bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ambient temperature and cardiovascular mortality: a systematic review and meta-analysis
Authors: Moghadamnia Mohammad Taghi , Ardalan Ali , Mesdaghinia Alireza , Keshtkar Abbas , Naddafi Kazem , Yekaninejad Mir Saeed 
Published: August 2017

Introduction
Our study aims at identifying and quantifying the relationship between the cold and heat exposure and the risk of cardiovascular mortality through a systematic review and meta-analysis.

Material and Methods
A systematic review and meta-analysis were conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Peer-reviewed studies about the temperature and cardiovascular mortality were retrieved in the MEDLINE, Web of Science, and Scopus databases from January 2000 up to the end of 2015. The pooled effect sizes of short-term effect were calculated for the heat exposure and cold exposure separately. Also, we assessed the dose–response relationship of temperature-cardiovascular mortality by a change in units of latitudes, longitude, lag days and annual mean temperature by meta-regression.

Result
After screening the titles, abstracts and full texts, a total of 26 articles were included in the meta-analysis. The risk of cardiovascular mortality increased by 5% (RR, 1.055; 95% CI [1.050–1.060]) for the cold exposure and 1.3% (RR, 1.013; 95% CI [1.011–1.015]) for the heat exposure. The short-term effects of cold and heat exposure on the risk of cardiovascular mortality in males were 3.8% (RR, 1.038; 95% CI [1.034–1.043]) and 1.1%( RR, 1.011; 95% CI [1.009–1.013]) respectively. Moreover, the effects of cold and heat exposure on risk of cardiovascular mortality in females were 4.1% (RR, 1.041; 95% CI [1.037–1.045]) and 1.4% (RR, 1.014; 95% CI [1.011–1.017]) respectively. In the elderly, it was at an 8.1% increase and a 6% increase in the heat and cold exposure, respectively. The greatest risk of cardiovascular mortality in cold temperature was in the 14 lag days (RR, 1.09; 95% CI [1.07–1.010]) and in hot temperatures in the seven lag days (RR, 1.14; 95% CI [1.09–1.17]). The significant dose–response relationship of latitude and longitude in cold exposure with cardiovascular mortality was found. The results showed that the risk of cardiovascular mortality increased with each degree increased significantly in latitude and longitude in cold exposure (0.2%, 95% CI [0.006–0.035]) and (0.07%, 95% CI [0.0003–0.014]) respectively. The risk of cardiovascular mortality increased with each degree increase in latitude in heat exposure (0.07%, 95% CI [0.0008–0.124]).

Conclusion
Our findings indicate that the increase and decrease in ambient temperature had a relationship with the cardiovascular mortality. To prevent the temperature- related mortality, persons with cardiovascular disease and the elderly should be targeted. The review has been registered with PROSPERO (registration number CRD42016037673).
Rater Bias Models
Authors: Saudino Kimberly J. 
Published: August 2017

Abstract
Raters' response tendencies, standards, or expectations can result in the tendency to consistently overestimate or underestimate the behavior of targets. Such rater biases can influence the outcomes of behavioral genetic studies. Quantitative genetic models allow researchers to determine the significance of rater biases and estimate genetic and environmental influences on behaviors controlling for bias. Moreover, the use of multiple raters of the same target within a genetically informative sample can provide information about sources of disagreement between raters.
Empirical Asset Pricing: The Cross Section of Stock Returns: An Overview
Authors: Bali Turan , Engle Robert , Murray Scott 
Published: August 2017

AbstractThis article summarizes our textEmpirical Asset Pricing: The Cross Section of Stock Returns. The text provides an overview of the empirical asset pricing research, with a focus on cross‐sectional studies of stock returns. The main objective of this research is to identify patterns in stock returns and understand the drivers of these patterns. The text has two main parts. The first part discusses in detail the main statistical and econometric techniques used in empirical asset pricing research, the most important of which are portfolio analysis and Fama and MacBeth regression analysis. The second part summarizes the main findings in empirical asset pricing research, beginning with the seminal research on the Capital Asset Pricing Model and ending with the most contemporary work as of the time of publication, 2016. The text is intended for use in a doctoral‐level or advanced masters‐level empirical asset pricing or investments course, as well as by professional portfolio managers, risk managers, and other practitioners.JEL Classifications:G11, G12, G13, G17
N
elder,
J
ohn
Authors: Payne Roger W. 
Published: August 2017

