bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantifying safety risks of deep neural networks
Authors: Xu Peipei , Ruan Wenjie , Huang Xiaowei 
Published: July 2022

AbstractSafety concerns on the deep neural networks (DNNs) have been raised when they are applied to critical sectors. In this paper, we define safety risks by requesting the alignment of network’s decision with human perception. To enable a general methodology for quantifying safety risks, we define a generic safety property and instantiate it to express various safety risks. For the quantification of risks, we take the maximum radius of safe norm balls, in which no safety risk exists. The computation of the maximum safe radius is reduced to the computation of their respective Lipschitz metrics—the quantities to be computed. In addition to the known adversarial example, reachability example, and invariant example, in this paper, we identify a new class of risk—uncertainty example—on which humans can tell easily, but the network is unsure. We develop an algorithm, inspired by derivative-free optimization techniques and accelerated by tensor-based parallelization on GPUs, to support an efficient computation of the metrics. We perform evaluations on several benchmark neural networks, including ACSC-Xu, MNIST, CIFAR-10, and ImageNet networks. The experiments show that our method can achieve competitive performance on safety quantification in terms of the tightness and the efficiency of computation. Importantly, as a generic approach, our method can work with a broad class of safety risks and without restrictions on the structure of neural networks.
A coin selection strategy based on the greedy and genetic algorithm
Authors: Wei Xuelin , Wu Chang , Yu Haoran , Liu Siyan , Yuan Yihong 
Published: July 2022

AbstractCoin selection method refers to the process undergone when selecting a set of unspent transaction outputs (UTXOs) from a cryptocurrency wallet or account to use as inputs in each transaction. The most applied coin selection method that UTXO-based cryptocurrencies currently employ is an algorithm that decides on a certain set of UTXOs that matches the target amount and limits the transaction fee. However this approach trades off favourable maintenance overhead of the entire network for low transaction fees, as many low-value UTXOs known as “dust” is produced. Over time, this will impact the scalability and management of the cryptocurrency network as the global set of UTXOs become larger. Therefore, there is an urgency to find a higher-performing coin selection method suitable for UTXO-based cryptocurrencies. This paper proposes a method based on the greedy and genetic algorithm for effectively choosing sets of UTXOs in Bitcoin. The main objective of this coin selection strategy is to get as close as possible to the target while also maintaining and possibly reducing the number of UTXO inputs.
Deep learning based brain tumor segmentation: a survey
Authors: Liu Zhihua , Tong Lei , Chen Long , Jiang Zheheng , Zhou Feixiang , Zhang Qianni , Zhang Xiangrong , Jin Yaochu , Zhou Huiyu 
Published: July 2022

AbstractBrain tumor segmentation is one of the most challenging problems in medical image analysis. The goal of brain tumor segmentation is to generate accurate delineation of brain tumor regions. In recent years, deep learning methods have shown promising performance in solving various computer vision problems, such as image classification, object detection and semantic segmentation. A number of deep learning based methods have been applied to brain tumor segmentation and achieved promising results. Considering the remarkable breakthroughs made by state-of-the-art technologies, we provide this survey with a comprehensive study of recently developed deep learning based brain tumor segmentation techniques. More than 150 scientific papers are selected and discussed in this survey, extensively covering technical aspects such as network architecture design, segmentation under imbalanced conditions, and multi-modality processes. We also provide insightful discussions for future development directions.
A simple method to form a forest of carbon nanotube bundles during growth stage
Authors: Alzahrani Ahmed Obaid M. , Alayash Meshari , Alghamdi Salem 
Published: July 2022

Abstract
This study reports a novel, cost-effective and reproducible method of densifying carbon nanotubes into bundles during growth stage. This is achieved by utilizing Fe3O4 catalyst nanoparticles and microwave plasma-enhanced chemical vapor deposition. The grown CNTs were characterized using TEM, SEM and Raman spectrometer. The achieved site density of bundles is 5 × 109 m–2, with an inter-bundle distance of 14 μm and bundle height of 17 μm. A qualitative investigation was carried out, and a possible densification mechanism was proposed.

