bluuebunny/crossref_metadata_2025 huggingface dataset:
Validating the knowledge bank approach for personalized prediction of survival in acute myeloid leukemia: a reproducibility study
Authors: Xu Yujun , Mansmann Ulrich
Published: April 2022

Reproducibility is not only essential for the integrity of scientific research but is also a prerequisite for model validation and refinement for the future application of predictive algorithms. However, reproducible research is becoming increasingly challenging, particularly in high-dimensional genomic data analyses with complex statistical or algorithmic techniques. Given that there are no mandatory requirements in most biomedical and statistical journals to provide the original data, analytical source code, or other relevant materials for publication, accessibility to these supplements naturally suggests a greater credibility of the published work. In this study, we performed a reproducibility assessment of the notable paper by Gerstung et al. (Nat Genet 49:332–340, 2017) by rerunning the analysis using their original code and data, which are publicly accessible. Despite an open science setting, it was challenging to reproduce the entire research project; reasons included: incomplete data and documentation, suboptimal code readability, coding errors, limited portability of intensive computing performed on a specific platform, and an R computing environment that could no longer be re-established. We learn that the availability of code and data does not guarantee transparency and reproducibility of a study; paradoxically, the source code is still liable to error and obsolescence, essentially due to methodological and computational complexity, a lack of reproducibility checking at submission, and updates for software and operating environment. The complex code may also hide problematic methodological aspects of the proposed research. Building on the experience gained, we discuss the best programming and software engineering practices that could have been employed to improve reproducibility, and propose practical criteria for the conduct and reporting of reproducibility studies for future researchers.
A New Therapeutic Approach for Dystussia and Atussia in Neurogenic Dysphagia: Effect of Aerosolized Capsaicin on Peak Cough Flow
Authors: Lüthi-Müller Eliane , Kool Jan , Mylius Veit , Diesener Paul
Published: April 2022

Swallowing and cough are crucial components of airway protection. In patients with neurogenic dysphagia (ND), there is a high prevalence of dystussia (impaired cough) and atussia (absence of cough). As a result, the ability to detect and remove aspirated material from the airway decreases, exacerbating the sequelae associated with ND, including aspiration pneumonia, a leading cause of mortality in ND. This controlled intervention study aimed to quantify the cough response to aerosolized capsaicin (AC) in patients with ND and assess the potential of AC as a therapeutic tool in treating ND-related dystussia and atussia. Furthermore, we propose a novel application method that enables AC treatment to be performed at home. Spirometry was used to measure peak cough flow (PCF) of voluntary cough (cough on command) and reflexive cough (cough secondary to pharyngeal exposure to AC) in 30 subjects with and 30 without ND. The capsaicin aerosol was generated by adding 1–10 drops of liquid cayenne extract (1.5–2% capsaicin) to 100 mL carbonated water (0.00075–0.001% to 0.0075–0.01% capsaicin). Voluntary PCF in the ND group was significantly lower than in the control group (p < 0.001), while there was no significant difference in reflexive PCF (p = 0.225). Within the ND group, reflexive PCF was significantly higher than voluntary PCF (p = 0.001), while in healthy controls, reflexive PCF was significantly lower (p < 0.001). The data show that AC increased the tracheobronchial clearance efficacy in ND patients with dystussia and atussia, as it enabled subjects to access their individual cough potential, which is present, but inaccessible, due to neurological disorder.
Solving three major biases of the ETAS model to improve forecasts of the 2019 Ridgecrest sequence
Authors: Grimm Christian , Hainzl Sebastian , Käser Martin , Küchenhoff Helmut
Published: April 2022

Strong earthquakes cause aftershock sequences that are clustered in time according to a power decay law, and in space along their extended rupture, shaping a typically elongate pattern of aftershock locations. A widely used approach to model earthquake clustering, theEpidemic Type Aftershock Sequence(ETAS) model, shows three major biases. First, the conventional ETAS approach assumes isotropic spatial triggering, which stands in conflict with observations and geophysical arguments for strong earthquakes. Second, the spatial kernel has unlimited extent, allowing smaller events to exert disproportionate trigger potential over an unrealistically large area. Third, the ETAS model assumes complete event records and neglects inevitable short-term aftershock incompleteness as a consequence of overlapping coda waves. These three aspects can substantially bias the parameter estimation and lead to underestimated cluster sizes. In this article, we combine the approach of Grimm et al. (Bulletin of the Seismological Society of America, 2021), who introduced a generalized anisotropic and locally restricted spatial kernel, with theETAS-Incomplete(ETASI) time model of Hainzl (Bulletin of the Seismological Society of America, 2021), to define an ETASI space-time model with flexible spatial kernel that solves the abovementioned shortcomings. We apply different model versions to a triad of forecasting experiments of the 2019 Ridgecrest sequence, and evaluate the prediction quality with respect to cluster size, largest aftershock magnitude and spatial distribution. The new model provides the potential of more realistic simulations of on-going aftershock activity, e.g. allowing better predictions of the probability and location of a strong, damaging aftershock, which might be beneficial for short term risk assessment and disaster response.
Myocardial function in COVID-19 patients after hospital discharge: a descriptive study comparing the first and second ‘wave’ patients
Authors: Elffers T. W. , de Graaf M. A. , Regeer M. V. , Omara S. , Schalij M. J. , Groeneveld G. H. , Roukens A. H. E. , Geelhoed J. J. M. , Antoni M. L.
Published: April 2022

