bluuebunny/crossref_metadata_2025_split huggingface dataset:
Preferences versus opportunities: on the conceptual foundations of normative welfare economics
Authors: Fumagalli Roberto 
Published: December 2022

AbstractNormative welfare economics commonly assumes that individuals’ preferences can be reliably inferred from their choices and relies on preference satisfaction as the normative standard for welfare. In recent years, several authors have criticized welfare economists’ reliance on preference satisfaction as the normative standard for welfare and have advocated grounding normative welfare economics on opportunities rather than preferences. In this paper, I argue that although preference-based approaches to normative welfare economics face significant conceptual and practical challenges, opportunity-based approaches fail to provide a more reliable and informative foundation for normative welfare economics than preference-based approaches. I then identify and rebut various influential calls to ground normative welfare economics on opportunities rather than preferences to support my qualified defence of preference-based approaches.
Behavioral and physiological differences during an emotion-evoking task in children at increased likelihood for autism spectrum disorder
Authors: Sacrey Lori-Ann R. , Zwaigenbaum Lonnie , Brian Jessica A. , Smith Isabel M. , Armstrong Vickie , Vaillancourt Tracy , Schmidt Louis A. 
Published: December 2022

AbstractLiterature examining emotional regulation in infants with autism spectrum disorder (ASD) has focused on parent report. We examined behavioral and physiological responses during an emotion-evoking task designed to elicit emotional states in infants. Infants at an increased likelihood for ASD (IL; have an older sibling with ASD; 96 not classified; 29 classified with ASD at age two) and low likelihood (LL; no family history of ASD; n = 61) completed the task at 6, 12, and 18 months. The main findings were (1) the IL-ASD group displayed higher levels of negative affect during toy removal and negative tasks compared to the IL non-ASD and LL groups, respectively, (2) the IL-ASD group spent more time looking at the baseline task compared to the other two groups, and (3) the IL-ASD group showed a greater increase in heart rate from baseline during the toy removal and negative tasks compared to the LL group. These results suggest that IL children who are classified as ASD at 24 months show differences in affect, gaze, and heart rate during an emotion-evoking task, with potential implications for understanding mechanisms related to emerging ASD.
Toward a Multi‐Representational Approach to Prediction and Understanding, in Support of Discovery in Hydrology
Authors: De la Fuente Luis A. , Gupta Hoshin V. , Condon Laura E. 
Published: December 2022

AbstractKey to model development is the selection of an appropriate representational system, including both the representation of what is observed (the data), and the formal mathematical structure used to construct the input‐state‐output mapping. These choices are critical, because they completely determine the questions we can ask, the nature of the analyses and inferences we can perform, and the answers we can obtain. Accordingly, a representation that is suitable for one kind of investigation might be limited in its ability to support some other kind. Arguably, how different representational approaches affect what we can learn from data is poorly understood. This paper explores three representational strategies as vehicles for understanding how catchment scale hydrological processes vary across hydro‐geo‐climatologically diverse Chile. Specifically, we test a lumped water‐balance model (GR4J), a data‐based dynamical systems model (LSTM), and a data‐based regression tree model (Random Forest). Insights were obtained regarding system memory encoded in data, spatial transferability by use of surrogate attributes, and informational deficiencies of the data set that limit our ability to learn an adequate input‐output relationship. As expected, each approach exhibits specific strengths, with LSTM providing the best characterization of dynamics, GR4J being the most robust under informationally deficient conditions, and Random Forest regression‐tree method being most supportive of interpretation. Overall, the contrasting nature of the three approaches suggests the value of adopting a multi‐representational framework to more fully extract information from the data and, by doing so, find information that better facilities the goals of robust prediction and improved understanding, ultimately supporting enhanced scientific discovery.
Effects of Afforestation on Soil Carbon and Nitrogen Accumulation Depend on Initial Soil Nitrogen Status
Authors: Hong Songbai , Cong Nan , Ding Jinzhi , Piao Shilong , Liu Lingli , Peñuelas Josep , Chen Anping , Quine Timothy A. , Zeng Hui , Houlton Benjamin Z. 
Published: December 2022

