bluuebunny/crossref_metadata_2025_split huggingface dataset:
Different Risk Factors for Early and Late Recurrence After Curative Resection of Hepatocellular Carcinoma
Authors: Hong Suk Kyun , Jin Xue‐Li , Suh Sanggyun , Hong Su young , Hong Kwangpyo , Han Eui Soo , Lee Jeong‐Moo , Choi YoungRok , Yi Nam‐Joon , Lee Kwang‐Woong , Suh Kyung‐Suk 
Published: September 2021

AbstractBackgroundFactors of early and late recurrence after curative resection of hepatocellular carcinoma (HCC) may be different. The aim of this study was to identify clinical factors, including liver stiffness measurement (LSM), which are associated with HCC recurrence after curative resection.MethodsPatients who underwent preoperative LSM and primary curative resection for HCC between October 2015 and May 2018 were retrospectively reviewed, with 1 year as the cut‐off between early and late recurrence.ResultsRecurrence was observed in 42/149 (28.2%) patients over a median follow‐up of 38.3 months (early recurrence: 10 [6.7%] patients; late recurrence: 32 [21.5%] patients). Multivariate analysis identified LSM (P = 0.026) and tumor size (P = 0.010) as the only factors that were significantly associated with recurrence‐free survival. Compared with patients without recurrence, those with early recurrence had larger tumor size (P = 0.035) and those with late recurrence had higher LSM (P = 0.024). Receiver‐operating characteristic analysis indicated that the optimal LSM cut‐off value for predicting HCC recurrence was 7.4 kPa.ConclusionTumor size was associated with early HCC recurrence after curative resection and LSM was associated with late recurrence. LSM cut‐off of 7.4 kPa is recommended in predicting recurrence.
Work situation of rheumatologists and residents in times of COVID-19
Authors: Kuhlmann Ellen , Bruns Luzia , Hoeper Kirsten , Richter Marianne , Witte Torsten , Ernst Diana , Jablonka Alexandra 
Published: September 2021

Abstract
Background and objective
The work situation is an important dimension of professional life and wellbeing, and a policy lever to strengthen recruitment and retention. This study aims to explore the work situation of physicians and residents in internal medical rheumatology, considering the impact of the coronavirus pandemic COVID-19.

Methods
A questionnaire-based online survey was conducted in early 2021 at the Hannover Medical School, supported by the German Society of Rheumatology. Target groups were all rheumatology physicians and residents in Germany. The main areas of investigation included work hours, task delegation, and collaboration; workload and mental health issues; discrimination and sexual harassment experiences; and the impact of COVID-19. Descriptive statistical analysis was performed for the standardized items and qualitative content analysis for the free-text information.

Results
The respondents (n = 101) expressed positive attitudes towards cooperation and task delegation to medical assistants, especially those specialized in rheumatology, while attitudes towards cooperation with GPs pointed to blockades. There was a strong mismatch between actual and desired work hours both in the group of women and in the group of men. 81% rated their workload as high or very high; every sixth rheumatologist has suffered from stress or burnout syndromes at least once in the past. Experiences of gender discrimination and sexual harassment/violence were frequently reported, mostly by women. COVID-19 was an amplifier of stress, with major stressors being digitalization and increased demand for communication and patient education.

Conclusion
There is an urgent need to improve the work situation of rheumatologists and reduce stress and mental health risks.
Using hydrodynamic and hydraulic modelling to study microbiological water quality issues at a backwater area of the Danube to support decision-making
Authors: Derx Julia , Komma Jürgen , Reiner Philipp , Vierheilig Julia , Savio Domenico , Sommer Regina , Kirschner Alexander K. T. , Frick Christina , Linke Rita , Farnleitner Andreas H. , Blaschke Alfred Paul 
Published: September 2021

