Cost Efficiency Analysis Research Articles

Monitoring the Effective Density of Airborne Nanoparticles in Real Time Using a Microfluidic Nanoparticle Analysis Chip.

Determining the effective density of airborne nanoparticles (NPs; particles smaller than 100 nm in diameter) at a point of interest is essential for toxicology and environmental studies, but it currently requires complex analysis systems comprising several high-precision instruments as well as a specially trained operator. To address these limitations, a field-portable and cost-efficient microfluidic NP analysis device is presented, which provides quantitative information on the effective density and size distribution of NPs in real time. Unlike conventional analysis systems, the device can operate in a standalone mode because of the chip operating principle based on the electrostatic/inertial classification and electrical detection methods. Moreover, the device is both compact (16.0 × 10.9 × 8.6 cm3) and light (950 g) owing to the hardware strip down enabled by integrating the essential functions for effective density analysis on a single chip. Quantitative experiments performed to simulate real-life applications utilizing effective density (i.e., effective density-based morphology analysis on engineered NPs and multi-parametric NP monitoring in ambient air) demonstrate that the developed device can be used as an analysis tool in toxicological studies as an on-site sensor for the monitoring of individual NP exposure and environments, for quality monitoring of engineered NPs via aerosol synthesis, and other applications.

Comparison of single-use flexible URS and re-usable flexible URS: Effectiveness, reliability, cost-efficiency analysis

Comparison of Single-use Flexible Ureterorenoscopy (SF-URS) with Reusable Fiberoptic Flexible Ureterorenoscopy (RF-URS) is one of the most popular subject in Endourology. Flexible Ureterorenoscopy (F-URS) is the gold standard method used in the treatment of kidney and ureteral stones smaller than 2 cm and together with ESWL.SF-URS has been widely used along with RF-URS. Our study aims to analyze retrospectively RF-URS and SF-URS in terms of effectiveness, reliability and cost. 200 patients who underwent F-URS due to renal stones were included in our study. Patients were divided into 2 groups: 100 patients who underwent SF-URS and 100 patients who underwent RF-URS. Mean age of the two groups was 49.58, 50.24 in the RF-URS and SF-URS groups, respectively. The presence of hypertension and diabetes, Body Mass-Index (BMI), and stone characteristics were recorded, and postoperative stone-free rates, duration of hospital stay, duration of operation, postoperative hemoglobin loss, postoperative urosepsis, and auxiliary procedures were evaluated. A cost effective analysis was carried out. The demographic data and stone characteristics of both groups were similar and there was no statistically significant difference (p> 0.05). The SF-URS group was found to be more advantageous in terms of the duration of operation (p0.05). The RF-URS group was found to be more advantageous after a cost-effective analysis (p

Conversion from pegfilgrastim with on-body injector to pegfilgrastim-jmdb: cost-efficiency analysis and budget-neutral expanded access to prophylaxis and treatment

Aims Therapeutic guidelines recommend prophylaxis against chemotherapy-induced (febrile) neutropenia (CIN/FN). Pegfilgrastim (Neulasta), biosimilar pegfilgrastim-jmdb (Fulphila), and pegfilgrastim with on-body injector (OBI; Neulasta Onpro) are options for CIN/FN prophylaxis. We aimed to simulate the cost-savings and budget-neutral expanded access to CIN/FN prophylaxis or anticancer treatment achieved through conversion from pegfilgrastim-OBI to pegfilgrastim-jmdb and to evaluate the economic impact of FN-related hospitalization costs due to pegfilgrastim-OBI failure. Methods Cost-savings from conversion from pegfilgrastim-OBI to biosimilar pegfilgrastim-jmdb were simulated in a panel of 15,000 patients with cancer from the US payer perspective. The primary analyses included conversion rates of 10% to 100%. Adjusted analyses also considered OBI device failure rates of 1% to 7% and associated costs of FN-related hospitalization. Simulations of budget-neutral expanded access to prophylaxis with pegfilgrastim-jmdb or to rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) for diffuse large B-cell lymphoma (DLBCL) were also performed. Results In a 15,000-patient panel, conversion from pegfilgrastim-OBI to pegfilgrastim-jmdb resulted in cost-savings ranging from $481,259 (10% conversion) to $4,812,585 (100% conversion) in a single cycle. Over 6 cycles at 100% conversion, savings were $28,857,510 and could provide 9,191 additional doses of pegfilgrastim-jmdb or 4,463 cycles of R-CHOP to patients with DLBCL. Adjusted for OBI failure, cost-savings over 6 cycles ranged from $2,935,565 (10% conversion; pegfilgrastim-OBI failure rate of 1%) to $32,236,499 (100% conversion; 7% failure). These cost-savings could provide 943 doses of pegfilgrastim-jmdb or 454 doses of R-CHOP (10% conversion; 1% pegfilgrastim-OBI failure) or provide 10,261 doses of pegfilgrastim-jmdb or 4,982 cycles of R-CHOP (100% conversion; 7% failure). Conclusion Conversion from pegfilgrastim to pegfilgrastim-jmdb is associated with significant cost-savings which increase markedly when also accounting for pegfilgrastim-OBI failure and associated FN-related hospitalizations. These general and failure-related cost-savings could be allocated on a budget-neutral basis to provide more patients with additional CIN/FN prophylaxis or antineoplastic treatment.

