bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic Mechanical Spectroscopy with Cylindrical Geometry: Application to the Comparison of Various Plasticizers of Thermoplastic Starch
Authors: Basson Jonathan , Carrot Christian , Chalamet Yvan , Mignard Nathalie 
Published: August 2024

AbstractDynamic mechanical spectroscopy is a common analysis for polymers. Rectangular specimens are usually used for measurement in the solid state due to their easy designing. However, in reason of the non‐symmetric shape of sample, rectangular specimens do not experience linear stress on their all body, leading to overestimation of shear modulus. Corrections are required to determine the right shear modulus. In this present work, straight shear modulus determination is carried out using specimens with a cylindrical shape. The reliability of the technique is described on a biosourced polymer materials made of thermoplastic starch, plasticized by glycerol, choline chloride/urea mixture (ChCl/U), 1‐ethyl‐3‐methylimidazolium chloride ([EMIM]Cl) and 1‐ethyl‐3‐imidazolium acetate ([EMIM]Ac). The technique is shown to be particularly interesting to avoid any additional shaping of the specimens prior to measurements, that can be detrimental to their properties (evaporation, degradation). A comparison between cylinder and rectangular specimen has also been made to illustrate the interest of cylinder clamping on biosourced polymer material.
Mega‐influencers and brand dynamics: Shaping attitudes toward leading and challenger brands through electronic word of mouth
Authors: Rialti Riccardo , Zollo Lamberto , Kim Kacy , Yoon Sukki 
Published: August 2024

AbstractThe aim of this paper is to explore how mega‐influencers' electronic word of mouth (eWOM) messages on social media influence consumers' brand attitudes in duopolistic markets. Through three experimental studies, we observe that when mega‐influencers send positive (vs. negative) eWOM messages about a leading brand, followers form positive (vs. negative) brand attitudes, but these effects fail to occur when influencers back challenger brands. The findings are consistent across three duopolistic market rivals (Apple vs. Samsung; UPS vs. FedEx; Nike vs. Adidas), three social media platforms (Facebook, Instagram, and X), and four mega‐influencers (Marques Brownlee, Gary Vaynerchuk, Kanye West, and Kylie Jenner). Findings indicate that mega‐influencers have more persuasive power when recommending or criticizing leading brands rather than challenger brands, irrespective of their follower base. The findings contribute to the marketing literature by showing that in duopolistic market contexts, mega‐influencers' e‐WOM has varied effects on followers' brand attitudes, depending on brand status in the market.
A generalized signal model for dual‐module velocity‐selective arterial spin labeling
Authors: Liu Thomas T. , Chen Conan , Guo Jia , Wong Eric C. , Bolar Divya S. 
Published: August 2024

AbstractPurposeTo develop a generalized signal model for dual‐module velocity‐selective arterial spin labeling (dm‐VSASL) that can integrate arbitrary saturation and inversion profiles.Theory and MethodsA recently developed mathematical framework for single‐module VSASL is extended to address the increased complexity of dm‐VSASL and to model the use of realistic velocity‐selective profiles in the label‐control and vascular crushing modules. Expressions for magnetization difference, arterial delivery functions, labeling efficiency, and cerebral blood flow (CBF) estimation error are presented. Sources of error are examined and timing requirements to minimize quantification errors are derived.ResultsFor ideal velocity‐selective profiles, the predicted signals match those of prior work. With realistic profiles, a CBF‐dependent estimation error can occur when velocity‐selective inversion (VSI) is used for the labeling modules and velocity‐selective saturation (VSS) is used for the vascular crushing module. The error reflects a mismatch between the leading and trailing edges of the delivery function for the second bolus and can be minimized by choosing a nominal labeling cutoff velocity that is lower than the nominal saturation cutoff velocity. In the presence of and inhomogeneities, the labeling efficiency of dual‐module VSI is more attenuated than that of dual‐module VSS.ConclusionThe proposed signal model will enable researchers to more accurately assess and compare the performance of realistic dm‐VSASL implementations and improve the quantification of dm‐VSASL CBF measures.
A human brain atlas of χ‐separation for normative iron and myelin distributions
Authors: Min Kyeongseon , Sohn Beomseok , Kim Woo Jung , Park Chae Jung , Song Soohwa , Shin Dong Hoon , Chang Kyung Won , Shin Na‐Young , Kim Minjun , Shin Hyeong‐Geol , Lee Phil Hyu , Lee Jongho 
Published: August 2024

