Multiple G-It\^{o} integral in the G-expectation space

In this paper, motivated by mathematic finance we introduce the multiple G-It\^{o} integral in the G-expectation space, then investigate how to calculate. We get the the relationship between Hermite polynomials and multiple G-It\^{o} integrals which is a natural extension of the classical result obtained by It\^{o} in 1951.Comment: 9 page

A decision tree algorithm for investigation of model biases related to dynamical cores and physical parameterizations

An object‐based evaluation method using a pattern recognition algorithm (i.e., classification trees) is applied to the simulated orographic precipitation for idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and the Eulerian spectral transform dynamical cores with varying resolutions. Daily simulations were analyzed and three different types of precipitation features were identified by the classification tree algorithm. The statistical characteristics of these features (i.e., maximum value, mean value, and variance) were calculated to quantify the difference between the dynamical cores and changing resolutions. Even with the simple and smooth topography in the idealized setups, complexity in the precipitation fields simulated by the models develops quickly. The classification tree algorithm using objective thresholding successfully detected different types of precipitation features even as the complexity of the precipitation field increased. The results show that the complexity and the bias introduced in small‐scale phenomena due to the spectral transform method of CAM Eulerian spectral dynamical core is prominent, and is an important reason for its dissimilarity from the FV dynamical core. The resolvable scales, both in horizontal and vertical dimensions, have significant effect on the simulation of precipitation. The results of this study also suggest that an efficient and informative study about the biases produced by GCMs should involve daily (or even hourly) output (rather than monthly mean) analysis over local scales.Key PointsThe complexity and the bias introduced in small‐scale phenomena due to the spectral transform method of CAM Eulerian spectral dynamical core are prominentThe classification tree algorithm with objective thresholding is successful in detecting different types of precipitation features with high spatial complexityAn efficient and informative study about the biases produced by GCMs should involve daily (or hourly) output (rather than monthly mean) analysis over local scalesPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/136040/1/jame20331.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/136040/2/jame20331_am.pd

Federated Learning in Vehicular Networks

Machine learning (ML) has already been adopted in vehicular networks for such applications as autonomous driving, road safety prediction and vehicular object detection, due to its model-free characteristic, allowing adaptive fast response. However, the training of the ML model brings significant overhead for the data transmission between the parameter server and the edge devices in the vehicles. Federated learning (FL) framework has been recently introduced as an efficient tool with the goal of reducing this transmission overhead while also achieving privacy through the transmission of only the model updates of the learnable parameters rather than the whole dataset. In this article, we investigate the usage of FL over ML in vehicular network applications to develop intelligent transportation systems. We provide a comprehensive analysis on the feasibility of FL for the ML based vehicular applications. Then, we identify the major challenges from both learning perspective, i.e., data labeling and model training, and from the communications point of view, i.e., data rate, reliability, transmission overhead/delay, privacy and resource management. Finally, we highlight related future research directions for FL in vehicular networks.Comment: 4 figures 7 pages. This work has been submitted to the IEEE for publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Treatment of Acute Otitis Media with Inner Ear Involvement in Adults

Inner ear involvement (IED) is a rare local complication of the very common acute otitis media (AOM). The most beneficial treatment for IED remains a matter of debate. The aim of this study is to analyze different treatment modalities based on hearing outcomes to contribute to the discussion of therapy for IED in AOM. This retrospective study includes 112 adult patients diagnosed with AOM with IED between 2000 and 2020. Patients either received conservative (systemic antibiotic and systemic steroid therapy), interventional (conservative plus myringotomy and tympanic tube) or operative (interventional plus antrotomy) treatment. Pre- and post-treatment pure tone audiometry was performed. The hearing outcome was compared, and hearing recovery was analyzed based on modified Siegel’s criteria. The pre-treatment pure tone average (PTA) was significantly (p < 0.05) higher in the operative group than in the other groups. All treatment modalities led to a significant hearing improvement (p < 0.001). The pre- and post-treatment hearing loss was predominantly observed in high frequencies 2–4 kHz. The operative group showed the highest rate of complete hearing recovery. While all treatment modalities led to a significant improvement in hearing, the operative group showed the most beneficial hearing results in patients with high pre-treatment hearing loss. It remains to be shown if the findings in patients with high pre-treatment hearing loss can be generalized to patients with mild or moderate pre-treatment hearing loss

SOCIAL APPEARANCE ANXIETY AND LEISURE TIME EXERCISE LEVEL OF HIGH SCHOOL STUDENTS

The aim of this study is to determine the Social Appearance Anxiety (SAA) and Leisure Time Exercise (LTE) levels of high school students according to school type, gender, sports license and grade levels and to find the correlation between SAA and LTE. 2383 high school students participate the study from 3 different cities. Data were collected using SAAS developed by Hart et al. (2008) was translated into Turkish by Doğan (2010) and LTEQ developed by Godin and Sheppard (1985 and 1997) was translated into Turkish by Lapa et al. (2016). As a result of the analysis, a significant difference was found between high school male and female students in terms of LTE. The research has shown that the SAA and LTE levels of vocational high school students are higher than Science and Anatolian high school students. In addition, 12th grade high school students have the lowest LTE level and the highest SAA level compared to other grades.  Article visualizations

