bluuebunny/crossref_metadata_2025_split huggingface dataset:
Responses of Four Peatland Emergent Macrophytes to Salinity and Short Salinity Pulses
Authors: Batistel Cheryl , Porsche Christian , Jurasinski Gerald , Schubert Hendrik 
Published: August 2022

AbstractSea-level rise intensifies saltwater influx into coastal wetlands causing osmotic stress and probably changing vegetation composition. To determine especially the impact of salinity pulses that occur during flooding events, Typha latifolia, Carex acutiformis, Schoenoplectus tabernaemontani and Phragmites australis were exposed to different salinity regimes consisting of control (permanently freshwater and permanently brackish water) and alternating freshwater and brackish water with different exposure durations (2 days brackish – 2 days fresh; 4 days brackish – 4 days fresh; 2 days brackish – 4 days fresh). Plant height, leaf area, chlorophyll fluorescence, root:shoot ratio and photosynthetic pigments were measured. Salinity suppressed the growth of T. latifolia resulting in shorter height, smaller mean leaf area and higher root:shoot ratio. Carex acutiformis had smaller mean leaf area and higher root:shoot ratio. Photosynthetic pigment and chlorophyll fluorescence of both species were not affected. Shorter but frequent salinity pulses (alternate 2 days brackish – 2 days freshwater, and 2 days brackish – 4 days freshwater) decreased the leaf area of T. latifolia while C. acutiformis was not affected. Salinity and salinity pulses did not affect the height and root:shoot ratio of P. australis and S. tabernaemontani. Phragmites australis showed signs of successful acclimation through decreased chlorophyll a:carotenoid ratio and high fluorescence Δyield at low and high irradiance. Our results imply that with increasing seawater influx into coastal peatlands, T. latifolia and C. acutiformis may experience growth retardation or may even be replaced by S. tabernaemontani or P. australis since they are more resilient against salinity and frequent salinity pulses.
Deconstructing the Conspiratorial Mind: the Computational Logic Behind Conspiracy Theories
Authors: Rigoli Francesco 
Published: August 2022

AbstractIn the social sciences, research on conspiracy theories is accumulating fast. To contribute to this research, here I introduce a computational model about the psychological processes underlying support for conspiracy theories. The proposal is that endorsement of these theories depends on three factors: prior beliefs, novel evidence, and expected consequences. Thanks to the latter, a conspiracy hypothesis might be selected because it is the costliest to reject even if it is not the best supported by evidence and by prior beliefs (i.e., even if it is not the most accurate). In this way, the model implies a key role for motivated reasoning. By examining the social conditions that favour the success of conspiracy theories, the paper embeds the model, whose focus is primarily psychological, within the broader social context, and applies this analysis to probe the role of conspiracy theories within contemporary Western societies. Altogether, the paper argues that a computational outlook can contribute to elucidate the socio-psychological dynamics underlying the attractiveness of conspiracy theories.
Smart Tramway Systems for Smart Cities: A Deep Learning Application in ADAS Systems
Authors: Guerrieri Marco , Parla Giuseppe 
Published: August 2022

AbstractArtificial intelligence and deep learning-based techniques undoubtedly are the future of Advanced Driver-Assistance Systems (ADAS) technologies. In this article is presented a technique for detecting, recognizing and tracking pedestrians, vehicles and cyclists along a tramway infrastructure in a complex urban environment by Computer Vision, Deep Learning approaches and YOLOv3 algorithm. Experiments have been conducted in the tramway Line 2 “Borgonuovo –Notarbartolo” (Palermo, Italy) in correspondence of the tramway segments crossing a roundabout having an external diameter of 24 m. A survey vehicle equipped with a video camera was used in the study. The results of the research show that the proposed method is able to search and detect the position and the speed of road users near and over the rails in front of the tram in a very precise way as demonstrate by the estimated values of the Accuracy, Loss and Precision obtained during the neural networks training process. The implementation of this advanced detection method in ADAS systems may increase the safety of novel autonomous trams and autonomous rapid trams (ARTs).
Mapping complications in thyroid surgery: statistical data are useful for medico-legal management of a recurrent safety issue
Authors: Padovano Martina , Scopetti Matteo , Tomassi Raoul , Manetti Federico , D’Errico Stefano , Santurro Alessandro , De Toma Giorgio , Frati Paola , Miccoli Paolo , Fineschi Vittorio 
Published: August 2022

