bluuebunny/crossref_metadata_2025_split huggingface dataset:
Odds of fussy eating are greater among children with obesity and anxiety
Authors: Thorsteinsdottir Sigrun , Olafsdottir Anna S. , Brynjolfsdottir Berglind , Bjarnason Ragnar , Njardvik Urdur 
Published: July 2021

AbstractBackgroundFussy eating has been associated with autism spectrum disorder (ASD), attention‐deficit/hyperactive disorder (ADHD), anxiety, and depression. Despite these disorders being prevalent in obesity treatment, no studies have been published on the association of fussy eating in children with obesity and these disorders. Understanding fussy eating in children with obesity and comorbid disorders is important as acceptance of healthy foods tends to be low, especially in children with sensory sensitivities.ObjectivesInvestigate the prevalence of fussy eating in a cross‐sectional sample of children with obesity and ASD, ADHD, anxiety, and depression; and whether they were more likely to be fussy eaters, comparing those with and without these disorders.MethodsOne hundred and four children referred to family‐based obesity treatment in Iceland 2011–2016, mean age 12.0 (SD = 3.0), mean body mass index standard deviation score 3.5 (SD = 0.9). Binary logistic regression was used to estimate the relationship between fussy eating and disorders, adjusting for medication use.ResultsA large minority (41.6%) were fussy eaters and 48.9% had at least one comorbid disorder. Over a third of children rejected bitter and sour tastes, and 1.9% and 7.9% rejected sweet and salty tastes, respectively. Compared with those without disorders, the odds of being a fussy eater were increased by a factor of 4.11 when having anxiety (95% confidence intervals) (1.02–16.58, p = 00.046), adjusting for medication use. The odds of being a fussy eater were not increased for other disorders; ASD, ADHD, or depression.ConclusionsIn children attending obesity treatment, fussy eating was common. Clinical care models in pediatric obesity treatment should address fussy eating, especially in children with anxiety.
Mechanical performance analysis of polyurethane‐modified asphalt using molecular dynamics method
Authors: Lu Pengzhen , Huang Simin , Shen Yang , Zhou Chenhao , Shao Limin 
Published: July 2021

AbstractIn this study, the mechanical performance of polyurethane (PU)‐modified asphalt was investigated. To this end, the molecular dynamics method was adopted to study the influence of the PU modifier on the compatibility, mechanical properties, and structure of asphalt. Using the Materials Studio software, a four‐component molecular model of asphalt, a PU molecular model, and an asphalt–PU mixed system model were constructed, and the molecular density and glass transition temperature () were used to verify the performance of the aforementioned models. Molecular dynamics simulations of the three molecular models were conducted under different temperatures, and the solubility parameter (), interaction energy, mechanical properties, and radial distribution functions (RDFs) were obtained. The results showed that at 413.15 K (140°C), the difference between the solubility parameters of the asphalt and PU molecules () is the smallest, and their interaction reaches the most optimal phase state. The effects of the PU modifier on the Young's modulus, bulk modulus, and shear modulus of asphalt were studied. Finally, the RDF analysis showed that the PU modifier has a direct effect on the degree of swelling and dispersion between the aromatic–aromatic and saturate–saturate components in the asphalt, reducing the aggregation of both molecules. This verifies the PU modification effect.
Plasma nontargeted peptidomics discovers potential biomarkers for major depressive disorder
Authors: Wang Yi , Liu Xinxin , Liu Dan , Cheng Mengchun , Zhao Nan , He Meixi , Zhang Xiaozhe 
Published: July 2021

AbstractPurposeThere are great demands for identifying biomarkers of major depressive disorder (MDD), a common mental illness with a prevalence of approximately 6%. Finding potential biomarkers to aid MDD diagnosis is in high demand.Experimental DesignIn this study, a combination of pretreatment methods named salt‐out assisted liquid‐liquid extraction (SALLE) and nontargeted peptidomics based on nano‐LC‐Orbitrap/MS was primarily employed to discover the candidate peptide markers from the plasma of 238 subjects.ResultsMany peptides were enriched and identified from the plasma, 42 of which showed significant differences between MDD patients and controls by univariate statistical analysis. A binary logistic regression (BLR) model combined four peptide markers (P1, P9, P17, P29) was established, yielding an overall prediction accuracy of 91.7% and 82.2% in the discovery and validation sets, respectively.Conclusions and Clinical RelevanceIn conclusion, the excellent performance of the BLR model in both discovery and validation sets demonstrates the robustness of the four peptide markers panel. It is very valuable for quantification of the absolute content of four peptides and further verification.
Impacts of anti‐inflammatory phosphodiesterase inhibitors on a murine model of chronic pulmonary inflammation
Authors: Zheng Xiao‐Fang , Chen Dan‐Dan , Zhu Xiao‐Ling , Le Grange Jehane Michael , Zhou Lu‐Qian , Zhang Jin‐Nong 
Published: July 2021

