bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cost of Respiratory Syncytial Virus Infections in US Infants: Systematic Literature Review and Analysis
Authors: Bowser Diana M , Rowlands Katharine R , Hariharan Dhwani , Gervasio Raíssa M , Buckley Lauren , Halasa-Rappel Yara , Glaser Elizabeth L , Nelson Christopher B , Shepard Donald S 
Published: April 2022

Abstract

Background
Limited data are available on the economic costs of respiratory syncytial virus (RSV) infections among infants and young children in the United States.

Methods
We performed a systematic literature review of 10 key databases to identify studies published between 1 January 2014 and 2 August 2021 that reported RSV-related costs in US children aged 0–59 months. Costs were extracted and a systematic analysis was performed.

Results
Seventeen studies were included. Although an RSV hospitalization (RSVH) of an extremely premature infant costs 5.6 times that of a full-term infant ($10 214), full-term infants accounted for 82% of RSVHs and 70% of RSVH costs. Medicaid-insured infants were 91% more likely than commercially insured infants to be hospitalized for RSV treatment in their first year of life. Medicaid financed 61% of infant RSVHs. Paying 32% less per hospitalization than commercial insurance, Medicaid paid 51% of infant RSVH costs. Infants’ RSV treatment costs $709.6 million annually, representing $187 per overall birth and $227 per publicly funded birth.

Conclusions
Public sources pay for more than half of infants’ RSV medical costs, constituting the highest rate of RSVHs and the highest expenditure per birth. Full-term infants are the predominant source of infant RSVHs and costs.
Development and application of triangulation joint network based on an FEM program (RS2)
Authors: Xi Peiqi , Huo Yuming , Zhu Defu , Xing Cunen , Wang Zhonglun 
Published: April 2022

Abstract
It is widely known that the triangle is the finest geometric unit, and therefore applying the triangulation joint to the rock mass simulation can not only accurately describe the fracture morphology of rock engineering, but also inversely deduce the mechanical parameters of blocks and joints. Based on the rock and soil two-dimensional analysis program (RS2), this paper compiles a program with MATLAB and realizes the parameterized setting of triangulation joint network (TJN) in RS2 for the first time, using it for the uniaxial compression model and roadway model accordingly. In the simulation of a RS2-TJN uniaxial compression model, its element parameters and joint parameters are calibrated according to the uniaxial compression strength and the elastic modulus obtained from the uniaxial compression test in a laboratory. Then its simulation results are compared with those of the particle flow code (PFC), which shows that the stress–strain curve obtained from the RS2-TJN uniaxial compression model matches the laboratory test one more closely. In the RS2-TJN roadway model, the simulation results obtained by adjusting the joint density are in good agreement with the roadway deformation in situ so as to study the failure characteristics of roadway surrounding rocks. Since the research on adding the triangulation joint network (cracks) to RS2 has not been found, its development and the realization of the parameterized control in this paper enrich the joint base of RS2 and provide a reference for the variety of joint numerical model.
High-frequency wavefield extrapolation using the Fourier neural operator
Authors: Song Chao , Wang Yanghua 
Published: April 2022

Abstract
In seismic wave simulation, solving the wave equation in the frequency domain requires calculating the inverse of the impedance matrix. The total cost strictly depends on the number of frequency components that are considered, if using a finite-difference method. For the applications such as seismic imaging and inversion, high-frequency information is always required and thus the wave simulation is always a challenging task as it demands tremendous computational cost for obtaining dispersion-free high-frequency wavefields for large subsurface models. This paper demonstrates that a data-driven machine learning method, called the Fourier neural operator (FNO), is capable of predicting high-frequency wavefields, based on a limited number of low-frequency components. As the FNO method is for the first time applied to seismic wavefield extrapolation, the experiment reveals three attractive features with FNO: high efficiency, high accuracy and, importantly, the predicted high-frequency wavefields are dispersion free.
Are Refugees (Really) a Hard-to-Survey Group? Fieldwork Experience with Syrian Refugees in Germany
Authors: Aljadeeah Saleh 
Published: April 2022

