale-invariant primordial curvature perturbations spectrum consistent with current cosmic microwave background (CMB) observations. It predicts a low tensor-to-scalar ratio, which the current primordial gravitational wave background (the B-modes in CMB) searches favor.
Fermionic spectral walls in kink collisions
Authors: Campos J. G. F. , Mohammadi A. , Queiruga J. M. , Wereszczynski A. , Zakrzewski W. J.
Published: January 2023

Abstract

We show that a spectral wall, i.e., an obstacle in the dynamics of a bosonic soliton, which arises due to the transition of a normal mode into the continuum spectrum, exists after coupling the original bosonic model to fermions. This spectral wall can be experienced if the boson or fermion field is in an excited state. Furthermore, while passing through a spectral wall, an incoming kink-fermion bound state can be separated into purely bosonic kink, which continues to move to spatial infinity and a fermionic cloud that spreads in the region before the wall.
A note on quark and gluon energy-momentum tensors
Authors: Ahmed Taushif , Chen Long , Czakon Michał
Published: January 2023

Abstract

We discuss the constraints on quark and gluon energy-momentum tensors in QCD that follow from the requirement of Renormalisation-Group invariance of the traces of these operators. Our study covers the most general form of the latter traces, while the energy-momentum tensors themselves are only subjected to very mild constraints. We derive Renormalisation-Group equations for the two finite independent functions of the strong coupling constant and renormalisation scale of minimal subtraction which completely define the energy-momentum tensors. We demonstrate that previously proposed definitions of the renormalized quark and gluon energy-momentum tensors are special cases of our results assuming no explicit dependence on the renormalisation scale. Finally, we present $$ \overline{\textrm{MS}} $$

MS
¯

-renormalised quark and gluon energy-momentum tensors at four-loop order.
Next-to-leading-power kinematic corrections to DVCS: a scalar target
Authors: Braun V. M. , Ji Yao , Manashov A. N.
Published: January 2023

Abstract

Using the recent results on the contributions of descendants of the leading twist operators to the operator product expansion of two electromagnetic currents we derive explicit expressions for the kinematic finite-t and target mass corrections to the DVCS helicity amplitudes to the 1/Q4 power accuracy. The cancellation of IR divergences for kinematic corrections is demonstrated to all powers in the leading order of perturbation theory. We also argue that target mass corrections in the coherent DVCS from nuclei are small and do not invalidate the factorization theorem.
The NNLO quark beam function for jet-veto resummation
Authors: Bell Guido , Brune Kevin , Das Goutam , Wald Marcel
Published: January 2023

Abstract

We consider the quark beam function that describes collinear initial-state radiation that is constrained by a veto on reconstructed jets. As the veto is imposed on the transverse momenta of the jets, the beam function is subject to rapidity divergences, and we use the collinear-anomaly framework to extract the perturbative matching kernels to next-to-next-to-leading order (NNLO) in the strong-coupling expansion. Our calculation is based on a novel framework that automates the computation of beam functions in Mellin space and it provides the ingredients to extend jet-veto resummations for quark-initiated processes to NNLL′ accuracy.
On polyharmonic helices in space forms
Authors: Branding Volker
Published: January 2023

In this article, we study polyharmonic curves of constant curvature where we mostly focus on the case of curves on the sphere. We classify polyharmonic curves of constant curvature in three-dimensional space forms and derive an explicit family of polyharmonic curves on the sphere. Our results give new insights into the geometric structure of higher order variational problems.
Global existence of a nonlinear wave equation arising from Nordström’s theory of gravitation
Authors: Brauer Uwe , Karp Lavi
Published: January 2023

We show global existence of classical solutions for the nonlinear Nordström theory with a source term and a cosmological constant under the assumption that the source term is small in an appropriate norm, while in some cases no smallness assumption on the initial data is required. In this theory, the gravitational field is described by a single scalar function that satisfies a certain semi-linear wave equation. We consider spatial periodic deviation from the background metric, that is why we study the semi-linear wave equation on the three-dimensional torus$${\mathord {\mathbb T}}^3$$T3in the Sobolev spaces$$H^m({\mathord {\mathbb T}}^3)$$Hm(T3). We apply two methods to achieve the existence of global solutions, the first one is by Fourier series, and in the second one, we write the semi-linear wave equation in a non-conventional way as a symmetric hyperbolic system. We also provide results concerning the asymptotic behavior of these solutions and, finally, a blow-up result if the conditions of our global existence theorems are not met.
Videobasierte Psychotherapie: Aktuelle Rahmenbedingungen und Entwicklungen sowie Empfehlungen für die praktische Umsetzung
Authors: Steubl Lena Sophia , Baumeister Harald
Published: January 2023

Videobasierte Psychotherapie ist ein möglicher digitaler Ansatz zur Bereitstellung psychotherapeutischer Behandlung – insbesondere dann, wenn Psychotherapie aufgrund von strukturellen Hindernissen nicht im unmittelbaren Kontakt stattfinden kann, zum Beispiel in Zusammenhang mit der COVID-19-Pandemie. Die Nutzung dieses Ansatzes hat sich sowohl als wirksam als auch als akzeptiert unter Psychotherapeutinnen und -therapeuten sowie Patientinnen und Patienten erwiesen. Rahmenbedingungen für die videobasierte Psychotherapie innerhalb der gesetzlichen Krankenversicherung in Deutschland und Empfehlungen für die praktische Umsetzung werden in diesem Artikel zusammengefasst.
Connecting ethics and epistemology of AI
Authors: Russo Federica , Schliesser Eric , Wagemans Jean
Published: January 2023

The need for fair and just AI is often related to the possibility of understanding AI itself, in other words, of turning an opaque box into a glass box, as inspectable as possible. Transparency and explainability, however, pertain to the technical domain and to philosophy of science, thus leaving the ethics and epistemology of AI largely disconnected. To remedy this, we propose an integrated approach premised on the idea that a glass-box epistemology should explicitly consider how to incorporate values and other normative considerations, such as intersectoral vulnerabilities, at critical stages of the whole process from design and implementation to use and assessment. To connect ethics and epistemology of AI, we perform a double shift of focus. First, we move from trusting the output of an AI system to trusting the process that leads to the outcome. Second, we move from expert assessment to more inclusive assessment strategies, aiming to facilitate expert and non-expert assessment. Together, these two moves yield a framework usable for experts and non-experts when they inquire into relevant epistemological and ethical aspects of AI systems. We dub our framework ‘epistemology-cum-ethics’ to signal the equal importance of both aspects. We develop it from the vantage point of the designers: how to create the conditions to internalize values into the whole process of design, implementation, use, and assessment of an AI system, in which values (epistemic and non-epistemic) are explicitly considered at each stage and inspectable by every salient actor involved at any moment.