In hospitalized COVID-19 patients, myocardial injury and echocardiographic abnormalities have been described. The present study investigates cardiac function in COVID-19 patients 6 weeks post-discharge and evaluates its relation to New York Heart Association (NYHA) class. Furthermore cardiac function post-discharge between the first and second wave COVID-19 patients was compared. We evaluated 146 patients at the outpatient clinic of the Leiden University Medical Centre. NYHA class of II or higher was reported by 53% of patients. Transthoracic echocardiography was used to assess cardiac function. Overall, in 27% of patients reduced left ventricular (LV) ejection fraction was observed and in 29% of patients LV global longitudinal strain was impaired (> − 16%). However no differences were observed in these parameters reflecting LV function between the first and second wave patients. Right ventricular (RV) dysfunction as assessed by tricuspid annular systolic planar excursion (< 17 mm) was present in 14% of patients, this was also not different between the first and second wave patients (15% vs. 12%; p = 0.63); similar results were found for RV fraction area change and RV strain. Reduced LV and RV function were not associated with NYHA class. In COVID-19 patients at 6 weeks post-discharge, mild abnormalities in cardiac function were found. However these were not related to NYHA class and there was no difference in cardiac function between the first and second wave patients. Long term symptoms post-COVID might therefore not be explained by mildly abnormal cardiac function.
The role of epigenetic modifications in Colorectal Cancer Metastasis
Authors: Su Riya , Wu Xinlin , Tao Liang , Wang Changshan
Published: April 2022

Distant metastasis is the major contributor to the high mortality rate of colorectal cancer (CRC). To overcome the poor prognosis caused by distant metastasis, the mechanisms of CRC metastasis should be further explored. Epigenetic events are the main mediators of gene regulation and further affect tumor progression. Recent studies have found that some epigenetic enzymes are often dysregulated or mutated in multiple tumor types, which prompted us to study the roles of these enzymes in CRC metastasis. In this review, we summarized the alteration of enzymes related to various modifications, including histone modification, nonhistone modification, DNA methylation, and RNA methylation, and their epigenetic mechanisms during the progression of CRC metastasis. Existing data suggest that targeting epigenetic enzymes is a promising strategy for the treatment of CRC metastasis.
Data mining of key genes expression in hepatocellular carcinoma: novel potential biomarkers of diagnosis prognosis or progression
Authors: Cabiati Manuela , Gaggini Melania , De Simone Paolo , Del Ry Silvia
Published: April 2022

Hepatocellular carcinoma (HCC) is one of the main cancer-related causes of death worldwide. The study aimed to perform a data mining analysis of the expression and regulatory role of key genes in HCC to reveal novel potential biomarkers of diagnosis prognosis, or progression since their availability is still almost lacking. Starting from data of our cohort of patients (HCV-positive HCC pts undergoing liver transplantation (LR, n = 10) and donors (LD, n = 14), deeply analyzed previously, in which apelin, osteopontin, osteoprotegerin, NOTCH-1, CASP-3, Bcl-2, BAX, PTX3, and NPTX2 were analyzed, we applied statistical analysis and in-silico tools (Gene Expression Profiling Interactive Analysis, HCCDB database and GeneMania, UALCAN) to screen and identify the key genes. Firstly, we performed a stepwise regression analysis using our mRNA-datasets which revealed that higher expression levels of apelin and osteopontin were positively associated with the HCC and identified that the most consistently differentially expressed gene across multiple HCC expression datasets was only OPN. This comprehensive strategy of data mining evidenced that OPN might have a potential function as an important tumor marker-driven oncogenesis being associated with poor prognosis of HCC patients.
Effect of heat treatments and loading orientation on the tensile properties and fracture toughness of AlSi7Mg alloy produced by Laser Powder Bed Fusion
Authors: de Menezes João Teixeira Oliveira , Castrodeza Enrique Mariano , Patriarca Luca , Casati Riccardo
Published: April 2022

The present study investigates the effect of building orientation and heat treatment routes on the mechanical behavior of the AlSi7Mg alloy (A357) produced by Laser Powder Bed Fusion. The microstructure and mechanical behavior of A357 in the as built, T5 (directly aged) and T6 (solution treated, water quenched and aged) conditions were compared. Tensile properties of the material were evaluated along two main directions (parallel and normal to the building platform), whereas fracture toughness was measured with cracks placed in three orthogonal orientations. The results indicate that the anisotropy in mechanical properties is greatly reduced after T6 temper, but the selection of the best condition between the as built, T5 and T6 temper must consider the main loading directions and possible crack growth orientations associated with the specific application.
Citizen science characterization of meanings of toponyms of Kenya: a shared heritage
Authors: Daniel Nyangweso , Mátyás Gede
Published: April 2022