Article Highlights

A cost-effective method to form bundles of carbon nanotubes.

Densification of carbon nanotubes occurs during growth stage.

The resultant structures are desirable for electron field emission applications.
Analyzing the EU Migration Crisis as Reflected on Twitter
Authors: Mukherjee Sagnik , Hauthal Eva , Burghardt Dirk 
Published: July 2022

AbstractThe proliferation of social media has resulted in its extensive use as a valuable source of information for researchers. This paper aims to use Twitter data to analyze and visualize tweets about the migration crisis in the European Union from 2016 to 2021. The paper uses a methodology to structure data for better understanding of complex social media data. The methods and metrics include the facet model of location based social media, the HyperLogLog data structure and novel uses of the metric typicality. The authors have also developed a web based interactive application closely following the methodology used to organize the dataset. Additionally the work also includes maps using spatial typicality which could be utilized for studying spatial phenomenon. The case study selected also provides unique insights and sets a template for working with multi-lingual geo-social media data. The authors believe that these methods and metrics could be reproduced for other case studies and aid in understanding and communication geo-social media data.
Modelling the Impact of Individual Preferences on Traffic Policies
Authors: Nguyen Johannes , Powers Simon T. , Urquhart Neil , Farrenkopf Thomas , Guckert Michael 
Published: July 2022

AbstractUrban traffic is a system always prone to overload, often approaching breakdown during rush hour times. Well-adjusted modifications of traffic policies, with appropriate interventions, promise potential improvements by inducing change in both individual as well as global system behaviour. However, truly effective measures are hard to identify, and testing in vivo is at least expensive and often hardly feasible. Computer-based simulations have successfully been applied for studying effects of policies, and multi-agent systems are accepted tools for that purpose as they provide means to model individual behaviour. These simulations have primarily studied effects of policies by measuring performance indicators on social benefit, while effects on individuals are hardly considered. However, successful implementation of policies hinges on whether they are accepted by the common public. Thus, effects on individuals cannot be neglected. Evaluating effects on individuals requires a more detailed modelling that is able to capture individual preferences as determining factors of agent decisions. In this paper, we present a simulation framework that focuses on modelling of individuals and thus allows evaluation of effects of policies on both the individual as well as global system behaviour. We use semantic technology (OWL ontologies and SWRL rules) to model preferences and knowledge of agents in our simulation. Using AGADE Traffic simulator, we demonstrate modelling and simulation for a mobility scenario and discuss observed results.
Spatial social network research: a bibliometric analysis
Authors: Wu Ling , Peng Qiong , Lemke Michael , Hu Tao , Gong Xi 
Published: July 2022

AbstractA restless and dynamic intellectual landscape has taken hold in the field of spatial social network studies, given the increasingly attention towards fine-scale human dynamics in this urbanizing and mobile world. The measuring parameters of such dramatic growth of the literature include scientific outputs, domain categories, major journals, countries, institutions, and frequently used keywords. The research in the field has been characterized by fast development of relevant scholarly articles and growing collaboration among and across institutions. The Journal of Economic Geography, Annals of the Association of American Geographers, and Urban Studies ranked first, second, and third, respectively, according to average citations. The United States, United Kingdom, and China were the countries that yielded the most published studies in the field. The number of international collaborative studies published in non-native English-speaking countries (such as France, Italy, and the Netherlands) were higher than native English-speaking countries. Wuhan University, the University of Oxford, and Harvard University were the universities that published the most in the field. “Twitter”, “big data”, “networks”, “spatial analysis”, and “social capital” have been the major keywords over the past 20 years. At the same time, the keywords such as “social media”, “Twitter”, “big data”, “geography”, “China”, “human mobility”, “machine learning”, “GIS”, “location-based social networks”, “clustering”, “data mining”, and “location-based services” have attracted increasing attention in that same time frame, indicating the future research trends.
Platelet Rich Plasma (PRP) Growth Factor Concentration Varies in Men with Erectile Dysfunction
Authors: Khodamoradi Kajal , Dullea Alexandra , Golan Roei , Molina Manuel , Arora Himanshu , Masterson Thomas A. , Ramasamy Ranjith 
Published: July 2022

ABSTRACT

Background
Platelet Rich Plasma (PRP) is a novel therapy rich in growth factors and cytokines used to target the underlying causes of erectile dysfunction (ED). It is not known, however, if the composition of growth factors in PRP varies between men.