Analysis of cost efficiency of hydrogen production via electrolysis: the Russian case study

The article focused on investigation of cost efficiency of hydrogen production via water electrolysis in Russia up to 2030. Different non-carbon generation technologies were assumed as input sources for electrolysis, namely wind, solar, hydro and nuclear power plants. Analysis is based on levelized cost of hydrogen (LCOH) framework incorporating all cost related to electrolysis (capital cost, operation & maintenance, electricity price, etc.). Additionally, we estimated LCOH sensitivity to some techno-economic parameters – cost of capital, capital expenses and capacity factor of different power supply sources.

시장형 공기업의 원가효율성 분석

[연구목적] 본 연구의 목적은 우리나라 공기업의 원가효율성을 자료포락분석을 통하여 측정하여 시장형 공기업과 준시장형 공기업의 원가효율성을 분석하고, 현행 공기업 경영평가지표와 DEA를 통한 원가효율성을 비교분석하는데 있다.<BR>공기업에서 시행되고 있는 경영실적 평가방법은 경영관리범주와 주요사업범주로 구성된다. 이러한 경영실적 평가방법이 공기업의 소기의 경영성과를 가져왔다고 할 수도 있지만, 다른 한편으로는 경영평가지표 자체의 한계로 인해 경영평가 결과에 대한 신뢰성 및 수용성 문제가 종종 제기되고 있다. 본 연구에서는 현행의 경영평가 방법을 일부 보완할 수 있는 공기업 경영평가지표를 제안하고자 한다.<BR>[연구방법] 2018년도 기준 16개 시장형 공기업과 19개 준시장형 공기업을 대상으로 비모수적 방법으로 상대적 효율성을 측정하는 분석방법인 DEA 모형을 이용하여 원가효율성을 분석하였다. DEA 효율치 측정을 위한 투입요소로는 총자산, 인원수, 자기자본을, 산출변수로는 매출액을 선정하였다.<BR>[연구결과] CCR모형에서는 시장형과 준시장형 공기업 간에 원가효율성의 차이가 없었으며, BCC모형에서는 시장형 공기업의 원가효율성이 준시장형 공기업의 원가효율성 보다 유의하게 큰 것으로 나타났다. 또한 공기업 경영실적 평가시스템의 신뢰성에 대한 근거를 제시하고자 공기업 경영실적 평가 결과와 DEA로 측정한 원가효율성을 비교한 결과, 기존 경영실적 평가 결과와 DEA 원가효율성 간의 일관성은 다소 부족한 것으로 나타났다.<BR>[연구의 시사점] 본 연구에서는 공기업에 대한 전반적인 경영효율성의 현실을 파악함으로써 원가효율성의 정책적 경영지원에 대한 가이드라인을 제공하고자 하였으며, 현행 경영평가지표와의 비교·분석을 통해 부가적인 공기업 경영평가지표를 제안하고자 하였다.

