bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interobserver agreement and prognostic impact for MRI–based 2018 FIGO staging parameters in uterine cervical cancer
Authors: Wagner-Larsen Kari S. , Lura Njål , Salvesen Øyvind , Halle Mari Kyllesø , Forsse David , Trovik Jone , Smit Noeska , Krakstad Camilla , Haldorsen Ingfrid S. 
Published: March 2022

Abstract
Objectives
To evaluate the interobserver agreement for MRI–based 2018 International Federation of Gynecology and Obstetrics (FIGO) staging parameters in patients with cervical cancer and assess the prognostic value of these MRI parameters in relation to other clinicopathological markers.

Methods
This retrospective study included 416 women with histologically confirmed cervical cancer who underwent pretreatment pelvic MRI from May 2002 to December 2017. Three radiologists independently recorded MRI–derived staging parameters incorporated in the 2018 FIGO staging system. Kappa coefficients (κ) for interobserver agreement were calculated. The predictive and prognostic values of the MRI parameters were explored using ROC analyses and Kaplan–Meier with log-rank tests, and analyzed in relation to clinicopathological patient characteristics.

Results
Overall agreement was substantial for the staging parameters: tumor size > 2 cm (κ = 0.80), tumor size > 4 cm (κ = 0.76), tumor size categories (≤ 2 cm; > 2 and ≤ 4 cm; > 4 cm) (κ = 0.78), parametrial invasion (κ = 0.63), vaginal invasion (κ = 0.61), and enlarged lymph nodes (κ = 0.63). Higher MRI–derived tumor size category (≤ 2 cm; > 2 and ≤ 4 cm; > 4 cm) was associated with a stepwise reduction in survival (p ≤ 0.001 for all). Tumor size > 4 cm and parametrial invasion at MRI were associated with aggressive clinicopathological features, and the incorporation of these MRI–based staging parameters improved risk stratification when compared to corresponding clinical assessments alone.

Conclusion
The interobserver agreement for central MRI–derived 2018 FIGO staging parameters was substantial. MRI improved the identification of patients with aggressive clinicopathological features and poor survival, demonstrating the potential impact of MRI enabling better prognostication and treatment tailoring in cervical cancer.

Key Points
• The overall interobserver agreement was substantial (κ values 0.61–0.80) for central MRI staging parameters in the 2018 FIGO system.
• Higher MRI–derived tumor size category was linked to a stepwise reduction in survival (p ≤ 0.001 for all).
• MRI–derived tumor size > 4 cm and parametrial invasion were associated with aggressive clinicopathological features, and the incorporation of these MRI–derived staging parameters improved risk stratification when compared to clinical assessments alone.
Could detection and attribution of climate change trends be spurious regression?
Authors: Cummins Donald P. , Stephenson David B. , Stott Peter A. 
Published: March 2022

AbstractSince the 1970s, scientists have developed statistical methods intended to formalize detection of changes in global climate and to attribute such changes to relevant causal factors, natural and anthropogenic. Detection and attribution (D&A) of climate change trends is commonly performed using a variant of Hasselmann’s “optimal fingerprinting” method, which involves a linear regression of historical climate observations on corresponding output from numerical climate models. However, it has long been known in the field of time series analysis that regressions of “non-stationary” or “trending” variables are, in general, statistically inconsistent and often spurious. When non-stationarity is caused by “integrated” processes, as is likely the case for climate variables, consistency of least-squares estimators depends on “cointegration” of regressors. This study has shown, using an idealized linear-response-model framework, that if standard assumptions hold then the optimal fingerprinting estimator is consistent, and hence robust against spurious regression. In the case of global mean surface temperature (GMST), parameterizing abstract linear response models in terms of energy balance provides this result with physical interpretability. Hypothesis tests conducted using observations of historical GMST and simulation output from 13 CMIP6 general circulation models produced no evidence that standard assumptions required for consistency were violated. It is therefore concluded that, at least in the case of GMST, detection and attribution of climate change trends is very likely not spurious regression. Furthermore, detection of significant cointegration between observations and model output indicates that the least-squares estimator is “superconsistent”, with better convergence properties than might previously have been assumed. Finally, a new method has been developed for quantifying D&A uncertainty, exploiting the notion of cointegration to eliminate the need for pre-industrial control simulations.
New FPT Algorithms for Finding the Temporal Hybridization Number for Sets of Phylogenetic Trees
Authors: Borst Sander , van Iersel Leo , Jones Mark , Kelk Steven 
Published: March 2022