AbstractIron and myelin are primary susceptibility sources in the human brain. These substances are essential for a healthy brain, and their abnormalities are often related to various neurological disorders. Recently, an advanced susceptibility mapping technique, which is referred to as χ‐separation (pronounced as “chi”‐separation), has been proposed, successfully disentangling paramagnetic iron from diamagnetic myelin. This method provided a new opportunity for generating high‐resolution iron and myelin maps of the brain. Utilizing this technique, this study constructs a normative χ‐separation atlas from 106 healthy human brains. The resulting atlas provides detailed anatomical structures associated with the distributions of iron and myelin, clearly delineating subcortical nuclei, thalamic nuclei, and white matter fiber bundles. Additionally, susceptibility values in a number of regions of interest are reported along with age‐dependent changes. This atlas may have direct applications such as localization of subcortical structures for deep brain stimulation or high‐intensity focused ultrasound and also serve as a valuable resource for future research.
Multiple ways to bend the curve of biodiversity loss: An analytical framework to support transformative change
Authors: Mehring Marion , Brietzke Anna S. , Kleemann Janina , Knauß Stefan , Poßer Christian , Schreiner Vera , Wittmer Heidi , Albert Christian , Fürst Christine , Grunewald Karsten , Kolkmann Michael , Lettenmaier Ludwig , Sanders Tanja G. M. , Schleyer Christian , Settele Josef , Straka Tanja M. , Hauck Jennifer 
Published: August 2024

Abstract

Humans are significantly impacting ecosystems worldwide. Scientists of the IPBES Global Assessment are therefore calling for a transformative change that includes all aspects of society in order to address drivers of biodiversity loss. However, these calls are rather abstract, and thus it remains unclear how this goal can be achieved.

With this conceptual contribution, we present an analytical framework for evaluating existing processes of societal change which are enhancing biodiversity, and we illustrate its application using three case studies in Germany. We argue that an empirical analysis provides insights into the causal mechanisms that initiate or promote change processes. In doing so, we can draw recommendations for future transformative change processes with regard to biodiversity conservation. In our analysis, we are dealing with questions concerning the following three areas: the drivers and context of societal change processes, the change processes themselves and finally their impacts.

Subsequently, we generate recommendations on how to enhance and support the process of future societal transformation that aims at biodiversity conservation: (a) Retaining co‐benefits for biodiversity with goals that are primarily focussing on other objectives; (b) harmonising biodiversity use and conservation by turning conflicts into drivers of transformation; (c) prioritising biodiversity conservation by taking advantage of windows of opportunity.

With our conceptual framework, we provide an analytical tool to learn from existing processes of societal change how to support future transformative change. This is an important step that contributes to the generation of relevant knowledge of promoting transformative change for nature and people.

Read the free Plain Language Summary for this article on the Journal blog.
Structural Classification Insights Into the Plant Defensive Peptides
Authors: Setyawati Inda , Husaini Ahmad Fadhlullah , Setiawan Aprijal Ghiyas , Artika I. Made , Ambarsari Laksmi , Nurcholis Waras , Vidilaseris Keni , Kurniatin Popi Asri 
Published: August 2024

ABSTRACTThis study presents a structural phylogenetic analysis of plant defensive peptides, revealing their evolutionary relationships, structural diversification, and functional adaptations. Utilizing a robust dataset comprising both experimental and predicted structures sourced from the RCSB Protein Data Bank and AlphaFold DB, we constructed a detailed phylogenetic tree to elucidate the distinct evolutionary paths of plant defensive peptide families. Our findings showcase the evolutionary intricacies of defensive peptides, highlighting their diversity and the conservation of key structural motifs critical to their antimicrobial or defensive functions. The results also underscore the adaptive significance of defensive peptides in plant evolution, highlighting their roles in responding to ecological pressures and pathogen interactions.
Near‐surface wind profiles from numerical model predictions. Part I: Algorithms and comparisons with wind profile based on Monin–Obukhov similarity theory
Authors: Ma Yimin 
Published: August 2024