Abstract
Quality of care assessment is a crucial tool for patient safety implementation. Litigation relating to thyroid surgery is one of the most represented sectors also due to the continuous increase in the number of thyroid interventions. Given the incidence of the problem, the present study aims to outline an operational methodology for risk mapping and litigation management in thyroid surgery. The study was conducted through the analysis of data collected at Umberto I General Hospital in Rome from 2007 to 2018. All thyroid surgery claims were included and, subsequently, a descriptive statistical analysis of the categorical variables was performed with the representation of frequencies in absolute terms and as a percentage. The results obtained show that in 94% of cases (44 cases) the reported event consists of incorrect treatment. The most frequent adverse events were identified in unilateral or bilateral recurrent nerve lesions (31; 70%); incomplete removal of the thyroid gland (6; 14%), post-surgical hypoparathyroidism (4; 9%), aesthetic damage secondary to surgical scars (2; 5%), dental avulsion during intubation maneuvers (1; 2%). The experience derived from the risk mapping through management of thyroid claims proved it to be a reactive tool of considerable importance in clinical governance. The promotion of measures aimed at improving the satisfaction of some critical parameters identified in the litigation management activity such as adherence to the indications for surgery, the preoperative diagnostic path, and the adequacy of the surgical report allows to further implement the quality of care in the surgical treatment of thyroid pathology.

Graphical Abstract
‘They can do many things’: rhymes as a pedagogical tool
Authors: Zhong Yuehong , Guo Karen 
Published: August 2022

AbstractRhymes are popular tools in children’s learning in many cultures, but the pedagogical underpinnings of rhyme practice are largely unknown. Drawing on insights from a study in China, this paper explores the pedagogical meaning and function of rhymes in early childhood education. Individual interviews were conducted with 10 Chinese early childhood teachers and a series of classroom observations of teachers’ rhyme practices were undertaken. An overarching theme from the data was the multifunctionality of rhymes, or in teachers’ words ‘they can do many things’. Framed by the notion of tools in sociocultural theory and existing studies on rhymes as a pedagogical tool, this theme is discussed with reference to the discourses on mediation, habitual practice, and professional support which bring to the fore some issues in Chinese early childhood education.
Financial Hardship, Religious Experience, and Health
Authors: Jung Jong Hyun 
Published: August 2022

Background Previous research has shown that religion mitigates the deleterious association between financial hardship and health. Although religion is a multidimensional construct, this strand of research has primarily focused on religious behavior or belief. Purpose The current study aims to extend previous findings by examining a neglected aspect of religious involvement—religious experience—and how it buffers the association between financial hardship and self-rated health. Methods The current study analyzes two waves of data from the Portraits of American Life Study (2006–2012) (N = 1020), a nationally representative sampling of American adults. It uses lagged dependent variable regression models. Results The analyses reveal that financial hardship measured at W2 is negatively associated with self-rated health at W2, net of W1 self-rated health and control measures. Religious experience of receiving direct help from angels in time of a need does not moderate this association. By contrast, the negative association between financial hardship and self-rated health is weakened among individuals who strongly agree that they experienced a supernatural miracle. Conclusions and Implications The findings in the study dovetail with the stress process model, indicating that religious experience serves as a personal resource that helps individuals deal with financial hardship. By highlighting the stress-buffering effects of religious experience, the current study rounds out our understanding of the complex linkages among stress, religion, and health.
Prognostic predictive value of intracranial pressure and cerebral oxygen metabolism monitoring in patients with spontaneous intracerebral hemorrhage
Authors: Sun Zhen , Liu Jing , Dong Shengpu , Duan Xianglong , Xue Fei , Miao Xingyu 
Published: August 2022

Abstract
Objective
Our study aimed to investigate the predictive value of intracranial pressure (ICP) and cerebral oxygen metabolism monitoring in the postoperative prognosis of patients with spontaneous intracerebral hemorrhage (SICH).

