Hypothetical Group Research Articles

The new micro-kingdoms of eukaryotes

The new micro-kingdoms of eukaryotes

DGI-053 Pharmacoeconomic Considerations Regarding the Treatment of Chronic Hepatitis C with Protease Inhibitors

BackgroundThe standard care for chronic hepatitis C is a double treatment that consists of associating ribavirin (RBV) and peginterferon (pegINF) α-2a/2b. New therapeutic agents telaprevir and boceprevir have recently been...

Sexual Wellness Enhancement and Enrichment Training (SWEET): A hypothetical group model for addressing sexual health and wellbeing

This article presents a four-stage literature review conducted as a first phase in determining the potential benefits of the proposed Sexual Wellness Enhancement and Enrichment Training (SWEET) model (a modified mind-body skills group), which combines a number of research-based healing modalities, including conscious breathing, mindfulness meditation, mindful eating, movement exercises, autogenics and biofeedback, as a possible alternative for improving sexual wellness through adequate and informed self-care. Educational and experiential components are geared toward teaching participants how to incorporate mind-body skills into their daily lives. The first stage of the literature review examines researched applications of the mind-body skills group (MBSG) model, upon which the SWEET model is based. As stress-reduction is a primary mechanism of the MBSG model, the second stage evaluates the relationship between stress and sexual function. The third stage summarizes research linking the primary modalities used in the SWEET model with aspects of sexual wellness. The final phase of this literature review focuses on the incorporation of targeted sexuality education and psychoeducation in addressing sexual concerns. Studies to determine the effectiveness of the model are called for. However, it appears that the approach is solidly grounded in the existing literature.

The New World of Clinical Genomics

The New World of Clinical Genomics

The clinical benefit of blood transfusion: a hypothetical experiment based on a nationwide survey of severe maternal morbidity

It is beyond doubt that blood transfusion services have added to the decline in maternal mortality in high-resource countries. To quantify the clinical benefit of red blood cell (RBC) transfusion in obstetric care, we performed a hypothetical experimental study using data from a prospective nationwide cohort of women giving birth in the Netherlands. Data were abstracted from a nationwide cohort study on severe maternal morbidity, including obstetric haemorrhage requiring 4 or more units of RBC, to obtain an observed and a hypothetical control group consisting of the same women. In the hypothetical control group, we simulated a situation where RBC transfusion was unavailable and estimated how many of these women would have died in that situation. A questionnaire survey asked experts in major (obstetric) haemorrhage to choose a critical minimal number of RBC transfusions at which a woman with obstetric haemorrhage would have died if RBC transfusion was not available. Maternal mortality rate per 100,000 maternities [maternal mortality ratios (MMR)] and relative risk were calculated for the observed and hypothetical group. The observed MMR was 13 per 100,000 maternities. According to 47 responding experts, the median number of RBC units without which a woman would have most probably died was nine, resulting in a hypothetical MMR of 87 per 100,000 maternities (relative risk 6·5; 95% confidence interval 4·2-10·0). It can be expected that unavailability of RBC transfusion in obstetric care increases the risk of maternal death 6.5-fold. Blood transfusion thus largely contributes to the decline of MMR and would also be an important pillar of improving quality of care in resource-poor settings.

Computer vision as a method complementary to molecular analysis: Grapevine cultivar seeds case study

Despite different breeding events, as well as the domestication phenomena which contributed to enrich the grape varietal heritage in Sardinia, many local varieties simply are the product of linguistic distorting due to the wide heterogeneity historic-cultural of the island. This phenomenon generated a great assortment of grape names, that, together with the huge real number of cultivars, is the cause of the incredible current grapevine Sardinian panorama. The goal of this article is to compare the published molecular data of 40 Sardinian autochthonous cultivars with the results achieved by the germplasm phenotypical characterization, on the basis of morpho-colorimetric features and Elliptic Fourier Descriptors (EFDs), measured by image analysis. Statistical classifiers were implemented to discriminate dissimilar seeds and carry out hypothetical synonymy groups to compare with those proposed on the basis of Simple Sequence Repeat (SSR) markers. This work represents the first trial to validate a morpho-colorimetric characterization method by direct comparison with molecular data, proving that the 113 measured features of the germplasm resulted adequate to achieve a clear discrimination among the synonymy groups.

