bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gene expression of adipokines and inflammatory cytokines in peripheral blood mononuclear cells of obese dogs
Authors: Hwang Seo‐Young , An Ju‐Hyun , Kim Kyung‐Bo , Lee Jeong‐Hwa , Park Su‐Min , Oh Ye‐in , Chae Hyung Kyu , Youn Hwa‐Young 
Published: January 2022

AbstractBackgroundPeripheral blood mononuclear cells (PBMCs) have been identified as a possible marker of inflammation in obesity. Understanding the expression of pro‐ and anti‐inflammatory cytokines in PBMCs in obese dogs will help control obesity‐related inflammatory diseases.ObjectivesThe aim of this study was to evaluate the role of PBMCs in obesity‐associated chronic inflammation by analyzing the expression of adipokines and inflammatory cytokines.MethodsBlood samples were obtained from 25 subjects and real‐time quantitative polymerase chain reaction determinations were performed to quantify the gene expression levels of adipokines and inflammatory cytokines, including TNF‐α, IL‐17, leptin, MCP‐1, and adiponectin, in the PBMCs.ResultsThe results showed that the gene expression levels of TNF‐α (p < 0.001), IL‐17 (p < 0.0001), and leptin (p < 0.0001) were strongly upregulated in the PBMCs of obese dogs compared to that in non‐obese dogs.ConclusionsThe changes in gene expression levels of inflammation‐related adipokines and pro‐inflammatory cytokines occur in PBMCs, which may contribute to the low‐grade chronic inflammation that is present in obesity.
Cross‐border migration on a warming planet: A policy framework
Authors: Byravan Sujatha , Rajan Sudhir C. 
Published: January 2022

AbstractMigration is frequently driven by the need to improve social and economic opportunities or to flee conditions of political insecurity. The increased risks of environmental hazards, including climate change, have intensified the push to migrate. Nevertheless, the relation between climate change and forced displacement is not direct and is complicated by globalization, local ecological conditions, and deteriorating domestic institutions. Significantly, the muddy situation means the question “did this person migrate because of climate change?” may never be fully answered. On the basis of ethical arguments, in this Perspective article we propose a framework with both strong and mild responses to address cross‐border migration. The strong version acknowledges that it is impossible to separate out fully the climate‐induced causes of migration from others and using climate attribution studies for this purpose is potentially harmful. This implies designing an open door policy for asylum seekers as the impacts of climate change unfold, bearing in mind that host countries having the most responsibility for climate change ought to be the most welcoming to them. In the mild version, the international community designates vulnerable zones, areas where significant land area is susceptible to overwhelming loss and damage. Such countries would include most small‐island states, those that are severely drought‐prone and those with substantial low‐lying deltaic areas. In both the mild and strong versions, asylum seekers are provided rights of free passage to host countries under nonrefoulement, so that they are not forced to return to their unliveable or unviable home countries and face continuing harm.This article is categorized under:
Climate, Nature, and Ethics > Climate Change and Global Justice
Truth as social practice in a digital era: iteration as persuasion
Authors: Foster Clare L. E. 
Published: January 2022

AbstractThis article reflects on the problem of false belief produced by the integrated psychological and algorithmic landscape humans now inhabit. Following the work of scholars such as Lee McIntyre (Post-Truth, MIT Press, 2018) or Cailin O’Connor and James Weatherall (The Misinformation Age: How False Beliefs Spread, Yale University Press, 2019) it combines recent discussions of fake news, post-truth, and science denialism across the disciplines of political science, computer science, sociology, psychology, and the history and philosophy of science that variously address the ineffectiveness, in a digital era, of countering individual falsehoods with facts. Truth and falsehood, it argues, rather than being seen as properties or conditions attached to individual instances of content, should now be seen as collective, performative, and above all persuasive phenomena. They should be practically evaluated as networked systems and mechanisms of sharing in which individually targeted actions are combining with structural tendencies (both human and mechanical) in unprecedented ways. For example, the persuasive agency of apparent consensus (clicks, likes, bots, trolls) is newly important in a fractured environment that only appears to be, but is no longer ‘public’; the control of narratives, labels, and associations is a live, time-sensitive issue, a continuous contest, or ongoing cusp. Taking a social approach to truth yields observations of new relevance; from how current strategies of negative cohesion, blame, and enemy-creation depend crucially on binary ways of constructing the world, to how the offer of identity/community powerfully cooperates with the structural tendencies of algorithm-driven advertiser platforms towards polarisation. Remedies for these machine-learned and psychological tendencies lie in end-user education. So the Arts and Humanities, whether via comparisons with previous historical periods, or via principles of critical thinking and active reading, offer crucial resources to help counter what since 1997 silicon valley executives and scholars have called ‘persuasive technology’ (Fogg in Persuasive Technology: Using Computers to Change What we Think and Do, Morgan Kaufmann, 2003; Hamari et al. (eds) in Persuasive Technology, Springer International Publishing, 2014; Harris in How a Handful of Tech Companies Control Billions of Minds Every Day, 2017; Lanier in Who Owns the Future? Simon & Schuster, 2014 and Ten Arguments for Deleting your Social Media Accounts Right Now, Picador, 2019). The article proposes a paradigm shift in public understandings of this new social environment: from a culture of discovery, where what matters is what exists or is in fact the case, to a culture of iteration, where what matters is what gets repeated.
Fatigue strength improvement due to alloying steel weld toes with WC tool constituent elements through friction stir processing
Authors: Yamamoto Hajime , Koga Shodai , Ito Kazuhiro , Mikami Yoshiki 
Published: January 2022

