Uncertainty Margins Research Articles

Ultra-Accelerated Photons, Protons or Brachytherapy for Favorable Early Breast Cancer: Long-Term Results of a 3-Fraction Partial Breast Irradiation Trial

<h3>Purpose/Objective(s)</h3> To report long-term outcomes of a novel partial breast irradiation (PBI) regimen. We hypothesized that condensing treatment to 3 fractions and reducing total dose could improve the therapeutic ratio based on emerging evidence that breast cancer (BC) is more sensitive than surrounding normal tissues to high dose fractions. <h3>Materials/Methods</h3> We conducted a phase 2 trial of photon, proton, or brachytherapy PBI. Technique was selected at physician and patient discretion. Eligible women were age ≥ 50 years and s/p lumpectomy with negative sentinel nodes for estrogen receptor positive (ER+) invasive BC without preoperative chemotherapy or any ductal carcinoma in-situ (DCIS) measuring ≤ 2.5 cm. The regimen was designed to have comparable biologically effective dose as 40 Gy in 15 fractions, assuming an α/β ratio of 3.5. Photon and proton target volumes were post-operative tumor bed plus 1 cm and a 3 mm setup uncertainty margin and prescribed 21.9 Gy (RBE) in 3 fractions. Intracavitary brachytherapy was prescribed 21 Gy in 3 daily fractions. Radiotherapy was administered on 3 consecutive business days. Primary outcome was nurse-assessed adverse (fair/poor) cosmesis by 4-point Harvard scale at 3 years versus pre-PBI. Patients completed quality of life and self-reported cosmesis surveys. Adverse events were assessed using CTCAE, v 4.0. <h3>Results</h3> Between 2015 and 2017, 162 eligible patients were treated: photons in 56, protons in 49, and brachytherapy in 57. Median patient age was 67 years. 79% had invasive BC (all ER+) and 22% had DCIS (83% ER+). Median tumor size was 1.1 cm. Median Ki67 was 10% (IQR 6-17) and grade was 2-3 in 62%. The median of the mean heart/ipsilateral lung doses were photons 0.1/1.6 Gy, protons <0.001/0.1 Gy, and brachytherapy 0.5/0.9 Gy. 55% received endocrine therapy. The proportion of patients with adverse cosmesis (by RN assessment) was 14.4% pre-PBI, 4.0% at 3 years, and 5.6% at last follow-up (at median 4.9 years) with six patients (3.8%, 3 photon, 3 brachytherapy) experiencing cosmetic worsening. 92.7%, 95.9%, and 94.7%, of patients in the photon, proton, and brachytherapy cohorts had good or excellent cosmesis at last follow-up. The proportion with adverse cosmesis by self-report was 0% pre-PBI and 2.0% at 3 years. Four patients developed local recurrence (1 photons, 2 protons, 1 brachytherapy). 5-year local recurrence-free, progression-free, and overall survival were 97.9%, 95.1%, and 96.9%, respectively. There were 2 treatment related grade ≥2 adverse events (grade 2 fibrosis and grade 2 seroma, both brachytherapy associated), and no evidence of deterioration in patient-reported pain, fatigue, breast related or overall quality of life. <h3>Conclusion</h3> Ultra-accelerated 3-fraction PBI exquisitely spared normal tissues, was associated with favorable cosmetic outcomes, disease control, and excellent tolerability. This is an attractive option for small node-negative ER+ BC and DCIS.

A New Technique to Infer Plasma Density, Flow Velocity, and Satellite Potential From Ion Currents Collected by a Segmented Langmuir Probe

Compared with other types of Langmuir probes, segmented probes are arguably the least often used, to diagnose the state of plasma. With linear dimensions of the order of centimeters, these probes would induce perturbations, which would make them impractical in many laboratory plasma experiments. Their size, and the fact that they consist of several equipotential faces or “segments,” from which individual currents are collected, introduces additional complexities in the construction of inference techniques for their characteristics. In this work, we focus on the use of spherical segmented probes mounted on a satellite and present new techniques to infer plasma (ion) densities, flow velocities, and satellite potentials, from currents collected by two segmented probes biased to two different fixed potentials relative to a spacecraft. This is done by carrying out 3-D kinetic self-consistent particle-in-cell (PIC) simulations to compute the response of a probe to space plasma under different environment conditions of relevance to satellites in low-Earth orbit (LEO) at low and mid-latitudes. Computed currents and the corresponding known plasma and satellite parameters used as input in the simulations are then used to create a solution library with which regression-based inference models are constructed, following standard machine learning techniques. The models trained with a subset of our synthetic dataset are found to yield excellent agreement with data in distinct validation sets. The models constructed with synthetic data are then applied to in situ measurements made with segmented Langmuir probes mounted on the Proba-2 satellite, and the inferences are compared with densities reported on the Proba-2 data portal. The advantage of our approach is that it readily produces uncertainty margins that are specifically related to the inference technique used.