Aim
To evaluate PRP growth factor variability among men with ED.

Methods
Whole blood was collected from 8 participants with at least a 6-month history of ED. Seven men with Peyronie’s disease and 1 healthy male (without sexual dysfunction) were used as the control group. PRP was extracted from whole blood using the Arthrex Angel system. A Human Growth Factor Antibody Array for 41 proteins was performed using 3 participants and the healthy control. Using all 16 samples, quantitative detection of factors from the array that were decreased by 1.5-fold were validated with western blot.

Outcomes
From the growth factor array, 2 growth factors—granulocyte-macrophage colony stimulating factor and transforming growth factor-β were identified as having a 1.5-fold decrease between the participants and the control. Vascular endothelial growth factor (VEGF) was selected because androgens can upregulate VEGF production. Other than a weak negative correlation between VEGF expression and age, we found no correlation between growth factor expression for granulocyte-macrophage colony stimulating factor or transforming growth factor-β and age, body mass index, or comorbidities.

Clinical Translation
PRP growth factor concentration appears to vary among men with ED. PRP treatment for ED may need to be personalized for patients, depending on individual growth factor concentration.

Strengths and Limitations
This study demonstrates the variability in PRP growth factors among men with ED. This is an important finding in the investigation of PRP as a restorative treatment option for men with ED. Our study, however, was limited by a small sample size.

Conclusion
PRP growth factors vary among men with ED.
The Housing Crisis in Superstar Cities: Labour Markets, Price Inflation, and Financialization
Authors: Findeisen Francesco 
Published: July 2022

AbstractThis article advances explanations of the housing crisis in modern political economies. It argues that the rise of agglomeration economies is driving the massive increase in housing prices in superstar cities. These concentrate high-paying jobs and life chances in central metropolitan areas, pulling in a highly skilled workforce who are willing and able to pay ‘whatever it takes’ for access to these opportunities. As a result, the value of homeownership in strategic urban locations has surged. Investors have thus found it rational to capitalize on longer-term price inflation and invest. Based on a comparison between New York City, London, Paris, and Berlin, this article demonstrates that housing prices in superstar cities move in lockstep with the reconfiguration of urban labour markets. Investors follow this trend in their decisions to invest in housing, which further compounds affordability pressures. The article concludes that access to homeownership in strategic urban locations increasingly mediates inequality and class formation in modern political economies.
Tisagenlecleucel for relapsed/refractory acute lymphoblastic leukemia in the Irish healthcare setting: cost-effectiveness and value of information analysis
Authors: Carey Niamh , Leahy Joy , Trela-Larsen Lea , McCullagh Laura , Barry Michael 
Published: July 2022

Abstract

Objectives
This study evaluates the cost-effectiveness of tisagenlecleucel (a CAR T-cell therapy), versus blinatumomab, for the treatment of pediatric and young adult patients with relapsed/refractory acute lymphoblastic leukemia (R/R ALL) in the Irish healthcare setting. The value of conducting further research, to investigate the value of uncertainty associated with the decision problem, is assessed by means of expected value of perfect information (EVPI) and partial EVPI (EVPPI) analyses.

Methods
A three-state partitioned survival model was developed. A short-term decision tree partitioned patients in the tisagenlecleucel arm according to infusion status. Survival was extrapolated to 60 months; general population mortality with a standardized mortality ratio was then applied. Estimated EVPI and EVPPI were scaled up to population according to the incidence of the decision.

