Framework For Quantitative Assessment Research Articles

Security of mineral resources: A new framework for quantitative assessment of criticality

This article discusses the limits of economic growth through the issue of criticality of mineral raw materials. It proposes to use and expand the existing work-but not in France or for France- and then apply them to the French economy between 2009 and 2014 via the example of lithium to provide available indicators and the methodology for identifying pressure signals in the supply of raw materials not so far undetectable in existing criticality studies. After building a database on 15 years of production and world trade of lithium, a literature contextualizing the issue of criticality and articulating the criticality factors with the functioning of commodity markets is performed. The reference model of the European Commission is then explained. In addition to these introductory contributions, the main are threefold: the reconfiguration of existing indicators criticality to the French case; the proposal of a new complementary criticality indicator to the Commission's two and which takes into account not only the upstream market of the material but also its downstream processing by the economy; finally the definition of high and low criticality allows to generate twelve indicators and variants (four strong(s) and eight low) from the two previous points and subjected to robustness checks.

Assessing real-time Zika risk in the United States

BackgroundConfirmed local transmission of Zika Virus (ZIKV) in Texas and Florida have heightened the need for early and accurate indicators of self-sustaining transmission in high risk areas across the southern United States. Given ZIKV’s low reporting rates and the geographic variability in suitable conditions, a cluster of reported cases may reflect diverse scenarios, ranging from independent introductions to a self-sustaining local epidemic.MethodsWe present a quantitative framework for real-time ZIKV risk assessment that captures uncertainty in case reporting, importations, and vector-human transmission dynamics.ResultsWe assessed county-level risk throughout Texas, as of summer 2016, and found that importation risk was concentrated in large metropolitan regions, while sustained ZIKV transmission risk is concentrated in the southeastern counties including the Houston metropolitan region and the Texas-Mexico border (where the sole autochthonous cases have occurred in 2016). We found that counties most likely to detect cases are not necessarily the most likely to experience epidemics, and used our framework to identify triggers to signal the start of an epidemic based on a policymakers propensity for risk.ConclusionsThis framework can inform the strategic timing and spatial allocation of public health resources to combat ZIKV throughout the US, and highlights the need to develop methods to obtain reliable estimates of key epidemiological parameters.

The Research Framework for Quantitative Safety Assessment for Safety-Critical Computer Systems

Objectives: A safety-critical computer system has to be designed with safety in mind. The purpose of this paper is to identify and assess the safety hazards by using the proposed framework for Safety-Critical Computer Systems (SCCS). Methods/Statistical Analysis: Computer software quality models like McCall’s and Boehm’s were deficient in addressing the basic safety issues of SCCS. This paper proposes another safety model for software safety by adjusting McCall’s product quality model that particularly distinguishes the conditions comparing to software safety in safety-critical applications. The conditions in the proposed software safety model relate to Hazard Analysis distinguishing of Completeness of safety requirements, Safety-critical Design, Coding, and Testing. Findings: The criteria in the proposed software safety model relate to Hazard Analysis (HA) distinguishing of safety requirements, Completeness of safety requirements, Safety-critical Design, Safety-critical Coding, and Safety-critical Testing. The proposed safety model changes the current quality model by presenting different safety criteria’s and metrics in all phases of Software life cycle to assess the software safety. This model was connected to a safety basic Railroad Crossing Control System (RCCS) which is a laboratory prototype and obtained better results in terms of safety. Application/Improvements: This model was connected to a safety basic Railroad Crossing Control System (RCCS) which is a laboratory prototype and obtained better results in terms of safety.

The American College of Academic International Medicine 2017 Consensus Statement on International Medical Programs: Establishing a system of objective valuation and quantitative metrics to facilitate the recognition and incorporation of academic international medical efforts into existing promotion and tenure paradigms.

The growth of academic international medicine (AIM) as a distinct field of expertise resulted in increasing participation by individual and institutional actors from both high-income and low-and-middle-income countries. This trend resulted in the gradual evolution of international medical programs (IMPs). With the growing number of students, residents, and educators who gravitate toward nontraditional forms of academic contribution, the need arose for a system of formalized metrics and quantitative assessment of AIM- and IMP-related efforts. Within this emerging paradigm, an institution's “return on investment” from faculty involvement in AIM and participation in IMPs can be measured by establishing equivalency between international work and various established academic activities that lead to greater institutional visibility and reputational impact. The goal of this consensus statement is to provide a basic framework for quantitative assessment and standardized metrics of professional effort attributable to active faculty engagement in AIM and participation in IMPs. Implicit to the current work is the understanding that the proposed system should be flexible and adaptable to the dynamically evolving landscape of AIM – an increasingly important subset of general academic medical activities.