Harvesting spatially dense legacy soil datasets for digital soil mapping of available water capacity in Southern France

Although considerable work has been conducted in recent decades to build soil databases, the legacy data from a lot of former soil survey campaigns still remain unused. The objective of this study was to determine the interest in harvesting such legacy data for mapping the soil available water capacities (SAWCs) at different rooting depths (30 cm, 60 cm, 100 cm) and to the maximal observation depth, over the commune of Bouillargues (16 km2, Occitanie region, southern France).An increasing number of available auger hole observations with SAWC estimations – from 0 to 2781 observations – were added to the existing soil profiles to calibrate quantile regression forests (QRFs) using the Euclidean buffer distances from the sites as soil covariates. The SAWC was first mapped separately for different soil layers, and the mapping outputs were pooled to estimate the required SAWC. The uncertainty of the SAWC prediction was estimated from the estimated mapping uncertainties of the individual soil layers by an error propagation model using a first-order Taylor analysis.The performances of the SAWC predictions and their uncertainties were evaluated with a 10-fold cross validation that was iterated 20 times. The results showed that the use of a quantile regression forest that was fed with auger hole observations and that used the Euclidean buffer distances as soil covariates considerably augmented the performances of the SAWC predictions (percentages of explained variance from 0.39 to 0.70) compared to the performance of a classical DSM approach, i.e., a QRF that solely used soil profiles and only environmental covariates (percentages of explained variance from 0.04 to 0.51). The analysis of the results revealed that the performances were also dependent on the spatial patterns of the different examined SAWCs and was limited by the observational uncertainties of the SAWCs determined from auger holes. The best performance tended to also provide the best view of the uncertainty patterns with an overestimation of uncertainty.Despite these gains in performance, the cost-efficiency analysis showed that the augmentation of soil observations was not cost efficient because of the highly time-consuming manual data harvesting protocol. However, this result did not account for the observed gain in map details. Furthermore, the cost efficiency could be further improved by automation.

Digital Pathology: Advantages, Limitations and Emerging Perspectives.

Digital pathology is on the verge of becoming a mainstream option for routine diagnostics. Faster whole slide image scanning has paved the way for this development, but implementation on a large scale is challenging on technical, logistical, and financial levels. Comparative studies have published reassuring data on safety and feasibility, but implementation experiences highlight the need for training and the knowledge of pitfalls. Up to half of the pathologists are reluctant to sign out reports on only digital slides and are concerned about reporting without the tool that has represented their profession since its beginning. Guidelines by international pathology organizations aim to safeguard histology in the digital realm, from image acquisition over the setup of work-stations to long-term image archiving, but must be considered a starting point only. Cost-efficiency analyses and occupational health issues need to be addressed comprehensively. Image analysis is blended into the traditional work-flow, and the approval of artificial intelligence for routine diagnostics starts to challenge human evaluation as the gold standard. Here we discuss experiences from past digital pathology implementations, future possibilities through the addition of artificial intelligence, technical and occupational health challenges, and possible changes to the pathologist’s profession.

Trade-off analysis of cost and nutrient efficiency of coffee farms in vietnam: A more generalised approach

Literature has documented significant trade-offs between economic and environmental performance in many areas of agricultural production. However, while it has focused on the trade-off for technically efficient farms there are differing types of trade-offs that exist for differing types of farms. The present paper addresses these gaps in the literature by proposing a more generalised approach to analysing cost and environmental trade-offs. There is also a lack of research on the nature of the trade-off in coffee farming. This is especially so in Vietnam where there is both significant overuse of nutrients and increasing autonomous adaption through voluntary participation in sustainability certification schemes. The proposed framework is employed to investigate a data set of 679 Vietnamese coffee farms. This study delivers several important findings. First, the proposed approach indicates four distinct groups of farms facing differing types of trade-offs with some farms not facing any trade-offs. Second, empirical results show that the average levels of technical, cost and environmental efficiency are relatively low. Third, sustainability certified farms are found to perform better than non-certified farms although the differences in performance diminish over time. Overall, the empirical results favour a heterogeneous and more integrated policy approach to improving the technical, cost and environmental efficiency of coffee farmers in Vietnam.

