bluuebunny/crossref_metadata_2025_split huggingface dataset:
A joint method to quantify source contributions of heavy metals to ecological and human health risks in oasis farmland soil
Authors: Tian Jing , Guan Qingyu , Shao Wenyan , Liu Zhan , Ma Yunrui , Li Huichun , Sun Yunfan 
Published: June 2021

AbstractSource identification and risk assessment of heavy metals are ongoing hot topics in current research, but few studies have been performed on the linkage mechanism between them. In the past, the amount of heavy metals discharged was the identification criterion for high‐risk source but failed to consider different toxicity of heavy metals in the risk level of each pollution source. Therefore, it is impossible to accurately determine high‐risk pollution source. For this situation, this study introduced a risk assessment model based on the source apportionment model, which can quantitatively analyze the source‐based risk. Meanwhile, pollution assessment indexes and a risk assessment model were applied to evaluate the levels of pollution and risk of heavy metals, showing that lead (Pb) caused relatively serious pollution and arsenic (As) generated the highest ecological risk and noncarcinogenic risk. Positive matrix factorization (PMF) model identified and quantified the sources of heavy metals (coal‐related activities source, mixed source of mining and traffic emissions, industrial activity source, agricultural source related to the application of agrochemicals) with the corresponding contributions of 42, 30, 26, and 2%, respectively. Then PMF was combined with potential ecological risk index and human health risk assessment model to quantify the risk from pollution sources, indicating that the coal‐related activities source was the largest pollution source (31–36%) that caused human health risks, while the mixed source of mining and transportation emissions posed the greatest threat (29%) to the ecosystem health. Therefore, both sources should be identified as the priority pollution sources.
Controllable Synthesis of Wafer‐Scale Graphene Films: Challenges, Status, and Perspectives
Authors: Jiang Bei , Wang Shiwei , Sun Jingyu , Liu Zhongfan 
Published: June 2021

AbstractThe availability of high‐quality, large‐scale, and single‐crystal wafer‐scale graphene films is fundamental for key device applications in the field of electronics, optics, and sensors. Synthesis determines the future: unleashing the full potentials of such emerging materials relies heavily upon their tailored synthesis in a scalable fashion, which is by no means an easy task to date. This review covers the state‐of‐the‐art progress in the synthesis of wafer‐scale graphene films by virtue of chemical vapor deposition (CVD), with a focus on main challenges and present status. Particularly, prevailing synthetic strategies are highlighted on a basis of the discussion in the reaction kinetics and gas‐phase dynamics during CVD process. Perspectives with respect to key opportunities and promising research directions are proposed to guide the future development of wafer‐scale graphene films.
Aqueous MnV2O6‐Zn Battery with High Operating Voltage and Energy Density
Authors: Wu Yan , Zhu Zhaohua , Li Yifan , Shen Dong , Chen Lina , Kang Tianxing , Lin Xiaohang , Tong Zhongqiu , Wang Hui , Lee Chun‐sing 
Published: June 2021

AbstractAqueous Zn ion batteries (AZIBs), featuring low cost, long‐term cycling stability, and superior safety are promising for applications in advanced energy storage devices. However, they still suffer from unsatisfactory energy density and operating voltage, which are closely related to cathode materials used. Herein, the use of monoclinic MnV2O6 (MVO) is reported, which can be activated for high‐capacity Zn ions storage by electrochemically oxidizing part of the Mn2+ to Mn3+ or Mn4+ while the remaining Mn2+ ions act as binders/pillars to hold the layer structure of MVO and maintain its integrity during charging/discharging process. Moreover, after introducing carbon nanotubes (CNT), the MVO:CNT composite not only provides robust 3D Zn‐ion diffusion channels but also shows enhanced structural integrity. As a result, a MVO:CNT cathode delivers a high midpoint voltage (1.38 V after 3000 cycles at 2 A g−1) and a high energy density of 597.9 W h kg−1. Moreover, DFT analyses clearly illustrate stepwise Zn ion insertion into the MnV2O6 lattice, and ex‐situ analyses results further verify the highly structural reversibility of the MnV2O6 cathode upon extended cycling, demonstrating the good potential of MnV2O6 for the establishment of viable aqueous Zn ion battery systems.
CsPbX3‐ITO (X = Cl, Br, I) Nano‐Heterojunctions: Voltage Tuned Positive to Negative Photoresponse
Authors: He Qiqian , Chen Gaoyu , Wang Yongkai , Liu Xiaoyu , Xu Danting , Xu Xiangxing , Liu Ying , Bao Jianchun , Wang Xun 
Published: June 2021