AbstractWinds are predicted on the discrete grid of numerical weather and climate models. Winds distribute nonlinearly on the height in the near‐surface layer, and a 10 m wind prediction within the layer is often diagnosed upon the Monin–Obukhov similarity theory flux–profile relationship determined from winds at the lowest grid level, the near‐surface atmospheric stability, and surface properties, which leads to concerns that systemic biases may be introduced to the diagnosed wind. Algorithms are proposed to derive near‐surface wind profiles from the grid‐based numerical model forecasts at multiple model levels under the framework of momentum conservations with an implicit solution, associated with simple logarithmic plus linear interpolation in exceptional exemptional conditions. The diagnosed wind profile coheres to the model prediction at the grid level and exhibits differences from the profile using the conventional scheme in the quasi‐steady thermal stratification and non‐steady transitional conditions, retreating to the same logarithmic profile in the neutral condition.
Can FDG‐PET after neoadjuvant chemotherapy plus nivolumab predict residual disease in non‐small cell lung cancer?
Authors: Iguchi Hideto , Akamatsu Hiroaki , Hirai Yoshimitsu , Nakaya Takahito , Fusamoto Aya , Yata Yumi , Nagai Takahiro , Kitahara Daiki , Takakura Toshiaki , Nishimura Yoshiharu , Yamamoto Nobuyuki 
Published: August 2024

AbstractNeoadjuvant therapy with nivolumab improves event‐free survival (EFS) in patients with resectable non‐small cell lung cancer, and a pathological complete response is a predictor of longer EFS. We assessed metabolic responses using 18F‐fluorodeoxyglucose‐positron emission tomography (FDG‐PET) before and after neoadjuvant treatment to explore its surrogacy for pathological complete response (pCR). We describe three patients with squamous cell lung carcinoma who underwent neoadjuvant therapy with nivolumab plus chemotherapy, followed by surgery. In Cases 1 and 2, preoperative tumour response were PR per RECIST and demonstrated marked metabolic response on FDG‐PET after neoadjuvant therapy, with both resected tumours showing a pCR. On the other hand, Case 3 showed a tumour response before surgery (PR per RECIST), however, the tumour, maintained FDG uptake (19.5 → 15.1), and the resected tumour remained residual cells (RVT, 15%). Thus, reduction of FDG uptake on FDG‐PET can predict the pathological response to neoadjuvant therapy with nivolumab.
F for Fantastic: Fostering Stability and Efficiency in Perovskite Solar Cells via Comb‐Like Perfluoroalkyl‐g‐Polyethylenimine Additive
Authors: Zhang Zilong , Hu Chongzhu , Li Yuheng , Xiong Qiu , Li Tinghao , Wang Can , Li Chi , Liang Lusheng , Zhang Ni , Li Feng , Liu Chunming , Fan Weihang , Lien Shui‐Yang , Gao Peng 
Published: August 2024

AbstractAdditive engineering has emerged as a promising strategy to address the inherent instability challenges of perovskite solar cells (PSCs) in the pursuit of commercial viability. However, achieving multifunctionality using a singular additive remains a considerable challenge. In this study, a novel comb‐like multifunctional perfluoroalkyl‐g‐polyethylenimmonium iodide (FPEI·HI) as additives to the PbI2 precursor solution to facilitate the formation of high‐quality and water‐resistant perovskite films is presented. FPEI·HI establishes robust interactions with both formamidinium iodide (FAI) and PbI2, mediated by hydrogen bonding and Lewis acid‐base interactions. These interactions play a pivotal role in simultaneously passivating negative and positive charged defects within the perovskite structure. Furthermore, the inclusion of perfluoroalkyl chains serves as resilience against moisture intrusion. As a consequence of these effects, a notably high device efficiency of 24.29% is achieved, demonstrating comprehensive improvement in various photovoltaic parameters compared to the control device (22.51%). Notably, unencapsulated devices exhibit remarkable stability in high‐humidity environments, retaining 90% of their initial efficiency even after 2500 h of storage. This work underscores the efficacy of FPEI·HI as a critical enabler for enhancing the stability and efficiency of perovskite solar cells, marking a significant stride toward their commercialization.
The fate of FAIT: Salvaging the Fed's framework
Authors: Beckworth David , Horan Patrick J. 
Published: August 2024