High-throughput analyses and Bayesian network modeling highlight novel epigenetic Adverse Outcome Pathway networks of DNA methyltransferase inhibitor mediated transgenerational effects

A number of epigenetic modulating chemicals are known to affect multiple generations of a population from a single ancestral exposure, thus posing transgenerational hazards. The present study aimed to establish a high-throughput (HT) analytical workflow for cost-efficient concentration-response analysis of epigenetic and phenotypic effects, and to support the development of novel Adverse Outcome Pathway (AOP) networks for DNA methyltransferase (DNMT) inhibitor-mediated transgenerational effects on aquatic organisms. The model DNMT inhibitor 5-azacytidine (5AC) and the model freshwater crustacean Daphnia magna were used to generate new experimental data and served as prototypes to construct AOPs for aquatic organisms. Targeted HT bioassays (DNMT ELISA, MS-HRM and qPCR) in combination with multigenerational ecotoxicity tests revealed concentration-dependent transgenerational (F0-F3) effects of 5AC on total DNMT activity, DNA promoter methylation, gene body methylation, gene transcription and reproduction. Top sensitive toxicity pathways related to 5AC exposure, such as apoptosis and DNA damage responses were identified in both F0 and F3 using Gaussian Bayesian network modeling. Two novel epigenetic AOP networks on DNMT inhibitor mediated one-generational and transgenerational effects were developed for aquatic organisms and assessed for the weight of evidence. The new HT analytical workflow and AOPs can facilitate future ecological hazard assessment of epigenetic modulating chemicals.

Identification of fetal unmodified and 5-hydroxymethylated CG sites in maternal cell-free DNA for non-invasive prenatal testing

BackgroundMassively parallel sequencing of maternal cell-free DNA (cfDNA) is widely used to test fetal genetic abnormalities in non-invasive prenatal testing (NIPT). However, sequencing-based approaches are still of high cost. Building upon previous knowledge that placenta, the main source of fetal circulating DNA, is hypomethylated in comparison to maternal tissue counterparts of cfDNA, we propose that targeting either unmodified or 5-hydroxymethylated CG sites specifically enriches fetal genetic material and reduces numbers of required analytical sequencing reads thereby decreasing cost of a test.MethodsWe employed uTOPseq and hmTOP-seq approaches which combine covalent derivatization of unmodified or hydroxymethylated CG sites, respectively, with next generation sequencing, or quantitative real-time PCR.ResultsWe detected increased 5-hydroxymethylcytosine (5hmC) levels in fetal chorionic villi (CV) tissue samples as compared with peripheral blood. Using our previously developed uTOP-seq and hmTOP-seq approaches we obtained whole-genome uCG and 5hmCG maps of 10 CV tissue and 38 cfDNA samples in total. Our results indicated that, in contrast to conventional whole genome sequencing, such epigenomic analysis highly specifically enriches fetal DNA fragments from maternal cfDNA. While both our approaches yielded 100% accuracy in detecting Down syndrome in fetuses, hmTOP-seq maintained such accuracy at ultra-low sequencing depths using only one million reads. We identified 2164 and 1589 placenta-specific differentially modified and 5-hydroxymethylated regions, respectively, in chromosome 21, as well as 3490 and 2002 Down syndrome-specific differentially modified and 5-hydroxymethylated regions, respectively, that can be used as biomarkers for identification of Down syndrome or other epigenetic diseases of a fetus.ConclusionsuTOP-seq and hmTOP-seq approaches provide a cost-efficient and sensitive epigenetic analysis of fetal abnormalities in maternal cfDNA. The results demonstrated that T21 fetuses contain a perturbed epigenome and also indicated that fetal cfDNA might originate from fetal tissues other than placental chorionic villi. Robust covalent derivatization followed by targeted analysis of fetal DNA by sequencing or qPCR presents an attractive strategy that could help achieve superior sensitivity and specificity in prenatal diagnostics.

Analysis of Energy Saving Effect and Cost Efficiency of ECMs to Upgrade the Building Energy Code

Building energy codes are key policy tools for improving building energy efficiency by defining the minimum requirement for the energy performance of new buildings. In Korea, the building energy code was focused on prescriptive criteria for a long time but is now gradually introducing performance criteria. However, switching to performance criteria is not straightforward because of the resistance of the market to abandoning the well-consolidated prescriptive criteria. The objective of this study is to derive appropriate measures to strengthen the prescriptive criteria and the performance criteria, considering both the energy-saving effect and the economic efficiency for new office buildings and educational buildings to increase the market acceptance of the building energy codes. To this end, the energy-saving effects of reference buildings resulting from the reinforcement of the prescriptive criteria in the past have been first analyzed. Then, based on the collected energy performance parameters and cost data, the economic efficiency relative to the energy saving deriving from the application of passive and active energy conservation measures (ECMs) were analyzed, and future building energy code’s reinforcement measures were derived.