Abstract
John Ashworth Nelder was one of the most influential statisticians of his generation, whose work will continue to have an important and widespread effect on statistical analysis. His work on algorithms (general balance, generalized linear models, hierarchical generalized linear models, and the simplex method) is well known, but it is important also to recognize his contributions to the philosophy of statistical analysis. He was very concerned about the way in which innovation was stifled by limited software. He believed strongly that statistical packages should provide an environment for the development and then distribution of new statistical techniques ‐ and he made this a key design feature for his statistical systems Genstat and GLIM. The fact that these ideas now seem noncontroversial is tribute to his influence and persuasiveness.
Joint Distribution and Two‐Year Outcome in 347 Patients With Monoarthritis of Less Than Sixteen Weeks’ Duration
Authors: Norli Ellen Sauar , Brinkmann Gina Hetland , Kvien Tore Kristian , Bjørneboe Olav , Haugen Anne Julsrud , Nygaard Halvor , Thunem Cathrine , Lie Elisabeth , Mjaavatten Maria Dahl 
Published: August 2017

ObjectiveThe present study was undertaken to investigate the joint distribution and 2‐year outcome of patients with recent‐onset monoarthritis.MethodsAdult patients with clinically apparent monoarthritis of ≤16 weeks’ duration were included in a multicenter 2‐year longitudinal study. Clinical characteristics, joint distribution, development of chronic inflammatory rheumatic disease (CIRD), as well as classification criteria according to the American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) 2010 criteria for RA were studied. Predictors for development of CIRD were analyzed by multivariable logistic regression analyses.ResultsThe knee (49.3%), ankle (16.7%), and wrist (14.1%) were the most frequently affected joints among the 347 included patients. A total of 91 patients (26.2%) developed CIRD during follow‐up; 21 (6.1%) were diagnosed with RA, and 16 (4.6%) with psoriatic arthritis. Longer duration of joint swelling, joint localization, and anti–citrullinated protein antibody (ACPA) and rheumatoid factor (RF) positivity were independent predictors of CIRD. Six of 58 patients (10.3%) with ankle monoarthritis and 21 of 49 patients (42.9%) with wrist monoarthritis developed CIRD during follow‐up. The 2010 ACR/EULAR Criteria for RA identified all patients diagnosed with seropositive RA at an early stage, mostly within 3 months.ConclusionApproximately one‐fourth of patients with recent‐onset monoarthritis developed CIRD over 2 years. Patients presenting with ankle arthritis rarely developed CIRD, whereas patients presenting with wrist arthritis more frequently did so. Longer duration of joint swelling and ACPA and RF positivity were also predictive of CIRD. Our findings facilitate the early identification of patients with monoarthritis who have an unfavorable prognosis.
Therapeutic Modulation of Plasmacytoid Dendritic Cells in Experimental Arthritis
Authors: Nehmar Ramzi , Alsaleh Ghada , Voisin Benjamin , Flacher Vincent , Mariotte Alexandre , Saferding Victoria , Puchner Antonia , Niederreiter Birgit , Vandamme Thierry , Schabbauer Gernot , Kastner Philippe , Chan Susan , Kirstetter Peggy , Holcmann Martin , Mueller Christopher , Sibilia Jean , Bahram Seiamak , Blüml Stephan , Georgel Philippe 
Published: August 2017