AbstractChronic obstructive pulmonary disease (COPD) often tends to respond poorly to glucocorticoid (GC) therapy. Reduced Histone deacetylase‐2 (HDAC‐2) activity is an important mechanism behind this GC insensitivity. In this study, we investigated the effects of three phosphodiesterase inhibitors (PDEIs), with an anti‐inflammatory propensity, on cigarette smoke (CS)‐induced pulmonary inflammation and HDAC‐2 activity. Male C57BL/6 mice were exposed to cigarette smoke (CS) over the course of 30 weeks. Administration of the PDEIs commenced from the 29th week and followed a schedule of once daily treatments, 5 days a week, for 2 weeks. Roflumilast (ROF) was administered intragastrically (5 mg·kg−1), while pentoxifylline (PTX) (10 mg·kg−1) and theophylline (THEO) (10 mg·kg−1) were administered intraperitoneally, either alone or in combination with a GC (triamcinolone acetonide or TRI, 5 mg·kg−1, i.m., single injection). Lung morphometry, as well as the activity of HDAC‐2, pro‐inflammatory cytokines and reactive oxygen species (ROS) were assessed at the end of the 30‐week course. CS exposure was associated with a reduction in HDAC‐2 activity and the up‐regulation of ROS expression. PTX, ROF, and THEO administration led to the partial restoration of HDAC‐2 activity, which was favorably associated with the reduction of ROS expression. However, combining TRI to any of these PDEIs did not synergistically augment HDAC‐2 activity. Inactivation of HDAC‐2 due to long‐term CS exposure is closely related to exaggerated oxidative stress, and this reduced HDAC‐2 activity could partially be restored through the use of PDEIs. This finding provides a potential novel approach for further clinical research.
Using knockoffs for controlled predictive biomarker identification
Authors: Sechidis Konstantinos , Kormaksson Matthias , Ohlssen David 
Published: July 2021

AbstractOne of the key challenges of personalized medicine is to identify which patients will respond positively to a given treatment. The area of subgroup identification focuses on this challenge, that is, identifying groups of patients that experience desirable characteristics, such as an enhanced treatment effect. A crucial first step towards the subgroup identification is to identify the baseline variables (eg, biomarkers) that influence the treatment effect, which are known as predictive variables. Many subgroup discovery algorithms return importance scores that capture the variables' predictive strength. However, a major limitation of these scores is that they do not answer the core question: “Which variables are actually predictive?” With our work we answer this question by using the knockoff framework, which is a general framework for controlling the false discovery rate when performingprognosticvariable selection. In contrast, our work is the first that uses knockoffs forpredictivevariable selection. We introduce two novel knockoff filters: one parametric, building on variable importance scores derived from a penalized linear regression model, and one non‐parametric, building on causal forest variable importance scores. We conduct extensive simulations to validate performance of the proposed methodology and we also apply the proposed methods to data from a randomized clinical trial.
A permutation‐based approach for heterogeneous meta‐analyses of rare events
Authors: Zabriskie Brinley N. , Corcoran Chris , Senchaudhuri Pralay 
Published: July 2021

