bluuebunny/crossref_metadata_2025_split huggingface dataset:
High pre-chemoradiotherapy pan-immune-inflammation value levels predict worse outcomes in patients with stage IIIB/C non-small-cell lung cancer
Authors: Topkan Erkan , Kucuk Ahmet , Ozkan Emine Elif , Ozturk Duriye , Besen Ali Ayberk , Mertsoylu Huseyin , Pehlivan Berrin , Selek Ugur 
Published: December 2023

Abstract
Background and objectives
We explored the prognostic usefulness of the pan-immune-inflammation value (PIV) in patients with stage IIIB/C non-small-cell lung cancer (NSCLC) who underwent concurrent chemoradiotherapy (CCRT).

Methods and patients
For all patients, the PIV was calculated using platelet (P), monocyte (M), neutrophil (N), and lymphocyte (L) measures obtained on the first day of CCRT: PIV = P × M × N ÷ L. Using receiver operating characteristic (ROC) curve analysis, we searched for the existence of an ideal cutoff that may partition patients into two groups with unique progression-free- (PFS) and overall survival (OS) results. The primary endpoint of this retrospective cohort research was to determine whether there were any significant relationships between pretreatment PIV measures and post-CCRT OS outcomes.

Results
The present research included a total of 807 stage IIIB/C NSCLC patients. According to ROC curve analysis, the ideal PIV cutoff was 516 [area under the curve (AUC): 67.7%; sensitivity: 66.4%; specificity: 66.1%], which divided the whole cohort into two: low PIV (L-PIV: PIV < 516; N = 436) and high PIV (H-PIV: PIV ≥ 516; N = 371). The comparisons between the PIV groups indicated that either the median PFS (9.2 vs. 13.4 months; P < 0.001) or OS (16.7 vs. 32.7 months; P < 0.001) durations in the H-PIV group were substantially inferior to their L-PIV counterpart. Apart from the H-PIV (P < 0.001), the N3 nodal stage (P = 0.006), IIIC disease stage (P < 0.001), and receiving only one cycle of concurrent chemotherapy (P = 0.005) were also determined to be significant predictors of poor PFS (P < 0.05, for each) and OS (P < 0.05, for each) outcomes in univariate analysis. The multivariate analysis findings revealed that all four variables had independent negative impacts on PFS (P < 0.05, for each) and OS (P < 0.05, for each).

Conclusions
The findings of this hypothesis-generating retrospective analysis claimed that the novel PIV was an independent and steadfast predictor of PFS and OS in stage IIIB/C NSCLC patients.
Biomass and bioenergy potentials of bioresidues: assessment methodology development and application to the region of Lafões
Authors: d’Espiney Ana , Pinheiro Helena M. , Marques Isabel P. , Kretzschmar Jörg , Cyffka Karl-Friedrich , Thrän Daniela 
Published: December 2023

AbstractBioenergy research aims to uncover the potentials of biological residues. Regional-specific characterization of such potentials is needed to improve the use of local resources, decisions on bioenergy conversion routes, and services within global efforts against climate change. The definition and calculation of the theoretical and technical biomass and bioenergy potentials are keys for developing sustainable use pathways at a regional level. The present work develops a methodology where theoretical framework, quantification methods, and values for the necessary parameters, to assess regional biomass and bioenergy potentials, are considered. The region of Lafões (Portugal) is the case study to illustrate the application of the methods, resulting in three bioresidue categories (agricultural by-products, forestry residues, and municipal waste) and two bioenergy conversion routes (biochemical and thermochemical). The biochemical conversion route revealed a technical energy potential of 765 TJ yr−1, comparing favourably with the 543 TJ yr−1 achieved by the thermochemical route. Also, the environmental and economic performances, associated with the implementation of bioenergy technologies, are possibly better achieved through the biochemical route, to be assessed through life cycle analyses and life cycle costing. Regardless of action priorities, the two conversion routes combined can potentially cover the entire current electrical energy demand of the region. This should also be appraised with expectations in mind for both flexible bioenergy services (with other renewables) and for bioenergy usage in applications which are difficult to defossilize.
Sensitivity of turbulence parameters to tidal energy converter loads in BEM simulations
Authors: Naberezhnykh Alyona , Ingram David , Ashton Ian , Miller Calum 
Published: December 2023

