bluuebunny/crossref_metadata_2025_split huggingface dataset:
Introduction
Authors: Ingram Stephen 
Published: July 2023

Abstract
This introductory chapter sets out the central concerns of the book, and outlines the positions and concepts that will be at issue in it. It first explains how the approach of the book—specifically, the focus on normative arbitrariness and interpersonal dialogue as a way of learning more about moral reality, moral knowledge, and moral language. It then introduces the distinction between realist theories (including naturalistic and non-naturalistic theories, and robust, relaxed and quasi-realist theories) and anti-realist theories (including error theory and two types of stance-dependence theory). The chapter ends with a brief chapter by chapter overview of the book.
Arbitrariness Charges
Authors: Ingram Stephen 
Published: July 2023

Abstract
Intuitions about arbitrariness and non-arbitrariness play a key role in metaethical debate. It is an interesting feature of such debate that both realists and anti-realists face ‘arbitrariness charges.’ Roughly put, to issue an arbitrariness charge against a metaethical theory is to accuse that theory of failing to capture the normative non-arbitrariness of moral choice. The precise nature of these charges remains obscure, for the concept of arbitrariness itself has never been examined in depth. This chapter clarifies the notion of arbitrariness, and then outlines five distinct arbitrariness charges—the bruteness charge, the privilege charge, the normative deficit charge, the ownership charge, and the stability charge. This sets the scene for Chapters 2–5, which ask whether realist and anti-realist theories are able to capture all the ways in which moral choices are normatively non-arbitrary.
Stance-Independence
Authors: Ingram Stephen 
Published: July 2023

Abstract
Having rejected the most promising stance-dependence theories in the previous two chapters, this chapter considers the prospects of a stance-independent moral ontology—that is, the ontology of moral realism. It shows that a realist view is well-placed to capture the non-arbitrariness of moral choice. It first explains how the commitment to stance-independent moral facts allows realists to avoid the arbitrariness charges that challenge stance-dependence theories. It then asks whether realists can handle the arbitrariness charges facing their own view—namely, the ownership charge and a version of the bruteness charge. It shows that answering the latter requires a commitment to categorical and (thus) irreducibly normative, non-natural reasons. This is a controversial commitment, so this chapter ends with a partial vindication of it. Specifically, it offers a ‘companions in innocence’ argument involving the normativity of non-moral needs.
Moral Reference
Authors: Ingram Stephen 
Published: July 2023

Abstract
The major meta-semantic question facing robust realists concerns how moral terms—like ‘right’ and ‘good’ in English—can refer to robust moral properties (given that such properties are stance-independent, non-natural, and causally inert). This chapter provides an answer to this question of semantic access. It rejects the conceptual role semantics that is often taken to be the best meta-semantic theory for robust realism, and instead defends a theory of ‘moral mental files.’ It argues that this theory is well-placed to explain certain judgements about when moral dialogue and disagreement are (and are not) possible. And it shows that the theory of moral mental files has two big payoffs for robust realism: it provides resources to accommodate certain views of moral motivation, and it affords a nuanced answer to the challenge posed by the alleged possibility of alternative normative concepts.
When not to Operate in Spinal Deformity
Authors: Passias Peter G. , Pierce Katherine E. , Dave Pooja , Lafage Renaud , Lafage Virginie , Schoenfeld Andrew J. , Line Breton , Uribe Juan , Hostin Richard , Daniels Alan , Hart Robert , Burton Douglas , Kim Han Jo , Mundis Gregory M. , Eastlack Robert , Diebo Bassel G. , Gum Jeffrey L. , Shaffrey Christopher , Schwab Frank , Ames Christopher P. , Smith Justin S. , Bess Shay , Klineberg Eric , Gupta Munish C. , Hamilton D. Kojo ,   on behalf of the International Spine Study Group
Published: July 2023

Study Design:
Retrospective review of a prospectively enrolled adult spinal deformity (ASD) database.

Objective:
To investigate what patient factors elevate the risk of sub-optimal outcomes after deformity correction.