Inferring the effect of therapies on tumor growth by using diffusion processes

Modeling the effect of therapies in cancer animal models remains a challenge. This point may be addressed by considering a diffusion process that models the tumor growth and a modified process that includes, in its infinitesimal mean, a time function modeling the effect of the therapy. In the case of a Gompertz diffusion process, where a control group and one or more treated groups are examined, a methodology to estimate this function has been proposed by Albano et al. (2011). This method has been applied to infer the effect of cisplatin and doxorubicin+cyclophosphamide on breast cancer xenografts. Although this methodology can be extended to other diffusion processes, it has an important restriction: it is necessary that a known diffusion process adequately fits the control group. Here, we propose the use of a stochastic process for a hypothetical control group, in such a way that both the control and the treated groups can be modeled by modified processes of the former. Thus, the comparison between models would allow estimating the real effect of the therapy. The new methodology has been validated by inferring the effects in breast cancer models, and we have checked the robustness of the procedure against the choice of stochastic model for the hypothetical control group. Finally, we have also applied the methodology to infer the effect of a therapeutic peptide and ovariectomy on the growth of a breast cancer xenograft, and its efficiency in modeling the effect of different treatments in the absence of control group data is shown.

C max and t max verification using Fibonacci sequence and absorption rate

The aim of this study was to verify the values of maximal observed concentration (C max,obs) and the time, at which maximum concentration is observed (t max,obs) using the analysis of the absorption rate constant (k ab). It focused on the changes in concentration over time (C-T) for drugs, for which several peaks of concentration occur. In addition, the attempt was made to use Fibonacci sequence to facilitate the visual analysis of the dynamics in changes of concentration on C-T graphs. The analyses were conducted with the use of three hypothetical data groups (groups I, II and III), which had distinct C-T profiles, and with the in vivo data form healthy subjects (n=10) taking part in a bioequivalence study, who was given a single oral dose of topiramate (100mg). The comparison of hypothetical and real in vivo data demonstrated that for the C-T curves, in which there are several peaks of concentration C max,obs and t max,obs values can easily be miscalculated when the increase in concentration is not properly related to the appropriate absorption phase (63.2, 87.50, 96.88%). It was also demonstrated that the data transformation with the use of Fibonacci sequence exposes slight differences in the observed concentration values in a semi-logarithmic scale. The results of this study show that in case of C-T curves with several peaks of concentration, the verification of C max and t max data obtained taking into account different absorption phases enables more precise evaluation of these parameters.