AbstractLong‐term carbon (C) sequestration in terrestrial vegetation and soil is mediated by soil nitrogen (N) supply. Afforestation is regarded as a global‐scale solution to climate change; thus, resolving the role of N in either facilitating or reducing the long‐term C benefits of this practice has essential implications to maximize its C sink potential. The impacts of afforestation on soil C, N, and their stoichiometric ratio have been widely explored but what regulates these impacts remains unclear at regional and global scales. In this study, we conducted an intensive field sampling investigation including 610 pairs of afforested and control plots in northern China and extensively compiled a global data set containing 211 afforested‐control pairs worldwide to evaluate responses of soil N concentrations and C:N ratios to afforestation and further explored their major regulator. We identified a soil N threshold, the inflection point where afforestation changes from increasing to decreasing soil C and N, which was 0.86 (95% CI: 0.81–0.91) kg N m−2 in 0–1 m depth. Changes in soil C:N ratios with afforestation were mediated by initial relative abundance of soil C and N and types of mycorrhiza associated with planted trees. Increases in soil C:N were mostly driven by trees with ectomycorrhizal associations but did not change for those associated with arbuscular mycorrhizal fungi. These results provide a data‐based understanding on soil C and N dynamics following afforestation and its underlying mechanisms and further highlight the importance of site selection based on initial soil properties in future afforestation.
Pitch Angle Isotropy of Relativistic Electron Microbursts as Observed by SAMPEX/HILT: Statistical and Storm‐Time Properties
Authors: Meyer‐Reed Conrad , Blum Lauren , Shumko Mykhaylo 
Published: December 2022

AbstractObservations of relativistic electron precipitation events from Earth's inner magnetosphere to the upper atmosphere provide essential information about the source/loss processes and dynamics of Earth's radiation belts. Equatorial electron pitch angle isotropy can be an indicator of electron precipitation into the atmosphere, with isotropic populations resulting in a full bounce loss cone (BLC) and anisotropic populations resulting in an emptier BLC. Here we study electron microbursts, which are ˜100 millisecond duration streams of relativistic electrons thought to be scattered into the BLC by particle‐wave scattering. By measuring the ratios of >1 MeV electron flux across different detector rows in the Heavy Ion Large Telescope (HILT) instrument onboard the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) satellite, we quantify the pitch angle isotropy of an electron population. Applying this calculation to microburst events, we have determined the dependence of microburst pitch angle distributions on burst magnitude, magnetic local time (MLT), L‐Shell, and storm phase. We found that high flux magnitude microbursts are typically highly isotropic, while lower flux magnitude microbursts have varying degrees of anisotropy. Furthermore, microbursts are most isotropic as compared to the background population in the afternoon/evening sector as well as initial and main phases of geomagnetic storms. These results have important implications for microburst scattering mechanisms as well as quantification of precipitation driven by this process.
Loss of tumor suppressor WWOX accelerates pancreatic cancer development through promotion of TGFβ/BMP2 signaling
Authors: Husanie Hussam , Abu-Remaileh Muhannad , Maroun Kian , Abu-Tair Lina , Safadi Hazem , Atlan Karine , Golan Talia , Aqeilan Rami I. 
Published: December 2022

AbstractPancreatic cancer is one of the most lethal cancers, owing to its late diagnosis and resistance to chemotherapy. The tumor suppressor WW domain-containing oxidoreductase (WWOX), one of the most active fragile sites in the human genome (FRA16D), is commonly altered in pancreatic cancer. However, the direct contribution of WWOX loss to pancreatic cancer development and progression remains largely unknown. Here, we report that combined conditional deletion of Wwox and activation of KRasG12D in Ptf1a-CreER-expressing mice results in accelerated formation of precursor lesions and pancreatic carcinoma. At the molecular level, we found that WWOX physically interacts with SMAD3 and BMP2, which are known activators of the TGF-β signaling pathway. In the absence of WWOX, TGFβ/BMPs signaling was enhanced, leading to increased macrophage infiltration and enhanced cancer stemness. Finally, overexpression of WWOX in patient-derived xenografts led to diminished aggressiveness both in vitro and in vivo. Overall, our findings reveal an essential role of WWOX in pancreatic cancer development and progression and underscore its role as a bona fide tumor suppressor.
NF-κB1 p50 stabilizes HIF-1α protein through suppression of ATG7-dependent autophagy
Authors: Zhu Junlan , Huang Shirui , Li Yang , Xu Jiheng , Chen Ruifan , Guo Mengxin , Qian Xiaohui , Li Tengda , Tian Zhongxian , Jin Honglei , Huang Chuanshu 
Published: December 2022

