Impact of noncommunicable diseases on direct medical costs and worker productivity, Saudi Arabia

Background: The prevalence of noncommunicable diseases (NCDs) has been increasing in Saudi Arabia. Aim: Our objective was to estimate the effect of NCDs on direct medical costs and workforce productivity in Saudi Arabia. Methods: To estimate direct medical costs, we estimated the unit cost of treating 10 NCDs, then multiplied the unit cost by disease prevalence and summed across diseases. To estimate workforce productivity losses, we multiplied gross domestic product per person in the labour force by the loss in productivity from each NCD and the prevalence in the labour force of each NCD. Results: We estimated annual direct medical costs of 11.8 billion international dollars (Int$) for the 10 NCDs assessed (13.6% of total annual health expenditure). We estimated workforce productivity losses of Int$ 75.7 billion (4.5% of gross domestic product). Conclusion: The economic burden of NCDs in Saudi Arabia – particularly the effect on worker productivity – is substantial.

The Structure of T-DNA Insertions in Transgenic Tobacco Plants Producing Bovine Interferon-Gamma

Many of the most modern drugs are of a protein nature and are synthesized by transgenic producer organisms. Bacteria, yeast, or animal cell cultures are commonly used, but plants have a number of advantages—minimal biomass unit cost, animal safety (plants are not attacked by mammalian pathogens), the agricultural scale of production, and the ability to produce complex proteins. A disadvantage of plants may be an unstable level of transgene expression, which depends on the transgene structure and its insertion site. We analyzed the structure of T-DNA inserts in transgenic tobacco plants (Nicotiana tabacum L.) belonging to two lines obtained using the same genetic construct but demonstrating different biological activities of the recombinant protein (bovine interferon-gamma). We found that, in one case, T-DNA was integrated into genomic DNA in the region of centromeric repeats, and in the other, into a transcriptionally active region of the genome. It was also found that in one case, the insert has a clustered structure and consists of three copies. Thus, the structure of T-DNA inserts in both lines is not optimal (the optimal structure includes a single copy of the insert located in the active region of the genome). It is desirable to carry out such studies at the early stages of transgenic plants selection.

Using Convolutional Neural Networks to Build a Lightweight Flood Height Prediction Model with Grad-Cam for the Selection of Key Grid Cells in Radar Echo Maps

Recent climate change has brought extremely heavy rains and widescale flooding to many areas around the globe. However, previous flood prediction methods usually require a lot of computation to obtain the prediction results and impose a heavy burden on the unit cost of the prediction. This paper proposes the use of a deep learning model (DLM) to overcome these problems. We alleviated the high computational overhead of this approach by developing a novel framework for the construction of lightweight DLMs. The proposed scheme involves training a convolutional neural network (CNN) by using a radar echo map in conjunction with historical flood records at target sites and using Grad-Cam to extract key grid cells from these maps (representing regions with the greatest impact on flooding) for use as inputs in another DLM. Finally, we used real radar echo maps of five locations and the flood heights record to verify the validity of the method proposed in this paper. The experimental results show that our proposed lightweight model can achieve similar or even better prediction accuracy at all locations with only about 5~15% of the operation time and about 30~35% of the memory space of the CNN.

The cost of community outreach HIV interventions: a case study in Thailand

Background There was an estimated 440,000 people living with HIV in Thailand in 2018. New cases are declining rapidly thanks to successful prevention programs and scaling up of anti-retroviral therapy (ART). Thailand aims to achieve its commitment to end the HIV epidemic by 2030 and implemented a cascade of HIV interventions through the Reach-Recruit-Test-Treat-Retain (RRTTR) program. Methods This study focused on community outreach HIV interventions implemented by Non-Governmental Organizations (NGOs) under the RRTTR program in 27 provinces. We calculated unit cost per person reached for HIV interventions targeted at key-affected populations (KAPs) including men who have sex with men/ transgender (MSM/TG), male sex workers (MSW), female sex workers (FSW), people who inject drugs (PWID) and migrants (MW). We studied program key outputs, costs, and unit costs in variations across different HIV interventions and geographic locations in Thailand. We used these estimates to determine costs of HIV interventions and evaluate economies of scale. Results The interventions for migrants in Samut Sakhon was the least costly with a unit cost of 21.6 USD per person to receive services, followed by interventions for migrants in Samut Prakan 23.2 USD per person reached, MSM/TG in Pratum Thani 26.5USD per person reached, MSM/TG in Nonthaburi 26.6 USD per person reached and, MSM/TG in Chon Buri with 26.7 USD per person. The interventions yielded higher efficiency in large metropolitan and surrounding provinces. Harm reduction programs were the costliest compare with other interventions. There was association between unit cost and scale of among interventions indicating the presence of economies scale. Implementing HIV and TB interventions jointly increased efficiency for both cases. Conclusion This study suggested that unit cost of community outreach HIV and TB interventions led by CSOs will decrease as they are scaled up. Further studies are suggested to follow up with these ongoing interventions for identifying potential contextual factors to improve efficiency of HIV prevention services in Thailand.