Abstract
Despite the increasing need for representative data on refugee health, refugees are underrepresented in health research in Germany and other European countries. Researchers often describe refugees as a hard-to-survey (or hard-to-reach) population. Labelling refugee populations with this phrase reflects the perspective of mainly local European researchers on a population they do not belong to. Moreover, refugees may not describe themselves with this phrase. Drawing upon my fieldwork experience as a member of the Syrian community in Germany who has conducted research with Syrian refugees, this practice paper challenges a common narrative among researchers in Europe in regard to refugee populations. I strongly recommend that researchers who are interested in conducting research with refugee populations involve them in all research design and implementation stages. I further call upon researchers to refrain from using the label ‘hard-to-survey’ to describe refugee populations before ensuring that they have done enough to engage with and involve their target population in their research.
Dark Energy Survey Year 3 results: calibration of lens sample redshift distributions using clustering redshifts with BOSS/eBOSS
Authors: Cawthon R , Elvin-Poole J , Porredon A , Crocce M , Giannini G , Gatti M , Ross A J , Rykoff E S , Carnero Rosell A , DeRose J , Lee S , Rodriguez-Monroy M , Amon A , Bechtol K , De Vicente J , Gruen D , Morgan R , Sanchez E , Sanchez J , Sevilla-Noarbe I , Abbott T M C , Aguena M , Allam S , Annis J , Avila S , Bacon D , Bertin E , Brooks D , Burke D L , Carrasco Kind M , Carretero J , Castander F J , Choi A , Costanzi M , da Costa L N , Pereira M E S , Dawson K , Desai S , Diehl H T , Eckert K , Everett S , Ferrero I , Fosalba P , Frieman J , García-Bellido J , Gaztanaga E , Gruendl R A , Gschwend J , Gutierrez G , Hinton S R , Hollowood D L , Honscheid K , Huterer D , James D J , Kim A G , Kneib J-P , Kuehn K , Kuropatkin N , Lahav O , Lima M , Lin H , Maia M A G , Melchior P , Menanteau F , Miquel R , Mohr J J , Muir J , Myles J , Palmese A , Pandey S , Paz-Chinchón F , Percival W J , Plazas A A , Roodman A , Rossi G , Scarpine V , Serrano S , Smith M , Soares-Santos M , Suchyta E , Swanson M E C , Tarle G , To C , Troxel M A , Wilkinson R D ,   (DES Collaboration)
Published: April 2022

ABSTRACT
We present clustering redshift measurements for Dark Energy Survey (DES) lens sample galaxies used in weak gravitational lensing and galaxy clustering studies. To perform these measurements, we cross-correlate with spectroscopic galaxies from the Baryon Acoustic Oscillation Survey (BOSS) and its extension, eBOSS. We validate our methodology in simulations, including a new technique to calibrate systematic errors that result from the galaxy clustering bias, and we find that our method is generally unbiased in calibrating the mean redshift. We apply our method to the data, and estimate the redshift distribution for 11 different photometrically selected bins. We find general agreement between clustering redshift and photometric redshift estimates, with differences on the inferred mean redshift found to be below |Δz| = 0.01 in most of the bins. We also test a method to calibrate a width parameter for redshift distributions, which we found necessary to use for some of our samples. Our typical uncertainties on the mean redshift ranged from 0.003 to 0.008, while our uncertainties on the width ranged from 4 to 9 per cent. We discuss how these results calibrate the photometric redshift distributions used in companion papers for DES Year 3 results.
Fine-Tuning a Global History of Music Theory: Divergences, Zhu Zaiyu, and Music-Theoretical Instruments
Authors: Rehding Alexander 
Published: April 2022

