bluuebunny/crossref_metadata_2025_split huggingface dataset:
Extinction in Public
Authors: O’Key Dominic 
Published: March 2023

AbstractThis essay argues that the concept of extinction, polysemous if not overdetermined, is becoming an emergent keyword of contemporary public life as it faces the climate crisis. To make this argument the essay critically considers the ways in which extinction is currently being made public—within and by the environmental humanities but also in the wider public sphere of political and cultural contestation. The essay begins by problematizing the concept of extinction itself, positing that it makes sense to think of the Sixth Extinction as the first historical extinction event—that is, as a social articulation of an organic process in which the causes and impacts are at once natural and social. Then the essay discusses the different extinction imaginaries that have operated across modernity, before finally turning to the writings of the Extinction Studies Working Group, whose conception of extinction as a process rather than event, and whose arguments that mass extinction presents an ethical call to responsibility, have become a template for how extinction is thought about within the field of the environmental humanities. The essay ends by posing some companionly criticisms of the extinction studies project.
“We Most Certainly Do Have a Language”
Authors: Nelson Diane , Kariri-Xocó Nhenety , Kariri-Xocó Idiane , Pitman Thea 
Published: March 2023

AbstractThis article proposes that languages should be embraced by the field of extinction studies while at the same time being mindful of the imbrication of colonialism in both the assignation and terminology of extinction and attempts to revive or reclaim endangered and extinct languages. It thus argues for a decolonizing approach to discourses of both language extinction and reclamation. The article starts by contextualizing the complementary extinction crises facing both species and languages. It then moves on to explore the links between colonialism and the extinction crisis for languages as well as the colonialist underpinnings of many attempts to document and revive endangered and extinct languages. The article then looks to a particularly unique case of decolonial language reclamation, focusing on the work of members of the Kariri-Xocó Indigenous community in present-day Northeast Brazil. It concludes that, by reclaiming their language in a way that is both agentive and coconstructed, the Kariri-Xocó bring together language, culture, and spirituality as tools for resistance.
Practicing Palliation for Extinction and Climate Change
Authors: Gibson Julia D. 
Published: March 2023

AbstractEven with the advent of climate change, mainstream environmentalism lacks a robust death ethics, that is, ethical theories and practices for attending directly to what is owed to the unjustly dead and dying. This article draws on Indigenous, Afrofuturist, and feminist science fiction narratives and their correlating lived practices to explore how death ethics for those driven extinct by climate change and other environmental injustices can and ought to go beyond affect, symbolism, and abstraction. It puts forward environmental palliation as an alternative framework for grappling with the injustice of extinction as and in publics. Far from a glorified form of euthanasia, palliation is an ethic and a practice geared toward providing good or better deaths for particular entities under specific conditions of injustice. In death, palliation cedes to remembrance, an ethic and practice for keeping the dead alive in memory so that they can be cared for. When done right, these death ethics are inextricably linked with climate justice for the living and those yet-to-be.
Serine hydroxymethyl transferase is required for optic lobe neuroepithelia development in Drosophila
Authors: Silva Eunice A. B. , Venda Ana M. , Homem Catarina C. F. 
Published: March 2023

ABSTRACT
Cell fate and growth require one-carbon units for the biosynthesis of nucleotides, methylation reactions and redox homeostasis, provided by one-carbon metabolism. Consistently, defects in one-carbon metabolism lead to severe developmental defects, such as neural tube defects. However, the role of this pathway during brain development and in neural stem cell regulation is poorly understood. To better understand the role of one carbon metabolism we focused on the enzyme Serine hydroxymethyl transferase (Shmt), a key factor in the one-carbon cycle, during Drosophila brain development. We show that, although loss of Shmt does not cause obvious defects in the central brain, it leads to severe phenotypes in the optic lobe. The shmt mutants have smaller optic lobe neuroepithelia, partly justified by increased apoptosis. In addition, shmt mutant neuroepithelia have morphological defects, failing to form a lamina furrow, which likely explains the observed absence of lamina neurons. These findings show that one-carbon metabolism is crucial for the normal development of neuroepithelia, and consequently for the generation of neural progenitor cells and neurons. These results propose a mechanistic role for one-carbon during brain development.
Epidermal growth factor outperforms placebo in the treatment of diabetic foot ulcer: a meta-analysis
Authors: Rahim Fazal , Yan Xie , Shah Jawad Ali , Bibi Nida , Khan Zafar Ullah , Nawaz Shah , Ming Yao 
Published: March 2023