AbstractRenewable energy is playing an increasingly central role in the global energy supply due to decarbonisation and energy security aims. A vital aspect of renewable energy systems will be the predictability of the energy source, something that tidal stream energy can provide. The tidal sites suitable for energy extraction are by their nature turbulent, creating variations in the tidal energy converter (TEC) loads and affecting device durability. Developers use Blade Element Momentum (BEM) models to predict loading and improve designs of TECs. To simulate turbulence effects within these models, a synthetic flow field is generated using a combination of measured and assumed parameters. Inaccuracies in these parameters can lead to uncertainties in the simulated loads. This study investigates the sensitivity of turbulence characteristics to loads using a commercial BEM software. Variability in parameters shows a profound impact on the loads. Varying turbulence intensity resulted in a $$90\%$$

90
%

change in fatigue loads for intensities ranging 2–24%. Length-scales showed a $$49\%$$

49
%

decrease in loads across the range tested (5–70 m). A coherent flow field increased loads by $$45\%$$

45
%

compared to a non-coherent flow. Hub-bending loads varied by $$30\%$$

30
%

between different shear profiles, however varying the standard deviation profiles did not show notable effects. The results from this study emphasise the necessity for accurate turbulence parameter inputs to reduce uncertainty in device load modelling. It also highlights the importance of using realistic shear profiles as well as appropriate coherence models.
Low Temperature Leaching Behavior of Allanite-(Ce) in Treating an Allanite-Concentrate by Sulfuric Acid
Authors: Kärenlampi Kimmo , Väänänen Emilia , Roivainen Tuomas , Perämäki Paavo 
Published: December 2023

AbstractAllanite is a common REE-bearing silicate mineral, which is found in potentially mineable abundances in many areas but has not been economically exploited for the REEs in an industrial scale. Conventional methods, such as sulfuric acid baking at high temperatures (200 to 650 °C) followed by extended water leaching near boiling temperature, have proven effective in decomposing allanite but come with substantial economic and environmental drawbacks. This study presents an alternative approach, investigating the dissolution behavior of allanite at low temperatures through direct treatment of an allanite concentrate with sulfuric acid. Through parametric optimization, the study reveals the practical and selective dissolution of allanite from a relatively coarse concentrate sample (particle size distribution D50 = 327 µm) after a 3-h leaching period with a mild dilute (2 M) H2SO4 solution at 22 °C, yielding overall recoveries of approximately 80% for light REEs and 60% for heavy REEs. The dissolved gangue elements, predominantly derived from allanite (e.g., Th, Fe, Al, Si, and Ca), exhibit contents in the leach solution comparable to or slightly higher than those reported in other studies utilizing acid bake–water leach processes. The notable efficiency of low-temperature sulfuric acid extraction is likely attributed to the heightened chemical reactivity of metamict allanite-(Ce) within the investigated concentrate. While these results are encouraging and demonstrate the potential of low-temperature leaching for allanite concentrates, additional research is necessary before testing the procedure on a larger scale.
Graphical Abstract
The Hodgepodge Reality: A Qualitative Systematic Review of the Challenges and Barriers in Child and Adolescent Mental Health Care Systems
Authors: Carbonell Ángela , Georgieva Sylvia , Navarro-Pérez José-Javier , Prades-Caballero Virginia 
Published: December 2023

AbstractThe literature to date has documented the presence of challenges and barriers in mental health systems and services for children and adolescents worldwide. However, studies addressing this reality often do so in a fragmented, residual, incomplete, or generalized way, therefore hindering a comprehensive understanding of this complex phenomenon. The aim of this qualitative systematic review is to analyze the barriers and challenges affecting global mental health care for children and adolescents. Searches were made in the Web of Science, Scopus, and PubMed databases between 2018 and 2022 using terms connected with mental health, childhood, adolescence, and health systems. The search resulted in the extraction of 9075 articles, of which 51 were considered eligible for inclusion and complied with quality indicators. A number of closely related structural, financial, attitudinal, and treatment barriers that limited the quality of life and well-being of children and adolescents with mental health needs were found. These barriers included inadequate public policies, operational deficiencies, insufficient insurance coverage, privatization of services, stigma, lack of mental health literacy, lack of training, overburdened care, dehumanization of care, and lack of community and integrated resources. The analysis of these barriers displays that this treatment gap reflects the historical injustice towards mental illness and the disregard for real needs in these crucial stages, perpetuating a systematic lack of protection for the mental health of children and adolescents. The complexity of the disorders and the absence of public resources have resulted in a hodgepodge of mental health services for children and adolescents that fails to provide the continuing specialist health care they need.
Eisenstein series, p-adic modular functions, and overconvergence, II
Authors: Kiming Ian , Rustom Nadim 
Published: December 2023

