Cancellation of soft and collinear divergences in noncommutative QED

In this paper, we investigate the behavior of non-commutative IR divergences and will also discuss their cancellation in the physical cross sections. The commutative IR (soft) divergences existing in the non-planar diagrams will be examined in order to prove an all order cancellation of these divergences using the Weinberg's method. In non-commutative QED, collinear divergences due to triple photon splitting vertex, were encountered, which are shown to be canceled out by the non-commutative version of KLN theorem. This guarantees that there is no mixing between the Collinear, soft and non-commutative IR divergences

Statistical Mechanics of the Chinese Restaurant Process: lack of self-averaging, anomalous finite-size effects and condensation

The Pitman-Yor, or Chinese Restaurant Process, is a stochastic process that generates distributions following a power-law with exponents lower than two, as found in a numerous physical, biological, technological and social systems. We discuss its rich behavior with the tools and viewpoint of statistical mechanics. We show that this process invariably gives rise to a condensation, i.e. a distribution dominated by a finite number of classes. We also evaluate thoroughly the finite-size effects, finding that the lack of stationary state and self-averaging of the process creates realization-dependent cutoffs and behavior of the distributions with no equivalent in other statistical mechanical models.Comment: (5pages, 1 figure

Investigating the relationship between low serum cholesterol and suicide in attempters with depression

Background & Objective: It has been postulated that depressed individuals with low total cholesterol levels may be more likely to die prematurely from suicide. This study aimed to examine the association between low serum cholesterol and suicide in depressed attempters. Materials & Methods: In this cross-sectional study, 180 suicide attempters, who met the inclusion criteria and were willing to participate in the study, were recruited in 2017. The data was collected using a demographic questionnaire and the Beck Depression Inventory-Second Edition (BDI-II). The blood cholesterol level was measured via an auto-analyzer. Results: The mean age was 26.39±10.75 years. The average cholesterol level in the moderate, severe, and serious depression groups was 151.30±35.23, 145.89±36.32, and 145.15±33.33, respectively. The mean age was higher in the group with a higher depression level, though the difference was not significant (P=0.06). The percentage of suicide attempts in single individuals was significantly higher (P=0.02). The mean cholesterol level in the group with the highest level of depression was the lowest, but the difference was insignificant (r=-.01, P=0.85). Only in females, the level of blood cholesterol showed a nearly significant difference between groups with different severities of depression (P=0.05). Cholesterol had a significant correlation with suicide frequency (P=0.008, r=0.28). Conclusion: Our results revealed no significant association between low serum cholesterol and suicide in attempters with depression; but low total serum cholesterol may be associated with depression and suicide in depressed subjects. Yet, more studies are required for verification of this causality. © 2020, Journal of Advances in Medical and Biomedical Research. All rights reserved

Competitive Intelligence Text Mining: Words Speak

Competitive intelligence (CI) has become one of the major subjects for researchers in recent years. The present research is aimed to achieve a part of the CI by investigating the scientific articles on this field through text mining in three interrelated steps. In the first step, a total of 1143 articles released between 1987 and 2016 were selected by searching the phrase "competitive intelligence" in the valid databases and search engines; then, through reviewing the topic, abstract, and main text of the articles as well as screening the articles in several steps, the authors eventually selected 135 relevant articles in order to perform the text mining process. In the second step, pre-processing of the data was carried out. In the third step, using non-hierarchical cluster analysis (k-means), 5 optimum clusters were obtained based on the Davies–Bouldin index, for each of which a word cloud was drawn; then, the association rules of each cluster was extracted and analyzed using the indices of support, confidence, and lift. The results indicated the increased interest in researches on CI in recent years and tangibility of the strong and weak presence of the developed and developing countries in formation of the scientific products; further, the results showed that information, marketing, and strategy are the main elements of the CI that, along with other prerequisites, can lead to the CI and, consequently, the economic development, competitive advantage, and sustainability in market

Path Signatures for Seizure Forecasting

Forecasting the state of a system from an observed time series is the subject of research in many domains, such as computational neuroscience. Here, the prediction of epileptic seizures from brain measurements is an unresolved problem. There are neither complete models describing underlying brain dynamics, nor do individual patients exhibit a single seizure onset pattern, which complicates the development of a `one-size-fits-all' solution. Based on a longitudinal patient data set, we address the automated discovery and quantification of statistical features (biomarkers) that can be used to forecast seizures in a patient-specific way. We use existing and novel feature extraction algorithms, in particular the path signature, a recent development in time series analysis. Of particular interest is how this set of complex, nonlinear features performs compared to simpler, linear features on this task. Our inference is based on statistical classification algorithms with in-built subset selection to discern time series with and without an impending seizure while selecting only a small number of relevant features. This study may be seen as a step towards a generalisable pattern recognition pipeline for time series in a broader context

Effects of different nutritional systems on seed germination and early seedling growth in medicinal pumpkin (Cucurbita pepo L.)