Background:
Currently, it is unknown what factors predict a poor outcome after adult spinal deformity surgery, which may require increased preoperative consideration and counseling.

Materials and Methods:
Patients >18 yrs undergoing surgery for ASD(scoliosis≥20°, SVA≥5 cm, PT≥25°, or TK≥60°). An unsatisfactory outcome was defined by the following categories met at two years: (1) clinical: deteriorating in ODI at two years follow-up (2) complications/reoperation: having a reoperation and major complication were deemed high risk for poor outcomes postoperatively (HR). Multivariate analyses assessed predictive factors of HR patients in adult spinal deformity patients.

Results:
In all, 633 adult spinal deformity (59.9 yrs, 79% F, 27.7 kg/m2, CCI: 1.74) were included. Baseline severe Schwab modifier incidence (++): 39.2% pelvic incidence and lumbar lordosis, 28.8% sagittal vertical axis, 28.9% PT. Overall, 15.5% of patients deteriorated in ODI by two years, while 7.6% underwent reoperation and had a major complication. This categorized 11 (1.7%) as HR. HR were more comorbid in terms of arthritis (73%), heart disease (36%), and kidney disease (18%), P<0.001. Surgically, HR had greater EBL (4431ccs) and underwent more osteotomies (91%), specifically Ponte(36%) and Three Column Osteotomies(55%), which occurred more at L2(91%). HR underwent more PLIFs (45%) and had more blood transfusion units (2641ccs), all P<0.050. The multivariate regression determined a combination of a baseline Distress and Risk Assessment Method score in the 75th percentile, having arthritis and kidney disease, a baseline right lower extremity motor score ≤3, cSVA >65 mm, C2 slope >30.2°, CTPA >5.5° for an R
2 value of 0.535 (P<0.001).

Conclusions:
When addressing adult spine deformities, poor outcomes tend to occur in severely comorbid patients with major baseline psychological distress scores, poor neurologic function, and concomitant cervical malalignment.
The pine pathogen Diplodia sapinea is associated with the death of large Douglas fir trees
Authors: Ritzer Elisabeth , Schebeck Martin , Kirisits Thomas 
Published: July 2023

AbstractClimate change poses severe pressures to European conifer forests. Using non‐native tree species, such as Douglas fir (Pseudotsuga menziesii), is one proposed strategy to circumvent adverse effects for forest management. However, novel forest health risks can impair the cultivation of non‐native trees. In 2022, we observed large Douglas fir trees (approximately 40–50 years old, diameter at breast height (dbh) 21–41 cm) that had recently died in spring or summer 2022 in three forest stands in Eastern Austria. Intensive resin flow, blue‐staining of the sapwood and the absence of bark‐ and wood‐boring insects indicated a fungal infection. Isolations from blue‐stained sapwood of the dead trees consistently yielded cultures of the opportunistic pathogen Diplodia sapinea. In a greenhouse wound inoculation experiment, seven D. sapinea isolates obtained from Douglas fir caused phloem necrosis, blue‐staining of sapwood and mortality and thus displayed pathogenicity towards seedlings of both Ps. menziesii and its common host, Scots pine (Pinus sylvestris). Diplodia sapinea produced significantly longer areas of blue‐stain as well as higher and faster mortality in Ps. menziesii compared to P. sylvestris. We conclude that D. sapinea substantially contributed to the death of seven of the 13 examined large Douglas fir trees. While this fungus has been described as a pathogen of young Douglas fir trees before, this is the first report that it can potentially kill large individuals of this conifer species under drought conditions. Thus, our results indicate that D. sapinea could represent a severe threat to the cultivation of Ps. menziesii in European forestry.
Racial residential segregation and COVID-19 vaccine uptake: an analysis of Georgia USA county-level data
Authors: Medcalfe Simon K. , Slade Catherine P. 
Published: July 2023

Abstract
Background
Foundational literature demonstrates that racial residential segregation results in poorer health outcomes for Black people than white people due to a variety of social determinants of health. COVID-19 vaccine uptake is important for better health outcomes, regardless of race. The COVID-19 pandemic has elevated concerns about racial health disparities but with little discussion of racial residential segregation as a predictor of disparate health outcomes. This paper investigates the relationship between racial residential segregation and COVID-19 vaccine uptake using county level data from the State of Georgia (USA).

