Comparison of deterministic, stochastic and fuzzy logic uncertainty modelling for capacity extension projects of DI/WFI pharmaceutical plant utilities with variable/dynamic demand

The last 30 years have seen Fuzzy Logic (FL) emerging as a method either complementing or challenging stochastic methods as the traditional method of modelling uncertainty. But the circumstances under which FL or stochastic methods should be used are shrouded in disagreement, because the areas of application of statistical and FL methods are overlapping with differences in opinion as to when which method should be used. Lacking are practically relevant case studies comparing these two methods. This work compares stochastic and FL methods for the assessment of spare capacity on the example of pharmaceutical high purity water (HPW) utility systems. The goal of this study was to find the most appropriate method modelling uncertainty in industrial scale HPW systems. The results provide evidence which suggests that stochastic methods are superior to the methods of FL in simulating uncertainty in chemical plant utilities including HPW systems in typical cases whereby extreme events, for example peaks in demand, or day-to-day variation rather than average values are of interest. The average production output or other statistical measures may, for instance, be of interest in the assessment of workshops. Furthermore the results indicate that the stochastic model should be used only if found necessary by a deterministic simulation. Consequently, this thesis concludes that either deterministic or stochastic methods should be used to simulate uncertainty in chemical plant utility systems and by extension some process system because extreme events or the modelling of day-to-day variation are important in capacity extension projects. Other reasons supporting the suggestion that stochastic HPW models are preferred to FL HPW models include: 1. The computer code for stochastic models is typically less complex than a FL models, thus reducing code maintenance and validation issues. 2. In many respects FL models are similar to deterministic models. Thus the need for a FL model over a deterministic model is questionable in the case of industrial scale HPW systems as presented here (as well as other similar systems) since the latter requires simpler models. 3. A FL model may be difficult to "sell" to an end-user as its results represent "approximate reasoning" a definition of which is, however, lacking. 4. Stochastic models may be applied with some relatively minor modifications on other systems, whereas FL models may not. For instance, the stochastic HPW system could be used to model municipal drinking water systems, whereas the FL HPW model should or could not be used on such systems. This is because the FL and stochastic model philosophies of a HPW system are fundamentally different. The stochastic model sees schedule and volume uncertainties as random phenomena described by statistical distributions based on either estimated or historical data. The FL model, on the other hand, simulates schedule uncertainties based on estimated operator behaviour e.g. tiredness of the operators and their working schedule. But in a municipal drinking water distribution system the notion of "operator" breaks down. 5. Stochastic methods can account for uncertainties that are difficult to model with FL. The FL HPW system model does not account for dispensed volume uncertainty, as there appears to be no reasonable method to account for it with FL whereas the stochastic model includes volume uncertainty.

The impact of chemotherapy dose density and dose intensity on breast cancer outcome: what have we learned?

Optimising chemotherapy dose density and dose intensity are strategies aimed at improving outcomes in adjuvant therapy for patients with breast cancer. There are, in theory, at least five models allowing the delivery of a higher overall drug dose intensity. These are reviewed in this article and vary according to three main variables: the dose per course, the interval between doses and the total cumulative dose. Cyclophosphamide, anthracyclines and taxanes are among the most active agents for the treatment of breast cancer and, as such, they have been or are currently the focus of prospective, randomised clinical trials testing some of these dose-intensity models in the adjuvant setting. The results of recent trials suggest that anthracyclines, but not cyclophosphamide, are associated with better outcomes if used at higher doses per course and at higher cumulative doses. However, care has to be taken with premenopausal women where an increased dose of anthracycline per course but a reduced cumulative dose appears to produce a worse outcome. Moreover, decreasing the interval between doses, for anthracyclines and cyclophosphamide, does not seem to provide, so far, additional benefits for women with locally advanced breast cancer. This approach is not feasible with docetaxel, since an increase in dose density induces unwanted side-effects. These results represent our current state of knowledge, but clinical trials are being performed to evaluate further the effect of dose intensity, dose density and cumulative dose of key therapeutic agents on patient outcomes.

Does higher hospital cost imply higher quality of care?

This study investigates whether higher input use per stay in the hospital (treatment intensity) and longer length of stay improve outcomes of care. We allow for endogeneity of intensity and length of stay by estimating a quasi-maximum-likelihood discrete factor model, where the distribution of the unmeasured variable is modeled using a discrete distribution. Data on elderly persons come from several waves of the National Long-Term Care Survey merged with Medicare claims data for 1984-1995 and the National Death Index. We find that higher intensity improves patient survival and some dimensions of functional status among those who survive.

The effect of involuntary job loss on smoking intensity and relapse.

