Estimates of the radiative flux perturbation (RFP) due to total anthropogenic aerosol effects, including direct, semi-direct and indirect aerosol effects (cloud albedo and cloud lifetime), and the couplings between them, are derived from the differ- ence in net radiation at the top of the atmosphere between pairs of parallel GCM simulations with present-day (PD) and pre-industrial (PI) aerosol emissions (e.g. Rotstayn and Pen- ner, 2001; Haywood et al., 2009; Lohmann et al., 2010). A summary of the global mean anthropogenic emissions rele- vant to aerosols in the pre-industrial and present-day runs is given in Table 4. The energy imbalance at the top of the atmo- sphere (TOA) ranges from 5.2 to 10.4 W m − 2 depending on model configuration and aerosol emissions. Since the model was run in atmosphere-only mode for the purposes of this study, some imbalance is inevitable. As with any change to a model that affects radiative fluxes, retuning of the model’s TOA radiation imbalance would be required before employ- ing the scheme for coupled atmosphere–ocean integrations, and such retuning is likely to change the RFP.
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tive ef ﬁ ciency [Forster et al., 2007] of different natural aerosol sources. Due to the nonlinear CAE, the CAE burden ef ﬁ ciency depends on the magnitude of the pertur- bation in source strength (Auxiliary Material Table A2). Table 1 details the burden ef ﬁ ciency for the complete removal of each natural aerosol source. In our model DMS sulfate (–616 Wg –1 ), monoterpene SOA (–554 Wg –1 ) and volcanic sulfate (–430 Wg –1 ) have the greatest clear-sky DRE burden ef ﬁ ciencies. There is even larger variability in the CAE burden ef ﬁ ciency with DMS sulfate (–1336 Wg –1 ) and volcanic sulfate (–892 Wg –1 ) ef ﬁ ciencies being up to two orders of magnitude larger than for other natural sources. The DMS sulfate ef ﬁ cien- cies for both DRE and CAE are larger than the corresponding volcanic sulfate ef ﬁ ciencies, likely due to the difference in vertical aerosol distributions [Graf et al., 1997]. Also, the ratio of annual global mean CAE to clear-sky DRE in the PD varies between the different natural aerosols from rela- tively small values for sea-salt (0.06) and terpene SOA (0.18) to larger values for wild ﬁ re (1.5), volcanic-sulfate (2.0) and DMS-sulfate (2.2). Aerosol sources that lead to large numbers of small particles (DMS and volcanoes) contribute greatly to CDNC per unit of emission, resulting in a greater CAE burden ef ﬁ ciency.
Four-month (January, April, July and October 2005) simulations using WRF/Chem version 3.3.1 are conducted at a grid resolution of 36-km over the East Asia domain. The model inputs, components, and configurations are summarized in Table 2.1. Same or similar physical and chemical options have been selected by previous studies (Zhang et al. 2010, 2012). The gas-phase chemistry is based on the Carbon Bond Mechanism-Z (CBM-Z) (Zaveri and Peters, 1999). The aerosol module is the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) (Zaveri et al., 2008). A main reason of using such combination is that in WRF/Chem version 3.3.1, when CBM-Z and MOSAIC are selected, aerosol direct and indirect effects (aerosols act as CCN in stratiform clouds) can only be simulated using the combination of the Goddard shortwave radiation scheme (Chou et al., 1998), Fast-J photolysis scheme (Wild et al., 2000), the Purdue Lin microphysics (Lin et al., 1983; Chen and Sun, 2002).