Background: Diabetic foot ulcers (DFUs) are a life-threatening ailment caused by diabetes. Several growth factors, as well as their various combinations, have shown promising effect in aiding diabetic foot ulcer. However, contradictory or paradoxical results are often available, and debates about this issue are ongoing. Therefore, a comprehensive meta-analysis was performed to compare the efficacy and safety of epidermal growth factor (EGF) and placebo in healing diabetic foot ulcers. Methods: The database search included relevant English literature from Cochrane Library, PubMed, Google Scholar, Elsevier, and EMBASE that was published between 2009 and 2021. Inclusion criteria included type 1 and 2 diabetic patients with foot wounds focusing on complete healing rate. Exclusion criteria included combined therapy, non-human studies, reviews, and protocols. To assess the quality of each study, biases regarding random sequence generation, allocation concealment, participant and personnel blinding, outcome assessment blinding and incomplete outcome data were thoroughly identified. Results: Eight randomized control trials comprising 620 patients (337 in EGF group, 283 in placebo group), were included in this meta-analysis. EGF achieved a significantly higher complete healing rate than placebo after four weeks of treatment, with relative risk (RR): 3.04 (0.50, 18.44) and heterogeneity (Chi2 = 6.46, df = 2 (P = 0.04) I2 = 69 %). Notably, the healing frequency in the placebo group was 17%, whereas the healing frequency in the epidermal growth factor group was 34%. Likewise, after eight weeks of treatment, the relative risk and heterogeneity were RR: 2.59 (1.42, 4.72) and (Chi2 =7.92, df= 4 (p= 0.09): I2= 49%), respectively. Moreover, the risk ratio at 12 weeks was RR: 1.01 (0.42, 2.46), and heterogeneity was (Chi2 =8.55, df= 2 (p= 0.01): I2= 77%). Conclusions: Our findings indicate that EGF significantly promotes wound healing, and could be recommended as an effective and safe treatment for DFUs.
Cloning and characterization of the LvCTL genes encoding C-type lectin from white-leg shrimp (Litopenaeus vannamei)
Authors: Phuong Tran Vinh , Nguyen Xuan Huy , Quang Lich Nguyen , Hoang Quang Tan , Tran Ngoc Nguyen , Nguyen Phuoc Ngoc , Linh Nguyen Quang 
Published: March 2023

Background: Lectins are carbohydrate-binding protein domains. The C-type designates a requirement for calcium for binding. Proteins contain C-type lectin domains that have a diverse range of functions, including cell-cell adhesion, immune response to pathogens, and apoptosis. This study aimed to investigate the characters of LvCTL-encoding genes from white-leg shrimp (Litopenaeus vannamei) in Central Vietnam. Methods: Two PCR products (LvCTL3 and LvCTL4) were cloned and sequenced. The structure and characterization of LvCTL proteins were predicted using bioinformatics tools. Results: The results showed that the LvCTL3 gene was 444 nucleotides long and 98.87% similar to the published LvCTL3 gene (accession number: KF156943). The polypeptide sequence had 147 amino acids, which were 97.28% identical to the reference sequence (AGV68681) and the LvCTL4 gene had a length of 417 nucleotides and homology of 99.52% compared to the published gene (KM387560). The deduced polypeptide sequence had 138 amino acids, and was 100% similar to the reference sequence (AKA64754). The LvCTL3 had a molecular weight of 16.91 kDa and an isoelectric point (pI) of 4.66, while LvCTL4 had 15.75 and 4.58 kDa, respectively. The structure prediction results showed that LvCTL3 and LvCTL4 had one domain (CTLD), LvCTL3 had two α helices and nine β sheets, and LvCTL4 had two α helices and eight β sheets. Conclusions: Our results provide essential information for the heterologous expression and biosynthesis production of C-type lectins.
Effect of polyamine precursors and antioxidants on growth and metabolism of salt-stressed barley
Authors: Eldakkak Eman , El-Shourbagy Mohamed 
Published: March 2023