AbstractThe Federal Reserve's transition to a flexible average inflation targeting (FAIT) framework in 2020 has come under intense scrutiny, given its failure to prevent the recent inflation surge. These developments are the result of both a public misunderstanding about how FAIT works and the challenges created by the asymmetric design of the framework. As a result, some observers have called on the Federal Reserve to abandon FAIT and return to its previous framework. This paper, however, argues that FAIT should not be abandoned but improved upon by applying symmetry to its makeup policy and treatment of supply shocks. Doing so would give FAIT the properties of a nominal GDP‐level target. This paper calls this proposed framework FAIT‐N and shows how to operationalize it using a measure called the NGDP gap.
Identifying and validating necroptosis‐associated features to predict clinical outcome and immunotherapy response in patients with glioblastoma
Authors: Yuan Qinghua , Gao Weida , Guo Mian , Liu Bo 
Published: August 2024

AbstractBackgroundNecroptosis is a type of programmed cell death involved in the pathogenesis of cancers. This work developed a prognostic glioblastoma (GBM) model based on necroptosis‐related genes.MethodsRNA‐Seq data were collected from the TCGA database. The “WGCNA” method was used to identify co‐expression modules, based on which GO and KEGG analyses were conducted. A protein–protein interaction (PPI) network was compiled. The number of key prognostic genes was reduced applying COX regression and least absolute shrinkage and selection operator (LASSO) analysis to build a RiskScore model. Differences in immune microenvironments were assessed using CIBERSORT, ESTIMATE, MCP‐count, and TIMER databases. The potential impact of key prognostic genes on GBM was validated by cellular experiments.ResultsGBM patients in the higher necroptosis score group had higher immune scores and worse survival. The Brown module, which was closely related to the necroptosis score, was considered as a key gene module. Three key genes (GZMB, PLAUR, SOCS3) were obtained by performing regression analysis on the five clusters. The RiskScore model was significantly, positively, correlated with necroptosis score. Low‐risk patients could benefit from immunotherapy, while high‐risk patients may be more suitable to take multiple chemotherapy drugs. The nomogram showed strong performance in survival prediction. GZMB, PLAUR, and SOCS3 played key roles in GBM development. Among them, high‐expressed GZMB was related to the invasive and migratory abilities of GBM cells.ConclusionsA genetic signature associated with necroptosis was developed, and we constructed a RiskScore model to provide reference for predicting clinical outcomes and immunotherapy responses of patients with GBM.
Shared molecular signatures between systemic lupus erythematosus and osteoporosis
Authors: Yuan Xin , Zheng Ze‐mao , Lai Weinan 
Published: August 2024

AbstractThis study explores the molecular interplay between systemic lupus erythematosus (SLE) and osteoporosis (OP), aiming to uncover shared gene signatures and pathways for better treatment approaches. Leveraging microarray data from the Gene Expression Omnibus (GEO) database, we employed weighted gene coexpression network analysis to identify coexpression modules in SLE and OP, with subsequent protein–protein interaction analysis clarifying the connections among shared genes. Key genes were pinpointed using CytoHubba and random forest algorithms, validated across independent GEO datasets, and further analyzed through gene set enrichment analysis (GSEA) and immune infiltration studies. We discovered two highly correlated modules in SLE and OP, isolating 30 shared genes and identifying GBP1, SOCS1, IFI16, and XAF1 as central to both conditions. Notably, XAF1 and GBP1 mRNA levels were significantly elevated in the peripheral blood of SLE patients compared with healthy and RA counterparts, underscoring their potential as biomarkers. GSEA and immune infiltration analyses indicated pronounced immune and inflammatory responses, especially in interferon signaling pathways, implicating these core‐shared gene networks in the diseases' pathogenesis. The findings highlight the involvement of GBP1, SOCS1, IFI16, and XAF1 in SLE with concurrent OP and suggest that targeting immune and inflammatory responses, particularly through interferon pathways, may offer therapeutic promise for these intertwined conditions.
Deciphering the role of lipid metabolism and acetylation in osteosarcoma: A comprehensive molecular analysis
Authors: Wen Yong , Zhang Xijiang , Zhang Jin , Lu Zhisheng 
Published: August 2024