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Abstract. We use a global aerosol microphysics model in combination with an offline radiative transfer model to quantify the radiative effect of biogenic secondary organic aerosol (SOA) in the present-day atmosphere. Through its role in particle growth and ageing, the presence of bio- genic SOA increases the global annual mean concentration of cloud condensation nuclei (CCN; at 0.2 % supersatura- tion) by 3.6–21.1 %, depending upon the yield of SOA pro- duction from biogenic volatile organic compounds (BVOCs), and the nature and treatment of concurrent primary carbona- ceous emissions. This increase in CCN causes a rise in global annual mean cloud droplet number concentration (CDNC) of 1.9–5.2 %, and a global mean first aerosol indirect effect (AIE) of between + 0.01 W m −2 and − 0.12 W m −2 . The ra- diative impact of biogenic SOA is far greater when biogenic oxidation products also contribute to the very early stages of new particle formation; using two organically mediated mechanisms for new particle formation, we simulate global annual mean first AIEs of − 0.22 W m −2 and − 0.77 W m −2 . The inclusion of biogenic SOA substantially improves the simulated seasonal cycle in the concentration of CCN-sized particles observed at three forested sites. The best correlation is found when the organically mediated nucleation mecha- nisms are applied, suggesting that the first AIE of biogenic SOA could be as large as − 0.77 W m −2 . The radiative im- pact of SOA is sensitive to the presence of anthropogenic emissions. Lower background aerosol concentrations simu-
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Abstract. Aerosol emissions from biofuel combustion im- pact both health and climate; however, while reducing emis- sions through improvements to combustion technologies will improve health, the net effect on climate is largely uncon- strained. In this study, we examine sensitivities in global aerosol concentration, direct radiative climate effect, and cloud-albedo aerosol indirect climate effect to uncertain- ties in biofuel emission factors, optical mixing state, and model nucleation and background secondary organic aerosol (SOA). We use the Goddard Earth Observing System global chemical-transport model (GEOS-Chem) with TwO Moment Aerosol Sectional (TOMAS) microphysics. The emission factors include amount, composition, size, and hygroscop- icity, as well as optical mixing-state properties. We also eval- uate emissions from domestic coal use, which is not biofuel but is also frequently emitted from homes. We estimate the direct radiative effect assuming different mixing states (ho- mogeneous, core-shell, and external) with and without ab- sorptive organic aerosol (brown carbon). We find the global- mean direct radiative effect of biofuel emissions ranges from − 0.02 to + 0.06 W m −2 across all simulation/mixing-state combinations with regional effects in source regions rang- ing from − 0.2 to + 0.8 W m −2 . The global-mean cloud- albedo aerosol indirect effect (AIE) ranges from + 0.01 to − 0.02 W m −2 with regional effects in source regions rang- ing from −1.0 to −0.05 W m −2 . The direct radiative effect is
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Objective: Birthing trauma (BT) (i.e., complicated birth) is an early life complex trauma for the baby and mother that never been empirically examined or considered within the trauma field as a traumatic stressor for the newborn. The goal of current study is to examine its effects on mental health and neurocognitive functioning and explore its proliferation to other life traumas. Method: Current study utilizes a novel developmental-based trauma framework (DBTF) to empirically test assumptions about some of its negative delayed psychosocial and neurocognitive effects in ado- lescents, and the dynamics of its proliferation to other potentially dependent traumas. A commu- nity sample of 410 African American and Iraqi adolescents have been administered measures of traumas (CTS), birthing trauma, PTSD, complex PTSD (CTD), existential anxiety and WISC IV. We controlled for the numerous cumulative stressors and traumas that could potentially be playing a role. .Results: Correlations and path analyses and multigroup invariance found that BT predicted elevated symptoms of post-trauma spectrum disorders, reduced IQ scores, and increased discre- pancy IQ index. These relationships were strongly invariant across gender and cultural groups. BT directly predicted other early childhood traumas, and indirectly all other life trauma types, which support BT proliferation hypothesis. These relationships were strongly invariant across gender. Conclusion: Screening for Birthing Trauma as one of the serious early childhood trauma is impor- tant. Early intervention with BT victims to provide early psychological and educational help and prevent proliferation dynamics is important.