AbstractAll‐Inorganic perovskite CsPbX3 (X = Cl, Br, I) quantum dots (QDs) have attracted tremendous attention in the past few years for their appealing performance in optoelectronic applications. Major properties of CsPbX3 QDs include the positive photoconductivity (PPC) and the defect tolerance of the in‐band trap states. Here it is reported that when hybridizing CsPbX3 QDs with indium tin oxide (ITO) nanocrystals to form CsPbX3‐ITO nano‐heterojunctions (NHJs), a voltage tuned photoresponse—from PPC to negative photoconductivity (NPC) transform—is achieved in lateral drain‐source structured ITO/CsPbX3‐ITO‐NHJs/ITO devices. A model combining exciton, charge separation, transport, and most critical the voltage driven electron filling of the in‐band trap states with drain–source voltage (VDS) above a threshold, is proposed to understand this unusual PPC‐NPC transform mechanism, which is different from that of any known nanomaterial system. This finding exhibits potentials for developing devices such as photodetectors, optoelectronic switches, and memories.
Income inequality and housing prices in the very long‐run
Authors: Hailemariam Abebe , Awaworyi Churchill Sefa , Smyth Russell , Baako Kingsley Tetteh 
Published: June 2021

AbstractWe examine the relationship between income inequality and house prices for a panel of 17 OECD countries over the period 1870 to 2015. Our identification strategy takes advantage of exogenous variation in culturally weighted communist influence to instrument for within‐country variations in income inequality. Controlling for endogeneity, time, and country fixed effects, our results suggest that an increase in income inequality has a significant negative effect on real house prices. This finding is robust to the use of both the Gini coefficient and top income share as measures of income inequality and the use of absolute and relative income inequality measures, as well as a range of other robustness checks. We examine crime as a mechanism through which income inequality influences housing prices and find that the theft rate is a channel via which higher income inequality contributes to lower house prices.
Rosselichnidae ifam. nov.: burrows with concentric, spiral or eccentric lamination
Authors: Knaust Dirk 
Published: June 2021

AbstractBurrows with a thick concentric, spiral or eccentric lamination are common constituents of Phanerozoic marine deposits and have been described under different names for more than 150 years. Ambiguous original diagnoses, questionable type specimens and morphological transitions between end members have led to a rather unstable ichnotaxonomy and varying indistinct definitions. This situation, in turn, hinders an application of these ichnotaxa in facies interpretations, and in palaeoenvironmental and evolutionary reconstructions. A revision of this group of trace fossils, collectively assembled under the new ichnofamily Rosselichnidae, aims for its consolidation. It includes the ichnogenera Rosselia Dahmer, Cylindrichnus Toots in Howard, Patagonichnus Olivero & López Cabrera, Artichnus Zhang et al., Lamellaecylindrica Knaust and Bromlichnus Vallon et al., together containing 15 ichnospecies. Burrow morphology, orientation, branching and type of lamination are used as ichnotaxobases. Artichnus serialis isp. nov. is erected, whereas Rosselia erecta (Torell), Rosselia prolifera (Fournier et al.) and Lamellaecylindrica ludwigae (Schlirf) are new combinations. Rosselia erecta is installed as the ichnospecies name for forms that historically have been assigned to Monocraterion isp. A review of established interpretations of potential producers and their ethology of ichnotaxa included in Rosselichnidae reveals that polychaetes and holothurians with a suspension‐ and deposit‐feeding behaviour are best equipped to produce such burrows. The stratigraphic record of Rosselia spans the entire Phanerozoic, whereas the other ichnogenera mainly occur in the Mesozoic and Cenozoic.
Mechanistic analysis of bladder cancer suppression by brassicasterol in a rat model of N‐butyl‐N‐(4‐hydroxybutyl)nitrosamine‐induced bladder cancer
Authors: Ikarashi Nobutomo , Ono Tetsuya , Hoshino Motohiro , Toda Takahiro , Yazawa Yasuharu , Sugiyama Kiyoshi 
Published: June 2021