AbstractThe alluvial backwater areas of the Danube are valuable ecological habitats containing important drinking water resources. Due to the river regulation and the construction of power plants, the river water levels and natural dynamics of the backwater areas continuously decline, threatening their typical characteristics. The aim of this study was to evaluate how an increased connectivity of the backwater branch located in a nature-protected riverine floodplain (enabled by diverting river water into the backwater system via a weir) affects the microbiological quality of groundwater resources. The defined quality criterion was that the diversion measures must not lead to an increased detection frequency of faecal indicators in groundwater. The microbiological water quality of the Danube, its backwater branch and the groundwater was analysed from 2010 to 2013. E. coli was selected as bacterial indicator for recent faecal pollution. C. perfringens (spores) was analysed as indicator for persistent faecal pollution and potentially occurring pathogenic protozoa. We simulated the microbial transport from the Danube and the backwater river into groundwater using a 3‑D unsaturated-saturated groundwater model coupled with 2‑D hydrodynamic flow simulations. Scenarios for no diversion measures were compared with scenarios for an additional discharge of 3, 20 and 80 m3/s from the Danube River into the backwater branch. While the additional discharge of 20 and 80 m3/s of Danube water into the floodplain strongly improved the ecological status according to ecological habitat models, the hydraulic transport simulations showed that this would result in a deterioration of the microbiological quality of groundwater resources. The presented approach shows how hydraulic transport modelling and microbiological analyses can be combined to support decision-making.
Characteristic phenotype of Chinese patients with adult-onset diabetes who are autoantibody positive by 3-Screen ICA™ ELISA
Authors: Wang Zhida , Guo Liang , Chen Shu , Guan Jun , Powell Michael , Furmaniak Jadwiga , Rees Smith Bernard , Chen Liming 
Published: September 2021

Abstract
Aims
To assess the prevalence of diabetes-associated autoantibodies in Chinese patients recently diagnosed with adult-onset diabetes and to evaluate the potential role of the autoantibody markers for characterization of disease phenotype in the patient population.

Methods
The study included 1273 recent-onset adult patients with phenotypic type 2 diabetes mellitus (T2DM). Serum samples were tested using the 3-Screen ICA™ ELISA (3-Screen) designed for combined measurement of GADAb and/or IA-2Ab and/or ZnT8Ab. 3-Screen positive samples were then tested for individual diabetes-associated and other organ-specific autoantibodies. Clinical characteristics of patients positive and negative in 3-Screen were analysed.

Results
Forty-four (3.5%) of the T2DM patients were positive in 3-Screen, and 38 (86%) of these were also positive for at least one of GADAb, IA-2Ab and ZnT8Ab in assays for the individual autoantibodies. 3-Screen positive patients had lower BMI, higher HbA1c, lower fasting insulin levels and lower fasting C-peptide levels compared to 3-Screen negative patients. Analysis using a homeostatic model assessment (HOMA2) indicated that HOMA2-β-cell function was significantly lower for the forty-four 3-Screen positive patients compared to 3-Screen negative patients.
Twenty (45%) 3-Screen positive patients were also positive for at least one thyroid autoantibody.

Conclusions
The 3-Screen ELISA has been used successfully for the first time in China to detect diabetes autoantibodies in patients with phenotypic T2DM. 3-Screen positive patients presented with poorer β cell function.
Coalition-proof stable networks
Authors: Luo Chenghong , Mauleon Ana , Vannetelbosch Vincent 
Published: September 2021

AbstractWe propose the notion of coalition-proof stability for predicting the networks that could emerge when group deviations are allowed. A network is coalition-proof stable if there exists no coalition which has a credible group deviation. A coalition is said to have a credible group deviation if there is a profitable group deviation to some network and there is no subcoalition of the deviating players which has a subsequent credible group deviation. Coalition-proof stability is a coarsening of strong stability. We emphasize the importance of coalition-proof stability by considering four models where a strongly stable network fails to exist while a coalition-proof stable network does exist. We provide an easy to verify condition for the existence of a coalition-proof stable network while a strongly stable network may not exist. There is no relationship between the set of coalition-proof stable networks and the set of networks induced by a coalition-proof Nash equilibrium of Myerson’s linking game.
The learning experiences of dyslexic medical students during the COVID-19 pandemic: a phenomenological study
Authors: Shaw Sebastian C. K. , Hennessy Laura R. , Anderson John L. 
Published: September 2021