AIMS: To assess the impact of involuntary job loss due to plant closure or layoff on relapse to smoking and smoking intensity among older workers. DESIGN, PARTICIPANTS, SAMPLE: Data come from the Health and Retirement Study, a nationally representative survey of older Americans aged 51-61 in 1991 followed every 2 years beginning in 1992. The 3052 participants who were working at the initial wave and had any history of smoking comprise the main sample. METHODS: Primary outcomes are smoking relapse at wave 2 (1994) among baseline former smokers, and smoking quantity at wave 2 among baseline current smokers. As reported at the wave 2 follow-up, 6.8% of the sample experienced an involuntary job loss between waves 1 and 2. FINDINGS: Older workers have over two times greater odds of relapse subsequent to involuntary job loss than those who did not. Further, those who were current smokers prior to displacement that did not obtain new employment were found to be smoking more cigarettes, on average, post-job loss. CONCLUSIONS: The stress of job loss, along with other significant changes associated with leaving one's job, which would tend to increase cigarette consumption, must outweigh the financial hardship which would tend to reduce consumption. This highlights job loss as an important health risk factor for older smokers.

Rationale and design of the Exercise Intensity Trial (EXCITE): A randomized trial comparing the effects of moderate versus moderate to high-intensity aerobic training in women with operable breast cancer.

BACKGROUND: The Exercise Intensity Trial (EXcITe) is a randomized trial to compare the efficacy of supervised moderate-intensity aerobic training to moderate to high-intensity aerobic training, relative to attention control, on aerobic capacity, physiologic mechanisms, patient-reported outcomes, and biomarkers in women with operable breast cancer following the completion of definitive adjuvant therapy. METHODS/DESIGN: Using a single-center, randomized design, 174 postmenopausal women (58 patients/study arm) with histologically confirmed, operable breast cancer presenting to Duke University Medical Center (DUMC) will be enrolled in this trial following completion of primary therapy (including surgery, radiation therapy, and chemotherapy). After baseline assessments, eligible participants will be randomized to one of two supervised aerobic training interventions (moderate-intensity or moderate/high-intensity aerobic training) or an attention-control group (progressive stretching). The aerobic training interventions will include 150 mins.wk⁻¹ of supervised treadmill walking per week at an intensity of 60%-70% (moderate-intensity) or 60% to 100% (moderate to high-intensity) of the individually determined peak oxygen consumption (VO₂peak) between 20-45 minutes/session for 16 weeks. The progressive stretching program will be consistent with the exercise interventions in terms of program length (16 weeks), social interaction (participants will receive one-on-one instruction), and duration (20-45 mins/session). The primary study endpoint is VO₂peak, as measured by an incremental cardiopulmonary exercise test. Secondary endpoints include physiologic determinants that govern VO₂peak, patient-reported outcomes, and biomarkers associated with breast cancer recurrence/mortality. All endpoints will be assessed at baseline and after the intervention (16 weeks). DISCUSSION: EXCITE is designed to investigate the intensity of aerobic training required to induce optimal improvements in VO₂peak and other pertinent outcomes in women who have completed definitive adjuvant therapy for operable breast cancer. Overall, this trial will inform and refine exercise guidelines to optimize recovery in breast and other cancer survivors following the completion of primary cytotoxic therapy. TRIAL REGISTRATION: NCT01186367.

Boosting high-intensity focused ultrasound-induced anti-tumor immunity using a sparse-scan strategy that can more effectively promote dendritic cell maturation.

BACKGROUND: The conventional treatment protocol in high-intensity focused ultrasound (HIFU) therapy utilizes a dense-scan strategy to produce closely packed thermal lesions aiming at eradicating as much tumor mass as possible. However, this strategy is not most effective in terms of inducing a systemic anti-tumor immunity so that it cannot provide efficient micro-metastatic control and long-term tumor resistance. We have previously provided evidence that HIFU may enhance systemic anti-tumor immunity by in situ activation of dendritic cells (DCs) inside HIFU-treated tumor tissue. The present study was conducted to test the feasibility of a sparse-scan strategy to boost HIFU-induced anti-tumor immune response by more effectively promoting DC maturation. METHODS: An experimental HIFU system was set up to perform tumor ablation experiments in subcutaneous implanted MC-38 and B16 tumor with dense- or sparse-scan strategy to produce closely-packed or separated thermal lesions. DCs infiltration into HIFU-treated tumor tissues was detected by immunohistochemistry and flow cytometry. DCs maturation was evaluated by IL-12/IL-10 production and CD80/CD86 expression after co-culture with tumor cells treated with different HIFU. HIFU-induced anti-tumor immune response was evaluated by detecting growth-retarding effects on distant re-challenged tumor and tumor-specific IFN-gamma-secreting cells in HIFU-treated mice. RESULTS: HIFU exposure raised temperature up to 80 degrees centigrade at beam focus within 4 s in experimental tumors and led to formation of a well-defined thermal lesion. The infiltrated DCs were recruited to the periphery of lesion, where the peak temperature was only 55 degrees centigrade during HIFU exposure. Tumor cells heated to 55 degrees centigrade in 4-s HIFU exposure were more effective to stimulate co-cultured DCs to mature. Sparse-scan HIFU, which can reserve 55 degrees-heated tumor cells surrounding the separated lesions, elicited an enhanced anti-tumor immune response than dense-scan HIFU, while their suppressive effects on the treated primary tumor were maintained at the same level. Flow cytometry analysis showed that sparse-scan HIFU was more effective than dense-scan HIFU in enhancing DC infiltration into tumor tissues and promoting their maturation in situ. CONCLUSION: Optimizing scan strategy is a feasible way to boost HIFU-induced anti-tumor immunity by more effectively promoting DC maturation.