Unraveling the carbene chemistry of oxymethylene ethers: Experimental investigation and kinetic modeling of the high-temperature pyrolysis of OME-2

Oxymethylene ethers (OMEs) form an interesting family of synthetic compounds to replace fossil fuels. This alternative liquid energy carrier can contribute to a circular carbon economy when produced via carbon capture and utilization technology using renewable electricity. Despite the potential to reduce greenhouse gas and particulate matter emissions and their ideal ignition characteristics, little is known about the thermal decomposition behavior of OMEs. In this work, new insights are obtained in the pyrolysis chemistry of oxymethylene ether-2 (OME-2) and the role of carbenes by performing experiments at high temperatures (> 850 K) in a tubular quartz reactor. The used continuous bench-scale pyrolysis unit has a dedicated on-line analysis section including comprehensive two-dimensional gas chromatography (GC × GC) coupled with flame ionization detection (FID) and mass spectroscopy (MS) to identify and quantify the full product spectrum over the complete temperature range. The reactor temperature was varied between 850 and 1150 K at a fixed pressure of 0.15 MPa and residence times of 400 to 850 ms. The major products are dimethoxymethane, formaldehyde, methyl formate, methane, CO2, CO and H2. Minor intermediate compounds comprise dimethyl ether, formic anhydride, formic acid, methoxymethyl formate and methoxymethanol. The yields of compounds with carbon-carbon bonds are low since no such bonds originally occur in OME-2. Precursors of aromatic compounds and soot particles are absent in the reactor effluent. The experimental results are simulated with a new first principles-based kinetic model for pyrolysis and combustion of OME-2. This model can predict the experimental trends of major products on average within the experimental uncertainty margin of ± 10% relative for major product species. A reaction pathway and sensitivity analysis are presented to highlight the importance of the carbenes for initiation of the radical chemistry under pyrolysis conditions.

Risk assessment of microplastics in freshwater sediments guided by strict quality criteria and data alignment methods

Determining the risks of microplastics is difficult because data is of variable quality and cannot be compared. Although sediments are important sinks for microplastics, no holistic risk assessment framework is available for this compartment. Here we assess the risks of microplastics in freshwater sediments worldwide, using strict quality criteria and alignment methods. Published exposure data were screened for quality using new criteria for microplastics in sediment and were rescaled to the standard 1–5000 µm microplastic size range. Threshold effect data were also screened for quality and were aligned to account for the polydispersity of environmental microplastics and for their bioaccessible fraction. Risks were characterized for effects triggered by food dilution or translocation, using ingested particle volume and surface area as ecologically relevant metrics, respectively. Based on species sensitivity distributions, we determined Hazardous Concentrations for 5% of the species (HC5, with 95% CI) of 4.9 × 109 (6.6 × 107 – 1.9 × 1011) and 1.1 × 1010 (3.2 × 108 – 4.0 × 1011) particles / kg sediment dry weight, for food dilution and translocation, respectively. For all locations considered, exposure concentrations were either below or in the margin of uncertainty of the HC5 values. We conclude that risks from microplastics to benthic communities cannot be excluded at current concentrations in sediments worldwide.