Methods
Using publicly available data, regression analysis is conducted for 138 of the 159 counties in Georgia USA, using a dissimilarity index that describes county level differences in racial residential segregation. The primary independent variable is Black-white differences in vaccine uptake at the county level. The analytic methods focus on a spatial analysis to support information for county level health departments as the basis for health policy and resource allocation.

Results
Constructing a variable of the difference in vaccination rates between Black and white residents we find that Black-white differences in COVID-19 vaccination are most notable in the 69 most segregated of the 159 counties in Georgia. A ten-point lower segregation index is associated with an improvement in the Black-white vaccination gap of 1.5 percentage points (95% CI -0.31, -0.00). Income inequality and access to health care resources, such as access to a primary care physician, also predict Black-white differences in vaccination rates at the county level. Suggested mapping approaches of publicly available data at a state county level, provides a resource for local policy makers to address future challenges for epidemic and pandemic situations.

Conclusion
County level and geospatial data analysis can inform policy makers addressing the impact of racial residential segregation on local health outcomes, even for pandemic and epidemic issues.
Understanding the barriers and facilitators of COVID-19 risk mitigation strategy adoption and COVID-19 vaccination in refugee settlements in Uganda: a qualitative study
Authors: Klabbers Robin E. , Muwonge Timothy R. , Ajidiru Scovia , Borthakur Sukanya , Mujugira Andrew , Sharma Monisha , Vinck Patrick , Pham Phuong , Celum Connie , Parkes-Ratanshi Rosalind , O’Laughlin Kelli N. 
Published: July 2023

Abstract
Background
Perspectives on COVID-19 risk and the willingness and ability of persons living in refugee settlements to adopt COVID-19 prevention strategies have not been rigorously evaluated. The realities of living conditions in Ugandan refugee settlements may limit the extent to which refugees can uptake strategies to mitigate COVID-19 risk.

Methods
In-depth qualitative interviews were conducted between April 2021 and April 2022 to assess COVID-19 knowledge, risk perception, prevention strategy adoption including COVID-19 vaccination, and COVID-19 impact on living conditions in refugee settlements in Uganda. Interview participants included 28 purposively selected refugees who called into “Dial-COVID”, a free telephone COVID-19 information collection and dissemination platform that was advertised in refugee settlements by community health workers. Interviews were analyzed using a combination of deductive and inductive content analysis. Emerging themes were mapped onto the Theoretical Domains Framework to identify domains influencing prevention behavior. Results were synthesized to provide intervention and policy recommendations for risk mitigation in refugee settlements for COVID-19 and future infectious disease outbreaks.

Results
The COVID-19 pandemic detrimentally impacted economic and food security as well as social interactions in refugee settlements. Youth were considered especially impacted, and participants reported incidents of child marriage and teenage pregnancy following school closures. Participants displayed general knowledge of COVID-19 and expressed willingness to protect themselves and others from contracting COVID-19. Risk mitigation strategy uptake including COVID-19 vaccination was influenced by COVID-19 knowledge, emotions surrounding COVID-19, the environmental context and resources, personal goals, beliefs about the consequences of (non)adoption, social influences, and behavior reinforcement. Resource constraints, housing conditions, and competing survival needs challenged the adoption of prevention strategies and compliance decreased over time.

Conclusions
Contextual challenges impact the feasibility of COVID-19 risk mitigation strategy uptake in refugee settlements. Pre-existing hardships in this setting were amplified by the COVID-19 pandemic and related lockdowns. Targeted dispelling of myths, alignment of information across communication mediums, supporting survival needs and leveraging of respected role models are strategies that may hold potential to mitigate risk of infectious diseases in this setting.