Bayesian variable selection in structured high-dimensional covariate spaces with applications in genomics

We consider the problem of variable selection in regression modeling in high-dimensional spaces where there is known structure among the covariates. This is an unconventional variable selection problem for two reasons: (1) The dimension of the covariate space is comparable, and often much larger, than the number of subjects in the study, and (2) the covariate space is highly structured, and in some cases it is desirable to incorporate this structural information in to the model building process. We approach this problem through the Bayesian variable selection framework, where we assume that the covariates lie on an undirected graph and formulate an Ising prior on the model space for incorporating structural information. Certain computational and statistical problems arise that are unique to such high-dimensional, structured settings, the most interesting being the phenomenon of phase transitions. We propose theoretical and computational schemes to mitigate these problems. We illustrate our methods on two different graph structures: the linear chain and the regular graph of degree k. Finally, we use our methods to study a specific application in genomics: the modeling of transcription factor binding sites in DNA sequences. © 2010 American Statistical Association.

Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem

This paper studies the multiplicity-correction effect of standard Bayesian variable-selection priors in linear regression. Our first goal is to clarify when, and how, multiplicity correction happens automatically in Bayesian analysis, and to distinguish this correction from the Bayesian Ockham's-razor effect. Our second goal is to contrast empirical-Bayes and fully Bayesian approaches to variable selection through examples, theoretical results and simulations. Considerable differences between the two approaches are found. In particular, we prove a theorem that characterizes a surprising aymptotic discrepancy between fully Bayes and empirical Bayes. This discrepancy arises from a different source than the failure to account for hyperparameter uncertainty in the empirical-Bayes estimate. Indeed, even at the extreme, when the empirical-Bayes estimate converges asymptotically to the true variable-inclusion probability, the potential for a serious difference remains. © Institute of Mathematical Statistics, 2010.

A dimensionless number for understanding the evolutionary dynamics of antigenically variable RNA viruses.

Antigenically variable RNA viruses are significant contributors to the burden of infectious disease worldwide. One reason for their ubiquity is their ability to escape herd immunity through rapid antigenic evolution and thereby to reinfect previously infected hosts. However, the ways in which these viruses evolve antigenically are highly diverse. Some have only limited diversity in the long-run, with every emergence of a new antigenic variant coupled with a replacement of the older variant. Other viruses rapidly accumulate antigenic diversity over time. Others still exhibit dynamics that can be considered evolutionary intermediates between these two extremes. Here, we present a theoretical framework that aims to understand these differences in evolutionary patterns by considering a virus's epidemiological dynamics in a given host population. Our framework, based on a dimensionless number, probabilistically anticipates patterns of viral antigenic diversification and thereby quantifies a virus's evolutionary potential. It is therefore similar in spirit to the basic reproduction number, the well-known dimensionless number which quantifies a pathogen's reproductive potential. We further outline how our theoretical framework can be applied to empirical viral systems, using influenza A/H3N2 as a case study. We end with predictions of our framework and work that remains to be done to further integrate viral evolutionary dynamics with disease ecology.

Differential predictability of four dimensions of affect intensity.

Individual differences in affect intensity are typically assessed with the Affect Intensity Measure (AIM). Previous factor analyses suggest that the AIM is comprised of four weakly correlated factors: Positive Affectivity, Negative Reactivity, Negative Intensity and Positive Intensity or Serenity. However, little data exist to show whether its four factors relate to other measures differently enough to preclude use of the total scale score. The present study replicated the four-factor solution and found that subscales derived from the four factors correlated differently with criterion variables that assess personality domains, affective dispositions, and cognitive patterns that are associated with emotional reactions. The results show that use of the total AIM score can obscure relationships between specific features of affect intensity and other variables and suggest that researchers should examine the individual AIM subscales.

The spatiotemporal dynamics of autobiographical memory: neural correlates of recall, emotional intensity, and reliving.