AbstractDyslexia is a Specific Learning Difficulty that impacts on reading and writing abilities. During the COVID-19 pandemic, medical schools have been forced to undertake distance learning and assessment. The wider literature suggested that e-learning might pose additional challenges for dyslexic students. Here we explore their overall experiences of learning/studying during this time in a phenomenological study. Five medical students were interviewed in depth and the audio-recordings were transcribed verbatim. Transcripts then underwent an interpretive phenomenological analysis. Our results highlighted a largely positive experience, with an improved culture of togetherness, freedom and sense of control. They also revealed issues with a lack of clinical exposure, potential negative impacts on ranking positions for those with dyslexia, and possible cheating in exams. There are some surprising results—in particular the positive responses to how remote learning was delivered. These seemed to put our participants more on a par with their non-dyslexic colleagues—except in some examinations. It is our hope that medical educators may resist a return to ‘the way things have always been done’ when the pandemic has resolved, and by doing so, continue to foster this new, positive culture and paradigm shift.
Modes and Dimensions of Being
Authors: Alvargonzález David 
Published: September 2021

AbstractIn this paper, I put forward a theory about the modes and dimensions of being. In the first section, I define existence through coexistence, understood as the codetermination of certain things and processes via other things and processes. In the second section, I differentiate between modes and dimensions of being. In the third section, I argue that the modes of existing are the different ways in which coexistence and codetermination take place and discuss two types of modes ("fundamental" and "categorial"), to subsequently present a classification thereof. In the fourth section, I posit a theory about the dimensions of any existing thing or process, arguing for the existence of two types of dimensions: configurational and processual.
Distinguishing pure histopathological growth patterns of colorectal liver metastases on CT using deep learning and radiomics: a pilot study
Authors: Starmans Martijn P. A. , Buisman Florian E. , Renckens Michel , Willemssen François E. J. A. , van der Voort Sebastian R. , Groot Koerkamp Bas , Grünhagen Dirk J. , Niessen Wiro J. , Vermeulen Peter B. , Verhoef Cornelis , Visser Jacob J. , Klein Stefan 
Published: September 2021

AbstractHistopathological growth patterns (HGPs) are independent prognosticators for colorectal liver metastases (CRLM). Currently, HGPs are determined postoperatively. In this study, we evaluated radiomics for preoperative prediction of HGPs on computed tomography (CT), and its robustness to segmentation and acquisition variations. Patients with pure HGPs [i.e. 100% desmoplastic (dHGP) or 100% replacement (rHGP)] and a CT-scan who were surgically treated at the Erasmus MC between 2003–2015 were included retrospectively. Each lesion was segmented by three clinicians and a convolutional neural network (CNN). A prediction model was created using 564 radiomics features and a combination of machine learning approaches by training on the clinician’s and testing on the unseen CNN segmentations. The intra-class correlation coefficient (ICC) was used to select features robust to segmentation variations; ComBat was used to harmonize for acquisition variations. Evaluation was performed through a 100 × random-split cross-validation. The study included 93 CRLM in 76 patients (48% dHGP; 52% rHGP). Despite substantial differences between the segmentations of the three clinicians and the CNN, the radiomics model had a mean area under the curve of 0.69. ICC-based feature selection or ComBat yielded no improvement. Concluding, the combination of a CNN for segmentation and radiomics for classification has potential for automatically distinguishing dHGPs from rHGP, and is robust to segmentation and acquisition variations. Pending further optimization, including extension to mixed HGPs, our model may serve as a preoperative addition to postoperative HGP assessment, enabling further exploitation of HGPs as a biomarker.
Negative Posttraumatic Cognitions Color the Pathway from Event Centrality to Posttraumatic Stress Disorder Symptoms
Authors: Johanßen Helen , Schoofs Nikola , Kliegl Reinhold , Bermpohl Felix , Ülsmann Dominik , Schulte-Herbrüggen Olaf , Priebe Kathlen 
Published: September 2021

Abstract
Background
The centrality of an event indicates the extent to which it becomes a core part of identity and life story. Event centrality (EC) has been shown to have a strong relationship with PTSD symptoms, which seems to be indirectly influenced by negative posttraumatic cognitions (PTC). However, research on this potential mediation and its causal links particularly with clinical samples is limited and essential to derive treatment implications.