Hemorrhagic Complications Associated With Aspirin

ASPIRIN IS WIDELY USED FOR PRIMARY AND SECONDary prevention of cardiovascular events. Substantial scientific evidence supports the beneficial role of aspirin in reducing the risk of cardiovascular events in secondary prevention. In a meta-analysis including 135 000 patients considered to be at high risk for vascular events (90% with known coronary artery disease, cerebral artery disease, or peripheral artery disease), aspirin was associated with a reduced relative risk of vascular events (myocardial infarction, stroke, and vascular death) by 22% (absolute risk reduction [ARR], 2.5%) but also was associated with an increased relative risk of major extracranial bleeding events by 60% (absolute risk increase [ARI], 0.42%). In another meta-analysis, aspirin used for secondary prevention was associated with a reduced relative risk of myocardial infarction by 31%, ischemic stroke by 22%, and cardiovascular death by 13%. For a hypothetical group of 10 000 patients, aspirin used for secondary prevention would be expected to prevent approximately 250 major vascular events (number needed to treat [NNT], 40) but would be expected to cause approximately 40 major extracranial bleeding events (number needed to harm [NNH], 240). Thus, the net benefit of aspirin for secondary prevention would substantially exceed the bleeding hazard. For 6 major vascular events prevented, approximately 1 major bleeding event would occur; therefore, the value of aspirin for secondary prevention is not disputed. In contrast, there is an ongoing debate surrounding use of aspirin for primary prevention. Published evidence does not support the assumption that the balance of benefits and harms of aspirin use is clearly favorable for primary prevention. In a meta-analysis using individual patient data from 6 randomized trials including 95 000 patients, aspirin was associated with a reduced relative risk of vascular events by 12% (ARR, 0.07%), but also was associated with an increased relative risk of extracranial bleeding events by 54% (ARI, 0.03%). Although aspirin was associated with reduced relative risk of myocardial infarction by 23% (ARR, 0.05%), there was no association between aspirin use and risk of stroke or vascular death. The proportional reduction of vascular events by aspirin in primary prevention was not affected by the predicted risk of coronary heart disease, age, sex, hypertension, or diabetes. For a hypothetical group of 10 000 patients, aspirin use for primary prevention would be expected to prevent 7 major vascular events (NNT, 1430) and cause 1 hemorrhagic stroke and 3 major extracranial bleeding events (NNH, 2500). This suggests that for 2 major vascular events prevented, approximately 1 major bleeding event would occur. A meta-analysis that focused on primary prevention suggested that the effects of aspirin were sex-related: aspirin was associated with a reduced relative risk of stroke by 24% among women and reduced relative risk of myocardial infarction by 32% among men, but these risk reductions were offset by an increase in the relative risk of major bleeding events by 68% among women and 72% among men. Another meta-analysis and a randomized trial support the findings that the magnitude of benefit with aspirin in primary prevention is small and at least partially balanced by the magnitude of harm. Before these clinical trial data were available, the US Preventive Services Task Force recommended use of aspirin for men aged 45 to 79 years and for women aged 55 to 79 years when the potential benefit due to a reduction in myocardial infarction outweighs the potential harm due to an increase in gastrointestinal hemorrhage. These recommendations seem to be mainly based on evidence extrapolated from large trials of populations at high risk of vascular events, under the assumption that age confers an elevated risk of cardiovascular disease. In light of more recent reports, the new European guidelines on cardiovascular disease prevention do not recommend aspirin for primary prevention because of its unfavorable risk-to-benefit profile. In this issue of JAMA, findings from the study by De Berardis et al reinforce the European recommendations for aspirin use. The authors performed a population-based co-

Cost-effectiveness and budget impact of saxagliptine as additional therapy to metformin for the treatment of diabetes mellitus type 2 in the Brazilian private health system

To compare costs and clinical benefits of three additional therapies to metformin (MF) for patients with diabetes mellitus type 2 (DM2). A discrete event simulation model was built to estimate the cost-utility ratio (cost per quality-adjusted life years [QALY]) of saxagliptine as an additional therapy to MF when compared to rosiglitazone or pioglitazone. A budget impact model (BIM) was built to simulate the economic impact of saxagliptine use in the context of the Brazilian private health system. The acquiring medication costs for the hypothetical patient group analyzed in a time frame of three years, were R$ 10,850,185, R$ 14,836,265 and R$ 14,679,099 for saxagliptine, pioglitazone and rosiglitazone, respectively. Saxagliptine showed lower costs and greater effectiveness in both comparisons, with projected savings for the first three years of R$ 3,874 and R$ 3,996, respectively. The BIM estimated cumulative savings of R$ 417,958 with the repayment of saxagliptine in three years from the perspective of a health plan with 1,000,000 covered individuals. From the perspective of private paying source, the projection is that adding saxagliptine with MF save costs when compared with the addition of rosiglitazone or pioglitazone in patients with DM2 that have not reached the HbA1c goal with metformin monotherapy. The BIM of including saxagliptine in the reimbursement lists of health plans indicated significant savings on the three-year horizon.