AbstractOsteosarcoma, known for its rapid progression and high metastatic potential, poses significant challenges in adolescent oncology. This study delves into the roles of lipid metabolism and acetylation genes in the disease's pathogenesis. Utilizing gene set variation analysis, we examined 14 lipid metabolism‐related pathways in osteosarcoma patients, identifying significant variances in three pathways between metastatic and primary cases. Additionally, differences in four acetylation genes between these groups were observed. A comprehensive analysis pinpointed 62 lipid metabolism‐related genes, with 39 exhibiting significant correlations with acetylation genes, termed lipid metabolism acetylation (LMA) genes. Employing machine learning techniques like Lasso+RSF and GBM, we developed a predictive model for overall survival based on LMA genes. This model, with an average c‐index of 0.771, focuses on three key genes: CYP2C8, PAFAH2, and ACOX3, whose prognostic value was confirmed through survival and receiver operating characteristic curve analyses. Quantitative RT‐PCR results indicated higher expression levels of ACOX3 and PAFAH2 in OS cells (143B, HOS, MG63) than in osteoblasts (hFOB1.19), while CYP2C8 was lower in OS cells. Furthermore, drug sensitivity analysis through the pRRophetic algorithm suggested potential targeted therapies, revealing drugs with differential sensitivity based on LMA scores and varied treatment responses related to the expression of core genes. This study not only highlights the crucial role of lipid metabolism and acetylation in osteosarcoma but also offers a foundation for personalized treatment strategies, marking a notable advancement in combating this severe form of adolescent cancer.
Interview Analysis: Remembering Marielle Franco
Authors: Merian Katharina 
Published: August 2024

AbstractIn the following pages, I will provide an analysis of the meaning of Marielle Franco’s trajectory in the context of Rio de Janeiro and how it was transformed through her assassination. The analysis is grounded in ten interviews done with some of Franco’s ex-staff members and people that accompanied her trajectory closely. The results will be interpreted in Chap. 4, which focuses on the aspect of memory. Interesting details in the data on Marielle Franco that are not central to the question of memory will be commented on in the footnotes of this chapter.
Discussion: Toward a Decolonial Dangerous Memory of Individual and Collective Self-Empowerment
Authors: Merian Katharina 
Published: August 2024

AbstractThis chapter contains a discussion of the results of the data analysis in the previous chapter. In the first part, I will interpret the data from the perspective of Johann Baptist Metz’s concept of dangerous memory. This concept served as the main sensitizing concept in the data analysis; that is, it helped identify meaningful aspects in the interviews collected for this study. As shown below, the concept represents a plausible starting point for understanding the meaning of the memory of Marielle Franco in the present, but there are also limits to the concept. For this reason, I will also explore new ways of interpreting the memory of Franco that go beyond Metz. My reading of the memory of Franco in this chapter will form the basis for a decolonial understanding of dangerous memory in Chap. 5.
How Firms Utilize the Data Provided by Space Firms
Authors: Haq Hafiz 
Published: August 2024

AbstractThis study posits some of the fundamental questions in the development of the new space economy and highlights the ways space data can be used in firms. The excess satellite data produced from nanosats leave gaps from the point of view of value creation and adoption in various business sectors. The project includes four interviews from industry and academic institutions to gather data about space data adoption and development. The interviews were conducted in Finland. The study uses opportunity creation/development lens as a basis to evaluate space data availability in various business activities. The findings include identifying key parameters before the adoption of space data in new product development. The study further emphasizes the available infrastructure and platforms for space data adoption. However, the lack of skill and knowledge present a great challenge for firms to incorporate space data in product development.