AbstractLet p be a prime number. Continuing and extending our previous paper with the same title, we prove explicit rates of overconvergence for modular functions of the form $$\frac{E^*_k}{V(E^*_k)}$$

E
k
∗

V
(

E
k
∗

)

where $$E^*_k$$

E
k
∗

is a classical, normalized Eisenstein series on $$\Gamma _0(p)$$

Γ
0

(
p
)

and V the p-adic Frobenius operator. In particular, we extend our previous paper to the primes 2 and 3. For these primes our main theorem improves somewhat upon earlier results by Emerton, Buzzard and Kilford, and Roe. We include a detailed discussion of those earlier results as seen from our perspective. We also give some improvements to our earlier paper for primes $$p\ge 5$$

p
≥
5

. Apart from establishing these improvements, our main purpose here is also to show that all of these results can be obtained by a uniform method, i.e., a method where the main points in the argumentation is the same for all primes. We illustrate the results by some numerical examples.
Sweety, salty, sour, and romantic biochar-supported ZnO: highly active composite catalysts for environmental remediation
Authors: Bhakta Arvind K. , Tang Mengqi , Snoussi Youssef , Khalil Ahmed M. , Mascarenhas Ronald J. , Mekhalif Zineb , Abderrabba Manef , Ammar Souad , Chehimi Mohamed M. 
Published: December 2023

AbstractThe present work focuses on valorizing the various biochar supports of nano-catalysts and investigates the effect of the type of the initial biomass on the deposition and salient physico-chemical features of the zinc oxide (ZnO) nanoparticles. In this regard, we have used four different biomasses, namely, sugarcane bagasse (Saccharum officinarum), algae (Phaeophyta), mandarin orange peels (Citrus reticulata), and China rose petals (Rosa chinensis) as sources of biochar. Their wet impregnation with zinc acetate was followed by pyrolysis at 500 °C. It led to biochar (nicknamed “sweety,” “salty,” “sour,” and “romantic” biochar, respectively) loaded with very well dispersed, 20–360 nm-sized (mostly) ZnO nanoparticles. Interestingly, depending on the type of biomass used, the size, shape (quartz-like, semi-spherical, spherical, semi-cauliflower, needle or rod-like), and degree of crystallinity of ZnO nanoparticles (hexagonal crystal system) vary, in spite of all other synthesis parameters being similar. Nanoparticle-induced graphitization and crystallization of biochar have been also observed by Raman spectroscopy. The malachite green dye mineralization efficiency in the presence of H2O2 and different biochar-supported ZnO nanocatalysts was 15.1%, 46.3%, 99.9%, 67.9%, and 66.4% for H2O2, china rose petals, algae, mandarin peels, and sugarcane bagasse-supported ZnO catalyst in the presence of H2O2, respectively. Malachite green removal fits in very well with a pseudo-first-order kinetic model with R2 = 0.9701 (at algae biochar-ZnO). 6.6 times enhancement in the mineralization efficiency is observed as compared to just H2O2. The recyclability test of algae biochar impregnated with ZnO after 5 cycles indicates the mineralization efficiency levels up to 81.4%. Beyond these scientific results, this work is based on the principle of biomass waste valorization for sustainable development and circular economy, on the one hand, and addresses the UN Sustainable Development Goals 6, 13, and 14, on the other hand. It is also very clear that biochar is the new romance in the field of materials science and for sustainable future.
Graphical Abstract
Artificial intelligence and sustainability in the fashion industry: a review from 2010 to 2022
Authors: Ramos Leo , Rivas-Echeverría Francklin , Pérez Anna Gabriela , Casas Edmundo 
Published: December 2023