This paper examines the toponymic heritage used in Kenya’s Authoritative Geographic Information (AGI) toponyms database of 26,600 gazetteer records through documentation and characterization of meanings of place names in topographic mapping. A comparison was carried out between AGI and GeoNames and between AGI and OpenStreetMap (OSM) volunteered records. A total of 15,000 toponymic matchings were found. Out of these, 1567 toponyms were then extracted for further scrutiny using AGI data in the historical records and from respondents on toponyms’ meanings. Experts in toponymy assisted in verifying these data. From the questionnaire responses, 235 names occurred in more than one place while AGI data had 284. The elements used to characterize the toponyms included historical perceptions of heritage evident in toponyms in their localities, ethnographic, toponymical and morphology studies on Kenya's dialects. There was no significant relationship established between the same place name usages among dialects as indicated by a positive weak correlation r (438), = 0.166, p < 0.001 based on the effect of using the related places and the distance between related places. The weak correlation implies that the one name one place principle does not apply due to diverse language boundaries, strong bonds associated with historical toponyms in the form of heritage and significant variations on how names resist changes to preserve their heritage.
Weighted iterated local branching for mathematical programming problems with binary variables
Authors: Rodrigues Filipe , Agra Agostinho , Hvattum Lars Magnus , Requejo Cristina
Published: April 2022

Local search algorithms are frequently used to handle complex optimization problems involving binary decision variables. One way of implementing a local search procedure is by using a mixed-integer programming solver to explore a neighborhood defined through a constraint that limits the number of binary variables whose values are allowed to change in a given iteration. Recognizing that not all variables are equally promising to change when searching for better neighboring solutions, we propose a weighted iterated local branching heuristic. This new procedure differs from similar existing methods since it considers groups of binary variables and associates with each group a limit on the number of variables that can change. The groups of variables are defined using weights that indicate the expected contribution of flipping the variables when trying to identify improving solutions in the current neighborhood. When the mixed-integer programming solver fails to identify an improving solution in a given iteration, the proposed heuristic may force the search into new regions of the search space by utilizing the group of variables that are least promising to flip. The weighted iterated local branching heuristic is tested on benchmark instances of the optimum satisfiability problem, and computational results show that the weighted method is superior to an alternative method without weights.
How to estimate carabid biomass?—an evaluation of size-weight models for ground beetles (Coleoptera: Carabidae) and perspectives for further improvement
Authors: Weiss Fabio , Linde Andreas
Published: April 2022

Biomass is an important metric for monitoring carabid populations and serves as an ecological indicator. Models that predict carabid weight based on body size represent a simple and straightforward method to estimate biomass and are therefore commonly used. However, such models are rarely evaluated against independent validation data. In this study, we evaluated the two widely used size-weight models by Szyszko (1983) and Booij et al. (1994) drawing on previously published independent data. Additionally, we developed and tested four new models to also evaluate the potential effect of taxonomic parameters; and compared model predictions with actual measurements of biomass using relative deviation graphs and observed versus predicted from regression. We show that the two models by Szyszko (1983) and Booij et al. (1994) contain systematic bias towards larger and smaller carabids, respectively, suggesting restricted applicability of such models. Additional taxonomic parameters improved weight predictions, indicating one possible solution to the issue of restricted applicability. We discuss further relevant limitations of size-weight models and their application and recommend a combined use of the models of Szyszko (1983) and Booij et al. (1994) for carabids ≥ 11.8 mm and < 11.8 mm, respectively.

Implications for insect conservation: Size-weight models are a suitable and simple method to estimate the biomass of carabids and have great potential to be used in monitoring schemes, the investigation of long-term trends and ecological studies. It is, however, essential that researchers pay special attention to potential restrictions in their applicability and methodological limitations.
State formation, social unrest and cultural distance
Authors: Lecce Giampaolo , Ogliari Laura , Orlando Tommaso
Published: April 2022

What determines violent reaction during state formation processes? To address this question, we exploit the uprisings that occurred when southern Italy was annexed to Piedmont during Italian unification in the 1860s. We assemble a novel dataset on episodes of brigandage, a form of violent rebellion against the unitary government, and on pre-unification social and economic characteristics of southern Italian municipalities. We find that the intensity of brigandage is ceteris paribus lower in and close to settlements of Piedmontese origin. We argue that geographical distance from these communities is a proxy for cultural distance from the Piedmontese rulers. Thus, our results suggest that, in the context of state formation, cultural proximity to the new ruler reduces social unrest by local communities. After ruling out alternative mechanisms consistent with the economic literature, we provide suggestive evidence of cultural persistence and diffusion in our context, and discuss two possible culture-based drivers of our results: social identification with the Piedmontese rulers, and a clash between local values and some specific content of the new institutions.
Honeycomb-like V2O5 Based Films: Synthesis, Structural, Thermal, and Optical Properties for Environmental Applications
Authors: Ali Heba , Ismail A. M.
Published: April 2022