Custo-efetividade e impacto orçamentário da saxagliptina como terapia adicional à metformina para o tratamento do diabetes mellitus tipo 2 no sistema de saúde suplementar do Brasil

Comparar custos e benefícios clínicos de três terapias adicionais à metformina (MF) para pacientes com diabetes mellitus tipo 2 (DMT2). Um modelo de simulação de eventos discretos foi construído para estimar a relação custo-utilidade (custo por QALY) da saxagliptina como uma terapia adicional à MF comparada à rosiglitazona ou pioglitazona. Um modelo de impacto orçamentário (BIM – Budget Impact Model ) foi construído para simular o impacto econômico da adoção de saxagliptina no contexto do Sistema Suplementar de Saúde brasileiro. O custo de aquisição da medicação para o grupo de pacientes hipotéticos analisados, para o horizonte temporal de três anos, foi de R$ 10.850.185,00, R$ 14.836.265,00 e R$ 14.679.099,00 para saxagliptina, pioglitazona e rosiglitazona, respectivamente. Saxagliptina exibiu menores custos e maior efetividade em ambas as comparações, com economias projetadas para os três primeiros anos de -R$ 3.874,00 e -R$ 3.996,00, respectivamente. O BIM estimou uma economia cumulativa de R$ 417.958,00 com o reembolso da saxagliptina em três anos a partir da perspectiva de uma operadora de plano de saúde com 1 milhão de vidas cobertas. Da perspectiva da fonte pagadora privada, a projeção é de que o acréscimo de saxagliptina à MF poupe custos quando comparado ao acréscimo de rosiglitazona ou pioglitazona em pacientes com DMT2 que não atingiram a meta de hemoglobina glicada (HbA1c) com metformina em monoterapia. O BIM, para a inclusão de saxagliptina nas listas de reembolso das operadoras de planos de saúde, indicou uma economia significativa para o horizonte de 3 anos. To compare costs and clinical benefits of three additional therapies to metformin (MF) for patients with diabetes mellitus type 2 (DM2). A discrete event simulation model was built to estimate the cost-utility ratio (cost per quality-adjusted life years [QALY]) of saxagliptine as an additional therapy to MF when compared to rosiglitazone or pioglitazone. A budget impact model (BIM) was built to simulate the economic impact of saxagliptine use in the context of the Brazilian private health system. The acquiring medication costs for the hypothetical patient group analyzed in a time frame of three years, were R$ 10,850,185, R$ 14,836,265 and R$ 14,679,099 for saxagliptine, pioglitazone and rosiglitazone, respectively. Saxagliptine showed lower costs and greater effectiveness in both comparisons, with projected savings for the first three years of R$ 3,874 and R$ 3,996, respectively. The BIM estimated cumulative savings of R$ 417,958 with the repayment of saxagliptine in three years from the perspective of a health plan with 1,000,000 covered individuals. From the perspective of private paying source, the projection is that adding saxagliptine with MF save costs when compared with the addition of rosiglitazone or pioglitazone in patients with DM2 that have not reached the HbA1c goal with metformin monotherapy. The BIM of including saxagliptine in the reimbursement lists of health plans indicated significant savings on the three-year horizon.

EFFICIENCY AND EQUITY: A STATED PREFERENCE APPROACH

Outcome measurement in the economic evaluation of health care considers outcomes independent of to whom they accrue. This article reports on a discrete choice experiment designed to elicit population preferences regarding the allocation of health gain between hypothetical groups of potential patients. A random-effects probit model is estimated, and a technique for converting these results into equity weights for use in economic evaluation is adopted. On average, the modelling predicts a relatively high social value on health gains accruing to nonsmokers, carers, those with a low income and those with an expected age of death less than 45 years. Respondents tend to favour individuals with similar characteristics to themselves. These results challenge the conventional practice of assuming constant equity weighting. For decision makers, whether a formal equity weighting system represents an improvement on more informal approaches to weighing up equity and efficiency concerns remains uncertain.