The american college of academic international medicine 2017 consensus statement on international medical programs: Establishing a system of objective valuation and quantitative metrics to facilitate the recognition and incorporation of academic international medical efforts into existing promotion and tenure paradigms

The growth of academic international medicine (AIM) as a distinct field of expertise resulted in increasing participation by individual and institutional actors from both high-income and low-and-middle-income countries. This trend resulted in the gradual evolution of international medical programs (IMPs). With the growing number of students, residents, and educators who gravitate toward nontraditional forms of academic contribution, the need arose for a system of formalized metrics and quantitative assessment of AIM- and IMP-related efforts. Within this emerging paradigm, an institution's “return on investment” from faculty involvement in AIM and participation in IMPs can be measured by establishing equivalency between international work and various established academic activities that lead to greater institutional visibility and reputational impact. The goal of this consensus statement is to provide a basic framework for quantitative assessment and standardized metrics of professional effort attributable to active faculty engagement in AIM and participation in IMPs. Implicit to the current work is the understanding that the proposed system should be flexible and adaptable to the dynamically evolving landscape of AIM – an increasingly important subset of general academic medical activities. The following core competencies are addressed in this article: Patient care, Medical knowledge, Professionalism, Interpersonal and communication skills, Practice-based learning and improvement, and Systems-based practice

Evaluation of Technology Change Effects on Quantitative Assessment of Water, Energy and Food Nexus

The quantitative assessment framework of the water, energy and food (WEF) nexus proposed by [1] permits the analysis of the WEF as an interconnected system of resources that directly and indirectly affect one another. The model performs simulation of policy options and scenarios that respond to quantitative variations of the use of WEF resources. One of the key outcomes of the mathematical formulation of the model is the WEF nexus intersectoral technology matrix. In order to take advantages and analyzing policy options of adopting high efficient intersectoral use technologies, WEF intersectoral use intensities and intersectoral allocation coefficients are introduced to the technology matrix of the nexus model proposed in [1]. The developed method is then applied to evaluate the WEF nexus case study of Lebanon. Lastly, the conclusions and further developments are presented.

An integrated modeling framework for quantitative business continuity assessment

Systems are increasingly exposed to threats of disruptive events, e.g., failures, natural disasters, terrorist attacks, etc. A proactive approach is needed to protect the business and reduce the potential losses caused by these disruptive events. Business Continuity Management (BCM) is a way to integrate the recovery process within the preventive framework of risk assessment. Such integrated risk management strategy offers great potential benefits. However, the complexity of applying it in practice is such that existing BCM strategies are mainly based on qualitative methods only, which limits the potential added values. To support quantitative BCM, in this paper we define a set of quantitative business continuity metrics. The defined metrics are based on the estimated losses incurred by the disruptive event in the whole business process. For this, the business process is divided into four sequential phases, i.e., protection phase, mitigation phase, emergency phase and recovery phase. For each phase, a specific modeling method is developed and an integrated modeling framework is constructed for the business continuity. Simulation can, then, be used to quantify the business continuity metrics. The developed methods are applied to assess the business continuity of an oil storage tank farm.

A Quantitative Assessment Framework for Water, Energy and Food Nexus

This paper presents a quantitative assessment framework of the Water, Energy and Food (W-E-F) nexus. The proposed approach allows integrated quantitative assessments by considering all the W-E-F intersectoral linkages and the competing demand for W-E-F resources to evaluate future development scenarios. Firstly, the conceptual model adopted for the proposed framework is presented. Secondly, a detailed methodological framework is introduced to serve as W-E-F nexus evaluation and planning platform. At the practical level, the model is applied to evaluate the W-E-F nexus in Lebanon. Finally, the conclusions and further developments are presented.

RNA2DNAlign: nucleotide resolution allele asymmetries through quantitative assessment of RNA and DNA paired sequencing data.

