bluuebunny/crossref_metadata_2025_split huggingface dataset:
Kinase inhibitors increase individual radiation sensitivity in normal cells of cancer patients
Authors: Jost Tina , Schuster Barbara , Heinzerling Lucie , Weissmann Thomas , Fietkau Rainer , Distel Luitpold V. , Hecht Markus 
Published: April 2022

Abstract
Purpose
Kinase inhibitors (KI) are known to increase radiosensitivity, which can lead to increased risk of side effects. Data about interactions of commonly used KI with ionizing radiation on healthy tissue are rare.

Patients and methods
Freshly drawn blood samples were analyzed using three-color FISH (fluorescence in situ hybridization) to measure individual radiosensitivity via chromosomal aberrations after irradiation (2 Gy). Thresholds of 0.5 and 0.6 breaks/metaphase (B/M) indicate moderate or clearly increased radiosensitivity.

Results
The cohorts consisted of healthy individuals (NEG, n = 219), radiosensitive patients (POS, n = 24), cancer patients (n = 452) and cancer patients during KI therapy (n = 49). In healthy individuals radiosensitivity (≥ 0.6 B/M) was clearly increased in 5% of all cases, while in the radiosensitive cohort 79% were elevated. KI therapy increased the rate of sensitive patients (≥ 0.6 B/M) to 35% significantly compared to 19% in cancer patients without KI (p = 0.014). Increased radiosensitivity of peripheral blood mononuclear cells (PBMCs) among patients occurred in six of seven KI subgroups. The mean B/M values significantly increased during KI therapy (0.47 ± 0.20 B/M without compared to 0.50 ± 0.19 B/M with KI, p = 0.047).

Conclusions
Kinase inhibitors can intensify individual radiosensitivity of PBMCs distinctly in 85% of tested drugs.
The evolution of regional entrepreneurship policies: “no one size fits all”
Authors: Ortega-Argilés Raquel 
Published: April 2022

AbstractIn the last two decades, entrepreneurship policies have gone through a radical transformation in many parts of the world. New theoretical and empirical approaches have helped to identify better the drivers of entrepreneurial creation, the main actors in the process, and the significant contribution of entrepreneurship to socio-economic prosperity. One of the main conclusions of these new theoretical and empirical approaches is that the drivers and outcomes of entrepreneurship are heavily shaped by place. There is no single ideal entrepreneurship policy formula because entrepreneurial mechanisms take a different form depending on different places. However, concepts such as path dependency, industrial ecology and heritage, connectivity, culture, and intra-and interregional knowledge spillovers are all linked in different ways with regional entrepreneurship in general and the Entrepreneurial Ecosystems literature. This paper discusses the impacts of these different influences on the evolution of modern entrepreneurship policies, examines what the current evidence points to, and identifies areas for further consideration. Examples will be drawn from different countries and regions. On the basis of the evidence reviewed, the paper contends that both conceptual and policy-thinking regarding the relationships between entrepreneurship and place are increasingly shifting to the challenges facing less successful regions, even though the current approaches are heavily based on the insights of successful places.
Abdominal pregnancy: a case report and review of 17 cases
Authors: Chen Yu , Peng Ping , Li Chunying , Teng Lirong , Liu Xinyan , Liu Juntao , Cao Dongyan , Zhu Lan , Lang Jinghe 
Published: April 2022

Abstract
Purpose
To analyze the clinical characteristics of abdominal pregnancy, and to explore the diagnosis and prognosis of different treatment methods.

Methods
The cases of patients with abdominal pregnancy admitted to Peking Union Medical College Hospital between January 1, 1989 and January 1, 2021, were analyzed retrospectively.

Results
The median age of 17 patients was 34 years (22–42 years); the median gestational duration was 57 days (from 41 days to 32 weeks). Among all 17 patients, 15 (88.24%) presented with abdominal pain. The implantation sites of the gestational sac included the bladder peritoneal reflection, anterior wall of the rectum, omentum, serous membrane of the uterus, and inside or on the surface of uterosacral ligament. In all, only 29.41% cases (5/17) were diagnosed before surgery. All 17 patients were treated via surgery. Further, 58.82% (10/17) patients recovered without complications, 29.41% (5/17) developed fever, 5.88% (1/17) underwent reoperation because of intra-abdominal bleeding, and 5.88% (1/17) developed double lower limb venous thrombosis. All 17 patients survived.