Registration details
World Pandemic Research Network – 490,652.
Association of variability in metabolic parameters with the incidence of type 2 diabetes: evidence from a functional community cohort
Authors: Chen Ning , Liu Yu-Hong , Hu Li-Kun , Ma Lin-Lin , Zhang Yu , Chu Xi , Dong Jing , Yan Yu-Xiang 
Published: July 2023

Abstract
Background
To investigate the association of variability in metabolic parameters such as total cholesterol concentrations (TC), uric acid (UA), body mass index (BMI), visceral adiposity index (VAI) and systolic blood pressure (SBP) with incident type 2 diabetes (T2D) and whether variability in these metabolic parameters has additive effects on the risk of T2D.

Methods
Based on the Beijing Functional Community Cohort, 4392 participants who underwent three health examinations (2015, 2016, and 2017) were followed up for incident T2D until the end of 2021. Variability in metabolic parameters from three health examinations were assessed using the coefficient of variation, standard deviation, variability independent of the mean, and average real variability. High variability was defined as the highest quartile of variability index. Participants were grouped according to the number of high-variability metabolic parameters. Cox proportional hazards models were performed to assess the hazard ratio (HR) and 95% confidence interval (CI) for incident T2D.

Results
During a median follow-up of 3.91 years, 249 cases of incident T2D were identified. High variability in TC, BMI, VAI and SBP was significantly associated with higher risks of incident T2D. As for UA, significant multiplicative interaction was found between variability in UA and variability in other four metabolic parameters for incident T2D. The risk of T2D significantly increased with the increasing numbers of high-variability metabolic parameters. Compared with the group with low variability for 5 parameters, the HR (95% CI) for participants with 1–2, 3, 4–5 high-variability metabolic parameters were 1.488 (1.051, 2.107), 2.036 (1.286, 3.222) and 3.017 (1.549, 5.877), respectively. Similar results were obtained in various sensitivity analyses.

Conclusions
High variability of TC, BMI, VAI and SBP were independent predictors of incident T2D, respectively. There was a graded association between the number of high-variability metabolic parameters and incident T2D.
Cross-Sectional Variation of Option-Implied Volatility Skew
Authors: Wu Liuren , Tian Meng 
Published: July 2023

The stock option-implied volatility skew reflects both the structural risk characteristics of the underlying company and the short-term information flow about the stock price movement. This paper builds a semistructural, cross-sectional option pricing model to separate the structural risk contributions from the information flow. The model identifies two structural risk sources that contribute to the cross-sectional variation of the skew: the company’s business cyclicality and its default risk. The model can explain as much as 44% of the cross-sectional variation in implied volatility skew and is particularly informative during and after recessions. The remaining skew variation reflects mainly short-term information flow and can be used to construct stock portfolios with much better investment performance and without hidden structural risk exposures. This paper was accepted by Agostino Capponi, finance. Funding: L. Wu gratefully acknowledges support by a grant from the City University of New York PSC-CUNY Research Award Program. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4872 .
Corporate responsibility in implementing CSR during the Covid-19 pandemic
Authors: Erytatina Erytatina Sukmawanti 
Published: July 2023

Corporate social responsibility (CSR) is a form of the company’s concern for the company’s environment through various activities carried out in the context of conservation, development participation, and various other social responsibilities. This study aims to determine the CSR challenge program and how the solutions that PT. SHRAP Electronics Indonesia do to solve these challenges. The type of research used is descriptive qualitative research, namely qualitative research that describes in detail the portrait of the actual conditions that occurred. Where to explain these conditions using interactive analysis Miles and Huberman. Data collection techniques with in-depth interviews, direct observation and literature study. Interviews were conducted with Research Informants as parties who understand and understand the process of implementing CSR programs that are implemented. The results of this study indicate that the CSR program of PT. SHARP Electronics Indonesia has a positive and significant impact on participation in providing social response programs in the midst of the COVID-19 pandemic so as to create a positive corporate image.
Thermal and mechanical properties of a new insulation composite material
Authors: Kocyigit Fatih , Kaya Alaattin Metin 
Published: July 2023