Cost impact of molecular testing for indeterminate thyroid nodule fine-needle aspiration biopsies.

Introduction:Molecular testing of fine-needle aspiration (FNA) results helps diagnose thyroid cancer, although the additional cost of this adjunct has not been studied. We hypothesized that FNA molecular testing of two indeterminate categories (follicular lesion of undetermined significance and follicular/Hürthle cell neoplasm) can be cost saving.Methods:For a hypothetical group of euthyroid patients with a 1-cm or larger solitary thyroid nodule, a decision-tree model was constructed to compare the estimated costs of initial evaluation according to the current American Thyroid Association guidelines, either with molecular testing (MT) or without [standard of care (StC)]. Model endpoints were either benign FNA results or definitive histological diagnosis.Results:Molecular testing added $104 per patient to the overall cost of nodule evaluation (StC $578 vs. MT $682). In this distributed cost model, MT was associated with a decrease in the number of diagnostic lobectomies (9.7% vs. StC 11.6%), whereas initial total thyroidectomy was more frequent (18.2% vs. StC 16.1%). Although MT use added a diagnostic cost of $5031 to each additional indicated total thyroidectomy ($11,383), the cumulative cost was still less than the comparable cost of performing lobectomy ($7684) followed by completion thyroidectomy ($11,954) in the StC pathway, when indicated by histological results. In sensitivity analysis, savings were demonstrated if molecular testing cost was less than $870.Conclusions:Molecular testing of cytologically indeterminate FNA results is cost saving predominantly because of reduction in two-stage thyroidectomy. Appropriate use of emerging molecular testing techniques may thus help optimize patient care, improve resource use, and avoid unnecessary operation.

Optimal Scheduling of Vehicle-to-Grid Energy and Ancillary Services

Vehicle-to-grid (V2G), the provision of energy and ancillary services from an electric vehicle (EV) to the grid, has the potential to offer financial benefits to EV owners and system benefits to utilities. In this work a V2G algorithm is developed to optimize energy and ancillary services scheduling. The ancillary services considered are load regulation and spinning reserves. The algorithm is developed to be used by an aggregator, which may be a utility or a third party. This algorithm maximizes profits to the aggregator while providing additional system flexibility and peak load shaving to the utility and low costs of EV charging to the customer. The formulation also takes into account unplanned EV departures during the contract periods and compensates accordingly. Simulations using a hypothetical group of 10 000 commuter EVs in the ERCOT system using different battery replacement costs demonstrate these significant benefits.

HISTORICAL DEVELOPMENT AND EVOLUTION OF EPRI'S POST-CLOSURE DOSE ASSESSMENT OF POTENTIAL RELEASES TO THE BIOSPHERE FROM THE PROPOSED HLW REPOSITORY AT YUCCA MOUNTAIN

This paper describes the development and evolution of the Electric Power Research Institute's (EPRI) post-closure dose assessment for potential releases of radionuclides from the proposed High Level Waste repository at Yucca Mountain. The starting point for this work was the 1995 publication of Technical Bases for Yucca Mountain Standards by the Commission on Geosciences, Environment and Resources of the National Research Council. This report proposed the development and application of an individual risk-based standard for releases from the repository to replace the existing one, which was based on radionuclide release limits. This in turn implied the development and application of methods to assess radiation doses to humans. Accordingly, EPRI produced a methodology for such dose assessment as part of its Total System Performance Assessment program for the proposed Yucca Mountain repository site. The methodology initially addressed releases via groundwater and then releases associated with extrusive igneous events. The methodology was updated and applied over the following years to take account of regulatory developments, changes in estimates of the source term to the biosphere, peer review through international model comparison exercises, new site generic data, and new data concerning conditions at the point of compliance in Amargosa Valley. The main outputs were Biosphere Dose Conversion Factors, which relate radionuclide levels in environmental media to the annual individual doses to a member of a hypothetical critical group and to the regulator-defined Reasonably Maximally Exposed Individual. Most recently, consideration has been given to uncertainty in the dose estimates based on a probabilistic analysis. The paper provides a perspective on the evolution of the dose assessments in response to the developments listed above.