Results
At list prices, the incremental cost-effectiveness ratio was EUR 73,086 per quality-adjusted life year (QALY) (incremental costs EUR 156,928; incremental QALYs 2.15). The probability of cost-effectiveness, at the willingness-to-pay threshold of EUR 45,000 per QALY, was 16 percent. At this threshold, population EVPI was EUR 314,455; population EVPPI was below EUR 100,000 for each parameter category.

Conclusions
Tisagenlecleucel is not cost effective, versus blinatumomab, for the treatment of pediatric and young adult patients with R/R ALL in Ireland (at list prices). Further research to decrease decision (parameter) uncertainty, at the defined willingness-to-pay threshold, may not be of value. However, there is a high degree of uncertainty underpinning the analysis, which may not be captured by EVPI analysis.
Psilocybin in neuropsychiatry: a review of its pharmacology, safety, and efficacy
Authors: Dodd Seetal , Norman Trevor R. , Eyre Harris A. , Stahl Stephen M. , Phillips Arnie , Carvalho André F. , Berk Michael 
Published: July 2022

AbstractPsilocybin is a tryptamine alkaloid found in some mushrooms, especially those of the genus Psilocybe. Psilocybin has four metabolites including the pharmacologically active primary metabolite psilocin, which readily enters the systemic circulation. The psychoactive effects of psilocin are believed to arise due to the partial agonist effects at the 5HT2A receptor. Psilocin also binds to various other receptor subtypes although the actions of psilocin at other receptors are not fully explored. Psilocybin administered at doses sufficient to cause hallucinogenic experiences has been trialed for addictive disorders, anxiety and depression. This review investigates studies of psilocybin and psilocin and assesses the potential for use of psilocybin and a treatment agent in neuropsychiatry. The potential for harm is also assessed, which may limit the use of psilocybin as a pharmacotherapy. Careful evaluation of the number needed to harm vs the number needed to treat will ultimately justify the potential clinical use of psilocybin. This field needs a responsible pathway forward.
Vertical Transport of Sensible Heat and Meteoric Na by the Complete Temporal Spectrum of Gravity Waves in the MLT Above McMurdo (77.84°S, 166.67°E), Antarctica
Authors: Chu Xinzhao , Gardner Chester S. , Li Xianxin , Lin Cissi Ying‐Tsen 
Published: July 2022

AbstractWe report the first lidar observations of vertical fluxes of sensible heat and meteoric Na from 78 to 110 km in late May 2020 at McMurdo, Antarctica. The measurements include contributions from the complete temporal spectrum of gravity waves and demonstrate that wave‐induced vertical transport associated with atmospheric mixing by non‐breaking gravity waves, Stokes drift imparted by the wave spectrum, and perturbed chemistry of reactive species, can make significant contributions to constituent and heat transport in the mesosphere and lower thermosphere (MLT). The measured sensible heat and Na fluxes exhibit downward peaks at 84 km (−3.0 Kms−1 and −5.5 × 104 cm−2s−1) that are ∼4 km lower than the flux peak altitudes observed at midlatitudes. This is likely caused by the strong downwelling over McMurdo in late May. The Na flux magnitude is double the maximum at midlatitudes, which we believe is related to strong persistent gravity waves in the MLT at McMurdo. To achieve good agreement between the measured Na flux and theory, it was necessary to infer that a large fraction of gravity wave energy was propagating downward, especially between 80 and 95 km where the Na flux and wave dissipation were largest. These downward propagating waves are likely secondary waves generated in‐situ by the dissipation of primary waves that originate from lower altitudes. The sensible heat flux transitions from downward below 90 km to upward from 97 to 106 km. The observations are explained with the fully compressible solutions for polarization relations of primary and secondary gravity waves with λ

z
> 10 km.
Magnetic Fabric Signature Within a Thrust Imbricate; an Analog Modeling Approach
Authors: Schöfisch T. , Koyi H. , Almqvist B. 
Published: July 2022