Abstract
The function and underlying mechanisms of p50 in the regulation of protein expression is much less studied because of its lacking of transactivation domain. In this study, we discovered a novel function of p50 in its stabilization of hypoxia-inducible factor 1α (HIF-1α) protein under the condition of cells exposed to arsenic exposure. In p50-deficient (p50−/−) cells, the HIF-1α protein expression was impaired upon arsenic exposure, and such defect could be rescued by reconstitutional expression of p50. Mechanistic study revealed that the inhibition of autophagy-related gene 7 (ATG7)-dependent autophagy was in charge of p50-mediated HIF-1α protein stabilization following arsenic exposure. Moreover, p50 deletion promoted nucleolin (NCL) protein translation to enhance ATG7 mRNA transcription via directly binding transcription factor Sp1 mRNA and increase its stability. We further discovered that p50-mediated miR-494 upregulation gave rise to the inhibition of p50-mediated NCL translation by interacting with its 3’-UTR. These novel findings provide a great insight into the understanding of biomedical significance of p50 protein in arsenite-associated disease development and therapy.
The effect of residual palladium on the performance of organic electrochemical transistors
Authors: Griggs Sophie , Marks Adam , Meli Dilara , Rebetez Gonzague , Bardagot Olivier , Paulsen Bryan D. , Chen Hu , Weaver Karrie , Nugraha Mohamad I. , Schafer Emily A. , Tropp Joshua , Aitchison Catherine M. , Anthopoulos Thomas D. , Banerji Natalie , Rivnay Jonathan , McCulloch Iain 
Published: December 2022

AbstractOrganic electrochemical transistors are a promising technology for bioelectronic devices, with applications in neuromorphic computing and healthcare. The active component enabling an organic electrochemical transistor is the organic mixed ionic-electronic conductor whose optimization is critical for realizing high-performing devices. In this study, the influence of purity and molecular weight is examined for a p-type polythiophene and an n-type naphthalene diimide-based polymer in improving the performance and safety of organic electrochemical transistors. Our preparative GPC purification reduced the Pd content in the polymers and improved their organic electrochemical transistor mobility by ~60% and 80% for the p- and n-type materials, respectively. These findings demonstrate the paramount importance of removing residual Pd, which was concluded to be more critical than optimization of a polymer’s molecular weight, to improve organic electrochemical transistor performance and that there is readily available improvement in performance and stability of many of the reported organic mixed ionic-electronic conductors.
Prediction of designer-recombinases for DNA editing with generative deep learning
Authors: Schmitt Lukas Theo , Paszkowski-Rogacz Maciej , Jug Florian , Buchholz Frank 
Published: December 2022

AbstractSite-specific tyrosine-type recombinases are effective tools for genome engineering, with the first engineered variants having demonstrated therapeutic potential. So far, adaptation to new DNA target site selectivity of designer-recombinases has been achieved mostly through iterative cycles of directed molecular evolution. While effective, directed molecular evolution methods are laborious and time consuming. Here we present RecGen (Recombinase Generator), an algorithm for the intelligent generation of designer-recombinases. We gather the sequence information of over one million Cre-like recombinase sequences evolved for 89 different target sites with which we train Conditional Variational Autoencoders for recombinase generation. Experimental validation demonstrates that the algorithm can predict recombinase sequences with activity on novel target-sites, indicating that RecGen is useful to accelerate the development of future designer-recombinases.
PRSS2 remodels the tumor microenvironment via repression of Tsp1 to stimulate tumor growth and progression
Authors: Sui Lufei , Wang Suming , Ganguly Debolina , El Rayes Tyler P. , Askeland Cecilie , Børretzen Astrid , Sim Danielle , Halvorsen Ole Johan , Knutsvik Gøril , Arnes Jarle , Aziz Sura , Haukaas Svein , Foulkes William D. , Bielenberg Diane R. , Ziemys Arturas , Mittal Vivek , Brekken Rolf A. , Akslen Lars A. , Watnick Randolph S. 
Published: December 2022