Abstract
The Taguchi optimization method was used to optimize waste and natural different components such as waste marble dust, expanded perlite, perlite aggregate size, cement, and molten tragacanth in the production of new insulation composite material. Compressive strength, thermal conductivity, abrasion loss, and water adsorption properties of the developed composite material were investigated. Taguchi’s standard L18 array was chosen for optimization of these four components with different levels. Response plots were created using the Taguchi and the optimum test condition was determined. The insulation composite material with the best thermal and mechanical properties was obtained under the condition of waste marble dust (1), expanded perlite (1), perlite aggregate size (1) and molten tragacanth (1). In addition, using the anova (Analysis of Variance), percentage impacts on the mechanical and thermal properties of the test parameters were determined. Statistical values obtained from anova and mathematical models are developed by using multi-linear regression method. It was found that the mathematical model and the experimental results were quite compatible. The optimum test conditions detected were verified by confirmation experiments. Confirmation experiment results were obtained between 99.9 % confidence interval values.
Research on the implantation and dissemination strategy of short creative advertising videos in the new media era
Authors: Liu Eryong , Li Yifei 
Published: July 2023

Interconnections and communication between people in social media enhance the information dissemination. This is leveraged by the business firms by using the social media as advertising platform for their products, brands and services. As interactive multimedia is more captivating than other media forms, the short and creative advertising videos are recently used as effective marketing tool. This work proposes a framework that taps the features of the video advertisements along with social networking properties like network clusters and network degree to determine the transmission and retransmission of video between primary and secondary level clusters. The degradation in retransmission is estimated using the connections and their influence computed as connection coefficient between the nodes. The proposed framework is validated on Facebook advertisement videos by assessing its efficacy in dissemination and implementation of the products. The detailed experimentation reveals that the proposed model is much effective in determining the dissemination and implementation of the video content with the average mean square error of 0.24. The work is robust and versatile, that it could be deployed to other social media networks by customising the estimation of transmission and retransmission rate.
Utility of Smartphone-Based Digital Phenotyping Biomarkers in Assessing Treatment Response to Transcranial Magnetic Stimulation in Depression: Proof-of-Concept Study
Authors: Kelkar Radhika Suneel , Currey Danielle , Nagendra Srilakshmi , Mehta Urvakhsh Meherwan , Sreeraj Vanteemar S , Torous John , Thirthalli Jagadisha 
Published: July 2023

Background
Identifying biomarkers of response to transcranial magnetic stimulation (TMS) in treatment-resistant depression is a priority for personalizing care. Clinical and neurobiological determinants of treatment response to TMS, while promising, have limited scalability. Therefore, evaluating novel, technologically driven, and potentially scalable biomarkers, such as digital phenotyping, is necessary.

Objective
This study aimed to examine the potential of smartphone-based digital phenotyping and its feasibility as a predictive biomarker of treatment response to TMS in depression.

Methods
We assessed the feasibility of digital phenotyping by examining the adherence and retention rates. We used smartphone data from passive sensors as well as active symptom surveys to determine treatment response in a naturalistic course of TMS treatment for treatment-resistant depression. We applied a scikit-learn logistic regression model (l1 ratio=0.5; 2-fold cross-validation) using both active and passive data. We analyzed related variance metrics throughout the entire treatment duration and on a weekly basis to predict responders and nonresponders to TMS, defined as ≥50% reduction in clinician-rated symptom severity from baseline.

Results
The adherence rate was 89.47%, and the retention rate was 73%. The area under the curve for correct classification of TMS response ranged from 0.59 (passive data alone) to 0.911 (both passive and active data) for data collected throughout the treatment course. Importantly, a model using the average of all features (passive and active) for the first week had an area under the curve of 0.7375 in predicting responder status at the end of the treatment.

Conclusions
The results of our study suggest that it is feasible to use digital phenotyping data to assess response to TMS in depression. Early changes in digital phenotyping biomarkers, such as predicting response from the first week of data, as shown in our results, may also help guide the treatment course.