AbstractWe study the problem of finding a temporal hybridization network containing at most k reticulations, for an input consisting of a set of phylogenetic trees. First, we introduce an FPT algorithm for the problem on an arbitrary set of m binary trees with n leaves each with a running time of $$O(5^k\cdot n\cdot m)$$

O
(

5
k

·
n
·
m
)

. We also present the concept of temporal distance, which is a measure for how close a tree-child network is to being temporal. Then we introduce an algorithm for computing a tree-child network with temporal distance at most d and at most k reticulations in $$O((8k)^d5^ k\cdot k\cdot n\cdot m)$$

O
(

(
8
k
)

d

5
k

·
k
·
n
·
m
)

time. Lastly, we introduce an $$O(6^kk!\cdot k\cdot n^2)$$

O
(

6
k

k
!
·
k
·

n
2

)

time algorithm for computing a temporal hybridization network for a set of two nonbinary trees. We also provide an implementation of all algorithms and an experimental analysis on their performance.
Full-length MAVS, a mitochondrial antiviral-signaling protein, inhibits hepatitis E virus replication, requiring JAK-STAT signaling
Authors: Qu Changbo , Li Yang , Li Yunlong , Pan Yihang 
Published: March 2022

AbstractHepatitis E virus (HEV) infection is the leading cause of acute hepatitis worldwide. The mitochondrial antiviral signaling protein (MAVS)-mediated interferon (IFN) response plays a pivotal role in hepatic antiviral immunity. However, little is known about the effect of overexpression of MAVS on HEV infection. Full-length MAVS (FL-MAVS) is the main form of MAVS that increases the production of IFNs. Here, we studied the effect of FL-MAVS on HEV infection. We found that overexpression of FL-MAVS profoundly inhibited HEV replication. Furthermore, we showed that the anti-HEV effect of FL-MAVS is largely dependent on JAK-STAT signaling activation.
Estimation of groundwater recharge rates using soil-water isotope profiles: a case study of two contrasting dune types on Langeoog Island, Germany
Authors: Post V. E. A. , Zhou T. , Neukum C. , Koeniger P. , Houben G. J. , Lamparter A. , Šimůnek J. 
Published: March 2022

AbstractThe creation of artificial dunes for coastal protection may have important consequences for freshwater lenses in coastal aquifers. The objective of this study was to compare the recharge processes below such a young dune with scant vegetation to an older dune covered by grass and herbaceous vegetation. To this aim, soil and water samples were collected from the unsaturated zone at two sites on Langeoog Island in northern Germany, and the soil water was analysed for stable water isotopes and chloride. Recharge rates were calculated by using a new version of HYDRUS-1D, which was modified to simulate isotope fractionation during evaporation. Both the model outcomes and the data highlight the importance of fractionation, which is slightly more pronounced at the older, more vegetated dune. At the newly constructed dune, vegetation dieback seemingly reduces the importance of transpiration during summer. Recharge occurs year-round, albeit predominantly during the winter months. Calculated recharge rates are consistent with lysimeter measurements, but are significantly higher than previously reported rates based on groundwater age data, which is primarily attributed to the absence of dune shrub at the sites investigated here. More data are needed to establish the importance of soil-water repellency and overland flow. Based on the results, it is proposed that repeated isotope sampling can yield important insights into the dynamics of recharge processes, including their response to climate change.
Subtle Differences in Brain Architecture in Patients with Congenital Anosmia
Authors: Thaploo Divesh , Georgiopoulos Charalampos , Haehner Antje , Hummel Thomas 
Published: March 2022

AbstractPeople suffering from congenital anosmia show normal brain architecture although they do not have functional sense of smell. Some studies in this regard point to the changes in secondary olfactory cortex, orbitofrontal cortex (OFC), in terms of gray matter volume increase. However, diffusion tensor imaging has not been explored so far. We included 13 congenital anosmia subjects together with 15 controls and looked into various diffusion parameters like FA. Increased FA in bilateral OFC confirms the earlier studies reporting increased gray matter thickness. However, it is quite difficult to interpret FA in terms of gray matter volume. Increased FA has been seen with recovery after traumatic brain injury. Such changes in OFC point to the plastic nature of the brain.
What Makes You a Whistleblower? A Multi-Country Field Study on the Determinants of the Intention to Report Wrongdoing
Authors: Latan Hengky , Chiappetta Jabbour Charbel Jose , Ali Murad , Lopes de Sousa Jabbour Ana Beatriz , Vo-Thanh Tan 
Published: March 2022