AbstractThe issue of equal temperament offers an object lesson in the challenges of the new global history of music theory: Twelve-tone equal temperament was mathematically formulated at almost the same time in Ming-dynasty China and sixteenth-century Europe. While the old debate got stuck on questions of dates and cultural rivalries, recent work in comparative humanities, especially Kuriyama (2002), opens up new avenues. His concept of “divergence” is applied to the specific “music-theoretical instruments” in which Chinese and European theories of tuning manifested themselves in sound. Zhu Zaiyu’s pathbreaking 1584 theory is reexamined specifically from this angle: He credits the qin (zither) for holding knowledge that the 12 lü, the traditional Chinese pitch-pipes, could not convey. Zhu’s example—and the concept of “divergence”—offers ways forward for a new, materially oriented, global history of music theory.
Producing decent work indicators: contested numbers at the ILO
Authors: Berten John 
Published: April 2022

Abstract
The article investigates the production of decent work indicators within the ILO, to demonstrate that developing measurement infrastructures in global policymaking requires political work. The concept of decent work responds to the perceived marginalization of the ILO in social and labor policy and was supposed to provide a new unifying normative framework for the organization. The article shows that creating decent work indicators encountered challenges due to its highly politicized production process. Proponents of quantification (mostly workers’ representatives) and opponents (mostly employers’ representatives) disagreed about the function of indicators: should they be country-specific or allow for universal assessment of progress from above. In effect, although indicators of decent work have been integrated into the Sustainable Development Goals—mostly as part of goal no. 8, many are still incomplete. As a result, the indicators did not establish a “framework of assessment,” which would have been guided by universal standards of progress allowing the ILO to “govern at a distance,” and could not initiate a paradigmatic policy shift, impeding the infrastructuralization of measurement. Theoretically, the article advances our understanding of policy formulation and design on the transnational level by showing the political foundation of knowledge-based instruments. Empirically, it rests on a Grounded Theory-based analysis of key ILO documents, including Governing Body minutes, conference and expert meeting reports, and official publications, mainly from the period from 1998 to 2015.
Understanding Bank Payouts during the Crisis of 2007–2009
Authors: Cziraki Peter , Laux Christian , Lóránth Gyöngyi 
Published: May 2022

Abstract
We study U.S. banks’ payout policy in 2007–2008. We benchmark these payouts against payouts before the crisis, measure stock price reactions to announcements of dividend changes, and analyze changes in the relation between payout growth and future performance. Further, we examine cross-sectional variation in banks’ payout policy to gauge the possible motives underlying banks’ payout decisions in 2007–2008. We do not find that banks that have a higher willingness to take risk or that have higher incentives to undertake asset substitution use their payout policy to engage in more wealth transfer compared to other banks. (JEL G21, G24, G28, G32, G35).
Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
Dezocine induces apoptosis in human cervical carcinoma Hela cells via the endoplasmic reticulum stress pathway
Authors: Wang Hanlin , Chiang Chengyao , Xue Chenyang , Zhou Lu , Li Shuaihu , Zhou Yaqi , Zhang Zhucheng , Xie Meng , Xiao Tian , Hu Hongyi , Zhu Lizhi , Long Cheng , Zou Yongdong , Wang Ting , Zheng Duo 
Published: April 2022

Abstract
Dezocine, a dual agonist and antagonist of the μ-opioid receptor and κ-opioid receptor, is widely used as an analgesic in China. At present, there are few studies on anti-tumor effects of dezocine, most of which are used to treat cancer pain. However, it has recently been reported that dezocine can induce apoptosis of triple negative breast cancer cells. Dezocine may have some anti-tumor activity, but the effect and potential mechanism of dezocine in the treatment of other types of cancer remain to be fully studied. The purpose of the present study was to investigate the effect of dezocine on human Hela cervical carcinoma cells, and to elucidate the underlying molecular mechanisms. We performed CCK-8 assays, clone formation assays, xenograft, flow cytometry analysis, western blot and RNA-seq analysis to evaluate the effects of dezocine on Hela cells. In addition, the role of endoplasmic reticulum (ER) stress in dezocine-induced apoptosis was investigated using qPCR and western blot analysis. Dezocine inhibited Hela cell viability in dose-dependent and time-dependent manners, and notably did not achieve this effect by targeting the opioid receptors. Further mechanistic studies demonstrated that dezocine activated ER stress by upregulating the expression of GRP78, IRE1 and p-JNK, and that dezocine-induced apoptosis was attenuated when the ER stress pathway was blocked. Our results provide a foundation to support the redefinition of dezocine as a novel, adjuvant treatment for patients with cervical cancer, although further research will be required to support its application in clinical practice.
Which Factors Are Important to Women When Choosing a Breast Reconstruction Surgeon?
Authors: Sergesketter Amanda R. , Lam Shravika , Broadwater Gloria , Shammas Ronnie L. , Langdell Hannah C. , Plichta Jennifer K. , Clancy Sharon , Rezak Kristen , Phillips Brett T. , Hollenbeck Scott T. 
Published: May 2022

