where P is the efficacy percent of each term and b is the coefficient of each term of the model (according to Eq. (7)). Considering this equation, the effect of each parameter is illustrated in Figure 11. In this figure, blue bars indicate terms with positive effects on the model, and red bars show terms with negative effects. As is observed, all factors, except pH, have positive effects on the model. In other words, if the interaction effects are not considered, as each of factors (except pH) increases, COD removal percent will increase. The interaction term of catalyst loading and pH (AB), the interaction term of pH and oxidant dosage (BC), the interaction term of oxidant dosage and aeration rate (CD) have positive effects; the interaction term of catalyst loading and oxidant dosage (AC) as well as interaction term of pH and aeration rate (BD) have negatively affected the model. The negative second-order terms were attained for all the factors studied that correspond to concave surfaces, showing a higher rate of decrease of COD removal efficiency at the very high level of the main factors over the considered range of experiments.
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First of all, low tariff rates show positive relationships with the duration of trade relationships, implying 8.1% lower hazard ratio for the manufactured goods, as well as 8.4% lower hazard ratio for the interaction term of low tariff in intra-regional trade. This result is reasonable; firm would like to export or export because of more free mobility and lower transaction costs and through regional integration and tariff cut. Next, we find parts and components with low tariff show 20.2% in Columns (2) and 18.4% in Columns (3) lower hazard ratios in international production networks. In particular, parts and components of ASEAN+6 with low tariff show 16.8% lower hazard ratios. Similar applied in Rauch product’s classification, it is noticeable that differentiated products with low tariff exhibit 11% lower hazard ratios in Columns (4). Besides, differentiated products of ASEAN+6 with low tariff show 7.7% lower hazard ratios. The results of homogenous goods are in line with Besedeš and Prusa (2006b), even though we consider the effect of tariff cut. However the results are inverse with inclusion of intra-regional effect, indicating the importance of regional trade. Our findings provide the presence of lower hazard ratios due to effect of regional trade and tariff cut regarding production networks and Rauch product’s classification that previous studies ignore.
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where λ is the constant birth rate, μ is the natural death rate, is the fraction of infected individuals who leave the infected class per unit time, β is the rate of production of new infected individuals, and f(S, I) is a function re- lating the rate of conversion of the susceptible population to the infected population. Mickens  introduced first time the square root interaction term in the SIR-model is given by
positively influences organizational reputation. The addition of the interaction term (organizational financial performance x the proportion of independent directors in the managerial board) into Model 2 makes an increase in the explanatory power of the research model to 0.413 from 0.389 (a increase by 0.023) with the change significance level of smaller than 5%. Moreover, the interaction term of organizational financial performance and the proportion of independent directors positively impacts organizational reputation at the 5% significance level with the influential coefficient of 6.725, in support of the moderating hypothesis ―the proportion of independent executives moderates the causal relationship from organizational financial performance to organizational reputation‖. The findings imply that, the composition of managerial boards affects the causal association between organizational financial performance and organizational reputation in the way if the proportion of independent executives in the managerial board increases, then the casual link from organizational financial performance to organizational reputation becomes stronger.
The findings in Table 13 shows that the moderating effect of external operating environment on the relationship between corporate growth strategies and firm performance was positive and significant since the interaction term had a positive and significant beta coefficient ( Beta = 0.010, P< 0.000). The findings corroborated findings by Henk, Niels, Ernst, Marten and Antonio (2012) that firms operating environment determined its adaptability of corporate growth strategies towards performance. The findings are also consistent with Hsiang, Hsien and Dja-Shin (2012) who established that operating environment has positive and significant impact on relationship between corporate growth strategies and firm performance. Results indicate that when the interaction of corporate growth strategies and external operating environment was introduced to the relationship between corporate growth strategies as well as external operating environment and firm performance, the effect of corporate growth strategies is increased ( from Beta = 0.011 to 0.028). This implies that through interaction with the external operating environment, the effect of corporate growth strategies improves performance. The findings therefore suggest that the manufacturing firms need to analyze external operating environment in developing effective corporate growth strategies towards superior performance.