Methods
The clinical data of 55 patients with SICH treated by neurosurgery were analyzed retrospectively. These patients were divided into two groups based on postoperative Glasgow Outcome Scale (GOS) scores, i.e., the poor prognosis group (GOS I-III) and the good prognosis group (GOS IV and V). Next, the ICP and cerebral oxygen metabolism indexes, such as brain temperature (BT), cerebral perfusion pressure (CPP), internal jugular venous oxygen saturation (SjvO2), and arterial partial pressure of carbon dioxide (PaCO2), were recorded after the operation. Further, the prognostic differences between the two groups were compared, and the predictive values were evaluated using the receiver operating characteristic curve (ROC) and area under the curve (AUC).

Results
The results showed that the average ICP and BT in the good prognosis group were lower than those in the poor prognosis group. However, the CPP and SjvO2 in the good prognosis group were higher than those in the poor prognosis group. Moreover, the incidence of low PaCO2 in the poor prognosis group was higher than that in the good prognosis group.

Conclusions
Our results demonstrated that the average ICP, BT, CPP, SjvO2, and arterial PaCO2 may reflect the changes in brain function and cerebral blood flow, which are significantly correlated with the prognosis of patients. Further, our findings indicated that the combined postoperative ICP levels with cerebral oxygen metabolism indexes could guide clinical treatments and predict prognosis.
Photo-assisted charging of carbon fiber paper-supported CeO2/MnO2 heterojunction and its long-lasting capacitance enhancement in dark
Authors: Yang Weiyi , Wang Jian , Gao Shuang , Zhang Haoyu , Wang Hongyang , Li Qi 
Published: August 2022

AbstractIt is important to develop green and sustainable approaches to enhance electrochemical charge storage efficiencies. Herein, a two-step in-situ growth process was developed to fabricate carbon fiber paper-supported CeO2/MnO2 composite (CeO2/MnO2—CFP) as a binder-free photo-electrode for the photo-assisted electrochemical charge storage. The formation of CeO2/MnO2 type II heterojunction largely enhanced the separation efficiency of photo-generated charge carriers, resulting in a substantially enhanced photo-assisted charging capability of ∼20%. Furthermore, it retained a large part of its photo-enhanced capacitance (∼56%) in dark even after the illumination was off for 12 h, which could be attributed to its slow release of stored photo-generated electrons from its specific band structure to avoid their reaction with O2 in dark. This study proposed the design principles for supercapacitors with both the photo-assisted charging capability and its long-lasting retainment in dark, which may be readily applied to other pseudocapacitive materials to better utilize solar energy.
Rational Inner Functions and their Dirichlet Type Norms
Authors: Bergqvist Linus 
Published: August 2022

AbstractWe study membership of rational inner functions in Dirichlet-type spaces in polydiscs. In particular, we prove a theorem relating such inclusions to $$H^p$$

H
p

integrability of partial derivatives of an RIF, and as a corollary we prove that all rational inner functions on $${\mathbb {D}}^n$$

D

n

belong to $${\mathcal {D}}_{1/n, \ldots ,1/n}({\mathbb {D}}^n)$$

D

1
/
n
,
…
,
1
/
n

(

D

n

)

. Furthermore, we show that if $$1/p \in {\mathcal {D}}_{\alpha ,\ldots ,\alpha }$$

1
/
p
∈

D

α
,
…
,
α

, then the RIF $$\tilde{p}/p \in {\mathcal {D}}_{\alpha +2/n,\ldots ,\alpha +2/n}$$

p
~

/
p
∈

D

α
+
2
/
n
,
…
,
α
+
2
/
n

. Finally we illustrate how these results can be applied through several examples, and how the Łojasiewicz inequality can sometimes be applied to determine inclusion of 1/p in certain Dirichlet-type spaces.
Psychopathology predicts mental but not physical bariatric surgery outcome at 3-year follow-up: a network analysis study
Authors: Monteleone Alessio Maria , Globus Inbal , Cascino Giammarco , Klomek Anat Brunstein , Latzer Yael 
Published: August 2022

Abstract
Purpose
This study aimed to explore the psychopathological variables that may predict bariatric surgery outcomes after 3 years.