Cost-Effectiveness of a Novel Molecular Test for Cytologically Indeterminate Thyroid Nodules

Determining which patients with thyroid nodules require surgery is limited by cytologically indeterminate findings. A new approach for preoperative molecular classification of cytologically indeterminate thyroid nodules has a reported sensitivity of 91% and specificity of 75%; however, its cost-effectiveness has yet to be assessed. Our objective was to evaluate the 5-yr cost-effectiveness of routine use of a molecular test in adult patients with indeterminate fine-needle aspiration biopsy results from a societal perspective. A 16-state Markov decision model was developed. Probabilities, costs, and quality-adjusted life years (QALY) were estimated from literature review, U.S. Department of Health and Human Services data, Medicare reimbursement schedules, and expert opinion. Decision analysis of a hypothetical group of adult patients with cytologically indeterminate thyroid nodules was conducted. Incremental cost-effectiveness ratio was calculated as incremental cost (measured in U.S. dollars) divided by incremental effectiveness (measured in QALY). Modifying current practice with use of the molecular test resulted in 74% fewer surgeries for benign nodules with no greater number of untreated cancers. Over 5 yr, mean discounted cost estimates were $12,172 for current practice and $10,719 with the molecular test. Current practice and molecular test use produced 4.50 and 4.57 QALY, respectively. Use of this novel molecular test for differential diagnosis of cytologically indeterminate thyroid nodules can potentially avoid almost three fourths of currently performed surgeries in patients with benign nodules. Compared with current practice based on cytological findings alone, use of this test may result in lower overall costs and modestly improved quality of life for patients with indeterminate thyroid nodules.

Invisible wounds, visible savings? Using microsimulation to estimate the costs and savings associated with providing evidence-based treatment for PTSD and depression to veterans of Operation Enduring Freedom and Operation Iraqi Freedom.

evidence-based treatment (EBT). Our results suggest that the 2-year social costs of depression and PTSD for this cohort will be $923 million. Policy simulations evaluating the savings associated with universal access to EBT suggest that such access would generate cost savings of $138 million (15%). Since 2001, more than 1.64 million U.S. troops have deployed to Operation Iraqi Freedom (OIF) or Operation Enduring Freedom (OEF), a pace unmatched in the history of the all-volunteer force (Tanielian & Jaycox, 2008). The future health-related costs of these deployments will undoubtedly be high because of physical and mental health injuries sustained during war. Calculation of these costs, which the government will be expected to pay, is a difficult task because of the inherent uncertainty underlying all the components that are necessary to construct such an estimate, including the number of people harmed, the number seeking treat- ment, the types of treatment given, the cost associated with treat- ment, and the subsequent outcomes that may befall a service member because of impaired health. In this article, we introduce an innovative method for estimating the future health costs for currently deployed service members that is well equipped to handle and quantify the uncertainty embedded in such a calculation: microsimulation modeling. Unlike standard accounting methods, a microsimulation model takes a hypothetical group of simulated individuals and predicts future cost-related events, allowing the simulated population to experience mental conditions, mental health treatment, and secondary outcomes such as employment. An advantage of the microsimulation approach is that it can treat mental disorders as chronic conditions, allowing for both remission and relapse over time. In addition, the micro- simulation model can be useful for evaluating different policy scenarios. In our case, we were particularly interested in asking the following policy question: If we increase the use of evidence- based treatment, will we save money in the long-run? This type of question would be difficult to evaluate in a standard accounting framework because standard accounting models are based on av- erage expenditures for a population and do not allow for different individuals to experience different treatments, subsequent out- comes, and costs. Data to parameterize the model, including in- formation about the probability of developing mental illness and the probability of remission following treatment, were taken from existing literature. We constructed a simplified microsimulation model that en- abled us to characterize the social cost over a 2-year period for two well-publicized and extremely prevalent health conditions associ- ated with combat exposure: posttraumatic stress disorder (PTSD) and major depression (Hoge, Auchterlonie, & Milliken, 2006;

Compressing the computational burden of matched‐field processing for sound source localization.

