«Малобюджетний» маркетинг

В умовах сьогоднішньої економічної кризи, яка зачепила всі вітчизняні підприємства, та постійного зниження української національної валюти актуальними стають питання пошуку способів економії коштів. Вирішенням таких проблем може стати «мало бюджетний» маркетинг, який допоможе розвиватися підприємству з використанням мінімальної кількості ресурсів. «Малобюджетний» маркетинг – це маркетингові інструменти залучення й утримання клієнтів, які припускають мінімальні витрати, а іноді можна взагалі обійтися без бюджету

Budget allocation and M&R design.

Maintenance and rehabilitation (M&R) is necessary to keep pavement networks in good condition. Due to the capital intensity, M&R funding is always insufficient. The annual budget, determining the available funding, is a critical criterion when planning M&R treatments. However, its values are often given, and the determination of the values is seldom discussed. To fill the gap, this paper focuses on both the determination of annual budgets and the budget allocations, and therefore enhances the network-level decision-making on M&R by developing a Multi-Objective Optimization (MOO) method. This method does not only optimize and trade off the annual budgets and their consequences, but also allocates the funding across the entire network through generating the optimized M&R decisions. According to a case study with 50 segments, the developed method successfully and effectively identified non-linear discrete relationship between the minimized annual budgets and the maximized M&R benefits subject to all the constraints, and generated the optimized annual budget allocation for each M&R decision. The achievements of this paper can be used to enhance the efficiency of M&R decisions and contribute to informed pavement management.</div

Example of the solution generation.

Maintenance and rehabilitation (M&R) is necessary to keep pavement networks in good condition. Due to the capital intensity, M&R funding is always insufficient. The annual budget, determining the available funding, is a critical criterion when planning M&R treatments. However, its values are often given, and the determination of the values is seldom discussed. To fill the gap, this paper focuses on both the determination of annual budgets and the budget allocations, and therefore enhances the network-level decision-making on M&R by developing a Multi-Objective Optimization (MOO) method. This method does not only optimize and trade off the annual budgets and their consequences, but also allocates the funding across the entire network through generating the optimized M&R decisions. According to a case study with 50 segments, the developed method successfully and effectively identified non-linear discrete relationship between the minimized annual budgets and the maximized M&R benefits subject to all the constraints, and generated the optimized annual budget allocation for each M&R decision. The achievements of this paper can be used to enhance the efficiency of M&R decisions and contribute to informed pavement management.</div

Generated Pareto solutions and their trade-off ratios.

Generated Pareto solutions and their trade-off ratios.</p

Algorithm of dichotomic approach.

Maintenance and rehabilitation (M&R) is necessary to keep pavement networks in good condition. Due to the capital intensity, M&R funding is always insufficient. The annual budget, determining the available funding, is a critical criterion when planning M&R treatments. However, its values are often given, and the determination of the values is seldom discussed. To fill the gap, this paper focuses on both the determination of annual budgets and the budget allocations, and therefore enhances the network-level decision-making on M&R by developing a Multi-Objective Optimization (MOO) method. This method does not only optimize and trade off the annual budgets and their consequences, but also allocates the funding across the entire network through generating the optimized M&R decisions. According to a case study with 50 segments, the developed method successfully and effectively identified non-linear discrete relationship between the minimized annual budgets and the maximized M&R benefits subject to all the constraints, and generated the optimized annual budget allocation for each M&R decision. The achievements of this paper can be used to enhance the efficiency of M&R decisions and contribute to informed pavement management.</div

Condition variation.