Determination of optimal oil pumping plans

This paper presents the results of determining the optimal plans for pumping oil through the main oil pipelines of Kazakhstan. The calculation methodology is based on determining the minimum unit cost of pumping depending on oil flow rate. Oil pumping energy-saving modes are determined under optimal operating conditions of pumping units and heating furnaces at stations. Determination of the optimal pumping plan is implemented as a separate module of the SmartTranPro software. Pumped oil volumes on the oil pipeline sections were determined on the basis of the automated system of control and metering of electrical energy data of KazTransOil JSC. Optimal pumping plans for monthly oil volumes in the Kalamkas – Karazhanbas and Dzhumagaliev – Atasu pipeline sections for cold and warm periods were calculated on the basis of the found dependence of the pumping unit cost. For each range of oil mass flow rate, specific costs for oil pumping and a list of operating pumps at oil pumping stations located along the pipeline section are indicated.

An Econometric Model for the Analysis of the Influence of the Refurbishment Costs on Housing Prices

With reference to the Italian context, the present research intends to analyze the functional relationships between the unit cost of restructuring and the selling prices in the residential segment. The analysis has been contextualized to the three clusters (Northern Italy, Central Italy, Southern Italy and Islands) in which the Italian territory is commonly divided. The case study concerns 965 residential units sold in the first half of 2019 and located in the 103 provincial capitals. The implemented econometric technique is a data-driven method that employs a genetic algorithm and allows the identification of the most influencing factors among the explanatory variables considered. For each cluster, a model has been selected in order to study the influence of unit cost of restructuring on housing prices.

Research on the cost effectiveness of carbon emission reduction in the full life cycle of electric vehicles based on grey prediction

In order to research the carbon emission reduction potential of electric vehicles, a cost effectiveness model is used to calculate and compare the economic costs and carbon emissions of fuel vehicles and electric vehicles throughout the life cycle, and an improved grey prediction model is utilized to analyze the future trends of electric vehicle emission reduction benefits. The results show that electric vehicles play a positive role in carbon emission reduction, and the unit cost of carbon emission reduction is decreasing by years. Therefore, China should vigorously develop the electric vehicle industry and technology, and achieve the strategic goal of carbon emission reduction by promoting the electrification of vehicles.

ECONOMIC VIABILITY OF BASALT-BASED BRAKE PAD IN NIGERIA

The economic analysis reveals the basic information on the expenditure and profit to an investor who is willing to invest on the production of basalt-based brake pad in Nigeria, Nigeria has huge demand of brake as revealed by data obtained from National Bureau of Statistics Abuja (NBS). The analysis was based on deductive economic analysis which assumptions were made and arrived at particular result and the costing was based on Activity-Based Costing (ABC) where overhead and indirect cost were assigned to the related product. The economic analysis will give an insight to an investor (s) who has been skeptic about investing in the manufacturing of brake pad in Nigeria. The analysis revealed that the total capital require for this investment is #54,520,184.00 to set up a manufacturing plant with a capacity of 12,960 pieces of brake pad per day with a depreciation period of ten years. It also showed that if the line will run at 75% efficiency, the annual production is 2,566,080 pieces of brake pads. The unit cost of production is #520.85, unit selling price is #572.935, interest before tax of #6,797,983.869, break-even quantity of 861,019pieces, payback period of eight months. The annual total cost of production is #1,373,924,104.00, annual total sales revenue of #1,470,309,952.00.Twenty-seven people are require for manning the plant.It is clear from above information the investment is worthwhile because of the good payback period and considering the huge demand in Nigeria.

Low carbon joint strategy and coordination for a dyadic supply chain with Nash bargaining fairness

<p style='text-indent:20px;'>In the paper, fairness concern criterion is utilized to explore the coordination of a dyadic supply chain with a fairness-concerned retailer (acting as a newsvendor), who is committed to low carbon efforts. Two models are developed for stochastic demand disturbances in the forms of multiplicative case and additive case, respectively. Firstly, the optimal joint decision of the retailer and the supply chain are proposed in two scenarios, i.e., decentralized decision and the centralized decision. Secondly, in order to realize channel coordination, the contract of revenue sharing combined with the mechanism of low-carbon cost sharing is designed. Moreover, the influences of the retailer's fairness concern and bargaining power on the joint decision and the contract parameters are also investigated. Finally, numerical examples are given to illustrate the theoretical results and some suggestions to supply chain management are also provided. The results show that the revenue sharing contract can make the supply chain achieved coordination with the cost sharing mechanism of low-carbon efforts. Furthermore, the optimal low-carbon effort level and ordering quantity decrease in terms of fairness-concerned parameter and Nash bargaining power parameter, which increases in unit cost. However, the optimal pricing makes the opposite change.</p>

Use of Qualitative Research to Generate a Function for Finding the Unit Cost of Software Test Cases

In this article, we demonstrate a novel use of case research to generate an empirical function through qualitative generalization. This innovative technique applies interpretive case analysis to the problem of defining and generalizing an empirical cost function for test cases through qualitative interaction with an industry cohort of subject matter experts involved in software testing at leading technology companies. While the technique is fully generalizable, this article demonstrates this technique with an example taken from the important field of software testing. The huge amount of software development conducted in today's world makes taking its cost into account imperative. While software testing is a critical aspect of the software development process, little attention has been paid to the cost of testing code, and specifically to the cost of test cases, in comparison to the cost of developing code. Our research fills the gap by providing a function for estimating the cost of test cases.