Portable Gait Analysis System with an Integration of Kinect sensor and Inertial Measurement Units

Clinical gait analysis is used for diagnosing, assessing, and for monitoring a patient by analyzing their kinetics, kinematics and electromyography while walking. Traditionally, gait analysis is performed in a formal laboratory environment making use of several high-resolution cameras, either video or infrared. The subject is asked to walk on a force platform or a treadmill with several markers attached to their body, allowing cameras to capture the joint coordinates across time. The space required for such a laboratory is non-trivial and often the associated costs of such an experimental setup is prohibitively expensive. The current work aims to investigate the coupled use of a Microsoft Kinect and Inertial Measurement Units as a portable and cost-efficient gait analysis system. Past studies on assessing gait using either Kinect or Inertial Measurement Units concluded that they achieve medium reliability individually due to some drawbacks related to each sensor. In this study, we propose that a combined system is efficient in detecting different phases of human gait, and the combination of sensors complement each other by overcoming the individual sensor drawbacks. Preliminary findings indicate that the IMU sensors are efficient in providing gait kinematics such as step length, stride length, velocity, cadence, etc., whereas the Kinect sensor helps in studying the gait asymmetries by comparing the right and left joint, such as hips, knees, and ankle.

Critical Assessment of Analytical Methods for the Harmonized and Cost-Efficient Analysis of Microplastics.

Microplastics are of major concerns for society and is currently in the focus of legislators and administrations. A small number of measures to reduce or remove primary sources of microplastics to the environment are currently coming into effect. At the moment, they have not yet tackled important topics such as food safety. However, recent developments such as the 2018 bill in California are requesting the analysis of microplastics in drinking water by standardized operational protocols. Administrations and analytical labs are facing an emerging field of methods for sampling, extraction, and analysis of microplastics, which complicate the establishment of standardized operational protocols. In this review, the state of the currently applied identification and quantification tools for microplastics are evaluated providing a harmonized guideline for future standardized operational protocols to cover these types of bills. The main focus is on the naked eye detection, general optical microscopy, the application of dye staining, flow cytometry, Fourier transform infrared spectroscopy (FT-Ir) and microscopy, Raman spectroscopy and microscopy, thermal degradation by pyrolysis-gas chromatography-mass spectrometry (py-GC-MS) as well as thermo-extraction and desorption gas chromatography-mass spectrometry (TED-GC-MS). Additional techniques are highlighted as well as the combined application of the analytical techniques suggested. An outlook is given on the emerging aspect of nanoplastic analysis. In all cases, the methods were screened for limitations, field work abilities and, if possible, estimated costs and summarized into a recommendation for a workflow covering the demands of society, legislation, and administration in cost efficient but still detailed manner.

Evaluation of Mass Sensitive Micro-Array biosensors for their feasibility in multiplex detection of low molecular weight toxins using mycotoxins as model compounds