AbstractThe fashion industry often falls short of sustainability goals, but contemporary technological advancements offer a wide range of tools to address this issue. Artificial Intelligence (AI) has emerged as a particularly promising ally in promoting sustainability in fashion. This literature review explores how AI can contribute to the fashion industry’s sustainability, highlighting its potential benefits and limitations. Following PRISMA guidelines, we conducted a review of scientific documents, focusing on the period from 2010 to 2022. After a meticulous selection process, we analyzed 37 scholarly articles to distill their key insights and contributions. Our findings demonstrate that AI has diverse applications in different aspects of the fashion industry, enhancing sustainability efforts in supply chain management, creative design, sales and promotion, waste control, and data analysis. While AI offers significant potential, it is important to acknowledge limitations, such as the volume of data required and associated implementation costs. The reviewed literature aligns with the multifaceted nature of sustainability, emphasizing responsible resource management, accessible services, and efficient customer satisfaction, both now and in the future. In conclusion, despite some reservations, AI stands as a crucial partner in guiding the fashion industry toward a more sustainable future.
Fast Processing of Bending Deflection for Euler–Bernoulli Beam Under Different Boundary Constraints Based on a Semi-Analytical Null Space Method
Authors: Luo W. J. , Liu T. Y. , Chai T. J. , Yan J. W. , Guo W. J. 
Published: December 2023

AbstractIn this paper, a semi-analytical method called null space method is proposed to realize fast processing of bending deflection for Euler–Bernoulli beam among various types of boundary constraints. The null space method employs a basis function such as trigonometric function with unknown weight coefficients to approximate the field function. The unknown weight coefficients can be independently solved by the boundary constraint matrix, thus this method can easily keep away from the high demanding of field function to match the given boundary constraint and fastly switch among various types of boundary constraints. The effect of basis function on the final results are first confirmed as compared with the analytical solutions, and the null space method is then applied to predict the settlement of the existing tunnel due to new shield tunneling. The calculated results by null space method gives a good prediction of FEM and in-situ test results.
A Stable Time-Dependent Mesh Method for Generalized Credit Rating Migration Problem
Authors: Sultan Saad , Zhang Zhengce 
Published: December 2023

AbstractThe r-adaptive difference scheme is advanced in this article for solving the generalized credit rating migration model for arbitrary volatility with multiple terminal conditions. The r-adaptive moving mesh method defines the coordinate mapping from the physical to the computational domain and then uses piece-wise polynomials to approximate the physical coordinates. The central implicit semi-discretization scheme is imposed on space, and the backward Euler time marching scheme, coupled with several moving mesh partial differential equations, is used to achieve the numerical solution. The numerical operations are performed with several examples, and the obtained results are sufficiently accurate. The convergence of the proposed scheme is second-order, which is verified with the analysis. The article also investigates the stability and convergence of the adaptive mesh discretization scheme, which are not available in the literature; the convergence of the scheme is second-order in space and first-order in time.
A novel heuristic method for detecting overfit in unsupervised classification of climate model data
Authors: Boland Emma J. D. , Atkinson Erin , Jones Dani C. 
Published: December 2023

Abstract
Unsupervised classification is becoming an increasingly common method to objectively identify coherent structures within both observed and modelled climate data. However, in most applications using this method, the user must choose the number of classes into which the data are to be sorted in advance. Typically, a combination of statistical methods and expertise is used to choose the appropriate number of classes for a given study; however, it may not be possible to identify a single “optimal” number of classes. In this work, we present a heuristic method, the ensemble difference criterion, for unambiguously determining the maximum number of classes supported by model data ensembles. This method requires robustness in the class definition between simulated ensembles of the system of interest. For demonstration, we apply this to the clustering of Southern Ocean potential temperatures in a CMIP6 climate model, and show that the data supports between four and seven classes of a Gaussian mixture model.
Regulating Gatekeeper Artificial Intelligence and Data: Transparency, Access and Fairness under the Digital Markets Act, the General Data Protection Regulation and Beyond
Authors: Hacker Philipp , Cordes Johann , Rochon Janina 
Published: December 2023