In the present study, new composite films consisting of hierarchical nanobelt V2O5and polymer mixture were prepared via a simple casting method. The incorporation of 30 wt.% of V2O5into the polymer matrix yielded a honeycomb like structure with abundant micro-voids (5.5 μm), higher roughness average by 45.8%, and a higher root mean square roughness by 52%, which are beneficial for the enhancement of active surface area for dye adsorption. Furthermore, optical property studies have shown that the incorporation of V2O5has made the nanocomposite film a suitable UV–visible light-sensitive material, and thus the application of films can be expanded towards photocatalytic degradation of various toxic pollutants such as nitrophenol, Cr(VI), antibiotects, and so on. Finally, the composite film exhibited enhanced thermostability in comparison to unmodified film, as confirmed by TGA and DSC analysis. The optimal film showed 96.3% removal efficiency and 27.02 mg/g adsorption capacity. The dye sorption performance of V2O5based films is studied at various times, dosages, and initial dye concentrations. The experimental data more closely fit the Langmuir isotherm model (R2 = 0.997) than the Freundlich, Temkin, and Dubinin–Radushkevich isotherm models, demonstrating a monolayer adsorption mechanism. The MB adsorption process on V2O5film was controlled by the chemical adsorption step, which was evidenced by the good-fitting of kinetic adsorption results to the pseudo second order model (R2 = 0.991). The obtained results indicated that the V2O5based films in this work are hopeful candidates for environmental applications.
Spectral Coarse Spaces for the Substructured Parallel Schwarz Method
Authors: Ciaramella Gabriele , Vanzan Tommaso
Published: April 2022

The parallel Schwarz method (PSM) is an overlapping domain decomposition (DD) method to solve partial differential equations (PDEs). Similarly to classical nonoverlapping DD methods, the PSM admits a substructured formulation, that is, it can be formulated as an iteration acting on variables defined exclusively on the interfaces of the overlapping decomposition. In this manuscript, spectral coarse spaces are considered to improve the convergence and robustness of the substructured PSM. In this framework, the coarse space functions are defined exclusively on the interfaces. This is in contrast to classical two-level volume methods, where the coarse functions are defined in volume, though with local support. The approach presented in this work has several advantages. First, it allows one to use some of the well-known efficient coarse spaces proposed in the literature, and facilitates the numerical construction of efficient coarse spaces. Second, the computational work is comparable or lower than standard volume two-level methods. Third, it opens new interesting perspectives as the analysis of the new two-level substructured method requires the development of a new convergence analysis of general two-level iterative methods. The new analysis casts light on the optimality of coarse spaces: given a fixed dimensionm, the spectral coarse space made by the firstmdominant eigenvectors is not necessarily the minimizer of the asymptotic convergence factor. Numerical experiments demonstrate the effectiveness of the proposed new numerical framework.
Time Series Path Integral Expansions for Stochastic Processes
Authors: Greenman Chris D.
Published: April 2022

A form of time series path integral expansion is provided that enables both analytic and numerical temporal effect calculations for a range of stochastic processes. All methods rely on finding a suitable reproducing kernel associated with an underlying representative algebra to perform the expansion. Birth–death processes can be analysed with these techniques, using either standard Doi-Peliti coherent states, or the $${\mathfrak {s}}{\mathfrak {u}}(1,1)$$

s
u
(
1
,
1
)

Lie algebra. These result in simplest expansions for processes with linear or quadratic rates, respectively. The techniques are also adapted to diffusion processes. The resulting series differ from those found in standard Dyson time series field theory techniques.
Informing policy with text mining: technological change and social challenges
Authors: Gyódi Kristóf , Nawaro Łukasz , Paliński Michał , Wilamowski Maciej
Published: April 2022

This study presents an innovative text mining methodology that supports policy analysts with problem recognition, definition and selection. The empirical analysis is based on four years of online news articles published in the period 2016–2019. Using a combination of text mining methods (analysis of term-frequencies, co-occurrence and sentiment analysis), we identify trending terms and explore selected regulatory issues. The analysis demonstrates that while each text mining algorithm provides insightful results, their combination yields more detailed and robust overview of regulatory problems. The results present early signals and trends, the connections between trending topics, and the changing public attitudes towards them.
Fiuncho: a program for any-order epistasis detection in CPU clusters
Authors: Ponte-Fernández Christian , González-Domínguez Jorge , Martín María J.
Published: April 2022

Epistasis can be defined as the statistical interaction of genes during the expression of a phenotype. It is believed that it plays a fundamental role in gene expression, as individual genetic variants have reported a very small increase in disease risk in previous Genome-Wide Association Studies. The most successful approach to epistasis detection is the exhaustive method, although its exponential time complexity requires a highly parallel implementation in order to be used. This work presents Fiuncho, a program that exploits all levels of parallelism present in x86_64 CPU clusters in order to mitigate the complexity of this approach. It supports epistasis interactions of any order, and when compared with other exhaustive methods, it is on average 358, 7 and 3 times faster than MDR, MPI3SNP and BitEpi, respectively.
Is the HYPE about strength warranted?
Authors: Fischer Martin
Published: April 2022