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To determine the extent to which the effect of a physiologic increment in epinephrine (EPI) on glucose production (GP) arises indirectly from its action on peripheral tissues (mus- cle and adipose tissue), epinephrine was infused intrapor- tally (EPI po) or peripherally (EPI pe) into 18-h–fasted con- scious dogs maintained on a pancreatic clamp. Arterial EPI levels in EPI po and EPI pe groups rose from 97 6 29 to 107 6 37 and 42 6 12 to 1,064 6 144 pg/ml, respectively. He- patic sinusoidal EPI levels in EPI po and EPI pe were indis- tinguishable (561 6 84 and 568 6 75 pg/ml, respectively). Dur- ing peripheral epinephrine infusion, GP increased from 2.2 6 0.1 to 5.1 6 0.2 mg/kg·min (10 min). In the presence of the same rise in sinusoidal EPI, but with no rise in arterial EPI (during portal EPI infusion), GP increased from 2.1 6 0.1 to 3.8 6 0.6 mg/kg·min. Peripheral EPI infusion increased the maximal gluconeogenic rate from 0.7 6 0.4 to 1.8 6 0.5 mg/ kg·min. Portal EPI infusion did not change the maximal gluconeogenic rate. The estimated initial increase in glyco- genolysis was ø 1.7 and 2.3 mg/kg·min in the EPI pe and EPI po groups, respectively. Gluconeogenesis was responsi- ble for 60% of the overall increase in glucose production stimulated by the increase in plasma epinephrine (EPI pe). Elevation of sinusoidal EPI per se had no direct gluconeo- genic effect on the liver, thus its effect on glucose produc- tion was solely attributable to an increase in glycogenolysis. Lastly, the gluconeogenic effects of EPI markedly decreased (60–80%) its overall glycogenolytic action on the liver. ( J. Clin. Invest. 1997. 99:1044–1056.) Key words: epinephrine • gluconeogenesis • glycogenolysis
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The implication of this third finding is that infrastructural investment needs to better target low- income rural areas in the peripheral districts. In that way, public investments could help to reduce the growing inequality among districts in Savannakhet, especially if it were to target low-income groups in remote villages. Moreover, the empirical evidence from this study clearly supports combination of transport and communication facilities, insofar as the impact on living standards is substantially greater when these two infrastructures are jointly supplied to villages. Measuring the Corridor’s impact will require further application of detailed socioeconomic data in Savannakhet. Of particular importance are comparative data on (i) trafficking of persons and animals across border; (ii) the incidence of HIV/AIDS in expanding hospitality industry in Savannakhet; (iii) trade and investment divergence from other border provinces and accompanying social welfare shifts; and (iv) other social problems in border areas related to increased crime, drugs, prostitution, and outside cultural influences. These developmental aspects of the EWEC have important effects on living standards that extend well beyond what is indicated by the present LECS.
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Detecting putative causal genes is of considerable inter- est for determining which traits will be affected by spe- cific loci from a biological perspective, and consequently partitioning the genetic signals according to the paths determined. Although the parameter interpretations of SEM as applied to QTL mapping [57, 58], expression QTL , or genetic selection  have been actively pursued, the work of Momen et al.  marks one of the first studies to account for the level of individual SNP effect in genome-wide SEM analyses. The SEM embeds a flexible framework for performing such network analysis in a GWAS context, and the current study demonstrates its the first application in crops. We assumed that mod- eling a system of four traits in rice simultaneously may help us to examine the sources of SNP effects in GWAS in greater depth. Therefore, we used two GWAS methodol- ogies that have the ability to embed multiple traits jointly, so that the estimated SNP effects from both models have different meanings. The main difference between SEM- GWAS and MTM-GWAS is that the former includes the relationship between SNPs and measured phenotypes, coupled with relationships that are potentially mediated by other phenotypes (mediator traits). This advances GWAS, and consequently the information obtained from trait networks describing such interrelationships can be used to predict the behavior of complex systems . Although we analyzed the observed phenotypes in the current study, the factor analysis component of SEM can be added to SEM-GWAS by deriving latent factors from multiple phenotypes [e.g., 60, 61]. The inference of a trait network structure was carried out using a Bayesian net- work, which has applications in genetics ranging from modeling linkage disequilibrium  to epistasis . Fig. 6 Distribution of projected shoot area (PSA) and water use
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Transformational leadership theory and LMX theory have been found to encourage innovative behavior (Basu & Green, 1997). Referring to Bass’ (1990) characteristics of the transformational leadership style, this research will elaborate the effect of transformational leadership on innovative behavior. Transformational leaders provide a common vision to all team members, enabling them to work together to accomplish a set goal, which is in contrary to the LMX theory. Besides, including all organizational members can lead to the enhancement of innovative behavior (Elkins & Keller, 2003). Shamir, House, and Arthur (1993) verify that transformational leaders build personal and social identifications among all employees, leading to a higher commitment in the individuals, which in turn can lead to innovative behavior (Meyer, Stanley, Herscovitch, & Topolnytsky, 2002). Furthermore, by means of intellectually stimulating subordinates to see problems from different vantage points and helping individual employees to develop to their full potential, transformational leaders can facilitate innovative behavior in all group members (Reuvers, van Engen, Vinkenburg, & Wilson-Evered, 2008). Besides, several recent studies supported the link between transformational leadership and innovative behavior (Elkins & Keller, 2003). For instance, the research of Jung, Chow, and Wu (2003) among 32 Taiwanese electronics and telecommunications supports the direct relationship between transformational leadership innovative behavior. Based on these findings it will be shown how transformational leadership accounts for innovative behavior.