Conclusion
The preoperative diagnosis rate of abdominal pregnancy is low. Planting sites in the pelvic peritoneum and pelvic organs are more common than the others. Laparoscopic surgery in the first trimester of pregnancy can achieve better therapeutic effects. However, the blood supply of the placenta should be fully evaluated before surgery. When it is expected that attempts to remove the placenta will cause fatal bleeding, the placenta can be left in place, but long-term close follow-up should be paid attention to.
The contribution of respiratory and hearing protection use to psychological distress in the workplace: a scoping review
Authors: Leung Richard , Cook Margaret M. , Capra Mike F. , Johnstone Kelly R. 
Published: April 2022

Abstract
Objective
Workers from various industries use personal protective equipment (PPE) including masks, respirators, and hearing protection to reduce their exposures to workplace hazards. Many studies have evaluated the physiological impacts of PPE use, but few have assessed the psychological impacts. The aim of the present study was to carry out a scoping review to compile existing evidence and determine the extent of knowledge on workplace mask, respirator or hearing protection use as a psychosocial hazard (stressor) that could result in a stress response and potentially lead to psychological injury.

Methods
The scoping review followed recognized methods and was conducted using Ovid Emcare, PubMed, Sage Journals, ScienceDirect, Scopus, SpringerLink, Google Scholar and preprint databases (OSF Preprints and medRxiv). Articles on the stressors associated with the use of masks, respirators, and hearing protection were included. The extracted data included author(s) name, year of publication, title of article, study design, population data, stressors assessed, and key findings.

Results
We retrieved 650 articles after removal of duplicates, of which 26 were deemed eligible for inclusion for review. Identified factors associated with PPE use that could potentially create a stress response were identified: communication impacts, physical impacts, psychological illness symptoms, cognitive impacts, and perceived PPE-related impacts. Evidence for respirators suggest that there may be psychological injury associated with their use. However, hearing protection appears to have a protective effect in reducing psychological symptoms such as anxiety, depression, and aggression.

Conclusions
Mask or respirator use may lead to an increase in work-related stress. Whereas hearing protection may have protective effects against psychological symptoms and improves speech intelligibility. More research is needed to better understand potential psychosocial impacts of mask, respirator and/or hearing protection use.
Seasonal diversity dynamics of a boreal zooplankton community under climate impact
Authors: Bellier Edwige , Engen Steinar , Jensen Thomas Correll 
Published: April 2022

AbstractSeasonality and long-term environmental variability affect species diversity through their effects on the dynamics of species. To investigate such effects, we fitted a dynamic and heterogeneous species abundance model generating the lognormal species abundance distribution to an assemblage of freshwater zooplankton sampled five times a year (June–October) during the ice-free period over 28 years (1990–2017) in Lake Atnsjøen (Norway). By applying a multivariate stochastic community dynamics model for describing the fluctuations in abundances, we show that the community dynamics was driven by environmental variability in spring (i.e., June). In contrast, community-level ecological heterogeneity is highest in autumn. The autumn months (i.e., September and October) that rearranged the community are most likely crucial months to monitor long-term changes in community structure. Indeed, noises from early summer are filtered away, making it easier to track long-term changes. The community returned faster towards equilibrium when ecological heterogeneity was the highest (i.e., in September and October). This occurred because of stronger density-regulation in months with highest ecological heterogeneity. The community responded to the long-term warming of water temperature with decreasing species diversity and increasing abundance. Unevenness associated with variabilities in abundances might affect species interactions within the community. These can have consequences for the stability and functioning of the ecosystem.
A spatio-temporal autoregressive model for monitoring and predicting COVID infection rates
Authors: Congdon Peter 
Published: April 2022

