We can compute total production of all individual sectors as a function of final demand and the magnitudes of the input coefficients following Eq. 3. The impact of a sector i on aggregate output is evaluated as the change in output of sectors needed to compensate a change in final demand of sector i.
Spatial variance σ 2 = σ x 2 + σ y 2 of three sectors as a function of (B ) time and (C ) number of offspring (fluorescent bacteria per sector).
Total output of a sector is expressed as a function of the demand for the different commodities produced in the economy and is defined in vector form as follows: mathbf{x = Z1+d} (1).
From the conceptual demand model derived from utility maximizing behavior on the part of consumers, the quantities demanded (q i 's) for (n- 1) foods and a nonfood sector can be expressed as a function of prices (p i 's) and per capita income (m): q i = f i p 1, p 2,..., p n, m i = 1, 2,..., n (2).
For the pathloss, the 3GPP Long Term Evolution (LTE) pathloss model has been used: (20). is the corresponding log-normal coefficient which models large-scale fading (shadowing),, and is the complex Gaussian coefficient which models small-scale fading,. is the sector antenna power gain as a function of the angle in degrees, also following the LTE evaluation parameters: (21).
We quantify the probability of MMHg production potential (MPP) associated with hydrology in each sector of the river system as a function of the spatial patterns of overbank inundation and drainage, which affect long-term redox history of contaminated sediments.
τ on (D 0,rho)) as series in coefficients in (E_{(beta,mu )}), for all (epsilonin D 0,epsilon_{0})), and can be analytically continued on each unbounded sector (U_{mathfrak {d}_{p}}) as a function (taumapstopsi_{k_{1}}^{mathfrak{d}_{p}} tau,m,epsilon)) which belongs to the space (F^{mathfrak{d}_{p}}_{(nu,beta,mu,k_{1},k_{1})}).
However, in order to foster the recovery process in agriculture, additional steps need to be taken including enhancement of both national and international investments into the agriculture sector as well as the improvement of market functioning to facilitate price transmission and better integration with global commodity prices.
Despite several cross-cutting similarities, these key-informant narratives of poverty, under-resourced housing service sectors, and stigma differed markedly as a function of gender, ethnicity and other points of intersection.
Institutional imbalances: These include the question of how to deploy staff between curative and preventive functions of the health sector, as well as their distribution at various tiers and facilities of the system [ 13].