ObjectiveThe role of plasmacytoid dendritic cells (PDCs) and type I interferons (IFNs) in rheumatoid arthritis (RA) remains a subject of controversy. This study was undertaken to explore the contribution of PDCs and type I IFNs to RA pathogenesis using various animal models of PDC depletion and to monitor the effect of localized PDC recruitment and activation on joint inflammation and bone damage.MethodsMice with K/BxN serum–induced arthritis, collagen‐induced arthritis, and human tumor necrosis factor transgene insertion were studied. Symptoms were evaluated by visual scoring, quantification of paw swelling, determination of cytokine levels by enzyme‐linked immunosorbent assay, and histologic analysis. Imiquimod‐dependent therapeutic effects were monitored by transcriptome analysis (using quantitative reverse transcriptase–polymerase chain reaction) and flow cytometric analysis of the periarticular tissue.ResultsPDC‐deficient mice showed exacerbation of inflammatory and arthritis symptoms after arthritogenic serum transfer. In contrast, enhancing PDC recruitment and activation to arthritic joints by topical application of the Toll‐like receptor 7 (TLR‐7) agonist imiquimod significantly ameliorated arthritis in various mouse models. Imiquimod induced an IFN signature and led to reduced infiltration of inflammatory cells.ConclusionThe therapeutic effects of imiquimod on joint inflammation and bone destruction are dependent on TLR‐7 sensing by PDCs and type I IFN signaling. Our findings indicate that local recruitment and activation of PDCs represents an attractive therapeutic opportunity for RA patients.
How a Transition‐Metal(II) Chloride Interacts with a Eutectic AlCl3‐Based Ionic Liquid: Insights into the Speciation of the Electrolyte and Electrodeposition of Magnetic Materials
Authors: Pulletikurthi Giridhar , Weidenfeller Bernd , Borodin Andriy , Namyslo Jan C. , Endres Frank 
Published: August 2017

AbstractElectrostatic interactions are characteristic of ionic liquids (ILs) and play a pivotal role in determining the formation of species when solutes are dissolved in them. The formation of new species/complexes has been investigated for certain ILs. However, such investigations have not yet focused on eutectic liquids, which are a promising class of ILs. These liquids (or liquid coordination complexes, LCCs) are rather new and are composed of cationic and anionic chloro complexes of metals. To date, these liquids have been employed as electrolytes to deposit metals and as solvents for catalysis. The present study deals with a liquid that is prepared by mixing a 1.2:1 mol ratio of AlCl3 and 1‐butylpyrrolidine. An attempt has been made to understand the interactions of FeCl2 with the organic molecule using spectroscopy. It was found that dissolved Fe(II) species interact mainly with the IL anion and such interactions can lead to changes in the cation of the electrolyte. Furthermore, the viability of depositing thick magnetic films of Fe and Fe–Al has been explored.
Intelligent, Biodegradable, and Self‐Healing Hydrogels Utilizing DNA Quadruplexes
Authors: Tanaka Shizuma , Wakabayashi Kenta , Fukushima Kazuki , Yukami Shinsuke , Maezawa Ryuki , Takeda Yuhei , Tatsumi Kohei , Ohya Yuichi , Kuzuya Akinori 
Published: August 2017

AbstractA new class of hydrogels utilizing DNA (DNA quadruplex gel) has been constructed by directly and symmetrically coupling deoxynucleotide phosphoramidite monomers to the ends of polyethylene glycols (PEGs) in liquid phase, and using the resulting DNA‐PEG‐DNA triblock copolymers as macromonomers. Elongation of merely four deoxyguanosine residues on PEG, which produces typically ≈10 grams of desired DNA‐PEG conjugates in one synthesis, resulted in intelligent and biodegradable hydrogels utilizing DNA quadruplex formation, which are responsive to various input signals such as Na+, K+, and complementary DNA strand. Gelation of DNA quadruplex gels takes place within a few seconds upon the addition of a trigger, enabling free formation just like Ca+‐alginate hydrogels or possible application as an injectable polymer (IP) gel. The obtained hydrogels show good thermal stability and rheological properties, and even display self‐healing ability.
Enhanced CO2 Capture Performance of Limestone by Industrial Waste Sludge
Authors: Hu Ying-chao , Liu Wen-qiang , Yang Yuan-dong , Sun Jian , Zhou Zi-jian , Xu Ming-hou 
Published: August 2017

AbstractAlthough inert supports have been proved effective to enhance CO2 capture performance of CaO sorbents, more commonly used supports are derived from expensive raw materials such as nitrates and organometallic precursors. Cheap waste sludge from the steel plant was utilized, which has a high daily output and has not received effective reuse, to promote the CO2 capture performance. The results showed that the sludge effectively promoted the performance of limestone. Homogeneously dispersed inert material of MgO, acting as the metal framework to resist sintering, was responsible for the enhanced performance. The introduction of waste sludge into the calcium looping could not only improve the sorbent performance, but also provide a potentially effective way to reuse the waste sludge.
Silicon Phthalocyanines Axially Disubstituted with Erlotinib toward Small‐Molecular‐Target‐Based Photodynamic Therapy
Authors: Chen Juan‐Juan , Huang Yi‐Zhen , Song Mei‐Ru , Zhang Zhi‐Hong , Xue Jin‐Ping 
Published: August 2017