There is no Nontrivial Hedging Portfolio for Option Pricing with Transaction Costs

Conventional wisdom holds that since continuous-time, Black-Scholes hedging is infinitely expensive in a model with proportional transaction costs, there is no continuous-time strategy which hedges a European call option perfectly. Of course, if one is attempting to dominate the European call rather than replicate it, then one can use the trivial strategy of buying one share of the underlying stock and holding to maturity. In this paper we prove that this is, in fact, the least expensive method of dominating a European call in a Black-Scholes model with proportional transaction costs

Efficiently correlating complex events over live and archived data streams

Correlating complex events over live and archived data streams, which we call Pattern Correlation Queries (PCQs), provides many benefits for domains which need real-time forecasting of events or identification of causal dependencies, while handling data at high rates and in massive amounts, like in financial or medical settings. Existing work has focused either on complex event processing over a single type of stream source (i.e., either live or archived), or on simple stream correlation queries (e.g., live events trigerring a database lookup). In this paper, we specifically focus on recency-based PCQs and provide clear, useful, and optimizable semantics for them. PCQs raise a number of challenges in optimizing data management and query processing, which we address in the setting of the DejaVu complex event processing system. More specifically, we propose three complementary optimizations including recent in-put buffering, query result caching, and join source ordering. Fur-thermore, we capture the relevant query processing tradeoffs in a cost model. An extensive performance study on synthetic and real-life data sets not only validates this cost model, but also shows that our optimizations are very effective, achieving more than two orders magnitude throughput improvement and much better scala-bility compared to a conventional approach

The ZEB1 Transcription Factor Is a Novel Repressor of Adiposity in Female Mice

gene located in that region, and as it influences the differentiation of various mesodermal lineages, we hypothesized that ZEB1 might also modulate adiposity. The goal of these studies was to test that hypothesis in mice. mice were heavier than WT controls, which was attributed by Echo MRI to increased fat mass (at three months on an HFD: 0.517±0.081 total fat/lean mass versus 0.313±0.036; at three months on an RCD: 0.175±0.013 versus 0.124±0.012). No differences were observed in food uptake or physical activity, suggesting that the genotypes differ in some aspect of their metabolic activity. ZEB1 expression also increases during adipogenesis in cell culture.These results show for the first time that the ZEB1 transcription factor regulates the accumulation of adipose tissue. Furthermore, they corroborate the genome-wide association studies that mapped an “obesity” gene at chromosome 10p11–12

A COMPARATIVE ANALYSIS OF THE FACTORS THAT INFLUENCE THE BRAND PREFERENCES OF UNIVERSITY STUDENTS STUDYING SPORTS IN TURKEY AND PORTUGAL

The purpose of this study is to find out and compare the factors effective in brand preferences of the students of Ondokuz Mayıs University Yaşar Doğu Faculty of Sport Sciences in Turkey and Instituto Politecnico da Guarda Faculty of Sports in Portugal in terms of sports products. 266 students (170 male, 96 female) attending sports faculties in Turkey and Portugal participated in this study. A questionnaire about the sports products preferences developed by Tozoğlu (2009) was used in order to find out the brand preferences of students. Student t-test was used to determine whether there is a significant difference between sport faculty students in Portugal and in Turkey. Chi square analysis was used to find out whether the students’ reasons for preferring a brand differed in terms of the schools, they were attending. Differences were found between the factors that affected the brand preferences of the students of Ondokuz Mayıs University (OMU) Yaşar Doğu Faculty of Sport Sciences and Instituto Politecnico da Guarda (IPG) Faculty of Sports in sports products. It was found that when compared with the students of IPG, students of OMU preferred brands since they provided quality guarantee, they were indicators of status and they gave a sense of security. It was found that students of OMU and IPG paid attention to the price while buying a brand product. Turkish students were found to be more dependent on brands when compared with Portuguese students. In addition, the price factor in the purchase of branded products is becoming a common element of the students of both countries. The tendency towards branded sporting products can manifest itself in increasing or decreasing proportions relative to advertising and promotional activities. The management of this orientation as a healthy process can be achieved by the effects of planned school education on the cultural structure.  Article visualizations

Vehicular Networks for Combating a Worldwide Pandemic: Preventing the Spread of COVID-19

As a worldwide pandemic, the coronavirus disease-19 (COVID-19) has caused serious restrictions in people's social life, along with the loss of lives, the collapse of economies and the disruption of humanitarian aids. Despite the advance of technological developments, we, as researchers, have witnessed that several issues need further investigation for a better response to a pandemic outbreak. With this motivation, researchers recently started developing ideas to stop or at least reduce the spread of the pandemic. While there have been some prior works on wireless networks for combating a pandemic scenario, vehicular networks and their potential bottlenecks have not yet been fully examined. This article provides an extensive discussion on vehicular networking for combating a pandemic. We provide the major applications of vehicular networking for combating COVID-19 in public transportation, in-vehicle diagnosis, border patrol and social distance monitoring. Next, we identify the unique characteristics of the collected data in terms of privacy, flexibility and coverage, then highlight corresponding future directions in privacy preservation, resource allocation, data caching and data routing. We believe that this work paves the way for the development of new products and algorithms that can facilitate the social life and help controlling the spread of the pandemic.Comment: 8pages5figure