ABSTRACTAimWe previously clarified that the herbal medicine Polyporus Sclerotium, a constituent of Choreito, has an inhibitory effect on bladder carcinogenesis and that ergosterol is the active ingredient. In addition, we showed that this action of ergosterol may be caused by the metabolite brassicasterol. Here, we aimed to elucidate the detailed molecular mechanism by which brassicasterol inhibits bladder carcinogenesis.MethodsA rat model of bladder cancer was established by feeding rats N‐butyl‐N‐(4‐hydroxybutyl)nitrosamine (BHBN) and sodium saccharin (SS). After intraperitoneal administration of brassicasterol to rats, the mRNA expression levels of cell cycle‐related genes (cyclin D1, c‐fos, and c‐jun), inflammation‐related genes (cyclooxygenase‐2; COX‐2), and androgen signal‐related genes (5α‐reductase type 1; 5α‐R1, 5α‐reductase type 2; 5α‐R2, and the androgen receptor; AR) in bladder epithelial cells were analyzed.ResultsBrassicasterol significantly suppressed bladder carcinogenesis induced by BHBN and SS. The mRNA expression levels of cyclin D1 in bladder epithelial cells were significantly higher in the carcinogenesis group than in the control group. Additionally, the expression levels of c‐fos and c‐jun, constituents of the transcription factor activator protein‐1 (AP‐1) upstream of cyclin D1, were significantly increased in the carcinogenesis group compared with the control group. Moreover, the expression levels of COX‐2, 5α‐R1, 5α‐R2, and AR were significantly higher in the carcinogenesis group. In contrast, in rats treated with brassicasterol, the increases in the expression levels of these molecules were significantly suppressed.ConclusionWe clarified that brassicasterol suppresses bladder carcinogenesis by acting on cell cycle‐related signaling, inflammation‐related signaling, and androgen signaling via multiple mechanisms.
Gadolinium spin dilution in the solid solution Gd1–xYxAuMg – gradual decrease of the Néel temperature
Authors: Reimann Maximilian Kai , Pöttgen Rainer 
Published: June 2021

AbstractThe intermetallic compounds GdAuMg and YAuMg form a continuous solid solution Gd1–xYxAuMg. Samples inx=0.1 steps were synthesized from the elements in sealed tantalum ampoules in an induction furnace. Phase purity of the samples was checked by powder X‐ray diffraction. The structures of two members of the solid solution were refined from single crystal X‐ray diffractometer data: ZrNiAl type,P2m,a=756.16(6),c=413.06(4) pm,wR2=0.0402, 328F2values, 16 variables for Gd0.80(2)Y0.20(2)AuMg anda=754.82(7),c=411.24(4) pm,wR2=0.0292, 325F2values, 16 variables for Gd0.37(1)Y0.63(1)AuMg. Temperature dependent magnetic susceptibility studies show a continuous decrease of the Néel temperature fromTN=81.1(1) K (GdAuMg) to 3.5(1) K (Gd0.1Y0.9AuMg). With increasingxin Gd1–xYxAuMg the saturation magnetization increases, with a maximal value of 6.44(1) μBGd atom−1for Gd0.1Y0.9AuMg at 3 K. The dilution of the gadolinium substructure with yttrium pushes the magnetization isotherms close to Brillouin type behavior (free Gd3+).
Data Science Technologies in Economics and Finance: A Gentle Walk-In
Authors: Barbaglia Luca , Consoli Sergio , Manzan Sebastiano , Reforgiato Recupero Diego , Saisana Michaela , Tiozzo Pezzoli Luca 
Published: June 2021

AbstractThis chapter is an introduction to the use of data science technologies in the fields of economics and finance. The recent explosion in computation and information technology in the past decade has made available vast amounts of data in various domains, which has been referred to as Big Data. In economics and finance, in particular, tapping into these data brings research and business closer together, as data generated in ordinary economic activity can be used towards effective and personalized models. In this context, the recent use of data science technologies for economics and finance provides mutual benefits to both scientists and professionals, improving forecasting and nowcasting for several kinds of applications. This chapter introduces the subject through underlying technical challenges such as data handling and protection, modeling, integration, and interpretation. It also outlines some of the common issues in economic modeling with data science technologies and surveys the relevant big data management and analytics solutions, motivating the use of data science methods in economics and finance.
Do the Hype of the Benefits from Using New Data Science Tools Extend to Forecasting Extremely Volatile Assets?
Authors: Lehrer Steven F. , Xie Tian , Yi Guanxi 
Published: June 2021