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For this end, an interaction term of the Lagrangian density of a weakly inter- acting Dirac particle has been constructed . The Lagrangian density obtained therein describes weak interactions between two spin- 1 2 Dirac particles which are mediated by an appropriate weak field. The theory abides by the dimensions of the Fermi coupling constant G F and by its universality. It is proved in 
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(12) These four equations derive that (6) = γ and (7) = δ . This implies that (6) can be expressed by one regression parameter regardless of the interaction term be- ing 0 when we use a regression model with dummy variables set to t = = p 1 2 and c = = − n 1 2 . Hence, γ can be used as a measure for prognosis. We note that, when we use ordinal dummy variables t = = p 1 and c = = n 0 , we again obtain (7) = δ , but (6) = γ + δ ⁄2, which is different to γ when δ ≠ 0 . This im- plies that (6) can only be expressed by one regression parameter when δ = 0 . 3.3. Expression by Response Type on a Binary Outcome
We measured COPD exacerbation rate, which was defined as the total number of COPD exacerbations during the 12-month post-index period divided by the total number of person years for each treatment group. ED visits resulting in a hospital stay were counted as an inpatient hospitaliza- tion only. OCS or antibiotic fills occurring within 14 days of an ED visit or inpatient hospitalization were counted as a single event. Similar to the primary outcome above, an interaction model – including an interaction term between prior asthma diagnosis and the index medication – was constructed as a post hoc sensitivity analysis of the COPD exacerbation rate outcome, and results stratified by asthma group were obtained.
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The aspect-based sentiment analysis (ABSA) task is to identify opinions expressed towards specific entities such as laptop or attributes of entities such as price (Liu, 2012a). This task involves three sub- tasks: Aspect Term Extraction (ATE), Aspect Po- larity Detection and Aspect Category Detection. As a fundamental subtask in ABSA, the goal of the ATE task is to identify opinionated aspect ex- pressions. One of most important characteristics is that opinion words can provide indicative clues for aspect detection since opinion words should co-occur with aspect words. Most publicly avail- able datasets contain the gold standard annotations for opinionated aspects, but the ground truth of the corresponding opinion words is not commonly provided. Some works tackling the ATE task ig- nore the consideration of opinion words and just focus on aspect term modeling and learning (Jin
In this representation λ is a plan and is composed of a sequence of terms t i . Each term could be either an atomic action a or a multiple branch over k sensed properties c 1 , . . . , c k . We assume all the conditions c i to be mutu- ally exclusive with each other and that each c i is associ- ated to a term t i that will be executed when c i is true. These branches are enclosed between angular brackets ( < > ) and colons (:) separate the different branches. In case conditions are not mutually exclusive and more conditions c i are true at the time they are evaluated by the PNP engine, a non- deterministic transition towards one of the true branches will occur.
This statement says that we can describe an observed value x ij (a response time, or accuracy measure, for example) as made up of three components - the over all mean µ, the average effect of the ith treatment effect ( τ i ), and a random error component ( ε ij ) that is unique to this particular observation j of treatment i. This statistical model assumes that the treatment effects (τ i ) which are the experimental factors or conditions in a psycholinguistic experiment are different from each other. When we find that the treatment effects are different from each other (see below) we can report that there was “a main effect of factor τ ” (we’ll get to interaction effects later). This means that the best fitting statistical model includes this factor. The ANOVA compares the model with τ against the null hypothesis which says that we can just as accurately describe the data with a “no treatments” model.
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Figure 3 shows representative sweeps taken from ve- hicle- and Cap-treated animal that received HFS for 6 days. Induction was characterized by an increase in the repetitive population spike activity which masked the enhancement of the early monosynaptic field excit- atory postsynaptic potential (fEPSP) and a potentiation of longer latency polysynaptic component (Chapman, et al., 1998; Trepel & Racine, 1998). There was a sig- nificant interaction effect between session and group for late component (ANOVA; P<0.001), the potential magnitude of both train (n=10) and Cap (n=9) groups were significantly higher compared to the control group (n=8) at the end of the stimulation period (Tukey HSD; P<0.005). The train group showed significantly greater potentiation than the Cap-treated group in the 6th day of induction period (P<0.01).
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The increasing complexity of Spoken Dialogue Systems (SDS) and the requirements that come with this progress made automatized recognition and modeling of user states crucial to ensure natu- ral and user adaptive interaction. User Satisfac- tion (US) is one important part of such a state. On the dialogue level (i.e. after the interaction is complete), it provides a measure for the interac- tion and allows to compare different SDS (Walker et al., 1997) or to learn appropriate dialogue strate- gies (Walker, 2000; Ultes et al., 2017a). However, if US is available in each turn, it can also be used for user adaptation (Ultes et al., 2011, 2012, 2016, 2014a).
The main contribution of this paper is the addition to Einstein’s equation of a term representing the propagation delay of the gravitational interaction between regions in the sphere in the Universe. The resulting equation can be used to model both the Big Bang and the later occurring rapid inflation of the Universe. The gravitational interaction between real galaxies takes time to propagate. The effect of the propagation delay of the gravitational interaction between galaxies involves the current position of one galaxy and the past and estimated future po- sition of another galaxy. The first galaxy has information about the past position and velocity of the other galaxy and can use this information to estimate the fu- ture position of that other galaxy. Therefore, the process is causal.