AbstractWhistleblowers have significantly shaped the state of contemporary society; in this context, this research sheds light on a persistently neglected research area: what are the key determinants of whistleblowing within government agencies? Taking a unique methodological approach, we combine evidence from two pieces of fieldwork, conducted using both primary and secondary data from the US and Indonesia. In Study 1, we use a large-scale survey conducted by the US Merit Systems Protection Board (MSPB). Additional tests are conducted in Study 1, making comparisons between those who have and those who do not have whistleblowing experience. In Study 2, we replicate the survey conducted by the MSPB, using empirical data collected in Indonesia. We find a mixture of corroboration of previous results and unexpected findings between the two samples (US and Indonesia). The most relevant result is that perceived organizational protection has a significant positive effect on whistleblowing intention in the US sample, but a similar result was not found in the Indonesian sample. We argue that this difference is potentially due to the weakness of whistleblowing protection in Indonesia, which opens avenues for further understanding the role of societal cultures in protecting whistleblowers around the globe.
Toward a collaborative governance model for distributed ledger technology adoption in organizations
Authors: Anthony Jnr. Bokolo 
Published: March 2022

AbstractDistributed ledger technology (DLT) is one of the emerging technologies adopted in organizations. Unlike traditional databases, the integrity of the DLT is maintained automatically by an algorithmic consensus mechanism and not by any dominant authority. Thus, the consensus mechanism controls the decision-making and governance process. But the adoption of DLT is faced with issues regarding how to ensure that governance decisions in distributed ledger systems in the interest of all actors and stakeholders involved in the operations of organizational operations. Therefore, it is imperative to provides a better understanding of the governance of DLT adoption in organizations. Accordingly, this study conducts an extensive literature review to investigate the governance issues and control of DLT adoption in intra-organizational domain. Findings from this study presents state-of-the-art governance practices to offer a comprehensive understanding on key governance issues in organizations. Additionally, the findings present factors associated with governance of DLT adoption solutions. More importantly, a governance model is developed to enhance the adoption of DLT adoption to accelerate the digitalization of organizational operations.
Effects of Macroprudential Policies on Bank Lending and Credit Risks
Authors: Behncke Stefanie 
Published: March 2022

AbstractI analyse the effects of two macroprudential policy measures implemented in Switzerland: the activation of the countercyclical capital buffer (CCyB) and a cap on the loan-to-value (LTV) ratios. I use a difference-in-differences method to estimate the effects of these measures on risk indicators, such as their LTV and loan-to-income (LTI) ratios and mortgage growth rates. I find that both the CCyB and the LTV cap led to a reduction in high LTV mortgages. The banks affected by the CCyB also reduced their mortgage growth rates. I do not find any evidence that these measures had unintended consequences on LTI risks, other measures of mortgage lending standards, or non-mortgage credit growth.
Parental Depression Symptoms and Internalizing Mental Health Problems in Autistic Children
Authors: Piro-Gambetti Brianna , Greenlee Jessica , Hickey Emily J. , Putney Jennifer M. , Lorang Emily , Hartley Sigan L. 
Published: March 2022

AbstractAutistic youth are at risk for internalizing mental health problems such as depression and anxiety. Similarly, parents of autistic youth report higher levels of depression than parents of typically developing children. The goal of this study was to examine bidirectional associations between parent depression symptoms and the internalizing problems of autistic youth in 188 families across four time points (T1–T4; spaced 12 months apart). A cross-lagged panel model revealed that mother (T1 and T2) and father (T1) depression symptoms positively predicted the youth’s internalizing problems 12 months later. The youth’s internalizing problems at T3 positively predicted maternal depression symptoms at T4. Future research should explore genetic and environmental pathways that link parent depression and internalizing problems in autistic youth.
Novel insights into the SLC7A11-mediated ferroptosis signaling pathways in preeclampsia patients: identifying pannexin 1 and toll-like receptor 4 as innovative prospective diagnostic biomarkers
Authors: El-Khalik Sarah Ragab Abd , Ibrahim Rowida Raafat , Ghafar Muhammad Tarek Abdel , Shatat Doaa , El-Deeb Omnia Safwat 
Published: March 2022