Uncertainty assessment for the Bayesian updating process of concrete strength properties

Reassessment of infrastructure buildings has become an essential approach to deal with increasing traffic loads on ageing infrastructure buildings and to verify the service-life of those structures. Good estimation of the actual material properties is highly relevant for reliable structural reassessment. Although this holds for all building materials, the importance of good parameter estimation is of special importance for concrete structures, where the strength properties show relatively high variation and where the nominal strength properties tend to be too conservative. Modern design guidelines allow to make use of scientific methods such as Bayesian Updating of material properties to enable a more realistic consideration of the actual material properties in the reassessment of existing structures. However, guidelines for application and experience with those methods are not yet reported much or are rather vague [1]. The presented study focuses on the effect of the Bayesian Updating process for material parameters with special emphasis on the number and sampling location of test specimens as well as on the accuracy and confidence in the obtained posterior distribution, since sampling also includes a certain margin of uncertainty. The investigation on the methodological potential and on the uncertainty margin in the updating process in this contribution uses a batch of 14 test results on the concrete compressive strength obtained from drill cores along with the inherent measurement uncertainties from the testing procedure. After a short review of Bayes’ Theorem, the Markov Chain Monte Carlo Method (MCMC) and the bootstrap methodology, all combinations of subsamples of size 1, 3 and 5 specimens were built and provided to the Bayes’ updating procedure via MCMC to determine the posterior distributions. The series of obtained posterior distributions for a certain subsample was used to determine the uncertainty in the Bayesian Updating process by evaluation of the scatter in the expected value, the standard deviation and the 5 %-quantile of the updated distribution. The simulations show the importance of an adequate sample size and quantify the uncertainties arising from the limited number of observations.

The secondary chemistry of synthetic fuel oxymethylene ethers unraveled: Theoretical and kinetic modeling of methoxymethyl formate and formic anhydride decomposition

Replacing fossil fuels by oxymethylene ethers (OMEs) produced from renewable resources could help to reduce the rising CO2 levels. In this work, the thermal decomposition chemistry of methoxymethyl formate (CH3OCH2OCHO) and formic anhydride (OCHOCHO) is investigated by means of a combination of quantum chemical calculations and kinetic modeling. The latter compounds are two important intermediates formed during the thermal decomposition chemistry of synthetic fuel OMEs. Two detailed kinetic models are developed based on first principles to describe the radical decomposition chemistry of methoxymethyl formate and formic anhydride, which are ultimately incorporated into the OME-2 model from De Ras et al. (Combustion and Flame, 2022). This newly obtained kinetic model describes experimental measurements for pyrolysis from literature significantly better than the model from the original study, without any fitting of thermodynamic or kinetic parameters. More particularly, some minor compounds are now satisfactorily reproduced within the experimental uncertainty margin of 10 mol% relative. Methoxymethyl formate and formic anhydride are found to be more reactive compared to OMEs. Both a reaction pathway analysis and sensitivity analysis reveal the important decomposition pathways under pyrolysis conditions.

Adesp. fr. 637 Kannicht-Snell: Ifigenia?

Even today there is a margin of uncertainty regarding the subject of adesp. fr. 637 Kannicht-Snell, upon which I have thrown more light through the philological analysis conducted in the present contribution. After showing that it is more prudent to attribute these verses to an unidentified Iphigenia, I have reflected upon the tragic evidence of Iphigenia’s myth, in order to search for the authorship of adesp. fr. 637 Kannicht-Snell.

Conversion resection for patients with hepatocellular carcinoma and inferior vena cava tumor thrombus: a consecutive case series

Conversion resection for patients with hepatocellular carcinoma and inferior vena cava tumor thrombus: a consecutive case series

Compressive strength of concrete cylindrical columns confined with fabric-reinforced cementitious matrix composites under monotonic loading: Application of machine learning techniques

The reinforcement of concrete columns with fabric reinforced cementitious matrix (FRCM) is one of the most challenging issues in the construction of concrete structures, as there is still an absence of a promising model to assess their performance. This is because the behavior of such elements is complex and accompanied by a high margin of uncertainty. To address this issue, this study compiles a large dataset of the performance of FRCM-reinforced concrete columns under monotonic load. The obtained dataset is then used to train an artificial neural network (ANN) as a promising method for predicting the compressive strength of concrete columns with acceptable accuracy. Afterward, using a genetic algorithm (GA)-based regression model, a simplified formula is developed as an explicit model for predicting the compressive strength of FRCM-confined concrete columns. Additionally, a reliability model is established and solved by the Monte Carlo sampling method to capture the uncertainty and provide the results probabilistically. The results indicate that with the increase of fcc, the probability of exceedance is sharply reduced, so that the failure probability of fcc greater than 68 MPa falls below 2%. Moreover, a reliability sensitivity analysis is performed to measure the effects of input parameters on the resulting exceedance probability. The results reveal that the greatest impact of column diameter and height falls within the small range of fcc between 25 and 35 MPa. The maximum effect of temperature and unconfined concrete compressive strength, however, happens in the medium range of fcc between 35 and 45 MPa. Additionally, the percentage of fiber mostly affects the large range of fcc between 45 and 49 MPa.