AbstractThe COVID-19 epidemic has raised major issues with regard to modelling and forecasting outcomes such as cases, deaths and hospitalisations. In particular, the forecasting of area-specific counts of infectious disease poses problems when counts are changing rapidly and there are infection hotspots, as in epidemic situations. Such forecasts are of central importance for prioritizing interventions or making severity designations for different areas. In this paper, we consider different specifications of autoregressive dependence in incidence counts as these may considerably impact on adaptivity in epidemic situations. In particular, we introduce parameters to allow temporal adaptivity in autoregressive dependence. A case study considers COVID-19 data for 144 English local authorities during the UK epidemic second wave in late 2020 and early 2021, which demonstrate geographical clustering in new cases—linked to the then emergent alpha variant. The model allows for both spatial and time variation in autoregressive effects. We assess sensitivity in short-term predictions and fit to specification (spatial vs space-time autoregression, linear vs log-linear, and form of space decay), and show improved one-step ahead and in-sample prediction using space-time autoregression including temporal adaptivity.
Novel materials in magnetic resonance imaging: high permittivity ceramics, metamaterials, metasurfaces and artificial dielectrics
Authors: Webb Andrew , Shchelokova Alena , Slobozhanyuk Alexey , Zivkovic Irena , Schmidt Rita 
Published: April 2022

AbstractThis article reviews recent developments in designing and testing new types of materials which can be: (i) placed around the body for in vivo imaging, (ii) be integrated into a conventional RF coil, or (iii) form the resonator itself. These materials can improve the quality of MRI scans for both in vivo and magnetic resonance microscopy applications. The methodological section covers the basic operation and design of two different types of materials, namely high permittivity materials constructed from ceramics and artificial dielectrics/metasurfaces formed by coupled conductive subunits, either in air or surrounded by dielectric material. Applications of high permittivity materials and metasurfaces placed next to the body to neuroimaging and extremity imaging at 7 T, body and neuroimaging at 3 T, and extremity imaging at 1.5 T are shown. Results using ceramic resonators for both high field in vivo imaging and magnetic resonance microscopy are also shown. The development of new materials to improve MR image quality remains an active area of research, but has not yet found significant use in clinical applications. This is mainly due to practical issues such as specific absorption rate modelling, accurate and reproducible placement, and acceptable size/weight of such materials. The most successful area has been simple “dielectric pads” for neuroimaging at 7 T which were initially developed somewhat as a stop-gap while parallel transmit technology was being developed, but have continued to be used at many sites. Some of these issues can potentially be overcome using much lighter metasurfaces and artificial dielectrics, which are just beginning to be assessed.
Error Estimates of the Godunov Method for the Multidimensional Compressible Euler System
Authors: Lukáčová-Medvid’ová Mária , She Bangwei , Yuan Yuhuan 
Published: April 2022

AbstractWe derive a priori error estimates of the Godunov method for the multidimensional compressible Euler system of gas dynamics. To this end we apply the relative energy principle and estimate the distance between the numerical solution and the strong solution. This yields also the estimates of the$$L^2$$L2-norms of the errors in density, momentum and entropy. Under the assumption, that the numerical density is uniformly bounded from below by a positive constant and that the energy is uniformly bounded from above and stays positive, we obtain a convergence rate of 1/2 for the relative energy in the$$L^1$$L1-norm, that is to say, a convergence rate of 1/4 for the$$L^2$$L2-error of the numerical solution. Further, under the assumption—the total variation of the numerical solution is uniformly bounded, we obtain the first order convergence rate for the relative energy in the$$L^1$$L1-norm, consequently, the numerical solution converges in the$$L^2$$L2-norm with the convergence rate of 1/2. The numerical results presented are consistent with our theoretical analysis.
Performance of Forwarding Operations in Biomass Recovery from Apple Orchards
Authors: Cataldo Maria Francesca , Marcu Marina Viorela , Iordache Eugen , Zimbalatti Giuseppe , Proto Andrea Rosario , Borz Stelian Alexandru 
Published: April 2022