AbstractThis chapter first provides an illustration of the benefits of using machine learning for forecasting relative to traditional econometric strategies. We consider the short-term volatility of the Bitcoin market by realized volatility observations. Our analysis highlights the importance of accounting for nonlinearities to explain the gains of machine learning algorithms and examines the robustness of our findings to the selection of hyperparameters. This provides an illustration of how different machine learning estimators improve the development of forecast models by relaxing the functional form assumptions that are made explicit when writing up an econometric model. Our second contribution is to illustrate how deep learning can be used to measure market-level sentiment from a 10% random sample of Twitter users. This sentiment variable significantly improves forecast accuracy for every econometric estimator and machine algorithm considered in our forecasting application. This provides an illustration of the benefits of new tools from the natural language processing literature at creating variables that can improve the accuracy of forecasting models.
Opening the Black Box: Machine Learning Interpretability and Inference Tools with an Application to Economic Forecasting
Authors: Buckmann Marcus , Joseph Andreas , Robertson Helena 
Published: June 2021

AbstractWe present a comprehensive comparative case study for the use of machine learning models for macroeconomics forecasting. We find that machine learning models mostly outperform conventional econometric approaches in forecasting changes in US unemployment on a 1-year horizon. To address the black box critique of machine learning models, we apply and compare two variables attribution methods: permutation importance and Shapley values. While the aggregate information derived from both approaches is broadly in line, Shapley values offer several advantages, such as the discovery of unknown functional forms in the data generating process and the ability to perform statistical inference. The latter is achieved by the Shapley regression framework, which allows for the evaluation and communication of machine learning models akin to that of linear models.
Classifying Counterparty Sector in EMIR Data
Authors: Lenoci Francesca D. , Letizia Elisa 
Published: June 2021

AbstractThe data collected under the European Market Infrastructure Regulation (“EMIR data”) provide authorities with voluminous transaction-by-transaction details on derivatives but their use poses numerous challenges. To overcome one major challenge, this chapter draws from eight different data sources and develops a greedy algorithm to obtain a new counterparty sector classification. We classify counterparties’ sector for 96% of the notional value of outstanding contracts in the euro area derivatives market. Our classification is also detailed, comprehensive, and well suited for the analysis of the derivatives market, which we illustrate in four case studies. Overall, we show that our algorithm can become a key building block for a wide range of research- and policy-oriented studies with EMIR data.
Sentiment Analysis of Financial News: Mechanics and Statistics
Authors: Arratia Argimiro , Avalos Gustavo , Cabaña Alejandra , Duarte-López Ariel , Renedo-Mirambell Martí 
Published: June 2021

AbstractThis chapter describes the basic mechanics for building a forecasting model that uses as input sentiment indicators derived from textual data. In addition, as we focus our target of predictions on financial time series, we present a set of stylized empirical facts describing the statistical properties of lexicon-based sentiment indicators extracted from news on financial markets. Examples of these modeling methods and statistical hypothesis tests are provided on real data. The general goal is to provide guidelines for financial practitioners for the proper construction and interpretation of their own time-dependent numerical information representing public perception toward companies, stocks’ prices, and financial markets in general.
Wrestling with the Inner Demons of Contemporary Life: A Brief Overview of Psychoanalytic Thought
Authors: Mitroff Ian I. , Kilmann Ralph H. 
Published: June 2021

AbstractWe begin our examination of Enlightened Leadership by exploring a number of Psychoanalytically based theories, in particular with regard to what they have to teach us about the human condition. Thus, we briefly examine some of the key concepts and ideas of Melanie Klein, Sigmund Freud, Donald Winnicott, Eric Berne, and John Bowlby. One of the major benefits is that they illuminate important aspects of the Coronavirus that are difficult to ascertain otherwise. For one, each provides a different take on the enormous stress we are experiencing as a result of the Virus. They also reinforce the absolute necessity of following the dictates of reputable scientific experts and science itself if we are to stand any hope at all in dealing with the Virus.
The Coronavirus: A Jungian Analysis
Authors: Mitroff Ian I. , Kilmann Ralph H. 
Published: June 2021