Background: Salinity is a serious problem that reduces crop productivity by affecting seed germination and seedling growth. It affects plant growth by disrupting plant osmosis, causing ionic toxicity, and metabolic and physiological changes. The aim of the present study was to examine the effect of polyamine precursors, besides the effect of some antioxidants such as glutathione and ascorbate on growth, metabolism, and productivity of two barley cultivars, different in salt tolerance, when subjected to salt stress. Methods: Salt-tolerant G124 and salt-sensitive G119 barley cultivars had their seeds planted in plastic pots with clay and sand soil that measured 10 cm in diameter and 4 cm in height (2:1). The pots were divided into five categories: the grains were presoaked for 24 hours in distilled water, an amino acid solution (Arginine, Methionine, and Ornithine) (1 mM each), glutathione, or ascorbic acid (0.1 mM for each), seedlings were cultivated in 0.1 mM sodium chloride alone, seedlings were cultivated using a combination of salt and glutathione, seedlings were grown using a combination of salt and ascorbic acid, seedlings were cultivated using a combination of salt and amino acid mixture. Results: Salinity has resulted in a reduction in all growth parameters in both barley cultivars. In the seedling, pre-flowering, and yield stages, the exposure to salt decreased photosynthetic pigments, total soluble carbohydrates, weight, and the number of grains, whereas it showed an increase in the activities of catalase and peroxidase, proline content, malondialdehyde, and membrane leakage. Conclusion: The addition of glutathione, ascorbic acid, or amino acid mixture alleviated the harmful effect of sodium chloride and improved barley's defense mechanism against salt stress. The results showed that the alleviating effect was eventually reflected in plant growth, indicating that glutathione might be suggested as an effective treatment to reduce the impacts of salinity on barley.
Outcomes of out-of-hospital cardiac arrest in Ireland 2012-2020: Protocol for an observational study
Authors: Barry Tomás , Kasemiire Alice , Quinn Martin , Deasy Conor , Bury Gerard , Masterson Siobhan , Segurado Ricardo , Murphy Andrew ,   Out-of-Hospital Cardiac Arrest Registry Steering Group
Published: March 2023

Background Out-of-hospital cardiac arrest (OHCA) is a leading cause of preventable mortality that now affects almost 3,000 people each year in Ireland. Survival is low at 6-7%, compared to a European average of 8%. The Irish Out-of-Hospital Cardiac Registry (OHCAR) prospectively gathers data on all OHCA in Ireland where emergency medical services attempted resuscitation. The Irish health system has undergone several developments that are relevant to OHCA care in the period 2012-2020. OHCAR data provides a means of exploring temporal trends in OHCA incidence, care, and outcomes over time. It also provides a means of exploring whether system developments were associated with a change in key outcomes. This research aims to summarise key trends in available OHCAR data from the period 2012 – 2020, to explore and model predictors of bystander CPR, bystander defibrillation, and survival, and to explore the hypothesis that significant system level temporal developments were associated with improvements in these outcomes. Methods The following protocol sets out the relevant background and research approach for an observational study that will address the above aims. Key trends in available OHCAR data (2012 – 2020) will be described and evaluated using descriptive summaries and graphical displays. Multivariable logistic regression will be used to model predictors of ‘bystander CPR’, ‘bystander defibrillation’ and ‘survival to hospital discharge’ and to explore the effects (if any) of system level developments in 2015/2016 and the COVID-19 pandemic (2020) on these outcomes. Discussion The findings of this research will be used to understand temporal trends in the care processes and outcomes for OHCA in Ireland over the period 2012-2020. The results can further be used to optimise future health system developments for Out-of-Hospital Cardiac Arrest in both Ireland and internationally.
Dynamic Pricing with Uncertain Capacities
Authors: Garcia Daniel , Janssen Maarten C. W. , Shopova Radostina 
Published: March 2023