AbstractThe increasingly widespread use of meta‐analysis has led to growing interest in meta‐analytic methods for rare events and sparse data. Conventional approaches tend to perform very poorly in such settings. Recent work in this area has provided options for sparse data, but these are still often hampered when heterogeneity across the available studies differs based on treatment group. We propose a permutation‐based approach based on conditional logistic regression that accommodates this common contingency, providing more reliable statistical tests when such patterns of heterogeneity are observed. We find that commonly used methods can yield highly inflated Type I error rates, low confidence interval coverage, and bias when events are rare and non‐negligible heterogeneity is present. Our method often produces much lower Type I error rates and higher confidence interval coverage than traditional methods in these circumstances. We illustrate the utility of our method by comparing it to several other methods via a simulation study and analyzing an example data set, which assess the use of antibiotics to prevent acute rheumatic fever.
Process improvement guidance for successful automotive SPI implementation
Authors: Messnarz Richard , Wegner Thomas , Ekert Damjan , Steger Bernhardt , Mayer Ralf , Dreves Rainer , Sechser Bernhard , Schlager Christian , Karner Christoph 
Published: July 2021

AbstractThe Verein der Deutschen Automobilindustrie (VDA) guidelines used for the interpretation of Automotive SPICE 3.1 contain many rules and recommendations and assessors apply them to check the consistency of ratings in an assessment. The VDA guidelines contain detailed procedures and templates to be used in planning, performing and reporting an assessment. However, an assessment is only a small part compared with the support and effort needed to implement improvements and to establish a company‐wide process improvement programme based on best practices. Whereas the VDA guidelines define the assessment process in detail, the ISO norm ISO/IEC 33014:2013 (Information technology—Process assessment—Guide for process improvement) defines a process improvement process. This paper analyses the ISO/IEC 33014:2013 norm and interprets it for the automotive sector and describes a state of the art improvement strategy typical of the automotive industry. Also, the SOQRATES group experiences about good and bad practices in implementing improvement programmes are shared and mapped onto the SPI manifesto principles. The paper concludes with a recommendation to add an improvement strategy‐related appendix to the VDA guidelines.
Supporting control programs on African swine fever in Ukraine through a knowledge, attitudes, and practices survey targeting backyard farmers
Authors: Muñoz‐Gómez Violeta , Solodiankin Oleksii , Rudova Nataliia , Gerilovych Anton , Nychyk Serhiy , Hudz Natalia , Ukhovska Tetiana , Sytiuk Mykola , Polischuk Volodymyr , Mustra David , De Nardi Marco , Lechner Isabel , Schuppers Manon 
Published: July 2021

AbstractA Knowledge, Attitudes, and Practices (KAP) questionnaire was designed to collect information on farmers’ knowledge of ASF and their practices surrounding that could impact the spread of the disease. The questionnaire was distributed, and data collected, from 233 backyard farmers from five selected Oblasts (Rivne, Kharkiv, Odessa, Zakarpattia and Kiev). Kruskal‐Wallis tests were conducted to identify factors that could influence knowledge, and Dunn tests were performed to determine differences between groups when the Kruskal‐Wallis tests were significant. Spearman tests were carried out to explore the association between knowledge and risky practices. Results show that comprehensive knowledge on ASF is not common in backyard farmers and that risky practices that influence the spread of ASF are regularly performed. Of the respondents, 47% felt well‐informed about how ASF can be transmitted and 31.8% felt confident about recognizing clinical signs of ASF. The independent variable “Oblast” was identified as a significant factor (p = 0.0015) associated with differences in knowledge on clinical signs. We demonstrated statistically significant differences of knowledge between backyard farmers from different Oblasts. Knowledge of preventive measures was positively correlated with risky handling practices related to edible pork products (p = 0.0053) and non‐edible pork products (p = 0.0417). In conclusion, our results show that backyard farmers have knowledge gaps on ASF and practice various risky behaviours that might favour the spread of the disease in Ukraine. There are regional differences in ASF knowledge and risky practices that should be taken into consideration in future evidence‐based ASF prevention and control programs, including public awareness activities.
Visualizing water‐energy nexus landscapes
Authors: Robb Douglas , Cole Harrison , Baka Jennifer , Bakker Karen 
Published: July 2021