Mathematical programming approaches for modeling a sustainable cropping pattern under uncertainty: a case study in Southern Iran

In recent years, the excessive and unreasonable use of chemicals, the occasional use of water, and the use of improper irrigation methods have created a worrying and unstable situation in developing countries’ agricultural activities. In the present study, the robust multi-objective fractional linear programming model (RMOLFP) was introduced to determine the sustainable optimal cropping pattern. This model was presented in the Gotvand irrigation and drainage network located in Khuzestan province, southern Iran, under two scenarios with and without considering the uncertainty to evaluate the ability of the model. The results showed that in the first scenario, the consumption of critical disruptive inputs of sustainable agriculture such as fertilizers and chemical pesticides decreased by 5.9% and 8.19%, respectively. On the other hand, the model's uncertainty condition was applied in the second scenario in which the increase in gross margin was reduced. There is a trade-off between protecting the optimization model against system uncertainty and gross margin. Finally, the ability of the proposed model to apply uncertainty conditions was verified by the Monte Carlo simulation method. The results of this simulation confirmed the use of the RMOLFP method in determining the sustainable optimal cropping pattern for the study area.

Local variability in snow concentrations of chlorinated persistent organic pollutants as a source of large uncertainty in interpreting spatial patterns at all scales.

Single point sampling, a widespread practice in snow studies in remote areas, due to logistical constraints, can present an unquantified error to the final study results. The low concentrations of studied chemicals, such as chlorinated persistent organic pollutants, contribute to the uncertainty. We conducted a field experiment in the Arctic to estimate the error stemming from differences in the composition of snow at short distances (1-3m), including 13 single organochlorine pesticides and 6 polychlorinated biphenyls, thus providing the most detailed published dataset on the subject. We contrasted this variability with the uncertainty at larger spatial scales, both within one valley (regional scale, this study) and as described in the worldwide literature. The range of values for the coefficient of variation for local samples was 20-58% for single organochlorine pesticides (OCPs) and 33-54% for polychlorinated biphenyls (PCBs), and for regional samples it was 21-69% for OCPs and 65-93% for PCBs. We suggest that, to observe the actual changes in the concentration of selected compounds in snow, they should vary at the level of 40-60%, depending on the compound in question. The uncertainty margin remains much smaller than the current discrepancy between observation data and atmospheric deposition models considering snow, deeming field data on snow concentrations a useful ground-truthing dataset. However, field observations on spatial differences at all scales need to be interpreted with caution, and the dataset provided here on the local sampling uncertainty helps define the margins of such interpretations.

Evaluation of Variability Across Rat Acute Oral Systemic Toxicity Studies.

Regulatory agencies rely upon rodent in vivo acute oral toxicity data to determine hazard categorization, require appropriate precautionary labeling, and perform quantitative risk assessments. As the field of toxicology moves toward animal-free new approach methodologies (NAMs), there is a pressing need to develop a reliable, robust reference data set to characterize the reproducibility and inherent variability in the in vivo acute oral toxicity test method, which would serve to contextualize results and set expectations regarding NAM performance. Such a data set is also needed for training and evaluating computational models. To meet these needs, rat acute oral LD50 data from multiple databases were compiled, curated, and analyzed to characterize variability and reproducibility of results across a set of up to 2441 chemicals with multiple independent study records. Conditional probability analyses reveal that replicate studies only result in the same hazard categorization on average at 60% likelihood. Although we did not have sufficient study metadata to evaluate the impact of specific protocol components (eg, strain, age, or sex of rat, feed used, treatment vehicle, etc.), studies were assumed to follow standard test guidelines. We investigated, but could not attribute, various chemical properties as the sources of variability (ie, chemical structure, physiochemical properties, functional use). Thus, we conclude that inherent biological or protocol variability likely underlies the variance in the results. Based on the observed variability, we were able to quantify a margin of uncertainty of ±0.24 log10 (mg/kg) associated with discrete in vivo rat acute oral LD50 values.