This study was carried out to determine the effect of different nutritional systems (chemical, biological and integrated) on germination and seedling growth in medicinal pumpkin (Cucurbita pepo L.). The statistical design was a randomized complete block design with four replications. Four levels of different fertilizing systems including chemical (T1), biological (a combination of nitrogen bacteria, Azospirillum brasilense and Glomus mosseae) (T2) and integrated fertilizing systems (biological fertilizer + 50% chemical fertilizer) (T3), and control (without fertilizer) (T0), were employed. The results indicated that the maximum seed germination was 95% and the highest seed germination rate with 30.4 per day was observed in the intergraded nutritional treatment. The experimental results showed that all nutritional treatments had positive effects on seed germination compared to control. The highest level of germination percentage with 95% and the highest rate of germination with 30.4 seeds per day were obtained in integrated nutritional treatment. However, the integrated nutritional system required more time to demonstrate its positive effect on the growth and yield of medicinal pumpkin compared to chemical system. The results of present experiment indicated that integrated nutritional treatment had the greatest positive impact on germination characteristics in medicinal pumpkin. Designing and developing such nutritional systems can guarantee and facilitate the achievement of long-term objectives of sustainable agriculture

Affordability assessment from a static to dynamic concept: A scenario�based assessment of cardiovascular medicines

The out�of�pocket payments for prescription medications can impose a financial burden on patients from low� and middle� incomes and who suffer from chronic diseases. The present study aims at evaluating the affordability of cardiovascular disease (CVD) medication in Iran. This includes measuring affordability through World Health Organization/Health Action International (WHO/HAI) methodology. In this method, affordability is characterized as the number of daysʹ wages of the lowest�paid unskilled government worker. The different medication therapy scenarios are defined in mono�and combination therapy approaches. This method adds on to WHO/HAI methodology to discover new approaches to affordability assessments. The results show the differences in the medicines affordability when different approaches are used in mono�and combination therapy between 6 main sub�therapeutic groups of CVD. It indicates the medicine affordability is not a static concept and it changes dynamically between CVD therapeutic subgroups when it used alone or in combination with other medicines regarding patients� characteristics and medical conditions. Hypertension and anti�arrhythmia therapeutic groups had the most non-affordability and hyperlipidemia had the most affordable medicines. Therefore, affordability can be considered as a dynamic concept, which not only affected by the medicine price but significantly affected by a patient�s characteristics, the number of medical conditions, and insurance coverage. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

Electrocardiographic changes in patients with tramadol-induced idiosyncratic seizures

Objectives To assess ECG changes in patients with tramadol-induced seizure(s) and compare these changes in lower and higher than 500 mg tramadol doses as a main goal. Material and methods In an analytical-cross sectional manner over 1 year, 170 patients with idiosyncratic seizure(s) after using tramadol, were studied. Full data were recorded for each patient. ECGs were taken from all the patients on admission and 1 h later and were assessed for findings. Results 70 of 170 patients (41.2) had used lower than 500 mg doses of tramadol while 90 patients (52.9) were included in the high dose group. Rate of female patients in the high dose group was significantly higher. The average age of patients in the high dose group was significantly lower (22.04 vs 25.76). The high dose group had significantly higher heart rates. There was no history of cardiovascular diseases; two patients had previous history of seizure. No significant difference was shown between low dose and high dose groups from the point of ECG changes. Discussion and conclusion Using doses higher than 500 mg is more frequently seen in women, young people and those who have not experienced previous use of tramadol. Terminal S wave, sinus tachycardia, and terminal R wave in the lead aVR are among the most common ECG changes in tramadol users. © 2016 The Emergency Medicine Association of Turke

Acute sleep deprivation increases portion size and affects food choice in young men

SummaryAcute sleep loss increases food intake in adults. However, little is known about the influence of acute sleep loss on portion size choice, and whether this depends on both hunger state and the type of food (snack or meal item) offered to an individual. The aim of the current study was to compare portion size choice after a night of sleep and a period of nocturnal wakefulness (a condition experienced by night-shift workers, e.g. physicians and nurses). Sixteen men (age: 23±0.9 years, BMI: 23.6±0.6kg/m2) participated in a randomized within-subject design with two conditions, 8-h of sleep and total sleep deprivation (TSD). In the morning following sleep interventions, portion size, comprising meal and snack items, was measured using a computer-based task, in both fasted and sated state. In addition, hunger as well as plasma levels of ghrelin were measured. In the morning after TSD, subjects had increased plasma ghrelin levels (13%, p=0.04), and chose larger portions (14%, p=0.02), irrespective of the type of food, as compared to the sleep condition. Self-reported hunger was also enhanced (p<0.01). Following breakfast, sleep-deprived subjects chose larger portions of snacks (16%, p=0.02), whereas the selection of meal items did not differ between the sleep interventions (6%, p=0.13). Our results suggest that overeating in the morning after sleep loss is driven by both homeostatic and hedonic factors. Further, they show that portion size choice after sleep loss depend on both an individual's hunger status, and the type of food offered