In markets, such as those for airline tickets and hotel accommodations, firms sell time-dated products and have private information about unsold capacities. We show that competition under private information may explain observed phenomena, such as increased price dispersion and higher expected prices toward the deadline. We also show that private information severely limits the market power of firms and that information exchange about capacity increases firms’ profits. Finally, we inquire into the incentives to unilaterally disclose information or to engage in espionage about rival’s capacity and show that they increase firms’ profits compared with the private information setting. This paper was accepted by Omar Besbes, revenue management and market analytics. Funding: This work was partially funded by the Austrian Science Foundation FWF under [Project FG 6]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.4613 .
The (Limited) Power of Blockchain Networks for Information Provision
Authors: Franke Benedikt , Fritz Qi Gao , Stenzel André 
Published: March 2023

We investigate the potential and limits of privacy-preserving corporate blockchain applications for information provision. We provide a theoretical model in which heterogeneous firms choose between adopting a blockchain application or relying on traditional third-party intermediaries to inform the capital market. The blockchain’s ability to generate information depends on each firm’s data profile and all firms’ endogenous adoption decisions. We show that blockchain technology can improve the information environment and outperform traditional institutions with firms’ adoption decisions serving as a credible value signal and the application uncovering firm values by analyzing all participating firms’ data. However, we also characterize an adverse mixed-adoption equilibrium in which neither of the two channels realizes its full potential and information provision declines not only for individual firms, but also in aggregate. The equilibrium is a warning sign that has broad implications for policymakers’ regulatory effort and investors’ assessment of corporate blockchain applications. This paper was accepted by Suraj Srinivasan, accounting. Funding: B. Franke and Q. Gao Fritz gratefully acknowledge financial support from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) Project-ID 403041268–TRR 266 Accounting for Transparency. A. Stenzel gratefully acknowledges financial support from the DFG through CRC TR 224 (Project C03) during prior employment at the University of Mannheim. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4718 .
No Permanent Friend or Enemy: Impacts of the IIoT-Based Platform in the Maintenance Service Market
Authors: Pei Jun , Yan Ping , Kumar Subodha 
Published: March 2023

As the industrial Internet-of-things (IIoT) is becoming increasingly valuable, manufacturers are eager to establish IIoT-based platforms for preventative maintenance (PM). These platforms reposition the roles of manufacturers and reshape the patterns of the after-sales service market. Manufacturers can adopt either the competitive strategy by introducing improved after-sales services to compete with independent maintenance, repair, and operations firms (MROs) or the “coopetitive” strategy by simultaneously opening the platform to these MROs. However, relevant research on this topic remains scarce. Hence, our study fills this gap by investigating a manufacturer’s decision for the IIoT-based platform and the subsequent relationship with an MRO. First, we find that even when the product value is relatively low and the IIoT adoption increases PM cost; interestingly, it is sometimes beneficial for the manufacturer to establish the platform. Next, we find that even if the royalty revenue is lower than the increased IIoT costs, the manufacturer may sometimes still adopt the coopetitive strategy of opening the platform. Moreover, with the opening of the platform, the manufacturer pays more technology investment, even in the competitive market. Furthermore, whenever the manufacturer opens the platform, the MRO can profit more by accessing the platform. Hence, there is sometimes a win-win equilibrium with the IIoT adoption. In addition, we find that the opening of the platform sometimes causes less customer surplus but generates more social welfare. Following the IIoT adoption, our findings offer insightful takeaways for the manufacturer’s decisions on the establishment and opening of the platform, the MRO’s reaction, and policymakers’ welfare policies. This paper was accepted by Jeannette Song, operations management. Funding: This work was supported by the National Natural Science Foundation of China [Grants 71922009, 72188101, 71871080, and 72071057]. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4733 .
Market Segmentation Trees
Authors: Aouad Ali , Elmachtoub Adam N. , Ferreira Kris J. , McNellis Ryan 
Published: March 2023