Methods
One hundred ninety-six candidates for bariatric surgery completed self-report questionnaires to assess eating attitudes, eating disorder (ED)-related psychopathology, affective symptoms, interpersonal and psycho-social functioning. One-hundred patients repeated this assessment 3 years after bariatric surgery. A network analysis was run including the pre-surgical measurements in the network. A composite score derived from the combination of the most central network nodes, as well as clinical and socio-demographical variables, was included in a multivariate regression analysis with weight loss, ED psychopathology and psycho-social functioning as outcomes.

Results
Depression, stress, and shape concerns were the most central network nodes. The composite network score predicted higher ED psychopathology and worse psycho-social functioning at 3-year follow-up, but not weight loss. Higher age, restricting type of bariatric surgery and higher pre-operative BMI were further predictors of reduced weight loss and greater ED psychopathology.

Conclusions
Affective symptoms and shape concern play a central role in the psychopathology of candidates to bariatric surgery and predict post-surgery ED psychopathology and psycho-social functioning. These variables may allow to identify patients with higher pre-operative risk and in need of further psycho-social interventions.

Level of evidence
III, evidence obtained from well-designed cohort study.
BugPre: an intelligent software version-to-version bug prediction system using graph convolutional neural networks
Authors: Wang Zixu , Tong Weiyuan , Li Peng , Ye Guixin , Chen Hao , Gong Xiaoqing , Tang Zhanyong 
Published: August 2022

AbstractSince defects in software may cause product fault and financial loss, it is essential to conduct software defect prediction (SDP) to identify the potentially defective modules, especially in the early stage of the software development lifecycle. Recently, cross-version defect prediction (CVDP) began to draw increasing research interests, employing the labeled defect data of the prior version within the same project to predict defects in the current version. As software development is a dynamic process, the data distribution (such as defects) during version change may get changed. Recent studies utilize machine learning (ML) techniques to detect software defects. However, due to the close dependencies between the updated and unchanged code, prior ML-based methods fail to model the long and deep dependencies, causing a high false positive. Furthermore, traditional defect detection is performed on the entire project, and the detection efficiency is relatively low, especially on large-scale software projects. To this end, we proposeBugPre, a CVDP approach to address these two issues.BugPreis a novel framework that only conducts efficient defect prediction on changed modules in the current version.BugPreutilizes variable propagation tree-based associated analysis method to obtain the changed modules in the current version. Besides,BugPreconstructs graph leveraging code context dependences and uses a graph convolutional neural network to learn representative characteristics of code, thereby improving defect prediction capability when version changes occur. Through extensive experiments on open-source Apache projects, the experimental results indicate that ourBugPreoutperforms three state-of-the-art defect detection approaches, and the F1-score has increased by higher than 16%.
Planning and visual-servoing for robotic manipulators in ROS
Authors: Maldonado-Valencia R. I. , Rodriguez-Garavito C. H. , Cruz-Perez C. A. , Hernandez-Navas J. S. , Zabala-Benavides D. I. 
Published: August 2022

AbstractThis article presents a probabilistic road map (PRM) and visual servo control (visual-servoing) based path planning strategy that allows a Motoman HP20D industrial robot to move from an initial positional to a random final position in the presence of fixed obstacles. The process begins with an application of the PRM algorithm to take the robot from an initial position to a point in space where it has a free line of sight to the target, to then apply visual servoing and end up, finally, at the desired position, where an image captured by a camera located at the robot’s end effector matches a reference image, located on the upper surface of a rectangular prismatic object. Algorithms and experiments were developed in simulation, specifically, the visual servo control that includes the dynamic model of the robot and the image sensor subject to realistic lighting were developed in robot operating system (ROS) environment.
A high fidelity general purpose 3-D Monte Carlo particle transport program JMCT3.0
Authors: Deng Li , Li Gang , Zhang Bao-Yin , Li Rui , Zhang Ling-Yu , Wang Xin , Fu Yuan-Gang , Shi Dun-Fu , Liu Peng , Ma Yan , Shangguan Dan-Hu , Hu Ze-Hua , Zhou Sheng-Cheng , Shen Jing-Wen 
Published: August 2022