We introduce RNA2DNAlign, a computational framework for quantitative assessment of allele counts across paired RNA and DNA sequencing datasets. RNA2DNAlign is based on quantitation of the relative abundance of variant and reference read counts, followed by binomial tests for genotype and allelic status at SNV positions between compatible sequences. RNA2DNAlign detects positions with differential allele distribution, suggesting asymmetries due to regulatory/structural events. Based on the type of asymmetry, RNA2DNAlign outlines positions likely to be implicated in RNA editing, allele-specific expression or loss, somatic mutagenesis or loss-of-heterozygosity (the first three also in a tumor-specific setting). We applied RNA2DNAlign on 360 matching normal and tumor exomes and transcriptomes from 90 breast cancer patients from TCGA. Under high-confidence settings, RNA2DNAlign identified 2038 distinct SNV sites associated with one of the aforementioned asymetries, the majority of which have not been linked to functionality before. The performance assessment shows very high specificity and sensitivity, due to the corroboration of signals across multiple matching datasets. RNA2DNAlign is freely available from http://github.com/HorvathLab/NGS as a self-contained binary package for 64-bit Linux systems.

Quantitative Framework for Retrospective Assessment of Interim Decisions in Clinical Trials.

This article presents a quantitative way of modeling the interim decisions of clinical trials. While statistical approaches tend to focus on the epistemic aspects of statistical monitoring rules, often overlooking ethical considerations, ethical approaches tend to neglect the key epistemic dimension. The proposal is a second-order decision-analytic framework. The framework provides means for retrospective assessment of interim decisions based on a clear and consistent set of criteria that combines both ethical and epistemic considerations. The framework is broadly Bayesian and addresses a fundamental question behind many concerns about clinical trials: What does it take for an interim decision (e.g., whether to stop the trial or continue) to be a good decision? Simulations illustrating the modeling of interim decisions counterfactually are provided.

Integrated maps of biodiversity in the Qinling Mountains of China for expanding protected areas

Habitat fragmentation and loss is the main cause of species extinction; thus, the appropriate placement of protected areas is critical for saving vulnerable and threatened species. However, how to expand the existing protected areas network for improving conservation efficiency is a vital concern. We examined the Qinling Mountains — a widely recognized biogeographic treasure in China and East Asia, to identify key biodiversity areas (KBAs) and compare them with existing protected areas. We focused on 259 key protected wild plant and animal species and modeled species distributions with elevation and habitat preference. We then adapted two established algorithms (biodiversity hotspots of species richness [BHSR] and systematic conservation planning [SCP]) to identify priority areas, respectively. Results from these two algorithms addressed two conservation criteria: “represented” single species and “well-represented” species assemblages. SCP showed better performance (~90%) than BHSR (~78%) using the “represented” criterion covering a small portion (~8%) of the total region; conversely, BHSR showed better performance (~61%) than SCP (~55%) using the “well-represented” criterion. The overlapping priority areas of both methods could achieve an optimal conservation that met dual criteria, which is considered as the candidate KBAs in this study. Surprisingly, we found that 63% of KBAs are not co-occurring with existing national nature reserves (NNRs). We highlight the unoccupied KBAs as deserving additional protection, with a result that the expansion of NNRs to KBAs will increase overall conservation coverage and efficiency. The integrated method developed here can be used generally as a repeatable and quantitative assessment framework to be implemented in protected areas network expansion and planning, in China and beyond.

A remote quantitative Fugl-Meyer assessment framework for stroke patients based on wearable sensor networks

To extend the use of wearable sensor networks for stroke patients training and assessment in non-clinical settings, this paper proposes a novel remote quantitative Fugl-Meyer assessment (FMA) framework, in which two accelerometer and seven flex sensors were used to monitoring the movement function of upper limb, wrist and fingers. The extreme learning machine based ensemble regression model was established to map the sensor data to clinical FMA scores while the RRelief algorithm was applied to find the optimal features subset. Considering the FMA scale is time-consuming and complicated, seven training exercises were designed to replace the upper limb related 33 items in FMA scale. 24 stroke inpatients participated in the experiments in clinical settings and 5 of them were involved in the experiments in home settings after they left the hospital. Both the experimental results in clinical and home settings showed that the proposed quantitative FMA model can precisely predict the FMA scores based on wearable sensor data, the coefficient of determination can reach as high as 0.917. It also indicated that the proposed framework can provide a potential approach to the remote quantitative rehabilitation training and evaluation.