In comparing classical and non-classical solutions to the semantic paradoxes arguments relying on strength have been influential. In this paper I argue that non-classical solutions should preserve the proof-theoretic strength of classical solutions. Leitgeb’s logic of HYPE is then presented as an interesting possibility to strengthen FDE with a suitable conditional. It is shown that HYPE allows for a non-classical Kripkean theory of truth, called KFL, that is strong enough for the relevant purposes and has additional attractive properties.
Effect of Moisture, Hydrogen, and Water–Gas Shift Reaction on the Prereduction Behavior of Comilog and Nchwaning Manganese Ores
Authors: Larssen Trine A. , Tangstad Merete
Published: April 2022

The ore–gas reactions in the prereduction zone in a ferromanganese furnace are largely decisive of the overall energy efficiency, carbon consumption, and climate gas emissions in ferromanganese production. An increased understanding of the prereduction zone is thus vital for optimization of the furnace operation. The ore–gas reactions are well known to be governed by kinetics rather than thermodynamics. The raw materials contain various amounts of both chemically bound and surface moisture when fed to the furnace, which may influence the reaction kinetics. This paper presents the investigation of the potential influence of moisture on the prereduction kinetics of two commercial manganese ores, i.e., Comilog and Nchwaning. TGA experiments were carried out by comparing dry and wet ore, as well as introducing H2(g) or H2O(g) to the CO–CO2 gas mixture.
Role of sucrose and phloem–xylem interaction in recovery of water status and hydraulic dehydration impacts in tobacco plants (Nicotiana tabacum)
Authors: Ennajeh Mustapha , Ehwald Rudolf , Kühn Christina
Published: April 2022

The role of phloem–xylem interaction via sucrose exchanges in recovery of dehydration impacts, specifically xylem embolism, has not been directly investigated thus far. Most previous studies were indirect approaches leading to suggestive conclusions. We hypothesized that a block in phloem loading and so no exchange of sucrose with xylem affect tolerance and recovery of tobacco plants (Nicotiana tabacum) during dehydration and after the rehydration phase. TransgenicN.tabacum(αNtSUT1-antisense) plants, which showed impaired phloem loading and high accumulation of soluble sugars in leaves, were compared to the wild-type (WT) plants. The water status, osmotic adjustments, leaf turgor, stomatal conductance, xylem cavitation, and stem xylem sucrose content were determined during dehydration and after the rehydration phases. Results showed that retention of sucrose outside phloem conduits highly improved water status, osmotic adjustment and turgidity of the source leaves in the transgenics during drought period. However, no impact occurred on stomata function and tolerance to xylem cavitation in αNtSUT1. After the rehydration period, WT plants with free phloem transport and phloem–-xylem exchange of sucrose recovered better their water status, leaf turgidity, stomatal conductance and xylem functioning thanαNtSUT1plants. The accumulation of sucrose in leaves of transformants ameliorated their tolerance to water deficit by reinforcing the osmotic adjustment mechanism at the leaf level. However, lack of sucrose in phloem sieve resulted in impairment of hydraulic recovery of xylem from drought ofαNtSUT1after rehydration. This suggests a crucial role of the phloem–-xylem exchange of sucrose in refilling of embolized xylem vessels.
Interplay of Obesity, Ethanol, and Contaminant Mixture on Clinical Profiles of Cardiovascular and Metabolic Diseases: Evidence from an Animal Study
Authors: Florian Maria , Li Bai , Patry Dominique , Truong Jocelyn , Caldwell Don , Coughlan Melanie C. , Woodworth Robert , Yan Jin , Chen Qixuan , Petrov Ivan , Mahemuti Laziyan , Lalande Michelle , Li Nanqin , Chan Laurie H. M. , Willmore William G. , Jin Xiaolei
Published: April 2022

Obesity, ethanol, and contaminants are known risk factors of cardiovascular and metabolic diseases (CMD). However, their interplay on clinical profiles of these diseases remains unclear, and thus were investigated in this study. Male lean or obese JCR rats were given water or 10% ethanol and orally treated with or without a contaminant mixture (CM) dissolved in corn oil and loaded on two cookies at 0, 1.6, or 16 mg/kg BW/day dose levels for 4 weeks. The CM consisted 22 environmental contaminants found in human blood or serum of Northern populations. Over 60 parameters related to CMD were examined. The results revealed that obesity in JCR rats resembles the clinical profiles of non-alcoholic fatty liver disease in humans. Obesity was also associated with increased serum and organ retention of mercury, one of the chemical components of CM. Exposure to ethanol lightened hyperlipidemia, increased liver retention of mercury, and increased risk for hypertension in the obese rats. CM lessened hyperlipidemia and hyperenzymemia, worsened systemic inflammation and increased the risk for hypertension in the obese rats. CM markedly increased serum ethanol levels with or without ethanol exposure. Tissue total mercury contents significantly correlated with clinical parameters with altered profiles by both ethanol and obesity. These results suggest that obese individuals may be more prone to contaminant accumulation. Ethanol and CM exposure can alter clinical profiles associated with obesity, which may lead to misdiagnosis of CMD associated with obesity. CM can alter endogenous production and/or metabolism of ethanol, further complicating disease progression, diagnosis, and treatment.
Affective Attitudes Toward Robots at Work: A Population-Wide Four-Wave Survey Study
Authors: Savela Nina , Latikka Rita , Oksa Reetta , Kortelainen Sanna , Oksanen Atte
Published: April 2022