AbstractArtificial intelligence (AI) is not only increasingly being used in business and administration contexts, but a race for its regulation is also underway, with the European Union (EU) spearheading the efforts. Contrary to existing literature, this article suggests that the most far-reaching and effective EU rules for AI applications in the digital economy will not be contained in the proposed AI Act, but in the Digital Markets Act (DMA). We analyse the impact of the DMA and related EU acts on AI models and underlying data across four key areas: disclosure requirements; the regulation of AI training data; access rules; and the regime for fair rankings. We demonstrate that fairness, under the DMA, goes beyond traditionally protected categories of non-discrimination law on which scholarship at the intersection of AI and law has focused on. Rather, we draw on competition law and the FRAND criteria known from intellectual property law to interpret and refine the DMA provisions on fair rankings. Moreover, we show how, based on Court of Justice of the European Union jurisprudence, a coherent interpretation of the concept of non-discrimination in both traditional non-discrimination and competition law may be found. The final section sketches out proposals for a comprehensive framework of transparency, access and fairness under the DMA and beyond.
A Class of Their Own: Newspaper Obituaries and the Colonial Public Sphere in Lagos, 1880–1920
Authors: Nwafor Okechukwu 
Published: December 2023

AbstractFrom the 1880s, obituaries of Africans and European colonial officials became a frequent genre in Lagos newspapers. This article examines obituary notices in seven Lagos newspapers to understand how print publications and the next of kin who commissioned obituaries used commemorative practices to frame colonial relations and reflect on imperial expansion. Revisiting Jürgen Habermas’s notion of the public sphere, I argue that colonial newspapers introduced gossipy anecdotes and sensationalism in obituary notices to define the colonial “public sphere” as one that is characterized by insinuations of social and economic class, Christian rhetoric, racial divides and anti-colonial sentiments as well as civic responsibilities around public health concerns.
Legally Recognizing Reproductive Coercion while Questioning Sexual Violence Exceptionalism
Authors: Stoever Jane 
Published: December 2023

AbstractWhile sexual violence should not be the prerequisite for legal abortion, expanding definitions of abuse to include reproductive coercion can open avenues of access to abortion following the Dobbs decision. Understanding the increased danger and compounding challenges of intimate partner violence can inform legislative initiatives, healthcare responses, and movements for reproductive justice.
Supreme Court Impacts in Public Health Law: 2022-2023
Authors: Hodge James G. , Barraza Leila , Piatt Jennifer L. , White Erica N. , Ghaith Summer , Hollinshead Samantha , Krumholz Lauren , Puchebner Madisyn , Smith Emma 
Published: December 2023

AbstractIn another tumultuous term of the United States Supreme Court in 2022-2023 a series of critical cases implicate instant and forthcoming changes in multiple fronts that collectively shift the national public health law and policy environment.
Harvey and Gurvir’s Law: Ontario Bill for Quality Prenatal Information about Down Syndrome: Terminology, Feasibility, and Ethical Issues
Authors: Lemoine Marie-Eve , Laberge Anne-Marie , Malo Marie-Françoise , Cloutier Stéphanie , Roy Marie-Christine , Birko Stanislav , Daigle Andréa , Ravitsky Vardit 
Published: December 2023

AbstractHarvey and Gurvir’s Law is a bill proposed to the Legislative Assembly of Ontario (Canada) to reduce stigma and bias associated with Down syndrome, by developing and disseminating quality information about Down syndrome in the context of prenatal testing.
From Constitutional Protections to Medical Ethics: The Future of Pregnant Patients’ Medical Self-Determination Rights After Dobbs
Authors: Sawicki Nadia N. , Kukura Elizabeth 
Published: December 2023

AbstractThis article argues that the Supreme Court’s decision in Dobbs is likely to impact medical decision-making by pregnant patients in a variety of contexts. Of particular concern are situations where a patient declines treatment recommended for its potential benefit to the fetus and situations where treatment is withheld due to potential risk to the fetus. The Court’s elevation of fetal interests, combined with a history of courts using abortion jurisprudence to guide their reasoning in compelled treatment cases, means that Dobbs has the potential to limit patient autonomy in a wide array of clinical settings. The article calls on professional medical associations to issue ethical guidance affirming the duty to respect the medical self-determination of pregnant patients.