AbstractFriction stir processing (FSP) enables surface modifications can likely be applied as a new post-weld treatment for improving fatigue strength. When applying FSP to high-strength materials, tool wear occurring at the interface between the tool tip and the topmost steel layer has been regarded as an unavoidable issue and is related to the tool rotational speed. The present study investigated the relationship between the tool rotational speed and fatigue strength of arc-welded high-strength low-alloy (HSLA) steel joints with weld toes subjected to FSP using a spherical-tip WC tool. FSP was conducted on the weld toe of HSLA steel joints with various tool rotational speeds. Tool wear increased with increase in tool rotational speed, and consequently contents of constituent elements of the WC tool increased in the topmost steel layer of weld toes, leading to large increase in fatigue strength. One reason for the increase with tool rotational speed is significant increase in solid solution hardening due to supersaturated W and C in the topmost steel layer consisting of martensite laths. The hardened topmost steel layer prevented fatigue crack initiation, and the increased fatigue strength depended on the contents of supersaturated W and C. Alloying of the topmost steel layer with tool constituent elements of W and C accompanied with WC tool wear during FSP is unique additive manufacturing to increase the fatigue strength of welded joints, and can be employed locally on structural components susceptible to fatigue.
Body mass index in type 2 spinal muscular atrophy: a longitudinal study
Authors: Ferrantini Gloria , Coratti Giorgia , Onesimo Roberta , Lucibello Simona , Bompard Sarah , Turrini Ida , Cicala Graziamaria , Caprarelli Michela , Pera Maria Carmela , Bravetti Chiara , Berti Beatrice , Giorgio Valentina , Bruno Claudio , Brolatti Noemi , Panicucci Chiara , D’Amico Adele , Longo Antonella , Leoni Chiara , Sansone Valeria A. , Albamonte Emilio , Messina Sonia , Sframeli Maria , Bertini Enrico , Pane Marika , Mercuri Eugenio ,   the Italian ISMAC study group
Published: January 2022

AbstractThe aim of this retrospective study was to review body mass index (BMI) in a large cohort of Italian pediatric type 2 spinal muscular atrophy (SMA) patients, aged between 0 and 20 years and to establish possible differences in relation to a number of variables such as ventilation, motor function, and survival motor neuron 2 gene copies. Cross-sectional data were collected from 102 patients for a total of 344 visits. Standard growth charts for height and weight were used as reference, with age adjusted BMI calculated using the Center for Disease and Prevention Children’s BMI Tool. In the 344 visits, weight ranged between 3.90 and 83 kg, and the BMI between 8.4 and 31.6 with a BMI/age z-scores <  − 2SD present in 28% and BMI/age z-scores >  + 2SD in 9% of the measurements. The BMI/age z-scores were relatively stable < 5 years of age with an increasing number of patients <  − 2SD after the age of 5, and a wider range of BMI/age z-scores after the age of 13. A difference on the BMI/age z-scores was found among the different age subgroups (< 5, 5–12, ≥ 13 years). A multivariate analysis in 58 patients with longitudinal assessments showed that baseline BMI/age z-scores and gender were significantly contributing to the changes while other variables were not.Conclusion: Our results confirm that careful surveillance of weight and BMI/age z-scores is needed in type 2 SMA. Further studies, including assessments of chewing and swallowing and of lean/fat body mass, will help to better understand the possible mechanisms underlying weight issues.

What is Known:• Feeding difficulties have been reported in a few studies and were invariably found in patients with type 1 SMA.• Type 2 SMA patients often have low BMI with a relevant number of patients requiring tube feeding.