Problem definition: We seek to provide an interpretable framework for segmenting users in a population for personalized decision making. Methodology/results: We propose a general methodology, market segmentation trees (MSTs), for learning market segmentations explicitly driven by identifying differences in user response patterns. To demonstrate the versatility of our methodology, we design two new specialized MST algorithms: (i) choice model trees (CMTs), which can be used to predict a user’s choice amongst multiple options, and (ii) isotonic regression trees (IRTs), which can be used to solve the bid landscape forecasting problem. We provide a theoretical analysis of the asymptotic running times of our algorithmic methods, which validates their computational tractability on large data sets. We also provide a customizable, open-source code base for training MSTs in Python that uses several strategies for scalability, including parallel processing and warm starts. Finally, we assess the practical performance of MSTs on several synthetic and real-world data sets, showing that our method reliably finds market segmentations that accurately model response behavior. Managerial implications: The standard approach to conduct market segmentation for personalized decision making is to first perform market segmentation by clustering users according to similarities in their contextual features and then fit a “response model” to each segment to model how users respond to decisions. However, this approach may not be ideal if the contextual features prominent in distinguishing clusters are not key drivers of response behavior. Our approach addresses this issue by integrating market segmentation and response modeling, which consistently leads to improvements in response prediction accuracy, thereby aiding personalization. We find that such an integrated approach can be computationally tractable and effective even on large-scale data sets. Moreover, MSTs are interpretable because the market segments can easily be described by a decision tree and often require only a fraction of the number of market segments generated by traditional approaches. Disclaimer: This work was done prior to Ryan McNellis joining Amazon. Funding: This work was supported by the National Science Foundation [Grants CMMI-1763000 and CMMI-1944428]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2023.1195 .
Real-time emotion detection by quantitative facial motion analysis
Authors: Saadon Jordan R. , Yang Fan , Burgert Ryan , Mohammad Selma , Gammel Theresa , Sepe Michael , Rafailovich Miriam , Mikell Charles B. , Polak Pawel , Mofakham Sima 
Published: March 2023

Background
Research into mood and emotion has often depended on slow and subjective self-report, highlighting a need for rapid, accurate, and objective assessment tools.

Methods
To address this gap, we developed a method using digital image speckle correlation (DISC), which tracks subtle changes in facial expressions invisible to the naked eye, to assess emotions in real-time. We presented ten participants with visual stimuli triggering neutral, happy, and sad emotions and quantified their associated facial responses via detailed DISC analysis.

Results
We identified key alterations in facial expression (facial maps) that reliably signal changes in mood state across all individuals based on these data. Furthermore, principal component analysis of these facial maps identified regions associated with happy and sad emotions. Compared with commercial deep learning solutions that use individual images to detect facial expressions and classify emotions, such as Amazon Rekognition, our DISC-based classifiers utilize frame-to-frame changes. Our data show that DISC-based classifiers deliver substantially better predictions, and they are inherently free of racial or gender bias.

Limitations
Our sample size was limited, and participants were aware their faces were recorded on video. Despite this, our results remained consistent across individuals.

Conclusions
We demonstrate that DISC-based facial analysis can be used to reliably identify an individual’s emotion and may provide a robust and economic modality for real-time, noninvasive clinical monitoring in the future.