AbstractThe progression of cancer from localized to metastatic disease is the primary cause of morbidity and mortality. The interplay between the tumor and its microenvironment is the key driver in this process of tumor progression. In order for tumors to progress and metastasize they must reprogram the cells that make up the microenvironment to promote tumor growth and suppress endogenous defense systems, such as the immune and inflammatory response. We have previously demonstrated that stimulation of Tsp-1 in the tumor microenvironment (TME) potently inhibits tumor growth and progression. Here, we identify a novel tumor-mediated mechanism that represses the expression of Tsp-1 in the TME via secretion of the serine protease PRSS2. We demonstrate that PRSS2 represses Tsp-1, not via its enzymatic activity, but by binding to low-density lipoprotein receptor-related protein 1 (LRP1). These findings describe a hitherto undescribed activity for PRSS2 through binding to LRP1 and represent a potential therapeutic strategy to treat cancer by blocking the PRSS2-mediated repression of Tsp-1. Based on the ability of PRSS2 to reprogram the tumor microenvironment, this discovery could lead to the development of therapeutic agents that are indication agnostic.
Classification and spatial mapping of atmospheric corrosion of China
Authors: Hao Wenkui , Xu Lingling , Chen Xin , Jin Yan , Han Yu , Zhang Xinghui , Chen Yun , Huang Luyao , Yang Bingkun , Zhu Zhixiang , Wang Xiaofang 
Published: December 2022

AbstractAtmospheric corrosion is ubiquitous in China but varies a lot among different regions covering the cold, temperate, and tropical zones. Categorizing the atmospheric corrosivity and plotting precise atmospheric corrosion map remain key interest for a variety of industries. The present work proposed an atmospheric corrosion map of China for hot-dip galvanized steels, which was constructed by inverse distance weighting (IDW) interpolation algorithm based on both the measured corrosion rates of coupons exposed at 2393 inland test stations and calculated corrosion rates from a prevalent dose-response function in 2918 sites in coastal regions. When the corrosion category was used as the criterion, the IDW interpolation algorithm of power 2 performed best. Cross-validation results confirmed that the prediction accuracy of IDW interpolation reached 85.6%. Based on the corrosion map, the categories of atmospheric corrosivity in China could be determined.
Lower SARS-CoV-2 household transmission in children and adolescents compared to adults
Authors: Schumm L. , Blankenburg J. , Kahre E. , Armann J. , Dalpke A. H. , Lück C. , Berner R. , Czyborra P. 
Published: December 2022

AbstractIn the COVID-19 pandemic, children were considered to play a major role in SARS-CoV-2 transmission similar to influenza. Thus, mitigation measures have been focused on children, impacting their everyday life severely. Despite this, infectivity in this age group regarding SARS-CoV-2 is not yet clarified. We performed a serology study in households with confirmed SARS-CoV-2 infection to evaluate virus transmission with focus on children and adolescents. Between January and July 2021, 341 minors and 650 adults from 300 households with a confirmed index case participated in the FamilyCoviDD19-study including serological assessment for SARS-CoV-2 antibodies and a questionnaire on demographics, recent and ongoing symptoms, hygiene measures and comorbidities. 45 (16.3%) of all index cases were < 18 years old. Thereof, 55.6% reported COVID-19 associated symptoms, while nearly all adult index cases were symptomatic (94.8%). There was significantly less virus transmission by children and adolescents compared to adult index cases with a secondary attack rate of 0.29 vs. 0.54. With the caveat that the results do not necessarily apply to the Delta and Omicron variants, we conclude that children and adolescents are less susceptible for SARS-CoV-2 infection, more frequently show an asymptomatic course of disease and are less infective than adults.
A cross-sectional, multicenter survey of the prevalence and risk factors for Long COVID
Authors: Imoto Waki , Yamada Koichi , Kawai Ryota , Imai Takumi , Kawamoto Kengo , Uji Masato , Kanda Hidenori , Takada Minoru , Ohno Yoshiteru , Ohtani Hiroshi , Kono Manami , Hikiishi Atsuhito , Eguchi Yosuke , Namikawa Hiroki , Kawaguchi Tomoya , Kakeya Hiroshi 
Published: December 2022