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zenith angle ( θ ) when the angle is small, aerosol forcing approaches zero as θ approaches 90°. Thus, the added aerosol radiative effect is multiplied by a scaling factor that depends on zenith angle. 8,68 The climate response is estimated as the difference between the simulation with observationally constrained ﬁ ne-mode aerosol (without dust and sea salt), and a corresponding control runs without observationally constrained ﬁ ne- mode aerosol (STANDARD signal). The idealized vertically uniform heating simulations are analogous, but the monthly mean aerosol atmospheric heating is vertically averaged at each grid box, and this vertically averaged value is prescribed to all pressure levels >100 hPa. The climate response of vertically uniform heating (VERTUNIF signal) is obtained by taking a difference with the same control simulation. We also perform simulations analogous to STANDARD, but with half the aerosol forcing (HALF). At each grid box, the (monthly) reduction in surface solar radiation and atmo- spheric solar heating are reduced by 50%. Signi ﬁ cance of all climate responses is based on a Student ’ s t test for the difference of means, using the pooled variance.
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Since the capital flows channel appeared to give the best model fit, Table 8 reports the direct and indirect effects estimates of these model extensions for the capital flows transmission channel. 8 The direct effect of M2/reserves during tranquil periods turns out to be small and insignificant, but its indirect effect amounts to a significant value of −0.023. This implies that a 1% point increase of the most influential foreign country (multiplication by 0.2539) reduces NPLs by 0.006 percentage points. In the crisis period, this direct effect increases to a weakly significant value of −0.003 and its indirect effect to a value of − 0.035, which is significantly different from zero. The outcomes for housing prices are listed in the final four columns of the table. The direct effects of housing prices are significantly negative, − 0.075, in the tranquil period, but increase significantly to a value of 0.152 during the crisis period. Indirect effects are insignificant in the tranquil period, but decrease to a weakly significant value of −0.226 during the crisis. These outcomes again underline the importance of controlling for interaction effects between interdependence effects and the crisis dummy.
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Aggregating the identified property market reactions based on estimated treatment effects, average property prices and housing stock at output area, we find substantial stadium effects in absolute terms, even compared to the large (public) investments into the new facilities. For all three stadium locations, the estimated change in aggregated value amounts to about £2 billion, leaving a positive net‐effect to the neighborhood of the New Wembley and a close to zero net‐effect to the broader neighborhood of the Arsenal venues as the effects within the catchment areas of the Emirates Stadium and Highbury Road cancel out each other.
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UV radiation that penetrated through the net may also have influenced plant physiology because the lack of UV radiation may have reduced acclimation and repair responses in plants. In addition, this may have modified secondary metabolism or have altered the production of phytohormones (Jansen et al. 1998). Thus, it is likely that aphids were ex- posed to a different composition of sap when feed- ing on lettuce plants covered with Bionet, which could had affected negatively its development. As a result, there could be both, direct and indirect ef- fects, on aphids mediated by their host plants when grown under photoselective covers.
Schematic showing method of clustering data adopted for analysis. For analysis I, data were clustered according to diffuse radiative flux fraction (Rd/Rg). For analysis II, data was clustered according to ‘Clear’ and ‘Cloudy’ sky conditions based on diurnal radiation flux characteristics and GOES satellite imagery. For analysis III, data were clustered according to aerosol loading quantified through aerosol optical depths (AOD). Each pair of clustered data was then compared for differences in observed carbon exchange (CO 2 flux
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In our framework, R&D effort is a hump-shaped function of competition as well, but can potentially be observed as a monotonic function because of the following logic. By contrast with R&D outcomes, R&D effort is affected not by two, but by four forces: two direct (the escape-costs effect and division effect 8 ) and two indirect (the indirect escape-costs effect and indirect depletion effect). 9 Thus, since the two aspects of innovation, as functions of competition, are affected by different sets of forces, their turning points do not have to coincide. If, in addition, the measure of competition can take values from a limited interval, and R&D effort’s turning point is outside this interval (whereas that of R&D outcomes is within it), then R&D effort and R&D outcomes will be observed as, respectively, a monotonic and a hump-shaped function, thus producing a situation of discrepancy in their behaviour.
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1000-seed weight/ plant (0.781) followed by seed oil content (0.442), capsules weight per plant (0.427) and plant height (0.414) showed highly positive direct effects on seed yield/ feddan at genotypic correlation. However, number of branches/plant (0.106) and numbers of capsules/plant (0.152) exhibited positive direct effect of low magnitude on seed yield per feddan. Whereas the fruit zone (-0.526) showed negative direct effects on seed yield /plant and non-significant positive correlation with seed yield/feddan. In this study, the residual effect (0.5197) was high value in magnitude which showed that some other important yield contributing characters which contributed to yield had to be included.