Mycotoxins produced by Fusarium species including trichothecenes, zearalenone and fumonisins, can co-contaminate food and feed throughout the supply chain, including cereal grains and animal feeds. There is an increasing demand to enhance global food security by improving the monitoring of mycotoxins throughout our food supply chain. For time and cost-efficient analysis, rapid tests capable of detecting multiple toxins from a single sample are ideal. Considering these current trends in mycotoxin testing, this project examined the feasibility of using both a portable and non-portable mass-based biosensor for multiplex mycotoxin detection. The biosensor was a mass sensitive microarray (MSMA) which consisted of 4 × 16 miniaturized mass sensitive transducer pixels based on solidly mounted resonator (SMR) technology. Functionalisation of individual pixels on the sensor surface using nano-spotting technology for the simultaneous and semi-quantitative detection of three regulated mycotoxins: T2-toxin (T2) zearalenone (ZEN), and fumonisin B1 (FumB1) was examined. With the integration of portable and non-portable microfluidic devices for antibody and standard sample injections, competitive inhibition assays were developed followed by singleplex and multiplex calibration curves. The characteristics and performance of the MSMA were evaluated including sensitivity which was determined as the concentration causing 50% inhibition. Sensitivity of singleplex assays using the portable microfluidic device (PMD) were 1.3 ng/ml, 2.0 ng/ml and 6.8 ng/ml for T2, FumB1 and ZEN, respectively. Sensitivity of the multiplex assay again using the PMD was 6.1 ng/ml, 3.6 ng/ml and 2.4 ng/ml for T2, FumB1 and ZEN, respectively. The PMD was an easy to use and highly sensitive screening tool which has been demonstrated for the multiplex detection of three regulated mycotoxins. Analysis was in real time and results were fully digital. Since detection of analytes was by mass it was both a label-free and cost-efficient method proposed method of analysis for mycotoxins.

A Cost Efficiency Analysis of Flood Proofing Measures for Hydraulic Risk Mitigation in an Urbanized Riverine Area

Non-structural measures for flood risk mitigation are often more economically accessible, easier to implement, and are highly effective, especially in view of the pursuit of risk resilience objectives. Among the non-structural measures, more importance is increasingly being attributed to flood proofing interventions. There are two main types of flood proofing: dry proofing and wet proofing. An example of dry proofing is shielding, which involves the use of flood barriers that can be installed in the entrances of buildings or outside the buildings in order to avoid contact with the houses and deviate the water flow. Their use must be supported by a detailed hydraulic analysis to ensure the correct design is used. This kind of intervention also avoids inducing a feeling of false security (the levee effect) in the exposed population, and therefore contributes to increasing their resilience. The aim of the work presented here is to determine an optimal combination of and choice between different types of structural and non-structural measures through the development of a methodology for assessing the real efficiency levels of different measures, using a cost–benefit analysis (CBA) and starting from the estimation of the direct flood damage. The application of the CBA to a case study of the Mela river in northeastern Sicily, which suffered a flooding event in October 2015, is supported by the determination of the real damages after the flood and the modeling of the same damages for alternative scenarios. The results affirm the possibility of reducing or avoiding some of the damage using the proposed flood proofing measures instead of classical ones.

Random Forest Machine Learning Model for Predicting Combustion Feedback Information of a Natural Gas Spark Ignition Engine

AbstractEngine calibration requires detailed feedback information that can reflect the combustion process as the optimized objective. Indicated mean effective pressure (IMEP) is such an indicator describing an engine’s capacity to do work under different combinations of control variables. In this context, it is of interest to find cost-effective solutions that will reduce the number of experimental tests. This paper proposes a random forest machine learning model as a cost-effective tool for optimizing engine performance. Specifically, the model estimated IMEP for a natural gas spark ignited engine obtained from a converted diesel engine. The goal was to develop an economical and robust tool that can help reduce the large number of experiments usually required throughout the design and development of internal combustion engines. The data used for building such correlative model came from engine experiments that varied the spark advance, fuel-air ratio, and engine speed. The inlet conditions and the coolant/oil temperature were maintained constant. As a result, the model inputs were the key engine operation variables that affect engine performance. The trained model was shown to be able to predict the combustion-related feedback information with good accuracy (R2 ≈ 0.9 and MSE ≈ 0). In addition, the model accurately reproduced the effect of control variables on IMEP, which would help narrow the choice of operating conditions for future designs of experiment. Overall, the machine learning approach presented here can provide new chances for cost-efficient engine analysis and diagnostics work.