Methods
Pre- and posttreatment data of 103 day-unit patients with PTSD was examined using mediation analyses and structural equation modeling.

Results
Negative PTC mediated the relationship between EC and PTSD symptoms, partially pre- and completely posttreatment. Within extended longitudinal analyses causal directions of the mediation pathways were not adequately interpretable due to unexpected suppression effects.

Conclusions
The results suggest that EC may only have an indirect effect on PTSD symptoms through negative PTC. Thus, decreasing negative PTC which are connected to centralized events might be a key element for PTSD treatment. Thereby, transforming the cognitions’ valence to more positive and constructive forms could be crucial rather than mere decentralization. Although suppression effects limited causal inferences, they do not contradict the mediation and further indicate potential interactional terms and a transformation of EC.
Know More, Spend More? The Impact of Financial Literacy on Household Consumption
Authors: Dinkova Milena , Kalwij Adriaan , Alessie Rob 
Published: September 2021

AbstractThis paper examines the relationship between household consumption and financial literacy. The economic framework is a simple life-cycle model of consumption in which financial literacy affects the rate of return on assets. The theoretical predictions are that, for plausible values of the intertemporal elasticity of substitution, financial literacy is positively related to both the level of consumption and consumption growth. We empirically test these theoretical predictions with Dutch data from the LISS household panel. Our results provide evidence in favour of a positive association between non-durable consumption, and in particular food consumption, and financial literacy. No evidence is, however, found in favour of an association between consumption growth and financial literacy.
Variation in herpetofauna detection probabilities: implications for study design
Authors: Baumgardt Jeremy A. , Morrison Michael L. , Brennan Leonard A. , Thornley Madeleine , Campbell Tyler A. 
Published: September 2021

AbstractPopulation monitoring is fundamental for informing management decisions aimed at reducing the rapid rate of global biodiversity decline. Herpetofauna are experiencing declines worldwide and include species that are challenging to monitor. Raw counts and associated metrics such as richness indices are common for monitoring populations of herpetofauna; however, these methods are susceptible to bias as they fail to account for varying detection probabilities. Our goal was to develop a program for efficiently monitoring herpetofauna in southern Texas. Our objectives were to (1) estimate detection probabilities in an occupancy modeling framework using trap arrays for a diverse group of herpetofauna and (2) to evaluate the relative effectiveness of funnel traps, pitfall traps, and cover boards. We collected data with 36 arrays at 2 study sites in 2015 and 2016, for 2105 array-days resulting in 4839 detections of 51 species. We modeled occupancy for 21 species and found support for the hypothesis that detection probability varied over our sampling duration for 10 species and with rainfall for 10 species. For herpetofauna in our study, we found 14 and 12 species were most efficiently captured with funnel traps and pitfall traps, respectively, and no species were most efficiently captured with cover boards. Our results show that using methods that do not account for variations in detection probability are highly subject to bias unless the likelihood of false absences is minimized with exceptionally long capture durations. For monitoring herpetofauna in southern Texas, we recommend using arrays with funnel and pitfall traps and an analytical method such as occupancy modeling that accounts for variation in detection.
The Grounds and the Components of Concepts
Authors: Claas Jan 
Published: September 2021

AbstractIn this paper I investigate the idea that in conceptual analysis we are in a substantial way concerned with revealing metaphysical grounds. I argue that a recent proposal fails, according to which we aim to reveal what complex concepts are grounded in. The notion ofcomposition, rather than that ofgrounding, is the best way to understand the intuitive hierarchy of concepts. In an analysis we reveal thecomponentsorpartsof complex concepts and their structure. Finally, I propose an alternative role for grounding in our accounts of analysis: in analyses we reveal truths about the composition of concepts that serve as grounds for truths about theirfunctions, which are what we want to understand.
Vacuity in synthesis
Authors: Bloem Roderick , Chockler Hana , Ebrahimi Masoud , Strichman Ofer 
Published: September 2021

AbstractIn reactive synthesis, one begins with a temporal specification $$\varphi $$
φ
, and automatically synthesizes a system $$M$$
M
such that $$M\models \varphi $$