What is New:• Reduction in BMI/age z-score overtime appeared to depend on baseline BMI/age z-score and gender.• Patients with a low BMI/age z-score were at higher risk of developing further reduction.
A model-driven approach to machine learning and software modeling for the IoT
Authors: Moin Armin , Challenger Moharram , Badii Atta , Günnemann Stephan 
Published: January 2022

AbstractModels are used in both Software Engineering (SE) and Artificial Intelligence (AI). SE models may specify the architecture at different levels of abstraction and for addressing different concerns at various stages of the software development life-cycle, from early conceptualization and design, to verification, implementation, testing and evolution. However, AI models may provide smart capabilities, such as prediction and decision-making support. For instance, in Machine Learning (ML), which is currently the most popular sub-discipline of AI, mathematical models may learn useful patterns in the observed data and can become capable of making predictions. The goal of this work is to create synergy by bringing models in the said communities together and proposing a holistic approach to model-driven software development for intelligent systems that require ML. We illustrate how software models can become capable of creating and dealing with ML models in a seamless manner. The main focus is on the domain of the Internet of Things (IoT), where both ML and model-driven SE play a key role. In the context of the need to take a Cyber-Physical System-of-Systems perspective of the targeted architecture, an integrated design environment for both SE and ML sub-systems would best support the optimization and overall efficiency of the implementation of the resulting system. In particular, we implement the proposed approach, called ML-Quadrat, based on ThingML, and validate it using a case study from the IoT domain, as well as through an empirical user evaluation. It transpires that the proposed approach is not only feasible, but may also contribute to the performance leap of software development for smart Cyber-Physical Systems (CPS) which are connected to the IoT, as well as an enhanced user experience of the practitioners who use the proposed modeling solution.
Exploring a landslide inventory created by automated web data mining: the case of Italy
Authors: Franceschini Rachele , Rosi Ascanio , Catani Filippo , Casagli Nicola 
Published: January 2022

AbstractNowadays, several systems to set up landslide inventories exist although they rarely rely on automated or real-time updates. Mass media can provide reliable info about natural hazard events with a relatively high temporal and spatial resolution. The news publication about a natural disaster inside newspaper or crowdsourcing platforms allows a faster observation, survey, and classification of these phenomena. Several techniques have been developed for data mining inside social media for many natural events, but they have been rarely applied to the automatic extraction of “landslide events”. This source of information allows continuous feedback from real world, and news concerning landslide events can be rapidly collected. In this work, the newspaper articles about landslides in Italy are automatically collected by an existing data mining algorithm, based on a semantic engine. The news has been analysed to assess their distribution over the territory and to verify the possibility of using them for hazard mapping purpose. In 10 years, from 2010 to 2019, the algorithm identified and geolocated 184322 articles referring to 32525 generical events (“news”). At first, the collected data underwent to a manual verification, followed by a classification based on news relevance, localization accuracy and time of publication. Then, these data have been used to identify the areas and the periods most affected by landslide phenomena. The analyses show that almost 42% of Italian municipalities have been affected by landslide. According to the results, the use of data mining is helpful for the creation of landslide databases where the day and the approximative location (municipality) of the possible landslide triggers are known. This database, in turn, can be used for scientific purposes, as the definition of the meteorological condition associated with landslide initiation, the validation of risk maps. It can also be used for a proper land use or risk mitigation planning, since the most landslide-prone municipalities can be defined.
Munitionsaltlasten vor deutschen Küsten und deren Bezug zum Gewässerschutz-, Naturschutz- und Gefahrenabwehrrecht
Authors: Kollenberg Roman 
Published: January 2022

ZusammenfassungInsbesondere der Politikdiskurs in den norddeutschen Bundesländern, aber auch die Wissenschaft
befasst sich schon seit einigen Jahren mit den Munitionsaltlasten, die sich vor den deutschen Küsten
befinden. Dass diese als Gefahrenquellen mit drohenden erheblichen schädlichen Folgen für Mensch
und Natur beseitigt werden müssen, erscheint immer dringlicher. Jedoch erweist sich der rechtliche
Rahmen dieser Beseitigungsmaßnahmen vor dem Hintergrund der bestehenden gewässerschutz-, naturschutz-
und gefahrenabwehrrechtlichen Regelungen als sehr unübersichtlich. Er soll daher in dem vorliegenden
Beitrag ausgeleuchtet werden.
Greenhouse Gas Emissions and Eco-Performance at Farm Level: A Parametric Approach
Authors: Stetter Christian , Sauer Johannes 
Published: January 2022