Sound source localization in shallow water environment is done using matched field processing (MFP), also referred to as time‐reversal imaging or backprojection method. Standard MFP is usually implemented by matching (using a cross‐correlation operation) the received acoustic data from the sought source with modeled data (or replicas) for point source located at multiple test locations over the a priori search area. Consequently, a direct implementation of MFP (i.e., brute force search) over a large search area can be highly computationally demanding especially when attempting to locate repeatedly several stationary or moving unknown sources in a complex environment. We formulated instead a compressive MFP approach allowing for significant computation time savings with a computational cost that scales with the logarithm of the number of independent‐or uncorrelated‐ test locations. This approach leverages the key concepts behind group testing and compressed sensing by computing instead the expected value of multiple ambiguity surface realizations obtained by backprojection of orthogonal random signals from the receiver locations. Thus compressive MFP allows to estimate the actual ambiguity function using few replica computations by evaluating hypothetical random groups of test locations instead of individual test locations (as done in conventional MFP).

Models of the Out-of-Body Experience: A New Multi-Etiological Phenomenological Approach

This paper compares several models of out-of-body experience (OBE) leading a new proposed multi-etiological model. Broadly the unitary hypotheses propose several single broad causes and explanations, though each of these recognizes that any specific explanation may not be all encompassing. These are best divided into four groups: Psychological, Brain, Psychopathology, and Experiential. The psychological models of Blackmore (reality distortion), Palmer (body concept) and Irwin (absorption) are followed by the brain empirical descriptions of Penfield, Blanke, and the cerebral explanations of Persinger (vectorial hemsiphericity), Wettach (midbrain near-death experiences), and Nelson (REM-intrusion in near death experiences [NDEs]). Additionally, there is the psychopathological psychiatric perspective, plus the spontaneous and induced OBEs that occur in subjective paranormal experients, which appear phenomenologically quite different. OBE research has generally been based on single questions without detailed qualitative differentiation of the OBE. This creates the erroneous situation of potentially misinterpreting diverse experiences under a single etiological umbrella. Optimally, OBE evaluations require detailed screening for OBEs so that “like” is classified with “like” not “unlike.” The author motivates for a detailed phenomenological analysis model which could accommodate the multiplicity of causes and the different subpopulations. This shifts the model from the unitary etiological hypotheses to Neppe’s Multi-etiological Phenomenological Approach. Detailed phenomenological analyses may demonstrate separate distinct kinds of out-of-body experience and therefore ensure that OBEs are appropriately phenomenologically classified in the context of the population samples being examined. This approach facilitates analyzing form, content, circumstance, and predisposed populations using a predominantly biopsychofamiliosociocultural approach and differentiating five possible legitimate hypothetical groups: 1. subjective paranormal experience (SPE) out-of-body experiences, 2. OBEs in SPE- non-experients who may have psychological experiences, 3. seizure and brain linked OBEs, 4. psychopathology interpreted as OBEs, 5. the non-OBE population.

Optimal Charging Strategies for Unidirectional Vehicle-to-Grid

Vehicle-to-grid (V2G) has been proposed as a way to increase the adoption rate of electric vehicles (EVs). Unidirectional V2G is especially attractive because it requires little if any additional infrastructure other than communication between the EV and an aggregator. The aggregator in turn combines the capacity of many EVs to bid into energy markets. In this work an algorithm for unidirectional regulation is developed for use by an aggregator. Several smart charging algorithms are used to set the point about which the rate of charge varies while performing regulation. An aggregator profit maximization algorithm is formulated with optional system load and price constraints analogous to the smart charging algorithms. Simulations on a hypothetical group of 10 000 commuter EVs in the Pacific Northwest verify that the optimal algorithms increase aggregator profits while reducing system load impacts and customer costs.