Our study contributes to the literature by filling the gap regarding the effect of laws on financial system development. First, in contrast to the previous studies, we use the corporate bond market instead of private bank credit and hence provide new insights into capital market development across countries. We find a strong relationship between creditor protection and corporate bond market development. Our results are in contrast to those of Musacchio (2008), who employed data for Brazil from 1885 to 2003 and found no stable relationship between creditor protections and bond market development in the long run. In our study, however, we use a large dataset of countries, and consequently, the results are more general. Second, Allen et al. (2012) demonstrated that the corporate bond market moves in the same direction as bank credit and experiences a short-term reversal with the stock market during a crisis. However, they concentrated only on the structure of the financial system, whereas we present the effects of crises only on the structure of capital markets.
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jSrst. There are four main reasons, three theoretical and one practical, why a cumulative approach to risk in its interaction with protection should be adopted. This would involve creating an index o f risk consisting o f the number o f risk Victors experienced by the subject. First, with regard to the theoretical reasons, there have been several studies in which significant relationships have been found between the number o f risk fectors present and a range o f outcomes (Jessor, Van Den Bos, Vanderryn, Costa & Turbin, 1995). Second, it appears form the review o f the maltreatment risk fector literature (see Chapter 3) that there is considerable overlap in thé e ^ c t s o f such risks and no clear theoretical or conceptual reason to weight one factor over another in relation to a perpetra^ting outcome. Finally, it has been found that diTerent risk fectors can have a potentiating effect on each other (Rutter, 1979). The pragmatic reason relates to the possibility that a number o f risk fectors may be found for sexually abusive behaviour. I f several risk fectors were to be assessed individually, the number o f logistic regressions that would need to be performed to test for all the possible combinations between the risks and the putative protective fectors would be prohibitive. Thus it seems appropriate to combine the risk fectors into a cumulative risk index to enable interactions with putative protective fectors to be analysed.
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The Interaction Energy between two magnets is a part of the full energy in the sys- tem. It does not take into account the internal energy in each magnet. But when the force or the torque must be obtained, it is not necessary to calculate the full value of the energy, only the variable part of energy is concerned.
A more plausible explanation for the absence of efficient contracts highlights the asymmetrical information over demand conditions between the bargainers. The firm is likely to exaggerate the bad times and hide the good ones and the costs of monitoring may be too high for the union to overcome the moral hazard problem. Presuming that the union discovers the true situation ex post (e.g. through the company accounts) then we are in a classical Prisioner’s Dilemma. This formal similarity has been noted by many writers (e.g. De La Rica and Espinosa, 1990) who have then used the Folk Theorem of repeated games to suggest that efficient bargains can be supported as the perfect equilibrium of a repeated Labour Demand Game if the future is discounted heavily enough. An important general idea is contained here which will be replayed often: long term contracts depend on the time-horizon of the union. Long tenured union members and leaders concerned with growth should
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Peter is 68 years old and lives alone. Peter is diagnosed as COPD patient for 15 years and lately his disease is getting worse. A couple of times Peter ended in a situation in which he experienced extreme dyspnea with the consequence that his self esteem was decreased. So, Peter avoids physical activities and situations that might induce a new attack of dyspnea, resulting in a poor physical con- dition, which made him vulnerable for new situations in which dyspnea might occur. To get out of this vicious circle Peter decided during his last visit at the lung physician to participate in a new disease management program. This program is carried out in close cooperation between the ﬁrst, second and third health care lines in a (virtual) COPD centre. First Peter gets an extensive screening and based on the results an individually tailored program is com- posed. Additionally, Peter keeps up a diary. Everyday Peter ﬁlls in his diary including mainly subjective information on the COPD home interaction device. So also today. The ﬁrst question of his medical diary is ”Did you have more complaints than normal in the last 24 hours?” The only two possible answers to this questions are ”Yes” and ”No”. Because Peter had a bad day with more complaints than average, his answer is yes. In the following questions Peter in- dicates the type and seriousness of his complaints. Are his complaints normal, some worse than normal or much worse than normal.
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The Software company (PD) team dataset is given as input to our framework and we observed the capabilities of our framework. The framework detects A8, A9 and A14 as a best case scenario to increase the knowledge diffusion value. These results indicate that this agent does not possess exclusive knowledge when compared to others. They interact with other agents, but the amount of knowledge diffused from one agent to another agent is more during the interaction phase. The knowledge diffusion rate increases predominantly as other agents interact with each other agents more accurately because the inefficient agents are isolated from the node in a network.
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