We sought to map the time course of autobiographical memory retrieval, including brain regions that mediate phenomenological experiences of reliving and emotional intensity. Participants recalled personal memories to auditory word cues during event-related functional magnetic resonance imaging (fMRI). Participants pressed a button when a memory was accessed, maintained and elaborated the memory, and then gave subjective ratings of emotion and reliving. A novel fMRI approach based on timing differences capitalized on the protracted reconstructive process of autobiographical memory to segregate brain areas contributing to initial access and later elaboration and maintenance of episodic memories. The initial period engaged hippocampal, retrosplenial, and medial and right prefrontal activity, whereas the later period recruited visual, precuneus, and left prefrontal activity. Emotional intensity ratings were correlated with activity in several regions, including the amygdala and the hippocampus during the initial period. Reliving ratings were correlated with activity in visual cortex and ventromedial and inferior prefrontal regions during the later period. Frontopolar cortex was the only brain region sensitive to emotional intensity across both periods. Results were confirmed by time-locked averages of the fMRI signal. The findings indicate dynamic recruitment of emotion-, memory-, and sensory-related brain regions during remembering and their dissociable contributions to phenomenological features of the memories.

Emotional intensity predicts autobiographical memory experience.

College students generated autobiographical memories from distinct emotional categories that varied in valence (positive vs. negative) and intensity (high vs. low). They then rated various perceptual, cognitive, and emotional properties for each memory. The distribution of these emotional memories favored a vector model over a circumplex model. For memories of all specific emotions, intensity accounted for significantly more variance in autobiographical memory characteristics than did valence or age of the memory. In two additional experiments, we examined multiple memories of emotions of high intensity and positive or negative valence and of positive valence and high or low intensity. Intensity was a more consistent predictor of autobiographical memory properties than was valence or the age of the memory in these experiments as well. The general effects of emotion on autobiographical memory properties are due primarily to intensity differences in emotional experience, not to benefits or detriments associated with a specific valence.

A range-wide experiment to investigate nutrient and soil moisture interactions in loblolly pine plantations

© 2015 by the authors.The future climate of the southeastern USA is predicted to be warmer, drier and more variable in rainfall, which may increase drought frequency and intensity. Loblolly pine (Pinus taeda) is the most important commercial tree species in the world and is planted on ~11 million ha within its native range in the southeastern USA. A regional study was installed to evaluate effects of decreased rainfall and nutrient additions on loblolly pine plantation productivity and physiology. Four locations were established to capture the range-wide variability of soil and climate. Treatments were initiated in 2012 and consisted of a factorial combination of throughfall reduction (approximate 30% reduction) and fertilization (complete suite of nutrients). Tree and stand growth were measured at each site. Results after two growing seasons indicate a positive but variable response of fertilization on stand volume increment at all four sites and a negative effect of throughfall reduction at two sites. Data will be used to produce robust process model parameterizations useful for simulating loblolly pine growth and function under future, novel climate and management scenarios. The resulting improved models will provide support for developing management strategies to increase pine plantation productivity and carbon sequestration under a changing climate.

The Application of an Exogenous Linear and Radial Electrical Field to an In Vitro Chronic Diabetic Ulcer Model for Evaluation as a Potential Treatment

Chronic diabetic ulcers affect approximately 15% of patients with diabetes worldwide. Currently, applied electric fields are being investigated as a reliable and cost-effective treatment. This in vitro study aimed to determine the effects of a constant and spatially variable electric field on three factors: endothelial cell migration, proliferation, and angiogenic gene expression. Results for a constant electric field of 0.01 V demonstrated that migration at short time points increased 20-fold and proliferation at long time points increased by a factor of 1.40. Results for a spatially variable electric field did not increase directional migration, but increased proliferation by a factor of 1.39 and by a factor of 1.55 after application of 1.00 V and 0.01 V, respectively. Both constant and spatially variable applied fields increased angiogenic gene expression. Future research that explores a narrower range of intensity levels may more clearly identify the optimal design specifications of a spatially variable electric field.

Are the reference values of B cell subpopulations used in adults for classification of common variable immunodeficiencies appropriate for children?

Detailed phenotypic characterization of B cell subpopulations is of utmost importance for the diagnosis and management of humoral immunodeficiencies, as they are used for classification of common variable immunodeficiencies. Since age-specific reference values remain scarce in the literature, we analysed by flow cytometry the proportions and absolute values of total, memory, switched memory and CD21(-/low) B cells in blood samples from 168 healthy children (1 day to 18 years) with special attention to the different subpopulations of CD21(low) B cells. The percentages of total memory B cells and their subsets significantly increased up to 5-10 years. In contrast, the percentages of immature CD21(-) B cells and of immature transitional CD21(low)CD38(hi) B cells decreased progressively with age, whereas the percentage of CD21(low) CD38(low) B cells remained stable during childhood. Our data stress the importance of age-specific reference values for the correct interpretation of B cell subsets in children as a diagnostic tool in immunodeficiencies.