AbstractIn recent decades, the use of forwarders in agroforestry systems has been increasing. In agroforestry systems, the possibility to use these machines in various operational contexts allows the reduction of hourly costs and favors its use also in small enterprises. In Europe, agroforestry or farm forestry represents an important resource that offers alternative and more sustainable land uses in agricultural or forestry areas. By covering large areas, fruit orchards represent an important source of income, but they require annual pruning which leaves abundant residues on the ground. And when fruit production declines, the trees are dismantled to make room for new ones. This study evaluated the performance of biomass recovery from dismantled apple orchards using a HSM 208 F forwarder. Time studies were implemented to estimate the productivity and fuel consumption of forwarding operations. Data was collected by means of a GPS unit, a video camera and an electric fuel pump, and 30 work cycles divided into elemental tasks were monitored. Models for time consumption and productivity as a function of extraction distance were developed by means of least-square simple regression, at different scales needed to characterize the forwarding operations. The average forwarding distance was of ca. 830 m and the net and gross forwarding production rates were of 21.79 and 15.35 loose m3 h − 1 (volume of woodchips produced), respectively. The study provides reference data for forwarding operations and demonstrates the successful use of forestry machines in the agricultural sector.
Encoding and decoding of several optimal rank metric codes
Authors: Kadir Wrya K. , Li Chunlei , Zullo Ferdinando 
Published: April 2022

AbstractThis paper presents encoding and decoding algorithms for several families of optimal rank metric codes whose codes are in restricted forms of symmetric, alternating and Hermitian matrices. First, we show the evaluation encoding is the right choice for these codes and then we provide easily reversible encoding methods for each family. Later unique decoding algorithms for the codes are described. The decoding algorithms are interpolation-based and can uniquely correct errors for each code with rank up to ⌊(d− 1)/2⌋ in polynomial-time, wheredis the minimum distance of the code.
Backbone and side chain resonance assignment of the intrinsically disordered human DBNDD1 protein
Authors: Wiedemann Christoph , Obika Kingsley Benjamin , Liebscher Sandra , Jirschitzka Jan , Ohlenschläger Oliver , Bordusa Frank 
Published: April 2022

AbstractThe dysbindin domain-containing protein 1 (DBNDD1) is a conserved protein among higher eukaryotes whose structure and function are poorly investigated so far. Here, we present the backbone and side chain nuclear magnetic resonance assignments for the human DBNDD1 protein. Our chemical-shift based secondary structure analysis reveals the human DBNDD1 as an intrinsically disordered protein.
Molecularly Imprinted Polymers Based Surface Plasmon Resonance Sensor for Sulfamethoxazole Detection
Authors: Kurç Önder , Türkmen Deniz 
Published: April 2022

AbstractSulfamethoxazole (SMX) is a sulfonamide antibiotic primarily used to treat urinary tract infections and used in veterinary and industrialized husbandry to treat diseases and food additives. Like other antibiotics, SMX is considered as a pollutant in water and food that threaten local life. This study developed a surface plasmon resonance (SPR) sensor chip that is fast, highly selective, and reusable, and requires no pretreatment for detecting SMX. As a receptor, SMX imprinted methacrylic acid-2-hydroxyethyl methacrylate-ethylene glycol dimethacrylate polymer [poly(MAA-HEMA-EGDMA)] was used. The surface of the gold SPR chips was coated with a drop-casting method. The nanofilm coated chips were characterized by scanning electron microscopy (SEM), atomic force microscopy (AFM), ellipsometer, contact angle measurement, and Fourier-transform infrared spectrometry (FTIR). Imprinting factor (IF) was calculated as: ΔR[MIP(molecularly imprinted polymers)]/ΔR[NIP(non-imprinted)]=12/3.5=3.4. Limit of detection (LOD) and limit of quantification (LOQ) values were calculated with 3 s/m and 10 s/m methods, and the results were found to be 0.001 1 µg/L for LOD 0.003 4 µg/L for LOQ. Adsorption studies on both standard SMX solution and commercial milk samples were applied. Also, we investigated the developed chip’s reusability, storability, and selectivity with amoxicillin and cefalexin.
Some approximation results for mild solutions of stochastic fractional order evolution equations driven by Gaussian noise
Authors: Fahim K. , Hausenblas E. , Kovács M. 
Published: April 2022