AbstractSmall‐molecular‐target‐based photodynamic therapy—a promising targeted anticancer strategy—was developed by conjugating zinc(II) phthalocyanine with a small‐molecular‐target‐based anticancer drug. To prevent self‐aggregation and avoid problems of phthalocyanine isomerization, two silicon phthalocyanines di‐substituted axially with erlotinib have been synthesized and fully characterized. These conjugates are present in monomeric form in various solvents as well as culture media. Cell‐based experiments showed that these conjugates localize in lysosomes and mitochondria, while maintaining high photodynamic activities (IC50 values as low as 8 nm under a light dose of 1.5 J cm−2). With erlotinib as the targeting moiety, two conjugates were found to exhibit high specificity for EGFR‐overexpressing cancer cells. Various poly(ethylene glycol) (PEG) linker lengths were shown to have an effect on the photophysical/photochemical properties and on in vitro phototoxicity.
Development of Substrate‐Derived Sirtuin Inhibitors with Potential Anticancer Activity
Authors: Kuhlmann Nora , Chollet Constance , Baldus Linda , Neundorf Ines , Lammers Michael 
Published: August 2017

AbstractRhoGDIα is a key regulator of Rho proteins, coordinating their GTP/GDP and membrane/cytosol cycle. Recently, it was demonstrated by quantitative mass spectrometry that RhoGDIα is heavily targeted by post‐translational lysine acetylation. For one site in its N‐terminal domain, namely K52, we reported earlier that acetylation completely switches off RhoGDIα function. Herein we show that K52‐acetylated RhoGDIα is specifically deacetylated by the sirtuin deacetylase Sirt2. We show that acetylation at K52 decelerates cervical cancer cell proliferation, suggesting RhoGDIα acetylation to be a promising therapeutic target. We demonstrate that treatment of cervical cancer cells with a RhoGDIα‐derived K52‐trifluoroacetylated, substrate‐derived peptidic sirtuin inhibitor severely impairs cell proliferation. Finally, we conclude that the potency of substrate‐derived sirtuin inhibitors depends on structural features, the substrate‐derived amino acid sequence as a determinant for selectivity, as well as the presence of an acetyl‐lysine analogue to increase its potency. These data reveal a prospective therapeutic potential for novel substrate‐derived sirtuin inhibitors.
Adaptive real‐time anomaly detection in cloud infrastructures
Authors: Agrawal Bikash , Wiktorski Tomasz , Rong Chunming 
Published: August 2017

SummaryCloud computing has become increasingly popular, which has led many individuals and organizations towards cloud storage systems. This move is motivated by benefits such as shared storage, computation, and transparent service among a massive number of users. However, cloud‐computing systems require the maintenance of complex and large‐scale systems with practically unavoidable runtime problems caused by hardware and software faults. Large systems are very complex due to heterogeneity, dynamicity, scalability, hidden complexity, and time limitations. Automatic anomaly detection is a critical technique for managing such complex cloud resources. This paper proposes a scalable model for automatic anomaly detection on a large system like a cloud. The anomaly detection process is capable of issuing a correct early warning of unusual behavior in dynamic environments after learning the system characteristic of normal operation. To detect unusual activity in the cloud, we need to monitor the data center and collect cloud performance logs. In this paper, we propose an adaptive anomaly detection mechanism, which investigates principal components of the performance metrics. It transforms the performance metrics into a low‐rank matrix and calculates the orthogonal distance using the Robust PCA algorithm. The proposed model updates itself recursively, while learning and adjusting the new threshold value, to minimize reconstruction errors. This paper also investigates robust principal component analysis in distributed environments using Apache Spark as the underlying framework. It specifically addresses cases in which normal operation might exhibit multiple hidden modes. The accuracy and sensitivity of the model were tested on Amazon CloudWatch datasets, and Yahoo! datasets. The model achieved an accuracy of 88.54%.
Efficient and scalable execution of smart city parallel applications
Authors: Mastroianni Carlo , Cesario Eugenio , Giordano Andrea 
Published: August 2017