Abstract

Purpose
Ferroptosis is associated with oxidative stress (OS) and is caused by iron-dependent lipid-peroxidative damage, but its role in PE is unclear. The aim of this study is to determine whether pannexin 1 (Panx1) and toll-like receptor 4 (TLR4) are key regulators of ferroptosis in PE.

Methods
The study included 65 patients with PE and 25 healthy pregnant women. In normal and PE placental tissues, OS and ferroptosis markers, including Fe2+, malondialdehyde (MDA), reduced glutathione (GSH) levels, heme oxygenase-1 (HO-1) and glutathione peroxidase 4 (Gpx4) activity, were estimated. Panx1 and solute carrier family 7 member 11 (SLC7A11) mRNA expression levels were relatively quantified in placental tissues using real‐time polymerase chain reaction (RT‐PCR), while serum Panx1, serum TLR4, and placental activating transcription factor 3 (ATF3) levels were measured by ELISA.

Results
In placental tissues, Panx1 and TLR4 expression levels were significantly increased in patients with PE compared to controls and were positively correlated with pro-ferroptosis mediators such as placental Fe2+ and MDA levels and negatively correlated with anti-ferroptosis regulators such as placental GSH level, HO-1, and Gpx4 activity. Additionally, Panx1 and TLR4 had a positive correlation with ATF3 and a negative correlation with SLC7A11. Serum Panx1 and TLR4 levels were positively correlated with their placental tissue expression and showed good diagnostic capabilities for ferroptosis in PE.

Conclusion
Therefore, Panx1 and TLR4 are suggested to induce ferroptosis in PE via SLC7A11-mediated signaling pathways, offering a novel perspective on PE pathogenesis and novel diagnostic tools for PE.
Automatic Cardiac Structure Contouring for Small Datasets with Cascaded Deep Learning Models
Authors: van den Oever L. B. , Spoor D. S. , Crijns A. P. G. , Vliegenthart R. , Oudkerk M. , Veldhuis R. N. J. , de Bock G. H. , van Ooijen P. M. A. 
Published: March 2022

AbstractCardiac structure contouring is a time consuming and tedious manual activity used for radiotherapeutic dose toxicity planning. We developed an automatic cardiac structure segmentation pipeline for use in low-dose non-contrast planning CT based on deep learning algorithms for small datasets. Fifty CT scans were retrospectively selected and the whole heart, ventricles and atria were contoured. A two stage deep learning pipeline was trained on 41 non contrast planning CTs, tuned with 3 CT scans and validated on 6 CT scans. In the first stage, An InceptionResNetV2 network was used to identify the slices that contained cardiac structures. The second stage consisted of three deep learning models trained on the images containing cardiac structures to segment the structures. The three deep learning models predicted the segmentations/contours on axial, coronal and sagittal images and are combined to create the final prediction. The final accuracy of the pipeline was quantified on 6 volumes by calculating the Dice similarity coefficient (DC), 95% Hausdorff distance (95% HD) and volume ratios between predicted and ground truth volumes. Median DC and 95% HD of 0.96, 0.88, 0.92, 0.80 and 0.82, and 1.86, 2.98, 2.02, 6.16 and 6.46 were achieved for the whole heart, right and left ventricle, and right and left atria respectively. The median differences in volume were -4, -1, + 5, -16 and -20% for the whole heart, right and left ventricle, and right and left atria respectively. The automatic contouring pipeline achieves good results for whole heart and ventricles. Robust automatic contouring with deep learning methods seems viable for local centers with small datasets.
Confidentiality considerations: multimedia signals transmission over different wireless channels utilized efficient secured model
Authors: Nassar Sabry S. , El-Bendary Mohsen A. M. 
Published: March 2022