AbstractOver the past decade, the water‐energy nexus (WEN) has emerged as a prominent framework with which to analyze and visualize interconnections between energy production, freshwater resources, and the hydrological cycle. The WEN is a fundamentally geographic concept embedded in landscapes. WEN analyses often include landscape visualizations, yet these are rarely conceptually rigorous; consequently, the visual‐representational dimensions of WEN analyses remain relatively weak. Our paper addresses this gap through a meta‐review of 503 WEN visualizations sourced from 336 scholarly articles. Based on this analysis, we argue that WEN visualizations often depict complex landscapes as technical systems, while eliding broader considerations of the multiscalar, spatiotemporal, and hydrosocial dimensions of water and energy. In response to these limitations, we offer an alternative approach to visualizing hydrosocial landscapes that draws upon parallel work in geography and cognate disciplines. In the concluding section of the paper, we formulate a set of interdisciplinary recommendations to guide the production of more theoretically‐informed nexus visualizations grounded in the concepts of spatiality, temporality, and hydrosociality.The article is categorized under:
Engineering Water > Planning Water
Human Water > Methods
Water and Life > Conservation, Management, and Awareness
Engineering Water > Methods
Advanced machine learning application for odor and corrosion control at a water resource recovery facility
Authors: Yang Fenghua , Pluth Thaís Bremm , Fang Xing , Francq Kyle Bradley , Jurjovec Matthew , Tang Yongning 
Published: July 2021

AbstractThe objective of this study was to develop a machine learning (ML) application to determine the optimal dosage of sodium hypochlorite (NaOCl) to curtail corrosion and odor by H2S in the headworks of a water resource recovery facility (WRRF) without overly consuming volatile fatty acids (VFAs) that are essential for the enhanced biological phosphorus removal. Given the highly diverse datasets available, three subproblems were formulated, and three cascaded ML modules were developed accordingly. The final ML models, chosen based on performance, were able to predict various targeted variables. More specifically, in Module 1, a recurrent neural network (RNN) was designed to predict wastewater characteristics. In Module 2, a random forest (RF) classifier and a support vector machine (SVM) classifier were built with the information from Module 1 along with other datasets to predict the concentrations of VFAs and H2S, respectively. Finally, in Module 3, with the information obtained from Module 2, another RF classifier was developed to predict NaOCl dosage to reduce H2S but keeping VFAs within the target range. These efforts are relevant and informative for WRRFs that are considering developing Intelligent Water Systems to predict the wastewater characteristics to make operational improvements.Practitioner Points

A recurrent neural network (RNN) using long short‐term memory (LSTM) successfully predicted influent wastewater parameters.
A support vector machine classifier predicted hydrogen sulfide (H2S) with 97.6% accuracy.
The concentration of VFAs, an important parameter in EBPR, was predicted using a random forest classifier with 93.4% accuracy.
The optimal NaOCl dosage for H2S control can be predicted with a random forest classifier using H2S, VFAs, and flow.
Einleitung
Authors: Karl Katrin Bente 
Published: July 2021

ZusammenfassungIn dieser Einleitung findet ein thematischer Einstieg in die Hintergründe und die Projektidee von UnVergessen statt. Dem schließt sich eine Darstellung der einzelnen Teile des Sammelbandes, ihrer jeweiligen inhaltlichen Ausrichtung und Autorenschaft an.
Reduction of one-loop integrals with higher poles by unitarity cut method
Authors: Feng Bo , Wang Hongbin 
Published: July 2021

Abstract
Unitarity cut method has been proved to be very useful in the computation of one-loop integrals. In this paper, we generalize the method to the situation where the powers of propagators in the denominator are larger than one in general. We show how to use the trick of differentiation over masses to translate the problem to the integrals where all powers are just one. Then by using the unitarity cut method, we can find the wanted reduction coefficients of all basis except the tadpole. Using this method, we calculate the reduction of scalar bubble, scalar triangle, scalar box and scalar pentagon with general power of propagators.
$$ T\overline{T} $$-deformed fermionic theories revisited
Authors: Lee Kyung-Sun , Yi Piljin , Yoon Junggi 
Published: July 2021

Abstract
We revisit $$ T\overline{T} $$
T

T
¯

deformations of d = 2 theories with fermions with a view toward the quantization. As a simple illustration, we compute the deformed Dirac bracket for a Majorana doublet and confirm the known eigenvalue flows perturbatively. We mostly consider those $$ T\overline{T} $$
T

T
¯

theories that can be reconstructed from string-like theories upon integrating out the worldsheet metric. After a quick overview of how this works when we add NSR-like or GS-like fermions, we obtain a known non-supersymmetric $$ T\overline{T} $$
T

