Effect of network density and size on the short-term fairness performance of CSMA systems

As the penetration of wireless networks increase, number of neighboring networks contending for the limited unlicensed spectrum band increases. This interference between neighboring networks leads to large systems of locally interacting networks. We investigate whether the short-term fairness of this system of networks degrades with the system size and density if transmitters employ random spectrum access with carrier sensing (CSMA). Our results suggest that (a) short-term fair capacity, which is the throughput region that can be achieved within the acceptable limits of short-term fairness, reduces as the number of contending neighboring networks, i.e., degree of the conflict graph, increases for random regular conflict graphs where each vertex has the same number of neighbors, (b) short-term fair capacity weakly depends on the network size for a random regular conflict graph but a stronger dependence is observed for a grid deployment. We demonstrate the implications of this study on a city-wide Wi-Fi network deployment scenario by relating the short-term fairness to the density of deployment. We also present related results from the statistical physics literature on long-range correlations in large systems and point out the relation between these results and short-term fairness of CSMA systems. © 2012 Koseoglu et al; licensee Springer

The Effects of Twitter Sentiment on Stock Price Returns

Social media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-know micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment about the 30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We find a relatively low Pearson correlation and Granger causality between the corresponding time series over the entire time period. However, we find a significant dependence between the Twitter sentiment and abnormal returns during the peaks of Twitter volume. This is valid not only for the expected Twitter volume peaks (e.g., quarterly announcements), but also for peaks corresponding to less obvious events. We formalize the procedure by adapting the well-known "event study" from economics and finance to the analysis of Twitter data. The procedure allows to automatically identify events as Twitter volume peaks, to compute the prevailing sentiment (positive or negative) expressed in tweets at these peaks, and finally to apply the "event study" methodology to relate them to stock returns. We show that sentiment polarity of Twitter peaks implies the direction of cumulative abnormal returns. The amount of cumulative abnormal returns is relatively low (about 1-2%), but the dependence is statistically significant for several days after the events

Market Imitation and Win-Stay Lose-Shift Strategies Emerge as Unintended Patterns in Market Direction Guesses.

Decisions made in our everyday lives are based on a wide variety of information so it is generally very difficult to assess what are the strategies that guide us. Stock market provides a rich environment to study how people make decisions since responding to market uncertainty needs a constant update of these strategies. For this purpose, we run a lab-in-the-field experiment where volunteers are given a controlled set of financial information -based on real data from worldwide financial indices- and they are required to guess whether the market price would go "up" or "down" in each situation. From the data collected we explore basic statistical traits, behavioural biases and emerging strategies. In particular, we detect unintended patterns of behavior through consistent actions, which can be interpreted as Market Imitation and Win-Stay Lose-Shift emerging strategies, with Market Imitation being the most dominant. We also observe that these strategies are affected by external factors: the expert advice, the lack of information or an information overload reinforce the use of these intuitive strategies, while the probability to follow them significantly decreases when subjects spends more time to make a decision. The cohort analysis shows that women and children are more prone to use such strategies although their performance is not undermined. Our results are of interest for better handling clients expectations of trading companies, to avoid behavioural anomalies in financial analysts decisions and to improve not only the design of markets but also the trading digital interfaces where information is set down. Strategies and behavioural biases observed can also be translated into new agent based modelling or stochastic price dynamics to better understand financial bubbles or the effects of asymmetric risk perception to price drops

Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics

The new digital revolution of big data is deeply changing our capability of understanding society and forecasting the outcome of many social and economic systems. Unfortunately, information can be very heterogeneous in the importance, relevance, and surprise it conveys, affecting severely the predictive power of semantic and statistical methods. Here we show that the aggregation of web users’ behavior can be elicited to overcome this problem in a hard to predict complex system, namely the financial market. Specifically, our in-sample analysis shows that the combined use of sentiment analysis of news and browsing activity of users of Yahoo! Finance greatly helps forecasting intra-day and daily price changes of a set of 100 highly capitalized US stocks traded in the period 2012–2013. Sentiment analysis or browsing activity when taken alone have very small or no predictive power. Conversely, when considering a news signal where in a given time interval we compute the average sentiment of the clicked news, weighted by the number of clicks, we show that for nearly 50% of the companies such signal Granger-causes hourly price returns. Our result indicates a “wisdom-of-the-crowd” effect that allows to exploit users’ activity to identify and weigh properly the relevant and surprising news, enhancing considerably the forecasting power of the news sentiment

Dose estimation and dating of pottery from Turkey

The luminescence method is a widely used technique for environmental dosimetry and dating archaeological, geological materials. In this study, equivalent dose (ED) and annual dose rate (AD) of an archaeological sample were measured. The age of the material was calculated by means of equivalent dose divided by the annual dose rate. The archaeological sample was taken from Antalya, Turkey. Samples were prepared by the fine grain technique and equivalent dose was found using multiple-aliquot-additive-dose (MAAD) and single aliquot regeneration (SAR) techniques. Also the short shine normalization-MAAD and long shine normalization-MAAD were applied and the results of the methods were compared with each other. The optimal preheat temperature was found to be 200. °C for 10. min. The annual doses of concentrations of the major radioactive isotopes were determined using a high-purity germanium detector and a low-level alpha counter. The age of the sample was found to be 510±40 years. © 2012 Elsevier Ltd

Locally recurrent paratesticular rhabdomyosarcoma treated with surgery and radiotherapy

Paratesticular rhabdomyosarcoma is a highly malignant neoplasm and is exceedingly rare in adults, Thus, its biological behavior is unclear and there is no standard established treatment, The prognosis of recurrent paratesticular rhabdomyosarcoma is dismal in the elderly. Herein we describe a case of locally recurrent paratesticular rhabdomyosarcoma in a 68-year-old patient treated with surgery and radiotherapy

Acute hematological and metabolical side effects of chemoradiotherapy for inoperabl cervical cancer

[No Abstract Available

Quality of life assessment in women with breast cancer: A prospective study including hormonal therapy

Purpose: Evaluating the effect of hormonal treatment on quality of life (QoL) in breast cancer patients by using the Functional Assessment of Cancer Treatment (FACT) questionnaire is the main purpose of this trial. Methods: Breast cancer patients treated with adjuvant between January 2007 and December 2009 were evaluated. The first survey was done after patients completed their whole adjuvant treatment except for the hormonal therapy and this was as 'basal assessment.' The second survey was done 6 to 12 months after the basal surveys during their routine policlinic controls. The last survey was done within the last 18 to 24 months of the follow-up period. Results: The effect of marital status, number of pregnancies, residence in the village or city, hemoglobin levels, chemotherapy and hormonal therapy for any other reason except for breast cancer on the QoL could not be seen. Endocrine subscale scores were detected to be higher in patients aged >60 years than in younger ones. The other dimension scores were low in the elderly patient group. There was a statistically significant relationship between being >30 years old and improvement in the social well-being score (p=0.028). The functional well-being scores were found to be significantly higher in the patient group that had no comorbid disease (p=0.018). Endocrine subscale scores were statistically worse in patients who had psychiatric disease (p=0.057) but the general QoL data were similar with others. It was shown that all QoL scores for all dimensions had statistically significant changes (p<0.001) in terms of hormonal regimes. Conclusion: The diagnosis of breast cancer was found to be an independent factor that affects social well-being and social life in a negative way. We must give attention to complaints including complaints about sexual life and hormonal status in order to ensure compliance of patients with the required hormonal regimens. By the help of future research, we can improve the prognosis of this disease through increased treatment adherence and belief of patients. © 2013 Korean Breast Cancer Society. All rights reserved