Maintenance and rehabilitation (M&R) is necessary to keep pavement networks in good condition. Due to the capital intensity, M&R funding is always insufficient. The annual budget, determining the available funding, is a critical criterion when planning M&R treatments. However, its values are often given, and the determination of the values is seldom discussed. To fill the gap, this paper focuses on both the determination of annual budgets and the budget allocations, and therefore enhances the network-level decision-making on M&R by developing a Multi-Objective Optimization (MOO) method. This method does not only optimize and trade off the annual budgets and their consequences, but also allocates the funding across the entire network through generating the optimized M&R decisions. According to a case study with 50 segments, the developed method successfully and effectively identified non-linear discrete relationship between the minimized annual budgets and the maximized M&R benefits subject to all the constraints, and generated the optimized annual budget allocation for each M&R decision. The achievements of this paper can be used to enhance the efficiency of M&R decisions and contribute to informed pavement management.</div

Image1_The Role of Lower Crustal Rheology in Lithospheric Delamination During Orogeny.PNG

The continental lower crust is an important composition- and strength-jump layer in the lithosphere. Laboratory studies show its strength varies greatly due to a wide variety of composition. How the lower crust rheology influences the collisional orogeny remains poorly understood. Here I investigate the role of the lower crust rheology in the evolution of an orogen subject to horizontal shortening using 2D numerical models. A range of lower crustal flow laws from laboratory studies are tested to examine their effects on the styles of the accommodation of convergence. Three distinct styles are observed: 1) downwelling and subsequent delamination of orogen lithosphere mantle as a coherent slab; 2) localized thickening of orogen lithosphere; and 3) underthrusting of peripheral strong lithospheres below the orogen. Delamination occurs only if the orogen lower crust rheology is represented by the weak end-member of flow laws. The delamination is followed by partial melting of the lower crust and punctuated surface uplift confined to the orogen central region. For a moderately or extremely strong orogen lower crust, topography highs only develop on both sides of the orogen. In the Tibetan plateau, the crust has been doubly thickened but the underlying mantle lithosphere is highly heterogeneous. I suggest that the subvertical high-velocity mantle structures, as observed in southern and western Tibet, may exemplify localized delamination of the mantle lithosphere due to rheological weakening of the Tibetan lower crust.</p

Generated Pareto solutions.

Maintenance and rehabilitation (M&R) is necessary to keep pavement networks in good condition. Due to the capital intensity, M&R funding is always insufficient. The annual budget, determining the available funding, is a critical criterion when planning M&R treatments. However, its values are often given, and the determination of the values is seldom discussed. To fill the gap, this paper focuses on both the determination of annual budgets and the budget allocations, and therefore enhances the network-level decision-making on M&R by developing a Multi-Objective Optimization (MOO) method. This method does not only optimize and trade off the annual budgets and their consequences, but also allocates the funding across the entire network through generating the optimized M&R decisions. According to a case study with 50 segments, the developed method successfully and effectively identified non-linear discrete relationship between the minimized annual budgets and the maximized M&R benefits subject to all the constraints, and generated the optimized annual budget allocation for each M&R decision. The achievements of this paper can be used to enhance the efficiency of M&R decisions and contribute to informed pavement management.</div

Dataset of AD-OnVDMP

Dataset of Glucose uptake and clearance in Alzheimer's disease mouse brain with tauopathy detected by onVDMP MRI. The related Matlab code can be downloaded at https://github.com/LinChenMRI/AD-OnVDMP.gi

Summary of the potential M&R treatments*.

Maintenance and rehabilitation (M&R) is necessary to keep pavement networks in good condition. Due to the capital intensity, M&R funding is always insufficient. The annual budget, determining the available funding, is a critical criterion when planning M&R treatments. However, its values are often given, and the determination of the values is seldom discussed. To fill the gap, this paper focuses on both the determination of annual budgets and the budget allocations, and therefore enhances the network-level decision-making on M&R by developing a Multi-Objective Optimization (MOO) method. This method does not only optimize and trade off the annual budgets and their consequences, but also allocates the funding across the entire network through generating the optimized M&R decisions. According to a case study with 50 segments, the developed method successfully and effectively identified non-linear discrete relationship between the minimized annual budgets and the maximized M&R benefits subject to all the constraints, and generated the optimized annual budget allocation for each M&R decision. The achievements of this paper can be used to enhance the efficiency of M&R decisions and contribute to informed pavement management.</div