AbstractLong-term sequelae of the coronavirus disease (COVID-19) constitute Long COVID. Although Long COVID has been reported globally, its risk factors and effects on quality of life (QOL) remain unclear. We conducted a cross-sectional study using questionnaires and electronic medical records of COVID-19 patients who were diagnosed or hospitalized at five facilities in Japan. Responses were obtained from 285 out of 1,150 patients. More than half of the participants reported Long COVID symptoms of varying severity 1 year after COVID-19. Common sequelae included fatigue, dyspnea, alopecia, concentration problems, memory problems, sleeplessness, and joint pain, which often significantly reduced their QOL. COVID-19 severity was strongly associated with sputum production, chest pain, dyspnea, sore throat, and diarrhea, but not with fatigue, dysgeusia, anosmia, alopecia, and sleeplessness. Fatigue, dysgeusia, anosmia, alopecia, and sleeplessness affected the QOL among participants with asymptomatic or mild COVID-19 during the acute phase. Moreover, these sequelae persisted for prolonged periods.
Predicting graft failure in pediatric liver transplantation based on early biomarkers using machine learning models
Authors: Jung Seungho , Park Kyemyung , Ihn Kyong , Kim Seon Ju , Kim Myoung Soo , Chae Dongwoo , Koo Bon-Nyeo 
Published: December 2022

AbstractThe early detection of graft failure in pediatric liver transplantation is crucial for appropriate intervention. Graft failure is associated with numerous perioperative risk factors. This study aimed to develop an individualized predictive model for 90-days graft failure in pediatric liver transplantation using machine learning methods. We conducted a single-center retrospective cohort study. A total of 87 liver transplantation cases performed in patients aged < 12 years at the Severance Hospital between January 2010 and September 2020 were included as data samples. Preoperative conditions of recipients and donors, intraoperative care, postoperative serial laboratory parameters, and events observed within seven days of surgery were collected as features. A least absolute shrinkage and selection operator (LASSO) -based method was used for feature selection to overcome the high dimensionality and collinearity of variables. Among 146 features, four variables were selected as the resultant features, namely, preoperative hepatic encephalopathy, sodium level at the end of surgery, hepatic artery thrombosis, and total bilirubin level on postoperative day 7. These features were selected from different times and represent distinct clinical aspects. The model with logistic regression demonstrated the best prediction performance among various machine learning methods tested (area under the receiver operating characteristic curve (AUROC) = 0.898 and area under the precision–recall curve (AUPR) = 0.882). The risk scoring system developed based on the logistic regression model showed an AUROC of 0.910 and an AUPR of 0.830. Together, the prediction of graft failure in pediatric liver transplantation using the proposed machine learning model exhibited superior discrimination power and, therefore, can provide valuable information to clinicians for their decision making during the postoperative management of the patients.
Fault location of cable hybrid transmission lines based on energy attenuation characteristics of traveling waves
Authors: Huo Wen , Qu Zhenbing , Ao Zirong , Zhang Yongjun , Zhao Erleng , Zhang Chen , Jiang Hao 
Published: December 2022

AbstractThe overhead-cable hybrid transmission lines are alternately connected by two types of lines, with a more complex structure and higher difficulty in fault location. This paper presents an ac-curate fault location method for overhead-cable hybrid lines based on traveling wave energy. Firstly, the basic concept of traveling wave energy is defined. Based on the attenuation charac-teristics of the traveling wave, the mapping relationship between traveling wave energy and fault location is analyzed. Secondly, considering the influence of S-transform error on the traveling wave energy propagation law, the traveling wave energy attenuation characteristics of common A-type and B-type hybrid lines are analyzed. Then, for the overhead-cable hybrid lines with different structures, the mapping relationship between the traveling wave energy at both ends of the line and the fault distance is quantitatively derived, and an accurate fault location method based on the initial traveling wave energy ratio at the same frequency at both ends of the line is proposed. Finally, a 110 kV hybrid transmission line fault simulation model is built in PSCAD/EMTDC, and the faults under different conditions are simulated in different line sections. The effectiveness and robustness of the proposed method are verified through the simulation.