T
¯

deformation of a $$ \mathcal{N} $$
N
= (1, 1) theory from the latter, based on the Noether energy-momentum. This world- sheet reconstruction implies that the latter is actually a supersymmetric subsector of a d = 3 GS-like model, implying hidden supercharges, which we do construct explicitly. This brings us to ask about different $$ T\overline{T} $$
T

T
¯

deformations, such as manifestly supersymmetric $$ T\overline{T} $$
T

T
¯

and also more generally via the symmetric energy-momentum. We show that, for theories with fermions, such choices often lead us to doubling of degrees of freedom, with potential unitarity issues. We show that the extra sector develops a divergent gap in the “small deformation” limit and decouples in the infrared, although it remains uncertain in what sense these can be considered a deformation.
Holographic teleportation in higher dimensions
Authors: Ahn Byoungjoon , Ahn Yongjun , Bak Sang-Eon , Jahnke Viktor , Kim Keun-Young 
Published: July 2021

Abstract
We study higher-dimensional traversable wormholes in the context of Rindler-AdS/CFT. The hyperbolic slicing of a pure AdS geometry can be thought of as a topological black hole that is dual to a conformal field theory in the hyperbolic space. The maximally extended geometry contains two exterior regions (the Rindler wedges of AdS) which are connected by a wormhole. We show that this wormhole can be made traversable by a double trace deformation that violates the average null energy condition (ANEC) in the bulk. We find an analytic formula for the ANEC violation that generalizes Gao-Jafferis-Wall result to higher-dimensional cases, and we show that the same result can be obtained using the eikonal approximation. We show that the bound on the amount of information that can be transferred through the wormhole quickly reduces as we increase the dimensionality of spacetime. We also compute a two-sided commutator that diagnoses traversability and show that, under certain conditions, the information that is transferred through the wormhole propagates with butterfly speed $$ {\upsilon}_B=\frac{1}{d-1} $$

υ
B

=

1

d
−
1

.
A Cryptographic Analysis of the TLS 1.3 Handshake Protocol
Authors: Dowling Benjamin , Fischlin Marc , Günther Felix , Stebila Douglas 
Published: July 2021

AbstractWe analyze the handshake protocol of the Transport Layer Security (TLS) protocol, version 1.3. We address both the full TLS 1.3 handshake (the one round-trip time mode, with signatures for authentication and (elliptic curve) Diffie–Hellman ephemeral ((EC)DHE) key exchange), and the abbreviated resumption/“PSK” mode which uses a pre-shared key for authentication (with optional (EC)DHE key exchange and zero round-trip time key establishment). Our analysis in the reductionist security framework uses a multi-stage key exchange security model, where each of the many session keys derived in a single TLS 1.3 handshake is tagged with various properties (such as unauthenticated versus unilaterally authenticated versus mutually authenticated, whether it is intended to provide forward security, how it is used in the protocol, and whether the key is protected against replay attacks). We show that these TLS 1.3 handshake protocol modes establish session keys with their desired security properties under standard cryptographic assumptions.
Comprehensive Systems: A formal foundation for Multi-Model Consistency Management
Authors: Stünkel Patrick , König Harald , Lamo Yngve , Rutle Adrian 
Published: July 2021

Abstract

Model management is a central activity in Software Engineering. The most challenging aspect of model management is to keep inter-related models consistent with each other while they evolve. As a consequence, there is a lot of scientific activity in this area, which has produced an extensive body of knowledge, methods, results and tools. The majority of these approaches, however, are limited to binary inter-model relations; i.e. the synchronisation of exactly two models. Yet, not every multi-ary relation can be factored into a family of binary relations. In this paper, we propose and investigate a novel
comprehensive system
construction, which is able to represent multi-ary relations among multiple models in an
integrated
manner and thus serves as a
formal
foundation
for artefacts used in consistency management activities involving multiple models. The construction is based on the definition of
partial
commonalities among a set of models using the same language, which is used to denote the (local) models. The main
theoretical
results of this paper are proofs of the facts that comprehensive systems are an admissible environment for (i) applying formal means of consistency verification (diagrammatic predicate framework), (ii) performing algebraic graph transformation (weak adhesive HLR category), and (iii) that they generalise the underlying setting of graph diagrams and triple graph grammars.