AbstractSince we’ve talked repeatedly about the importance of Systems Thinking, we want to examine the Coronavirus from a different form. It brings out different aspects of the Virus that along with the Psychodynamic theories we examined in Chap. 10.1007/978-3-030-71764-3_1 are difficult to ascertain without it.
Heuristics and Meta-heuristics for Coping with Messes
Authors: Mitroff Ian I. , Kilmann Ralph H. 
Published: June 2021

AbstractGiven the importance of Wicked Messes, we need to say more about ways of dealing with them. In a series of publications, we and our colleagues have developed a number of Heuristics for Coping with Messes. If the underlying conditions are met, there is every reason to believe that they will accomplish their intended job. Nonetheless, they are only Heuristics, i.e., approximate rules of thumb. As such, they do not guarantee that we’ll be able to cope successfully with a Mess. Worst of all, they can even backfire such that instead of making Messes more manageable, they can make them worse, thus producing the exact opposite of what’s intended. Still, they’re all that we have. Nonetheless, by not looking at their potential downsides, the inescapable conclusion is that some of the most important aspects of Messes have not been given the serious consideration they demand.
Benefits and Challenges of Adopting SAFe - An Empirical Survey
Authors: Putta Abheeshta , Uludağ Ömer , Paasivaara Maria , Hong Shun-Long 
Published: June 2021

AbstractDuring the last two decades, turbulent business environments tempted firms to adopt agile methods to cope with the ever-changing customer demands. The success of agile methods in small and co-located teams inspired companies to apply them to large-scale endeavors. Agile scaling frameworks, such as the Scaled Agile Framework (SAFe), have been proposed by practitioners to scale agile practices to large projects and enterprises. Companies are increasingly taking these frameworks into use. However, the number of quantitative empirical studies assessing the benefits and challenges of adopting the agile scaling frameworks is still limited. This paper starts filling in this gap by presenting the results from a survey of 100 industry participants around the world on their perception of the benefits and challenges of adopting the SAFe framework. Our results show that the SAFe adoption improves transparency, as well as collaboration and dependency management between agile teams. The most commonly mentioned challenges of the SAFe adoption are organizational politics, difficulties in establishing an agile mindset, change resistance, and team formation challenges.
Comparing Participants’ Brainwaves During Solo, Pair, and Mob Programming
Authors: Shiraishi Makoto , Washizaki Hironori , Saito Daisuke , Fukazawa Yoshiaki 
Published: June 2021

AbstractParticipants’ feelings and impressions utilizing electroencephalography (EEG) and the effectiveness of code are compared for different types of programming sessions. EEG information is obtained as an alternate viewpoint during three programming sessions (solo, pair, and mob programming). MindWave Mobile 2 (brainwave detector) is equipped to collect the attention levels, meditation levels, and EEG brainwaves. These data are utilized to distinguish efficiencies, weaknesses, and points of interest by programming session. The results provide preliminary information to distinguish between the three sessions, but further studies are necessary to make firm conclusions. Additionally, alternative methods or systems are required to analyze the collected data.
UX Work in Software Start-Ups: Challenges from the Current State of Practice
Authors: Silveira Sofia A. M. , Choma Joelma , Pereira Roberto , Guerra Eduardo M. , Zaina Luciana A. M. 
Published: June 2021

AbstractSoftware start-ups develop innovative software products working with disruptive technologies in time pressure and market-driven environment. Recently, User eXperience (UX) has become a hot topic that interests software teams of start-ups. However, software and UX professionals have struggled to match UX practices into the development activities, partially because of the lack of resources in the start-ups. This paper investigates how software start-ups handle UX activities during software development and how relevant UX is to these companies’ professionals. To achieve our aim, we surveyed 88 professionals who take part in software teams in star-ups, analyzing the responses using descriptive and statistical methods. Our results reveal that regardless of having or not a UX position in the start-up, UX practices are spread in different software development phases and not fitting into them. Results also show although professionals consider UX relevant and recognize important skills to perform UX activities, some obstacles hinder the effective use of UX in software start-ups. From the survey results, we identified a set of challenges to be overcome in consolidating the UX work in software start-ups. By diagnosing the UX state-of-practice in start-up scenarios and identifying such challenges, our work contributes to provides relevant insights to further academic and practical studies in this field.