AbstractIn this study, we report results from three analog models with a similar initial setup and different amounts of bulk shortening, to simulate the development of a thrust imbricate in fold‐and‐thrust belts at different stages. Samples are taken at the back‐ and forethrusts, in the complex forekink zones, and at random distances to thrusts for analysis using anisotropy of magnetic susceptibility as strain indicator. This analysis shows that three distinct types of magnetic fabric can be identified throughout the models: (a) a compactional oblate fabric that changes as a function of distance toward a localized deformation zone (e.g., thrust or kinkzone), (b) a thrust‐induced fabric with magnetic foliation parallel to the thrust surface depicting its geometry, and (c) a complex forekink zone fabric with broad girdle distributions of principal axes and magnetic lineation perpendicular to the shortening direction. The latter indicates an interplay between folding and thrusting of the shortened sand layers. Additionally, a decrease in the degree of anisotropy with appearance of a quantitatively more prolate fabric can be observed toward the thrusts and kinkzones. Moreover, a thrust‐induced fabric is inherited by the variation of strain, depicted by changes in magnetic fabrics. In conclusion, our analysis of model results shows that strain changes as a function of distance toward localized deformation zones with characteristic magnetic fabrics that develop as deformation continues.
Distribution of Rare Earth Elements and Yttrium in Sediments From the Clarion‐Clipperton Fracture Zone, Northeastern Pacific Ocean
Authors: Kim Mun Gi , Hyeong Kiseong , Yoo Chan Min 
Published: July 2022

AbstractDeep‐sea sediments enriched in rare earth elements and yttrium (REY) are attracting scientific and exploration attention as a new REY resource. In the Clarion‐Clipperton Fracture Zone (CCFZ) of the northeastern Pacific, sedimentary units with high REY contents (average REY content >700 ppm) occur sporadically at only a few decimeters beneath the sediment surface covered with polymetallic nodules. Here we report the results of bulk chemical and sequential extraction analyses of sediment cores containing these units, collected from the southeastern part of the CCFZ. Correlations between element contents and shale‐normalized REY patterns suggest that the REY are associated primarily with calcium phosphates. Sequential extraction to determine the contribution from different sedimentary components confirms that calcium phosphates contain >70% of trivalent REY in REY‐enriched units. Despite the study location being favorable for nodule formation and subject to distal hydrothermal plume fallout, only subordinate amounts of REY are hosted by Mn‐ and Fe‐(oxyhydr)oxides. Hydrothermal Fe‐(oxyhydr)oxides may have played a more important role in accumulating REY, as evidence suggest that large amounts of Fe‐(oxyhydr)oxides have been transformed into Fe‐rich smectite during early diagenesis of REY‐enriched units.
The Relative Contribution of Climatic, Demographic Factors, Disease Control Measures and Spatiotemporal Heterogeneity to Variation of Global COVID‐19 Transmission
Authors: Cao Yihan , Whittington Jason D. , Kausrud Kyrre , Li Ruiyun , Stenseth Nils Chr. 
Published: July 2022

AbstractDespite a substantial number of COVID‐19 related research papers published, it remains unclear as to which factors are associated with the observed variation in global transmission and what are their relative levels of importance. This study applies a rigorous statistical framework to provide robust estimations of the factor effects for a global and integrated perspective on this issue. We developed a mixed effect model exploring the relative importance of potential factors driving COVID‐19 transmission while incorporating spatial and temporal heterogeneity of spread. We use an integrated data set for 87 countries across six continents for model specification and fitting. The best model accounts for 70.4% of the variance in the data analyzed: 10 fixed effect factors explain 20.5% of the variance, random temporal and spatial effects account for 50% of the variance. The fixed effect factors are classified into climatic, demographic and disease control groups. The explained variance in global transmission by the three groups are 0.6%, 1.1%, and 4.4% respectively. The high proportion of variance accounted for by random effects indicated striking differences in temporal transmission trajectories and effects of population mobility among the countries. In particular, the country‐specific mobility‐transmission relationship turns out to be the most important factor in explaining the observed global variation of transmission in the early phase of COVID‐19 pandemic.