AbstractThe confidentiality of highly-sensitive multimedia signals is considered in this paper, it can be enhanced by efficient secured model utilizing several-layer security algorithms. The hybrid data hiding and cryptographic techniques are merged for constructing secured model. The Least Significant Bit (LSB) data hiding steganography is utilized with a 2-D Logistic-based map (Model-I) and second Model-II involves data hiding merging within chaotic-Baker-based image encryption security techniques. ِPerformance analyzing and comparison have been presented utilizing various images for examining the applicability of the different proposed image security scenarios for securing wireless image transmission over noise-free, and noisy channels. Moreover, the proposed algorithms are applied for transmission over Orthogonal Frequency-Division Multiplexing (OFDM) channels, and their performance is evaluated under different conditions of fading environments with utilizing the powerful error control schemes in the case of SUI-3 model channel and randomizing the packet based on the encryption tools. An equalizer is used to mitigate the impact of composite fading. A multi-layer security model using Discrete Wavelet Transform (DWT) steganography with chaotic Baker encryption is proposed to protect highly-sensitive text based data records. The results reveal that it can be used efficiently for protecting highly-sensitive text message and records (text-based data). The timing analysis and comparative study are considered with respect to the previous related works.
The use of composite time trade-off and discrete choice experiment methods for the valuation of the Short Warwick-Edinburgh Mental Well-being Scale (SWEMWBS): a think-aloud study
Authors: Yiu Hei Hang Edmund , Al-Janabi Hareth , Stewart-Brown Sarah , Petrou Stavros , Madan Jason 
Published: March 2022

Abstract
Purpose
To identify patterns and problems in completing composite time trade-off (C-TTO) and discrete choice experiment (DCE) exercises for the valuation of the Short Warwick-Edinburgh Mental Well-being Scale (SWEMWBS) to inform the optimisation of a valuation protocol.

Methods
Fourteen cognitive interviews were conducted in the UK using concurrent and retrospective think-aloud and probing techniques. Each participant completed 8 C-TTO tasks and 8 DCE tasks within a computer-assisted personal interview setting. Verbal information was transcribed verbatim. Axial coding and thematic analysis were used to organise the qualitative data and identify patterns and problems with the completion of tasks.

Results
While participants found the tasks generally manageable, five broad themes emerged to explain and optimise the response to the tasks. (1) Format and structure: attention to the design of practice examples, instructions, and layout were needed. (2) Items and levels: underlying relationships were discovered across different combinations of levels of SWEMWBS items. (3) Decision heuristics: participants engaged in diverse strategies to assist trade-off decisions. (4) Valuation feasibility: certain states were difficult to imagine, compare and quantify. (5) Valuation outcome: the data quality was affected by participants’ discriminatory ability across states and their time trade-off decisions.

Conclusion
The interviews contributed insights regarding the robustness of the proposed methods. The application of C-TTO and DCE valuation techniques was practical and suitable for capturing individual attitudes towards different mental well-being scenarios. A modified protocol informed by the results is being tested in a larger sample across the UK.
Graphical test for discrete uniformity and its applications in goodness-of-fit evaluation and multiple sample comparison
Authors: Säilynoja Teemu , Bürkner Paul-Christian , Vehtari Aki 
Published: March 2022

AbstractAssessing goodness of fit to a given distribution plays an important role in computational statistics. The probability integral transformation (PIT) can be used to convert the question of whether a given sample originates from a reference distribution into a problem of testing for uniformity. We present new simulation- and optimization-based methods to obtain simultaneous confidence bands for the whole empirical cumulative distribution function (ECDF) of the PIT values under the assumption of uniformity. Simultaneous confidence bands correspond to such confidence intervals at each point that jointly satisfy a desired coverage. These methods can also be applied in cases where the reference distribution is represented only by a finite sample, which is useful, for example, for simulation-based calibration. The confidence bands provide an intuitive ECDF-based graphical test for uniformity, which also provides useful information on the quality of the discrepancy. We further extend the simulation and optimization methods to determine simultaneous confidence bands for testing whether multiple samples come from the same underlying distribution. This multiple sample comparison test is useful, for example, as a complementary diagnostic in multi-chain Markov chain Monte Carlo (MCMC) convergence diagnostics, where most currently used convergence diagnostics provide a single diagnostic value, but do not usually offer insight into the nature of the deviation. We provide numerical experiments to assess the properties of the tests using both simulated and real-world data and give recommendations on their practical application in computational statistics workflows.