AbstractAgriculture is an important source of greenhouse gas (GHG) emissions and thus contributes considerably to global warming. However, farms can vary substantially in terms of their climatic impact. So far, most policies aiming at reducing GHG emissions from farming have largely been based on findings at the aggregate level, without taking farm heterogeneity properly into account. This study seeks to provide a better understanding of the GHG mitigation potential at the micro-level. We develop a comprehensible analytical framework for analyzing economic-ecological performance by way of stochastic frontier analysis. We introduce the concept of emission efficiency, where we distinguish between persistent and time-varying efficiency. We further analyze farms with respect to their emission-performance dynamics. Results from our (2005–2014) empirical application from Bavaria—an important region for the EU – show considerable differences in farm-level GHG emissions across different farm types. The same applies to emission efficiencies. Overall, emission performance improved over time. The results have important climate-policy implications as they help to provide better target measures for mitigating GHG emissions from agriculture, without compromising economic performance levels.
Solving non-monotone equilibrium problems via a DIRECT-type approach
Authors: Lucidi Stefano , Passacantando Mauro , Rinaldi Francesco 
Published: January 2022

AbstractA global optimization approach for solving non-monotone equilibrium problems (EPs) is proposed. The class of (regularized) gap functions is used to reformulate any EP as a constrained global optimization program and some bounds on the Lipschitz constant of such functions are provided. The proposed global optimization approach is a combination of an improved version of the algorithm, which exploits local bounds of the Lipschitz constant of the objective function, with local minimizations. Unlike most existing solution methods for EPs, no monotonicity-type condition is assumed in this paper. Preliminary numerical results on several classes of EPs show the effectiveness of the approach.
Seasonal phosphorus and nitrogen cycling in four Japanese cool-temperate forest species
Authors: Seidel Felix , Lopez C. M. Larry , Bonifacio Eleonora , Kurokawa Hiroko , Yamanaka Toshiro , Celi Luisella 
Published: January 2022

Abstract
Purpose
In plant-soil systems, phosphorus partitioning during the annual cycle related to nitrogen partitioning remains largely unknown. The present study aims at assessing the soil-plant P allocation patterns of four tree species along four phenological stages and its relationship with tissues and soil N concentrations.

Methods
Cryptomeria japonica, Larix kaempferi, Fagus crenata and Robinia pseudoacacia trees were selected to sample coarse roots, sapwood, foliage, litter and soil during four phenological stages where total and Olsen extractable P and nitrogen content were measured respectively.

Results
Intra- and inter plant tissue nitrogen correlated well with phosphorus during the four phenological stages, especially root nitrogen. Fagus and Robinia were phosphorus limited, Larix was nitrogen limited and Cryptomeria co-limited. All species reabsorbed phosphorus and nitrogen from foliage prior to leaf abscission and stored nitrogen in roots and sapwood. Phosphorus storage was solely found in sapwood of Robinia. Soil dissolved ammonium correlated positively with nitrogen reabsorption efficiency during the green leaf stage, while single soil nutrient variables did not correlate with phosphorus reabsorption efficiency.

Conclusions
Plant tissues nitrogen partitioning correlated well with their respective phosphorus partitioning and the increase of soil NH4+ correlated positively with nitrogen reabsorption efficiency, regardless of tree species during the green leaf stage. The results of this study show the intricate relationship that exists between nitrogen and phosphorus in the soil-plant continuum as well as the tree species specific internal cycling of these nutrients.
2018 Real Estate Finance & Investment Symposium
Authors: Lindenthal Thies , Ling David C. , Ooi Joseph 
Published: January 2022

AbstractIn October 2018, the Real Estate Finance & Investment Symposium, sponsored and organized by the University of Cambridge, the University of Florida, and the National University of Singapore, was held in Gainesville, Florida. Ten papers on various research topics were presented over the day and one-half symposium. Each presentation
was followed by remarks from a discussant as well as general discussion from the audience. This short editorial discusses the five papers from the symposium that are included in this special issue.
A novel data solution to inform curriculum decolonisation: the case of the Imperial College London Masters of Public Health
Authors: Price Robyn , Skopec Mark , Mackenzie Simon , Nijhoff Coco , Harrison Ruth , Seabrook Gemma , Harris Matthew 
Published: January 2022

AbstractThere is increasing interest within Higher Education Institutions (HEIs) to examine curricula for legacies of colonialism or empire that might result in a preponderance of references to research from the global north. Prior attempts to study reading lists for author geographies have employed resource-intensive audit and data collection methods based on manual searching and tagging individual reading list items by characteristics such as author country or place of publication. However, these manual methods are impractical for large reading lists with hundreds of citations that change over instances the course is taught. Laborious manual methods may explain why there is a lack of quantitative evidence to inform this debate and the understanding of geographic distribution of curricula. We describe a novel computational method applied to 568 articles, representing 3166 authors from the Imperial College London Masters in Public Health programme over two time periods (2017–18 and 2019–20). Described with summary statistics, we found a marginal shift away from global north-affiliated authors on the reading lists of one Masters course over two time periods and contextualise the role and limitations of the use of quantitative data in the decolonisation discourse. The method provides opportunities for educators to examine the distribution of course readings at pace and over time, serving as a useful point of departure to engage in decolonisation debates.