SummaryRecent research efforts in the field of urban computing aim to develop innovative services for citizens through the application of ubiquitous and pervasive computing paradigms in urban spaces. Smart city applications need to cope with a large number of involved users and devices. Since data and objects are strictly related to the territory on which they are defined and used, it is preferable, when possible, to perform computation locally through the adoption of dispersed computing nodes such as CPU‐equipped sensors. In this context, the computation related to smart city applications can be profitably and efficiently parallelized by partitioning the territory into regions and assigning the computation related to each single region to a local node. Nevertheless, the adoption of parallel computing models poses several communication and synchronization issues, especially when the number of nodes is large and the time constraints of applications are compelling. This paper presents and analyzes a parallel computing model for smart city applications in which each node needs to exchange information only with a subset of neighbor nodes, allowing the synchronization overhead to be significantly reduced. As sample application, we consider the analysis and prediction of internet traffic generated by vehicle and pedestrian devices moving on a smart avenue equipped with distributed computing nodes. This work offers a detailed performance evaluation in a number of scenarios, including uniform and nonuniform user distribution and different types of user mobility behavior. The results show that the presented computation model offers notable advantages in terms of computation efficiency and speedup, with respect to a classical all–to‐all synchronization paradigm, in which the nodes need to coordinate with a central entity.
An efficient approach of improving privacy and security in online social networks
Authors: Almasoud Suliman K. , Almogren Ahmad , Hassan Mohammad Mehedi , Alrassan Iehab 
Published: August 2017

SummaryOnline social networks (OSNs) have become popular and widely used by many people nowadays. As those OSNs increase, the virtual social interactions have resulted in increasing privacy and security concern. Many approaches have been proposed in order to provide users with “better” privacy protection, but none of those approaches have “fully succeeded,” due to their conflict with service providers' economic benefits or due to the suggestion of changing the OSNs architecture. In this paper, we propose a new model that would improve privacy and security in OSNs by preventing users from revealing private and or confidential information online as possible. We endeavor to create a balance between privacy and security improvement versus the service provider business model.
Continuous Carbon Hollow Shell with Zinc Oxide Nanoparticles Embedded as an Anode Material with Excellent Lithium Storage Capability
Authors: Mao Yuting , Wang Qin , Wu Xi , Xie Huiqi , Ma Xiaomei , Chen Min 
Published: August 2017

AbstractContinuous carbon hollow shells with embedded ZnO nanoparticles were synthesized from colloidal polystyrene/ZnO as templates and glucose oligomer as the carbon source followed by calcination. The resulting uniform ZnO/C hollow spheres display a relatively high reversible capacity of 994 mAh g−1 after 100 cycles at 0.1 A g−1 and 812 mAh g−1 after 200 cycles at 1 A g−1, which is superior to most reported ZnO‐based anode materials. The excellent electrochemical performance of the ZnO/C hollow spheres may arise from the following aspects: the shortened pathway of Li ions and electrolyte attributed to the unique hollow shell structures, improved electronic conductivity, firm encapsulation of ZnO nanoparticles, and high specific surface area of the products, which together facilitate the ZnO nanoparticles to undergo the alloying reaction completely.
Misreporting and econometric modelling of zeros in survey data on social bads: An application to cannabis consumption
Authors: Greene William , Harris Mark N. , Srivastava Preety , Zhao Xueyan 
Published: August 2017

AbstractWhen modelling “social bads,” such as illegal drug consumption, researchers are often faced with a dependent variable characterised by a large number of zero observations. Building on the recent literature on hurdle and double‐hurdle models, we propose a double‐inflated modelling framework, where the zero observations are allowed to come from the following: nonparticipants; participant misreporters (who have larger loss functions associated with a truthful response); and infrequent consumers. Due to our empirical application, the model is derived for the case of an ordered discrete‐dependent variable. However, it is similarly possible to augment other such zero‐inflated models (e.g., zero‐inflated count models, and double‐hurdle models for continuous variables). The model is then applied to a consumer choice problem of cannabis consumption. We estimate that 17% of the reported zeros in the cannabis survey are from individuals who misreport their participation, 11% from infrequent users, and only 72% from true nonparticipants.