Robotization of work is progressing fast globally, and the process has accelerated during the COVID-19 pandemic. Utilizing integrated threat theory as a theoretical framework, this study investigated affective attitudes toward introducing robots at work using a four timepoint data (n = 830) from a Finnish working population longitudinal study. We used hybrid multilevel linear regression modelling to study within and between participant effects over time. Participants were more positive toward introducing robots at work during the COVID-19 pandemic than before it. Increased cynicism toward individuals’ own work, robot-use self-efficacy, and prior user experiences with robots predicted positivity toward introducing robots at work over time. Workers with higher perceived professional efficacy were less and those with higher perceived technology-use productivity, robot-use self-efficacy, and prior user experiences with robots were more positive toward introducing robots at work. In addition, the affective attitudes of men, introverts, critical personalities, workers in science and technology fields, and high-income earners were more positive. Robotization of work life is influenced by workers’ psychological well-being factors and perceived as a welcomed change in the social distancing reality of the pandemic.
Experimental analysis and deliverability calculation of abnormally pressured carbonate gas reservoir considering stress sensitivity
Authors: Cheng Youyou , Guo Chunqiu , Tan Chengqian , Chen Pengyu , Shi Haidong , Xing Yuzhong
Published: April 2022

The stress sensitivity of abnormally pressured carbonate gas reservoirs is of great complexity and exerts much influence on gas well deliverability calculation. Fifty core samples from the AD Gas Reservoirs were selected in the experiment to study the effect of abnormally high pressure and fracture on the stress sensitivity of carbonate gas reservoir. The results show that the permeability decline mainly occurs in the abnormally high-pressure stage and is rather small in normal pressure stage. The existence of the fracture could substantially enhance the stress sensitivity. The higher fracture density could induce the stronger stress sensitivity. Furthermore, a mathematical model with the consideration of the variable permeability modulus was established to calculate gas well deliverability in the abnormally pressured carbonate gas reservoir with developed natural fractures. It is revealed that previous method assuming a fixed permeability modulus would lead to an overestimation of the real stress sensitivity and thus underestimating the absolute open flow of the gas well.
Smaller farm size and ruminant animals are associated with increased supply of non-provisioning ecosystem services
Authors: Karlsson Johan O. , Tidåker Pernilla , Röös Elin
Published: April 2022

To balance trade-offs between livestock’s negative environmental impacts and their positive contributions (e.g. maintaining semi-natural grasslands, varied agricultural landscapes and crop rotations), a better understanding is needed of how the supply of ecosystem services differs across farms. We analysed a suite of indicators for non-provisioning ecosystem services on a large subset of Swedish farms (71% of farms, covering 82% of agricultural land) and related these to farm type, farm size and livestock density. The analysed indicators exhibited clear geographical patterns with hotspots especially in less productive regions. Controlling for this spatial variation we still found that small-scale and ruminant farms were associated with more varied landscapes, small-scale habitats, semi-natural grasslands and better crop sequences compared to nearby farms specialised in crop production, while farms specialising in monogastric livestock were associated with less varied landscapes and inferior crop sequences. Results for cultural ecosystem services indicated that farms with more semi-natural grassland were associated with more visitors and more likely located within designated recreation or nature conservation areas.
Cascaded Random Raman Fiber Laser With Low RIN and Wide Wavelength Tunability
Authors: Han Bing , Dong Shisheng , Liu Yang , Wang Zinan
Published: April 2022

Cascaded random Raman fiber lasers (CRRFLs) have been used as a new platform for designing high power and wavelength-agile laser sources. Recently, CRRFL pumped by ytterbium-doped random fiber laser (YRFL) has shown both high power output and low relative intensity noise (RIN). Here, by using a wavelength- and bandwidth-tunable point reflector in YRFL, we experimentally investigate the impacts of YRFL on the spectral and RIN properties of the CRRFL. We verify that the bandwidth of the point reflector in YRFL determines the bandwidth and temporal stability of YRFL. It is found that with an increase in the bandwidth of the point reflector in YRFL from 0.2nm to 1.4nm, CRRFL with higher spectral purity and lower RIN can be achieved due to better temporal stability of YRFL pump. By broadening the point reflector’s bandwidth to 1.4nm, the lasing power, spectral purity, and RIN of the 4th-order random lasing at 1349nm can reach 3.03W, 96.34%, and −115.19 dB/Hz, respectively. For comparison, the spectral purity and RIN of the 4th-order random lasing with the point reflector’s bandwidth of 0.2 nm are only 91.20% and −107.99dB/Hz, respectively. Also, we realize a wavelength widely tunable CRRFL pumped by a wavelength-tunable YRFL. This work provides a new platform for the development of ideal distributed Raman amplification pump sources based on CRRFLs with both good temporal stability and wide wavelength tunability, which is of great importance in applications of optical fiber communication and distributed sensing.
Catalysts of Connectedness: A Case for Greater Complexity in Religious Identity Formation Research
Authors: Bankier-Karp Adina Leah
Published: April 2022

Background

Religious identity research has predominantly investigated effects of discrete factors, despite many factors exercising interconnected effects on religious connectedness, resulting in a limited understanding of the mechanism influencing religious identity development.

