The role of U(1)AU(1)_A symmetry breaking in the QCD corrections to the pion mass difference

The charged and neutral pion mass difference can be attributed to both the QED and QCD contributions. The current quark mass difference ($\Delta m$) is the source of the QCD contribution. Here, in a two-flavour non-local NJL model, we try to estimate the QCD contribution. Interestingly, we find that the strength of the $U(1)_A$ symmetry-breaking parameter $c$ plays a crucial role in obtaining the pion mass difference while intertwined with the current quark mass difference. To obtain the QCD contribution for the pion mass difference, we scan the parameter space in $\{\Delta m,\; c\}$, and by comparing this with the existing results, we constrained the parameter space. Further, using a fitted value of $c$, we determine the allowed range for the $\Delta m$ in the model. The model estimated $\Delta m$ ranges enable us to extract the chiral perturbation theory low-energy constant, $l_7$ and verify the dependence of the pion mass difference on $\Delta m$. We also find out its dependence on $c$ \textemdash\, it increases with the decreasing value of $c$, i.e., toward an axial anomaly restored phase.Comment: 12 pages, 6 captioned figures, discussion on l7 has been added, accepted in JP

Developing implementation indicators for public policy, case study: Tehran and Qom Agricultural Organizations

Public policies are problem oriented and solve a public problem. Making decision and policies does not solve problems by itself but they must be executed effectively. As executing policies is a main step of policy making, formulating indicators for implementing policy is necessary. In this article we conducted a content analysis of elites’ opinions to improve implementation of public policies. Therefore, three major factors have been introduced including policy making, environmental policy implementation and organizational structure factors. Sample data were taken from agricultural organizations of Tehran and Qom. For data gathering library research, interview and questionnaire were used. To analyze the data, k-s, Pearson’s correlation coefficient, confirmatory factors analysis and means comparisons were applied using SPSS and LISREL. Results show all of proposed indicators and measures are valid for implementation of public policies and about important of indicators between two participant groups, indicators in Tehran groups is more important

TOPOLOGICALLY-COMPRESSED ENERGYLESS FLIP-FLOP TO REDUCE CURRENT DISSIPATION

The paper proposes a higher speed i.e., a lesser delay TCFF with almost exactly the same power reduction, performance and cell area than the existing TCFF. Therefore the Massive Integration (LSI) makes the main focus because it is the area which needs to be overhauled. TCFF has a reduced transistor count according to logical equivalency. An very low-power switch-flop (FF) named topologically-compressed flip-flop (TCFF) is suggested. Compared to conventional FFs, the FF reduces power dissipation by 75% at % data activity. This power reduction ratio may be the greatest among FFs which have been reported to date. The reduction is achieved by making use of topological compression method, merger of logically equivalent transistors for an unconventional latch structure. The few transistors, only three, linked to clock signal cuts down on the power drastically, and also the smaller sized total transistor count assures exactly the same cell area as conventional FFs. Additionally, fully static full-swing operation helps make the cell loving toward supply current and input slew variation. A brand new approach is conducted, to be able to keep up with the same area and almost same power dissipation when compared with TCFF with a rise in speed. The Modified TCFF promises high-speed operation in which the Clubpenguin-Q delay continues to be reduced considerably associated with any the above mentioned methods. It utilizes a mix coupled logic with several Cascaded stage’s in which the logic functions like a Current Mirror Circuit to be able to supply the necessary current needed. An experimental nick design with 40 nm CMOS technology shows that the majority conventional FFs are replaceable with suggested FF while preserving exactly the same system performance and layout area

Importance of Financial Analysis for Published Financial Information to Predict the Stocks Behavior (Case study-ASE –Industrial Sector-Jordan)

This study aimed to identify the dimensions of the financial analysis and its advantages and how to benefit from it; in predicting stock prices by testing group of financial ratios and find a model quantitatively can be relied upon to predict the price per share of the industrial sector in the Amman Stock Exchange in order to help investors make rational decisions when they the investment process. To achieve this purpose has been tested three financial ratios for a sample of 30 companies listed their shares in the financial market, where data has been relying on published financial statements for its annual information. These ratios have been analyzed using the method of statistical known as a multiple regression to find the best model for the industrial sector of the financial market, which includes group of ratios (Many Variables) of Finance in which they can predict the price of stock in companies listed on the Amman Stock Exchange by this classification. Has been reached model for the industry where it appeared that the industry was affected by several variables affect the share price of this sector is the ratio of market value to book value and the percentage of the book value per ordinary share and the study concluded that it can rely on a set of financial ratios for each of the sectors (classified by the Palestine Securities Exchange) to predict the price of the arrow, study also recommended increased attention to the financial statements and transparency in the preparation and disclosure of the data and prepared according to international accounting standards, and it can an investor rely on financial analysis of the financial statements when making investment decisions. Keywords: Capital Asset Pricing Model (CAP.M), General Accounting Accepted Principle (GAAP), Earnings per Share (EPS), Book Value of share, Market Value of share, Stock Price