Background:
Women undergoing breast reconstruction often research their health care provider options. The authors studied which factors may influence how a woman selects a plastic surgeon for breast reconstruction surgery.

Methods:
An online survey was distributed by means of Amazon Mechanical Turk (MTurk; Amazon Web Services, Inc., Seattle, Wash.) to 1025 adult women. Participants were asked to imagine a scenario in which they had breast cancer, needed to undergo mastectomy, and were choosing a reconstructive surgeon. They were then asked to rank factors influencing this decision on a 1 to 7 Likert scale. Two-sample t tests were used to compare Likert scores between dichotomized categories based on participant characteristics.

Results:
Women assigned the highest scores [mean (standard deviation)] to online reviews on Vitals or WebMD [6.1 (1.2)], years of experience [5.7 (1.4)], recommendations from another surgeon [5.7 (1.3)] or family/friend [4.9 (1.7)], and attending a top medical school [4.7 (1.7)]. Lowest ranked factors were online advertising and surgeon demographics, including having a sex concordant (female) surgeon. After amalgamation into attribute subsections, mean (standard deviation) rated relative importance of surgeon reputation [0.72 (0.13)] was higher than that of appearance [0.46 (0.19)] and demographics [0.31 (0.13)]. Patient demographics influenced relative importance of certain attributes; older, educated, and higher-income patients placed higher value on surgeon appearance (all p < 0.05).

Conclusions:
When selecting a breast reconstruction surgeon, women place the highest value on surgeons’ online, educational, and personal reputations. Though most show no strong preferences for surgeon demographics or physical attributes, specific features may be important for some patients. Cognizance of these preferences may enable providers to more effectively understand patient expectations.
Long-Term Clinical and Aesthetic Results of a Systematic Fat Transfer Protocol for Total Breast Reconstruction after Nipple-Sparing Mastectomy
Authors: Sorotos Michail , Paolini Guido , D’Orsi Gennaro , Firmani Guido , Santanelli di Pompeo Fabio 
Published: May 2022

Background:
Autologous fat transfer can be safely offered for total breast reconstruction after nipple-sparing mastectomy. The aim of this study was to extend a fat transfer protocol to smokers and compare the long-term results among them and irradiated and nonirradiated patients.

Methods:
One hundred seventeen breasts after nipple-sparing mastectomy were prospectively enrolled and stratified in group A (25 irradiated), group B (21 smokers), or group C (71 controls). A standardized fat transfer protocol was used. Data collected were patient demographics, surgery information, and aesthetic analysis. Continuous and categorical variables were analyzed with the Kruskal-Wallis test, and the Cohen Kappa test was used to test interrater variability for the aesthetic analysis.

Results:
Groups were homogeneous for demographics (p > 0.05) but significantly different in number of fat transfer sessions (p < 0.001), mean volume of the first two treatments (p = 0.003), and mean total volume of injected fat (p = 0.002). Volume, shape, position of the breast mound, inframammary fold, and scar location subscales obtained high score evaluations without a significant difference among groups (p > 0.05), whereas skin texture subscale showed a lower score evaluation in group A (p = 0.003). Although a significant difference for total subscales was worse in group A (p = 0.004), the global score had a high rate evaluation in all groups (p = 0.145). Interrater reliability showed substantial agreement among all categories.