A multi-scale, multi-disciplinary approach for assessing the technological, economic and environmental performance of bio-based chemicals.

In recent years, bio-based chemicals have gained interest as a renewable alternative to petrochemicals. However, there is a significant need to assess the technological, biological, economic and environmental feasibility of bio-based chemicals, particularly during the early research phase. Recently, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain and the de novo prediction of metabolic pathways connecting existing host metabolism to desirable chemical products. This multi-scale, multi-disciplinary framework for quantitative assessment of bio-based chemicals will play a vital role in supporting engineering, strategy and policy decisions as we progress towards a sustainable chemical industry.

Valuation of ecotoxicological impacts from tributyltin based on a quantitative environmental assessment framework.

In the scientific literature, few valuations of biodiversity and ecosystem services following the impacts of toxicity are available, hampered by the lack of ecotoxicological documentation. Here, tributyltin is used to conduct a contingent valuation study as well as cost-benefit analysis (CBA) of measures for improving the environmental status in Swedish coastal waters of the Baltic Sea. Benefits considering different dimensions when assessing environmental status are highlighted and a quantitative environmental assessment framework based on available technology, ecological conditions, and economic valuation methodology is developed. Two scenarios are used in the valuation study: (a) achieving good environmental status by 2020 in accordance with EU legislation (USD 119 household(-1) year(-1)) and (b) achieving visible improvements by 2100 due to natural degradation (USD 108 household(-1) year(-1)) during 8 years. The later scenario was used to illustrate an application of the assessment framework. The CBA results indicate that both scenarios might generate a welfare improvement.

Computer‐aided molecular pathology interpretation in exploring prospective markers for oral submucous fibrosis progression

Evaluation of molecular pathology markers using a computer-aided quantitative assessment framework would help to assess the altered states of cellular proliferation, hypoxia, and neoangiogenesis in oral submucous fibrosis and could improve diagnostic interpretation in gauging its malignant potentiality. Immunohistochemical (IHC) expression of c-Myc, hypoxia-inducible factor-1-alpha (HIF-1α), vascular endothelial growth factor (VEGF), VEGFRII, and CD105 were evaluated in 58 biopsies of oral submucous fibrosis using computer-aided quantification. After digital stain separation of original chromogenic IHC images, quantification of the diaminobenzidine (DAB) reaction pattern was performed based on intensity and extent of cytoplasmic, nuclear, and stromal expression. Assessment of molecular expression proposed that c-Myc and HIF-1α may be used as strong screening markers, VEGF for risk-stratification and VEGFRII and CD105 for prognosis of precancer into oral cancer. Our analysis indicated that the proposed method can help in establishing IHC as an effective quantitative immunoassay for molecular pathology and alleviate diagnostic ambiguities in the clinical decision process.

A tiered assessment framework to evaluate human health risk of contaminated sediment.

For sediment contaminated with bioaccumulative pollutants (e.g., PCBs and organochorine pesticides), human consumption of seafood that contain bioaccumulated sediment-derived contaminants is a well-established exposure pathway. Historically, regulation and management of this bioaccumulation pathway has focused on site-specific risk assessment. The state of California (United States) is supporting the development of a consistent and quantitative sediment assessment framework to aid in interpreting a narrative objective to protect human health. The conceptual basis of this framework focuses on 2 key questions: 1) do observed pollutant concentrations in seafood from a given site pose unacceptable health risks to human consumers? and 2) is sediment contamination at a site a significant contributor to seafood contamination? The first question is evaluated by interpreting seafood tissue concentrations at the site, based on health risk calculations. The second question is evaluated by interpreting site-specific sediment chemistry data using a food web bioaccumulation model. The assessment framework includes 3 tiers (screening assessment, site assessment, and refined site assessment), which enables the assessment to match variations in data availability, site complexity, and study objectives. The second and third tiers use a stochastic simulation approach, incorporating information on variability and uncertainty of key parameters, such as seafood contaminant concentration and consumption rate by humans. The framework incorporates site-specific values for sensitive parameters and statewide values for difficult to obtain or less sensitive parameters. The proposed approach advances risk assessment policy by incorporating local data into a consistent region-wide problem formulation, applying best available science in a streamlined fashion.