Integration of PCA and Fuzzy Clustering for Delineation of Soil Management Zones and Cost-Efficiency Analysis in a Citrus Plantation

Citrus spp. are one of the most important commercial crops with global marketing potential in the world, as in Iran. A soil management zone (MZ) as an appropriate approach is necessary to achieve sustainable production, along with improving soil management and increasing economic benefits in the commercial citrus plantations of northern Iran. As the first report, the biological and terrain attributes along with the physicochemical properties (57 soil samples, 0–30 cm) were used for MZ delineation using the integration of principal component analysis (PCA) and the fuzzy c-means clustering methods. An economic analysis based on the MZ results was also performed to determine the changes in each MZ using a relative cost (RC) value. The high correlation between soil properties and terrain attributes and the considerable spatial variation of these factors in the study area call for site-specific nutrient management. The optimal number of MZs was six and there was a significant heterogeneity variation among different MZs. The ranking of the MZs were MZ5 &gt; MZ2 &gt; MZ6 &gt; MZ1 &gt; MZ3 &gt; MZ4 based on higher soil quality and lower costs per tree. The MZ4, MZ3, MZ1, MZ6, and MZ2 required 34.4, 30.6, 29.4, 9.77, and 9.44% more costs than MZ5 (as reference MZ) for achieving similar productivity, respectively. Therefore, this simple and cost-effective approach could be an initial step to utilize fertilizers site-specifically for data-scarce areas and reduce the soil property variability within the delineated MZs, which is fundamental for precision agriculture management.

Cost-Efficiency Index of the Development Plan of Medellín, 2015

This article illustrates a microsimulation exercise on the Local Development Plan 2016–2019: Medellin Cuenta con Vos using a cost-efficiency approach [A Cost-Efficiency Analysis (CEA) when focused on the study of public policy establishes how the investment in one or several interventions impacts the well-being of the population in a quantifiable value. I will conceive this analysis as the monetary resources that are required to impact a well-being indicator in a specific percentage, what allows me to make a policy comparison]. Public projects in education, health, social inclusion, security, housing, urban integral projects (UIP), environmental development and mobility are simulated, using as an objective function the Cost-Efficiency Index of the Development Plan (CEIDP). I found that by executing the whole investment plan, the index increases by 3.07% points for the 4-year period. The most cost-efficient public interventions are those attached to the UIP. I estimate that the investment of COP 1.0 billion in the UIP projects might trigger by 0.01% the CEIDP, followed by training for work projects (COP 2.5 billion) and childhood projects (COP 2.6 billion).

Cost-efficiency analysis of voluntary vaccination against n-serovar diseases using antibody-dependent enhancement: A game approach

Records of epidemics acknowledge immunological multi-serotype illnesses as an important aspect of the occurrence and control of contagious diseases. These patterns occur due to antibody-dependent-enhancement (ADE) among serotype diseases, which leads to infection of secondary infectious classes. One example of this is dengue hemorrhagic fever and dengue shock syndrome, which comprises the following four serotypes: DEN-1, DEN-2, DEN-3, and DEN-4. The evolutionary vaccination game approach is able to shed light on this long-standing issue in a bid to evaluate the success of various control programs. Although immunization is regarded as one of the most accepted approaches for minimizing the risk of infection, cost and efficiency are important factors that must also be considered. To analyze the n-serovar aspect alongside ADE consequence in voluntary vaccination, this study establishes a new mathematical epidemiological model that is dovetailed with evolutionary game theory, an approach through which we explored two vaccine programs: primary and secondary. Our findings illuminate that the ‘cost-efficiency’ effect for vaccination decision exhibits an impact on controlling n-serovar infectious diseases and should be designed in such a manner as to avoid adverse effects. Furthermore, our numerical result justifies the fact that adopting ADE significantly boosted emerging disease incidence, it also suggest that the joint vaccine policy works even better when the complex cyclical epidemic outbreak takes place among multi serotypes interactions. Research also exposes that the primary vaccine is a better controlling tool than the secondary; however, introducing a highly-efficiency secondary vaccine against secondary infection plays a key role to control the disease prevalence.

Cost Efficiency Analysis in the Banking Industry

The efficiency of commercial banks is essential for the stability of banks by implying that banks that take higher risks are more inefficient. This paper builds on a stochastic heteroscedastic boundary model, where one will analyze a sample of 70 banks in Western Balkan countries such as Albania, Northern Macedonia, Serbia, Kosovo, and Montenegro for the period 2007-2017, highlighting determinants of bank cost efficiency. Banks with less liquidity, with a lower solvency rate and a higher credit risk, are more ineffective than prudent credit institutions. The paper also aims to address the relative lack of studies on the efficiency of banks in the region through the use of the stochastic frontier analysis (SFA).