AbstractJMCT is a large-scale, high-fidelity, three-dimensional general neutron–photon–electron–proton transport Monte Carlo software system. It was developed based on the combinatorial geometry parallel infrastructure JCOGIN and the adaptive structured mesh infrastructure JASMIN. JMCT is equipped with CAD modeling and visualizes the image output. It supports the geometry of the body and the structured/unstructured mesh. JMCT has most functions, variance reduction techniques, and tallies of the traditional Monte Carlo particle transport codes. Two energy models, multi-group and continuous, are provided. In recent years, some new functions and algorithms have been developed, such as Doppler broadening on-the-fly (OTF), uniform tally density (UTD), consistent adjoint driven importance sampling (CADIS), fast criticality search of boron concentration (FCSBC) domain decomposition (DD), adaptive control rod moving (ACRM), and random geometry (RG) etc. The JMCT is also coupled with the discrete ordinate SN code JSNT to generate source-biasing factors and weight-window parameters. At present, the number of geometric bodies, materials, tallies, depletion zones, and parallel processors are sufficiently large to simulate extremely complicated device problems. JMCT can be used to simulate reactor physics, criticality safety analysis, radiation shielding, detector response, nuclear well logging, and dosimetry calculations etc. In particular, JMCT can be coupled with depletion and thermal-hydraulics for the simulation of reactor nuclear-hot feedback effects. This paper describes the progress in advanced modeling, high-performance numerical simulation of particle transport, multiphysics coupled calculations, and large-scale parallel computing.
Leveraging Patient Preference Information in Medical Device Clinical Trial Design
Authors: Rincon-Gonzalez Liliana , Selig Wendy K. D. , Hauber Brett , Reed Shelby D. , Tarver Michelle E. , Chaudhuri Shomesh E. , Lo Andrew W. , Bruhn-Ding Dean , Liden Barry 
Published: August 2022

AbstractUse of robust, quantitative tools to measure patient perspectives within product development and regulatory review processes offers the opportunity for medical device researchers, regulators, and other stakeholders to evaluate what matters most to patients and support the development of products that can best meet patient needs. The medical device innovation consortium (MDIC) undertook a series of projects, including multiple case studies and expert consultations, to identify approaches for utilizing patient preference information (PPI) to inform clinical trial design in the US regulatory context. Based on these activities, this paper offers a cogent review of considerations and opportunities for researchers seeking to leverage PPI within their clinical trial development programs and highlights future directions to enhance this field. This paper also discusses various approaches for maximizing stakeholder engagement in the process of incorporating PPI into the study design, including identifying novel endpoints and statistical considerations, crosswalking between attributes and endpoints, and applying findings to the population under study. These strategies can help researchers ensure that clinical trials are designed to generate evidence that is useful to decision makers and captures what matters most to patients.
Three Dimensional Homogeneous Hyperbolic Ricci Solitons
Authors: Faraji Hamed , Azami Shahroud , Fasihi-Ramandi Ghodratallah 
Published: August 2022

AbstractIn this paper, we consider the self-similar solutions to the hyperbolic geometric flow, called hyperbolic Ricci solitons. Also, we investigate hyperbolic Ricci solitons on three-dimensional homogeneous manifolds with Riemannian and Lorentzian metrics and obtain some hyperbolic Ricci solitons on such manifolds.
Application of Microbiome in Forensics
Authors: Zhang Jun , Liu Wenli , Simayijiang Halimureti , Hu Ping , Yan Jiangwei 
Published: August 2022

AbstractRecent advances in next-generation sequencing technologies and improvements in bioinformatics have expanded the scope of microbiome analysis as a forensic tool. Microbiome research is concerned with the study of the compositional profile and diversity of microbial flora as well as the interactions between microbes, hosts, and the environment. It has opened up many new possibilities for forensic analysis. In this review, we discuss various applications of microbiome in forensics, including identification of individuals, geolocation inference, and post-mortem interval (PMI) estimation.