Purpose

This study examined the mechanism underlying the religious identity development in Jewish young adults, also showcasing the benefits of bringing together a range of known catalysts for examination in a single analytic model.

Methods

Informed by Bronfenbrenner's bioecological model, data from a sample of 1712 young adults from the Gen17: Australian Jewish Community Study (2018) was used to estimate bivariate and OLS regression models including moderated mediation to examine the relationships between Jewish schooling, critical Jewish experiences, parental religious connectedness and young adult religious connectedness.

Results

Jewish schooling significantly affected young adults' religious connectedness; without mediating effects of other critical Jewish experiences, however, Jewish schooling effects were negligible. Upbringing by parents with high religious connectedness had an intensifying effect, while parents with low religious connectedness had a diminishing effect on the association between Jewish schooling and young adult religious connectedness. Those raised by parents with high religious connectedness had higher religious connectedness than those raised by parents with low-to-moderate religious connectedness, regardless of Jewish schooling. In addition, having a high proportion of Jewish peers in one's friendship network was the most powerful of the critical Jewish experiences in mediating the effect of Jewish schooling on religious connectedness.

Conclusions and implications

Parents and Jewish friendship networks play important roles in the development of young adults' religious connectedness, which is only apparent with research approaches that acknowledge the complexity of the formation of religious connectedness. The enduring nature of these influences even into young adulthood has implications for scholars of religion as well as religious communities, as there may be greater gain from investment in agency-building in families and coreligionist friendship networks rather than outsourcing to program development by communal institutions.
Dissecting the correlates of N-terminal prohormone brain natriuretic peptide in acute infective endocarditis
Authors: Bertolino Lorenzo , Ursi Maria Paola , Iossa Domenico , Karruli Arta , D’Amico Fabiana , Zampino Rosa , Dialetto Giovanni , De Feo Marisa , Durante-Mangoni Emanuele ,   The Monaldi Hospital Cardiovascular Infection Study Group, Durante-Mangoni Emanuele , Iossa Domenico , Bertolino Lorenzo , Ursi Maria Paola , D’Amico Fabiana , Karruli Arta , Ramadan Mohammad , Andini Roberto , Zampino Rosa , Bernardo Mariano , Ruocco Giuseppe , Dialetto Giovanni , Covino Franco Enrico , Manduca Sabrina , Della Corte Alessandro , De Santo Luca S. , Carozza Antonio , De Feo Marisa , De Vivo MD Stefano , De Rimini Maria Luisa , Galdieri Nicola
Published: April 2022

Purpose

To explore the prognostic value and the correlates of NT-proBNP in patients with acute infective endocarditis, a life-threatening disease, with an often unpredictable outcome given by the lack of reliable prognostic parameters.

Methods

We retrospectively studied 337 patients admitted to our centre between January 1, 2006 and September 30, 2020 with available NT-proBNP level at admission. Our analyses were performed considering NT-proBNP as both a categorical variable, using the median value as the cut-off level, and numerical variable. Study end points were in-hospital mortality, cardiac surgery and 1 year survival.

Results

NT-proBNP was an independent predictor of in-hospital mortality (OR 14.9 [95%C.I. 2.46–90.9]; P = .003). Levels below 2926 pg/mL were highly predictive of a favorable in-hospital outcome (negative predictive value 96.6%). Patients with higher NT-proBNP levels showed a significantly lower survival rate at 1 year follow-up (log-rank P = .005). NT-proBNP was strongly associated with chronic kidney disease (P < .001) and significantly higher in patients with prior chronic heart failure (P = .001). NT-proBNP was tightly related to staphylococcal IE (P = .001) as well as with higher CRP and hs-troponin I (P = 0.023, P < .001, respectively).

Conclusion

Our results confirm the remarkable prognostic role of NT-proBNP in patients with IE and provide novel evidences of its multifaceted correlates in this unique clinical setting. Our data strongly support the incorporation of NT-proBNP into the current diagnostic work-up of IE.
Combination of selective androgen and estrogen receptor modulators in orchiectomized rats
Authors: Roch P. J. , Wolgast V. , Gebhardt M.-M. , Böker K. O. , Hoffmann D. B. , Saul D. , Schilling A. F. , Sehmisch S. , Komrakova M.
Published: April 2022

Purpose

Selective androgen and estrogen receptor modulators, ostarine (OST) and raloxifen (RAL), reportedly improve muscle tissue and offer therapeutic approaches to muscle maintenance in the elderly. The present study evaluated the effects of OST and RAL and their combination on musculoskeletal tissue in orchiectomized rats.

Methods

Eight-month-old Sprague Dawley rats were analyzed. Experiment I: (1) Untreated non-orchiectomized rats (Non-ORX), (2) untreated orchiectomized rats (ORX), (3) ORX rats treated with OST during weeks 0–18 (OST-P), (4) ORX rats treated with OST during weeks 12–18 (OST-T). Experiment II: 1) Non-ORX, (2) ORX, 3) OST-P, (4) ORX rats treated with RAL, during weeks 0–18 (RAL-P), 5) ORX rats treated with OST + RAL, weeks 0–18 (OST + RAL-P). The average daily doses of OST and RAL were 0.4 and 7 mg/kg body weight (BW). Weight, fiber size, and capillarization of muscles, gene expression, serum markers and the lumbar vertebral body were analyzed.