New online voltage stability margins and risk assessment for multi-bus smart power grids

This paper presents a quantitative framework for assessment of voltage stability in smart power networks. First, new stability indices similar to gain and phase margins in linear time invariant control systems are introduced. These indices can be computed online in conjunction with load-flow calculations. Then, a novel risk assessment framework incorporating the new stability indices is developed to methodologically quantify the voltage stability risks a power system faces at any given operating condition. In contrast to existing local stability indices and qualitative risk approaches, the indices and framework introduced provide analytical and quantitative evaluation of voltage stability and associated risks. The results are illustrated with a numerical example.

General network reliability problem and its efficient solution by Subset Simulation

Complex technological networks designed for distribution of some resource or commodity are a pervasive feature of modern society. Moreover, the dependence of our society on modern technological networks constantly grows. As a result, there is an increasing demand for these networks to be highly reliable in delivering their service. As a consequence, there is a pressing need for efficient computational methods that can quantitatively assess the reliability of technological networks to enhance their design and operation in the presence of uncertainty in their future demand, supply and capacity. In this paper, we propose a stochastic framework for quantitative assessment of the reliability of network service, formulate a general network reliability problem within this framework, and then show how to calculate the service reliability using Subset Simulation, an efficient Markov chain Monte Carlo method that was originally developed for estimating small failure probabilities of complex dynamic systems. The efficiency of the method is demonstrated with an illustrative example where two small-world network generation models are compared in terms of the maximum-flow reliability of the networks that they produce.

Global protected area expansion is compromised by projected land-use and parochialism.

Protected areas are one of the main tools for halting the continuing global biodiversity crisis caused by habitat loss, fragmentation and other anthropogenic pressures. According to the Aichi Biodiversity Target 11 adopted by the Convention on Biological Diversity, the protected area network should be expanded to at least 17% of the terrestrial world by 2020 (http://www.cbd.int/sp/targets). To maximize conservation outcomes, it is crucial to identify the best expansion areas. Here we show that there is a very high potential to increase protection of ecoregions and vertebrate species by expanding the protected area network, but also identify considerable risk of ineffective outcomes due to land-use change and uncoordinated actions between countries. We use distribution data for 24,757 terrestrial vertebrates assessed under the International Union for the Conservation of Nature (IUCN) 'red list of threatened species', and terrestrial ecoregions (827), modified by land-use models for the present and 2040, and introduce techniques for global and balanced spatial conservation prioritization. First, we show that with a coordinated global protected area network expansion to 17% of terrestrial land, average protection of species ranges and ecoregions could triple. Second, if projected land-use change by 2040 (ref. 11) takes place, it becomes infeasible to reach the currently possible protection levels, and over 1,000 threatened species would lose more than 50% of their present effective ranges worldwide. Third, we demonstrate a major efficiency gap between national and global conservation priorities. Strong evidence is shown that further biodiversity loss is unavoidable unless international action is quickly taken to balance land-use and biodiversity conservation. The approach used here can serve as a framework for repeatable and quantitative assessment of efficiency, gaps and expansion of the global protected area network globally, regionally and nationally, considering current and projected land-use pressures.

Quantitative diagnostics of soft tissue through viscoelastic characterization using time-based instrumented palpation

Although palpation has been successfully employed for centuries to assess soft tissue quality, it is a subjective test, and is therefore qualitative and depends on the experience of the practitioner. To reproduce what the medical practitioner feels needs more than a simple quasi-static stiffness measurement. This paper assesses the capacity of dynamic mechanical palpation to measure the changes in viscoelastic properties that soft tissue can exhibit under certain pathological conditions. A diagnostic framework is proposed to measure elastic and viscous behaviors simultaneously using a reduced set of viscoelastic parameters, giving a reliable index for quantitative assessment of tissue quality. The approach is illustrated on prostate models reconstructed from prostate MRI scans. The examples show that the change in viscoelastic time constant between healthy and cancerous tissue is a key index for quantitative diagnostics using point probing. The method is not limited to any particular tissue or material and is therefore useful for tissue where defining a unique time constant is not trivial. The proposed framework of quantitative assessment could become a useful tool in clinical diagnostics for soft tissue.