Conclusion:
Although further investigation is required, the authors confirm the efficacy of their fat transfer protocol for both irradiated and nonirradiated nipple-sparing mastectomy patients and propose its indication to smokers with comparable clinical and aesthetic results.

CLINICAL QUESTION/LEVEL OF EVIDENCE:
Risk, II.
Understanding Diagnostic Delays for Kaposi Sarcoma in Kenya: A Qualitative Study
Authors: McMahon Devon E. , Chemtai Linda , Grant Merridy , Singh Rhea , Semeere Aggrey , Byakwaga Helen , Laker-Oketta Miriam , Maurer Toby , Busakhala Naftali , Martin Jeffrey , Bassett Ingrid V. , Butler Lisa , Freeman Esther E. 
Published: May 2022

Background:
Although HIV-associated Kaposi sarcoma (KS) is frequently diagnosed at an advanced stage in sub-Saharan Africa, reasons for diagnostic delays have not been well described.

Methods:
We enrolled patients >18 years with newly diagnosed KS between 2016 and 2019 into the parent study, based in western Kenya. We then purposively selected 30 participants with diversity of disease severity and geographic locations to participate in semistructured interviews. We used 2 behavioral models in developing the codebook for this analysis: situated Information, Motivation, and Behavior framework and Andersen model of total patient delay. We then analyzed the interviews using framework analysis.

Results:
The most common patient factors that delayed diagnosis were lack of KS awareness, seeking traditional treatments, lack of personal efficacy, lack of social support, and fear of cancer, skin biopsy, amputation, and HIV diagnosis. Health system factors that delayed diagnosis included previous negative health care interactions, incorrect diagnoses, lack of physical examination, delayed referral, and lack of tissue biopsy availability. Financial constraints were prominent barriers for patients to access and receive care. Facilitators for diagnosis included being part of an HIV care network, living near health facilities, trust in the health care system, desire to treat painful or disfiguring lesions, and social support.

Conclusions:
Lack of KS awareness among patients and providers, stigma surrounding diagnoses, and health system referral delays were barriers in reaching KS diagnosis. Improved public health campaigns, increased availability of biopsy and pathology facilities, and health provider training about KS are needed to improve early diagnosis of KS.
Machine learning-based detection of label-free cancer stem-like cell fate
Authors: Chambost Alexis J. , Berabez Nabila , Cochet-Escartin Olivier , Ducray François , Gabut Mathieu , Isaac Caroline , Martel Sylvie , Idbaih Ahmed , Rousseau David , Meyronet David , Monnier Sylvain 
Published: May 2022

ABSTRACTMost imaging methods rely on labelling biological samples in order to provide specific and easily detectable features. However, label-free imaging is a non-invasive and non-toxic alternative that requires accurate image analysis algorithm based on cell morphology. Such analysis has to deal with a high image variability while fewer features are extractable, so far, fast analysis of label-free brightfield microscopy (LFBM) images remains a challenging task. With the development of microfabricated devices during the last decades, high throughput image generation makes it possible to use machine learning-based algorithms in order to analyse LFBM images. Fast algorithms are also crucially needed to analyze high throughput experiments. In this paper, we provide a data-driven study in order to assess the complexity of LFBM time-lapses monitoring isolated cancer stem-like cells (CSCs) fate in non-adherent conditions. We combined for the first time individual cell fate and cell state temporality analysis in a unique algorithm. Several image analysis algorithms of increasing processing capacities were tested: a classical computer vision algorithm (CCVA), a shallow learning-based algorithm (SLBA) and a deep learning-based algorithm (DLBA). We show that our optimized DLBA has by far the best accuracy compared to CCVA and SLBA, is at least as accurate as other state-of-the-art DLBAs while being faster. With this study, we demonstrate that optimizing our DLBA accordingly to the image analysis problem can overall provide better results than pretrained models. Such a fast and accurate DLBA is therefore compatible with the generation of high throughput data and opens the route for on-the-fly analysis of CSC fate from LFBM time-lapses.