AbstractWe investigate the quality of space approximation of a class of stochastic integral equations of convolution type with Gaussian noise. Such equations arise, for example, when considering mild solutions of stochastic fractional order partial differential equations but also when considering mild solutions of classical stochastic partial differential equations. The key requirement for the equations is a smoothing property of the deterministic evolution operator which is typical in parabolic type problems. We show that if one has access to nonsmooth data estimates for the deterministic error operator together with its derivative of a space discretization procedure, then one obtains error estimates in pathwise Hölder norms with rates that can be read off the deterministic error rates. We illustrate the main result by considering a class of stochastic fractional order partial differential equations and space approximations performed by spectral Galerkin methods and finite elements. We also improve an existing result on the stochastic heat equation.
Parallel Evaluation of Chebyshev Approximations: Applications in Astrodynamics
Authors: Atallah Ahmed M. , Younes Ahmad Bani 
Published: April 2022

AbstractApproximations based on Chebyshev polynomials have several astrodynamic applications. The performance of these approximations can be improved by parallel implementations exploiting parallel architectures, such as OpenMP and CUDA. In this paper, we introduce the parallel implementation to two astrodynamic applications. The first is the gravitational finite element model (FEM): a piecewise Chebyshev approximation that replaces high degree and order gravitational spherical harmonic models (SHMs). Thus, much lower degree, locally valid functions can efficiently model and compute local gravity perturbations in parallel structure for efficient performance. For this model, the total gravity acceleration is split into a reference and disturbance term. The reference includes two-body plus $$J_2$$

J
2

, which are relatively cheap to compute. The FEM approximates the higher-order gravity terms. It is developed from a 2D mesh grid covering a sphere of a specified radius, and a family of spherical shells is sampled using a cosine distribution in the radial direction. To reduce the required memory when seeking a specific accuracy, an adaptive version of the gravitational FEM is introduced. In addition, a parallel implementation of the FEM using OpenMP is preseneted. We show the runtime comparison for the 200 degree × 200 order EGM2008 SHM and the serial and parallel equivalent FEM algorithms. The other application is the Chebyshev-Picard method (CPM): a numerical integrator that solves an ordinary differential equation by approximating the integrand using a Chebyshev approximant and iterates over the trajectory via Picard iteration. A parallel CUDA implementation of the CPM method in conjunction with the EGM2008 SHM and the FEM is introduced. We present numerical examples for propagating four Earth-orbiting satellites considering both the $$200\times 200$$

200
×
200

EGM2008 SHM and the equivalent FEM representation to test the algorithm’s performance via parallel and serial computation (i.e., a single CPU thread).
Reduced order and surrogate models for gravitational waves
Authors: Tiglio Manuel , Villanueva Aarón 
Published: April 2022

AbstractWe present an introduction to some of the state of the art in reduced order and surrogate modeling in gravitational-wave (GW) science. Approaches that we cover include principal component analysis, proper orthogonal (singular value) decompositions, the reduced basis approach, the empirical interpolation method, reduced order quadratures, and compressed likelihood evaluations. We divide the review into three parts: representation/compression of known data, predictive models, and data analysis. The targeted audience is practitioners in GW science, a field in which building predictive models and data analysis tools that are both accurate and fast to evaluate, especially when dealing with large amounts of data and intensive computations, are necessary yet can be challenging. As such, practical presentations and, sometimes, heuristic approaches are here preferred over rigor when the latter is not available. This review aims to be self-contained, within reasonable page limits, with little previous knowledge (at the undergraduate level) requirements in mathematics, scientific computing, and related disciplines. Emphasis is placed on optimality, as well as the curse of dimensionality and approaches that might have the promise of beating it. We also review most of the state of the art of GW surrogates. Some numerical algorithms, conditioning details, scalability, parallelization and other practical points are discussed. The approaches presented are to a large extent non-intrusive (in the sense that no differential equations are invoked) and data-driven and can therefore be applicable to other disciplines. We close with open challenges in high dimension surrogates, which are not unique to GW science.