M
⊧
φ

. As many systems can satisfy a given specification, it is natural to seek ways to force the synthesis tool to synthesize systems that are of a higher quality, in some well-defined sense. In this article we focus on a well-known measure of the way in which a system satisfies its specification, namely vacuity. Our conjecture is that if the synthesized system M satisfies $$\varphi $$
φ
non-vacuously, then M is likely to be closer to the user’s intent, because it satisfies $$\varphi $$
φ
in a more “meaningful” way. Narrowing the gap between the formal specification and the designer’s intent in this way, automatically, is the topic of this article. Specifically, we propose a bounded synthesis method for achieving this goal. The notion of vacuity as defined in the context of model checking, however, is not necessarily refined enough for the purpose of synthesis. Hence, even when the synthesized system is technically non-vacuous, there are yet more interesting (equivalently, less vacuous) systems, and we would like to be able to synthesize them. To that end, we cope with the problem of synthesizing a system that is as non-vacuous as possible, given that the set of interesting behaviours with respect to a given specification induce a partial order on transition systems. On the theoretical side we show examples of specifications for which there is a single maximal element in the partial order (i.e., the most interesting system), a set of equivalent maximal elements, or a number of incomparable maximal elements. We also show examples of specifications that induce infinite chains of increasingly interesting systems. These results have implications on how non-vacuous the synthesized system can be. We implemented the new procedure in our synthesis tool PARTY. For this purpose we added to it the capability to synthesize a system based on a property which is a conjunction of universal and existential LTL formulas.
Influence of drought and salt stress on the growth of young Populus nigra ‘Italica’ plants and associated mycorrhizal fungi and non-mycorrhizal fungal endophytes
Authors: Kulczyk-Skrzeszewska Magdalena , Kieliszewska-Rokicka Barbara 
Published: September 2021

AbstractPopulus nigra ‘Italica’ (Lombardy poplar) is a breeding cultivar of black poplar, widely used as a street tree or windbreak, often exposed to salinity and limited water availability. Populus roots can develop dual mycorrhizal associations with ectomycorrhizal (ECM) and arbuscular mycorrhizal (AM) fungi, and with non-mycorrhizal fungal endophytes (FE). The symbiotic fungi may alleviate the effects of adverse environmental conditions. We investigated the performance (growth and symbiotic associations) of one-year-old Populus nigra ‘Italica’ grown from woody cuttings in soil from natural poplar habitat and subjected to water scarcity and soil salinity (50 mM NaCl, 150 mM NaCl, 250 mM NaCl). With increasing soil salinity, a decrease in the growth parameters of the aboveground parts of the poplar plantlets and their fine roots were found; however, the roots were more resistant to the stress factors analyzed than the shoots. ECMF, AMF, and non-mycorrhizal FE were all tolerant to increased salt levels in the soil, and the ECM abundance was significantly higher under conditions of mild salinity (50 mM NaCl, 150 mM NaCl) compared to the control plants and those treated with 250 mM NaCl. Our results indicated that enhanced soil salinity increased the content of sodium and chlorine in leaves, but did not affect significantly the concentrations potassium, magnesium, calcium, phosphorus, or nitrogen. Significant accumulation of proline in leaves suggest salt stress of P. nigra ‘Italica’ treated with 250 mM NaCl and contribution of proline to the plant defense reactions.
High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood
Authors: Suotsalo Kimmo , Xu Yingying , Corander Jukka , Pensar Johan 
Published: September 2021

AbstractLearning vector autoregressive models from multivariate time series is conventionally approached through least squares or maximum likelihood estimation. These methods typically assume a fully connected model which provides no direct insight to the model structure and may lead to highly noisy estimates of the parameters. Because of these limitations, there has been an increasing interest towards methods that produce sparse estimates through penalized regression. However, such methods are computationally intensive and may become prohibitively time-consuming when the number of variables in the model increases. In this paper we adopt an approximate Bayesian approach to the learning problem by combining fractional marginal likelihood and pseudo-likelihood. We propose a novel method, PLVAR, that is both faster and produces more accurate estimates than the state-of-the-art methods based on penalized regression. We prove the consistency of the PLVAR estimator and demonstrate the attractive performance of the method on both simulated and real-world data.