Results

OST-P exerted favorable effects on muscle weight, expression of myostatin and insulin growth factor-1, but increased prostate weight. OST-T partially improved muscle parameters, showing less effect on the prostate. RAL-P did not show anabolic effects on muscles but improved body constitution by reducing abdominal area, food intake, and BW. OST + RAL-P had an anabolic impact on muscle, reduced androgenic effect on the prostate, and normalized food intake. OST and RAL improved osteoporotic bone.

Conclusions

The OST + RAL treatment appeared to be a promising option in the treatment of androgen-deficient conditions and showed fewer side effects than the respective single treatments.
Dialysis symptom index burden and symptom clusters in a prospective cohort of dialysis patients
Authors: You Amy S. , Kalantar Sara S. , Norris Keith C. , Peralta Rene Amel , Narasaki Yoko , Fischman Ronald , Fischman Michael , Semerjian Avedik , Nakata Tracy , Azadbadi Zahra , Nguyen Danh V. , Kalantar-Zadeh Kamyar , Rhee Connie M.
Published: April 2022

Background

Dialysis patients experience a high symptom burden, which may adversely impact their quality of life. Whereas other specialties emphasize routine symptom assessment, symptom burden is not well-characterized in dialysis patients. We sought to examine the prevalence and severity of unpleasant symptoms in a prospective hemodialysis cohort.

Methods

Among 122 hemodialysis patients from the prospective Malnutrition, Diet, and Racial Disparities in Chronic Kidney Disease (CKD) study, CKD-associated symptoms were ascertained by the Dialysis Symptom Index, a validated survey assessing symptom burden/severity (with higher scores indicating greater symptom severity), over 6/2020–10/2020. We examined the presence of (1) individual symptoms and symptom severity scores, and (2) symptom clusters (defined as ≥ 2 related concurrent symptoms), as well as correlations with clinical characteristics.

Results

Symptom severity scores were higher among non-Hispanic White and Hispanic patients, whereas scores were lower in Black and Asian/Pacific Islander patients. In the overall cohort, the most common individual symptoms included feeling tired/lack of energy (71.3%), dry skin (61.5%), trouble falling asleep (44.3%), muscle cramps (42.6%), and itching (42.6%), with similar patterns observed across racial/ethnic groups. The most prevalent symptom clusters included feeling tired/lack of energy + trouble falling asleep (37.7%); trouble falling asleep + trouble staying asleep (34.4%); and feeling tired/lack of energy + trouble staying asleep (32.0%). Lower hemoglobin, iron stores, and dialysis adequacy correlated with higher individual and overall symptom severity scores.

Conclusion

We observed a high prevalence of unpleasant symptoms and symptom clusters in a diverse hemodialysis cohort. Further studies are needed to identify targeted therapies that ameliorate symptom burden in CKD.

Graphical abstract
Impulse balancing versus equilibrium learning an experimental study of competitive portfolio selection
Authors: Avrahami Judith , Güth Werner , Kareev Yaakov , Ploner Matteo
Published: April 2022

The experiment lets investors interact in portfolio choices involving different risky assets, one for each state of the world. Probabilities of random states are commonly known. All assets pay the same dividend when their state is realized and becomes worthless otherwise. Whereas evolutionary stability and equilibrium behavior predict equal expected profits across assets, impulse balancing (Selten and Buchta, Games and human behavior: essays in the Honor of Amnon Rapoport, 1999) equalizes the expected regret. Thus, impulse balancing seems to capture tendencies of cyclical direction learning. In addition to analyzing whether and when behavior converges to impulse balancing or to equilibrium portfolios, we categorize portfolio adaptation by path dependence and sensitivity to state-specific probabilities. We show that portfolio choices are driven mainly by probability matching, but the effect becomes weaker over time. Furthermore, most portfolio adjustments are not compatible with directional learning.
Machine learning-integrated 5D BIM informatics: building materials costs data classification and prototype development
Authors: Banihashemi Saeed , Khalili Saeed , Sheikhkhoshkar Moslem , Fazeli Abdulwahed
Published: April 2022

Non-informatics cost estimation is a tedious process and requires substantial amount of time and manual operations. However, BIM adoption approaches have attracted significant attention with this respect. Since BIM models are object-based with built-in parametric information, it is easier to capture the quantities of building elements and deliver more accurate estimates with less errors and omissions. As most of the current cost estimation standards are designed and developed based on old-fashioned construction project delivery systems, a lack of compatibility between their classification and BIM-based informatics is observed. This study, therefore, aims to develop an informatics framework to integrate a cost estimation standard with BIM in order to expedite the 5D BIM process and enhance the digital transformation practices in construction projects. The developed framework is considered to be a new approach which can automatically estimate the cost of building elements using machine learning-integrated algorithms and MATLAB engine for its effective implementation.