TRAFFIC DEDUCTION SCHEME WITH MANIPULATING ISSUES IN WSNS

Contextual info may be disclosed by eavesdropping on over-the-air communications and acquiring automatic transmission attributes, for instance inter-wrapper occasions, wrapper authority and haven IDs, and product and sizes of transmitted bags. Leakage of environmental info poses an appreciable risk for the WSN quest and action. We refined two methods for separating the WSN to MCDSs and SS-MCDSs and evaluated their show via simulations. When come forward methods in a reputation to surviving off your comprehensive snoop, we proven that restricting the oaf trade automatic transmissions to MCDS nodes, cuts pare over the link upward in consequence of movement normalization. Within the army control plot, the foe can link the occasions detected moment practicing the WSN to compromised worth. We feature our goal isn't to assemble presumably intelligent presumably compelling doubtless gorgeous delicate raid. This somewhat raid is extremely-time employing invulnerability agency and could call for further a pasta perceptive. First, auditors are laid-back devices whichever are demanding to diagnose. Second, the transfer of economical stock wireless plumbing causes it impending sane to open torrent of snoops. Third, even when file encryption allows you to comprise the carton weight, some fields not beyond the wrapper headers be transmitted not over the overt for respectable contract trip. We notify an interested form that computes an estimation of V’s dissolution by balancing in remembrances to the arrival prevalence, in the interest of MCDSs that span V, united with MCDS size

Critical Role of CA1 Nicotinic Receptors on Memory Acquisition Deficit Under Induction of Total Sleep Deprivation and REM Sleep Deprivation

Objective: Sleep disorder or sleep deprivation (SD) is a common issue in today’s society. Numerous evidences show that sleep is essential for proper brain performance and cognitive processes; on the other hand, cognitive functions have a broad range with learning and long-term memory as the most important ones related to attention. Since many studies show that cholinergic system has a significant role in sleep, learning, and memory, this study aims to investigate the impacts of CA1 Cholinergic Nicotinic Receptors on memory acquisition deficit which is stimulated by total sleep deprivation (TSD) and REM sleep deprivation (RSD).Methodology: In this study a water box or a multi-platform apparatus was used in order to induce total sleep deprivation (TSD) or REM sleep deprivation (RSD). In order to investigate interactions of cholinergic system and hippocampus-dependent memory, nicotinic receptor agonist (nicotine) or nicotinic receptor antagonist (mecamylamine) was injected in hippocampal CA1.  Results: According to the results of this study, 24 hours TSD or RSD decreased memory acquisition and injection of nicotine (0.0001  or mecamylamine (0.001  in TSD and RSD sham groups didn’t change memory acquisition. However, injection of sub-threshold dose of nicotine (0.0001  and mecamylamine (0.001  could reduce negative effects of SD in both TSD and RSD.Discussion; According to the present study, cholinergic nicotinic receptors are effective in learning and memory improvement.

The Relationship between the EPS & the Market Stock Return (Case Study: Industrial Sector-Jordan)

This topic is one of the more threads of financial market theory that have been studied by researchers in the accounting and finance field, and on the following the attempts by some scientists specialized financial to confirm or explain the result that reached by each of the study (Ball, R & P Brown) and study (Brown, L. D), which lead to low explanatory power of profit-variable in the regression model used to describe the relationship between stock returns and accounting profits. Because those researchers found during their review of previous studies and its evaluations in this area that profits generally do not explain more than 11% of the change in stock returns.   After we test the relationship between each of the (EPS &LEBS) and the market stock return we found the ability of each variable of the change in earnings per share and a variable level of earnings per share does not explain more than 9.9% of the market returns of shares joint stock companies listed in the industrial sector in the Amman Financial Market; The variation in the ability of winning each of the variable change in earnings per share and variable earnings per share in the interpretation of stock market returns makes it subject to identify the most variable interpretation of returns is not possible, or at least is characterized by a certain degree of difficulty. Finally the use of more than one representative of profits in the form of the relationship makes profits more ability to interpret market returns and reduce bias resulting from errors in the measurement of profits. Keywords’: Earnings per Share, Level of EPS, Industrial Sector, Amman Stock Exchange (ASE), Expected & Unexpected Return, Market Stock Return

Diabetes Prediction by Optimizing the Nearest Neighbor Algorithm Using Genetic Algorithm

Introduction: Diabetes or diabetes mellitus is a metabolic disorder in body when the body does not produce insulin, and produced insulin cannot function normally. The presence of various signs and symptoms of this disease makes it difficult for doctors to diagnose. Data mining allows analysis of patients’ clinical data for medical decision making. The aim of this study was to provide a model for increasing the accuracy of diabetes prediction. Method: In this study, the medical records of 1151 patients with diabetes were studied, with 19 features. Patients’ information were collected from the UCI standard database. Each patient has been followed for at least one year. Genetic Algorithm (GA) and the nearest neighbor algorithm were used to provide diabetes prediction model. Results: It was revealed that the prediction accuracy of the proposed model equals 0.76. Also, for the methods of Naïve Bayes, Multi-layer perceptron (MLP) neural network, and support vector machine (SVM), the prediction accuracy was 0.62, 0.65, and 0.75, respectively. Conclusion: In predicting diabetes, the proposed model has the lowest error rate and the highest accuracy compared to the other models. Naïve Bayes method has the highest error rate and the lowest accuracy