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Because direct e ff ects such as direct killing of prey or migration of a species can be easily observed in an ecological community, and have been the central topic in research by far, indirect e ff ects may play an even more important role in determining the demography of species. Indirect e ff ects between predators and prey are mainly induced by anti-predator behaviors of prey. It has been argued by theoretical biologists that prey can perceive predation risk at least to some extent and avoid direct killing by predators through a variety of anti-predator behaviors ([15, 35, 36, 37, 41]). The fear of predators drives prey to show anti-predators responses, which include habitat switch, foraging behaviors change, and increased vigilance (). Specifically, when prey are in breeding season, any change of the above anti-predator responses may lead to a loss on prey reproduction success even though no direct killing has been involved ([9, 15, 30, 31]). Because of such decay on prey reproduction, anti-predator behaviors may increase short-term survival rate of prey but in the long-term, there is a cost in the fitness of prey as a species (). Recently, a field study on song sparrow populations confirms the theoretical argument that even rare presence of predators can exert a large impact on prey demography ().
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The econometric model of Alfredsson (2004) finds direct and indirect effects of 14% for transport abatement, and 20% for ‘green’ housing, and a back-‐fire (approx 200%) for a ‘green’ diet and a total direct and indirect rebound effect for a combination of these actions of 20% in terms of GHG emissions. Alfredsson (2004) also considers the impact of increasing incomes offsetting any benefits made by consumption pattern changes. She finds that exogenous income growth of 1% per year offsets all but 7% of the decrease in GHG emissions from the combination of changes by 2020, while income growth of 2% will more than compensate for consumption pattern changes, and lead to a 13% increase in GHG emissions by 2020.
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Each qualified OMI retrieval of the above-cloud aerosols is assigned with an appropriate algorithm quality flag. Table 1 describes the algorithm quality flags attached to each valid retrieval and their associated observed conditions. Retrievals with the quality flag equal to “0” are expected to be the best in quality as they are associated with the larger mag- nitudes of UVAI (> 1.3) and LER388 (> 0.25) with both pro- viding high confidence in the detection of absorbing aerosols above the cloud. An analysis using the OMMYCLD product over the southeastern Atlantic Ocean for the period of June– July–August 2007 revealed a well-constrained non-linear re- lationship between the MODIS-derived COD multiplied by the geometric cloud fraction, and LER388. A threshold for LER388 of 0.25, adopted for the best quality retrievals, com- pares to the COD times geometric cloud fraction of 3–4. Thus, given the geometric cloud fraction of unity the mini- mum COD retrieved by OMACA would be in the range 3–4. Lower magnitudes in both parameters might result in less confidence in the detection of either overcast pixels (0.20 < LER388 < 0.25, quality flag = 1) or the presence of absorbing aerosols above cloud (0.8 < UVAI < 1.3, quality flag = 2). Lower LER values (0.20–0.25) might pose a risk of identifying broken clouds in the OMI pixels, resulting in a geometric cloud fraction less than unity – a condition, under which the assumption of fully overcast pixels breaks down. Nevertheless, it is also possible that the increased aerosol loading (AOD > 2) with a significant absorption ca- pacity (SSA < 0.90) above the fully overcast pixels reduces LER measured at TOA (Fig. 6 of Jethva et al., 2013). On the other hand, the lower values of UVAI (0.8–1.3) associ- ated with the quality flag “2” may be related to the non- aerosol related artifacts resulting from the inherent uncertain- ties in the derivation of UVAI. The sources of uncertainties include spectral surface albedo, the unaccounted presence of ice clouds, and viewing geometry of the Sun and satellites. The magnitudes of UVAI depend on several aerosol param- eters including ACAOD, COD, SSA, ALH, and spectral de- pendence of aerosol absorption. Radiative transfer calcula- tions show that for a given value of SSA of 0.90 (388 nm) with an ALH of 3, 4, and 5 km, the UVAI value of 1.3 can be equated to the AOD (388 nm) of 0.30, 0.28, and 0.26, respec- tively. For a given SSA of 0.84, the values of AOD are 0.22, 0.20, and 0.19. The results of these simulations presented in Table 2 suggest that the minimum value of AOD retrieved us- ing the thresholds in UVAI depends on the actual condition of the scene.
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