Dosimetric feasibility of moderately hypofractionated/dose escalated radiation therapy for localised prostate cancer with intensity-modulated proton beam therapy using simultaneous integrated boost (SIB-IMPT) and impact of hydrogel prostate-rectum spacer

PurposeTo examine the dosimetric feasibility of hypofractionated/dose escalated radiation therapy in patients with localized prostate carcinoma using simultaneous integrated boost intensity-modulated proton beam therapy (SIB-IMPT) in absence or presence of prostate-rectum spacer.MethodsIMPT technique was implemented in 23 patients with intermediate- and high-risk prostate cancer treated at West German Proton Therapy Centre from March 2016 till June 2018, using SIB technique prescribing 60 GyRBE and 72 GyRBE in 30 fractions to PTV1 (prostate and seminal vesicle) and PTV2 boost (prostate and proximal seminal vesicle), respectively. In 15 patients, a transperineal injection of hydrogel was applied prior to radiotherapy to increase the distance between prostate and rectum. Planning and all treatments were performed with a 120 ml fluid-filled endorectal balloon customised daily for each patient. For each patient, 2 lateral IMPT beams were implemented taking a field-specific range uncertainty (RU) into account. Dose volume histograms (DVH) were analyzed for PTV2, PTV2 with range uncertainty margin (PTV2RU), rectum, bladder, right/left femoral heads, and penile bulb. For late rectal toxicities, the normal tissue complication probabilities (NTCP) were calculated using different biological models. A DVH- and NTCP-based dosimetric comparison was carried out between non-spacer and spacer groups.ResultsFor the 23 patients, high-quality plans could be achieved for target volume and for other organs at risk (OARs). For PTV2, the V107% was 0% and the Dmax did not exceed 106.2% of the prescribed dose. The volume PTV2RU covered by 95% of the dose ranged from 96.16 to 99.95%. The conformality index for PTV2RU was 1.12 ± 0.057 and the homogeneity index (HI) was 1.04 ± 0.014. Rectum Dmax and rectal volume receiving 73–50 Gy could be further reduced for the spacer-group. Significant reductions in mean and median rectal NTCPs (stenosis/necrosis, late rectal bleeding ≥ 2, and late rectal toxicities ≥ 3) were predicted for the spacer group in comparison to the non-spacer group.ConclusionHypofractionated/dose escalated radiotherapy with SIB-IMPT is dosimetrically feasible. Further reduction of the rectal volumes receiving high and medium dose levels (73–50 Gy) and rectal NTCP could be achieved through injection of spacers between rectum and prostate.

Roots and other residues from leys with or without red clover: Quality and effects on N2O emission factors in a partly frozen soil following autumn ploughing

Revised IPCC guidelines assume that a constant share of N in decomposing crop residues is directly emitted as N2O (emission factor: EFN2O), and calculate the amount of nitrogen (N) in non-removable residues of temporary grasslands proportionally to the average annual herbage yield. However, EFN2O depends on the intrinsic quality of the residues and their interactions with environmental conditions. Only a few field studies on N2O emissions from grassland renewal are available, and none have simultaneously quantified the N amount and quality of non-removable residues (roots and stubble).To gain insight into the effect of non-removable residue quality on EFN2O, we studied the amount and quality of roots and stubble and their effect on EFN2O following the ploughing of three-year-old swards.The measured amount of N in non-removable residues was approximately 20, 25, and 31 kg N per 1 Mg average annual dry matter yield in grass, red clover-grass, and red clover, and 70–83% of it was below ground. However, the EFN2O of non-removable residues measured over 252 days was lower (0.24%, SE = 14% for grass and red clover-grass) than the IPCC default value (0.6%, CV: 50%) for wet regions, although within the uncertainty margin, and was significantly lower than the EFN2O of incorporated herbage, which was related to differences in EFCO2. We advocate for more specific studies that separate the effects of belowground and aboveground residues (AGR), considering the possibility of simplifying the accounting of N2O emissions from belowground residues while improving that of non-removable AGR from temporary grasslands and other green crops.We observed the accumulation of N2O in the frozen soil under snow, which was released during diurnal percolation of meltwater. N2O emissions from frozen soil accounted for 30% or more of the total emissions.

Computation of parametric uncertainty margin using stability boundary locus: An application to load frequency control

In this paper, computation of parametric uncertainty margin (PUM) of a system is explored. In the presence of parametric uncertainty, maintaining the stability of the system is a daunting task. In view of this, in this paper, a new methodology is proposed to determine the maximum parametric uncertainty or PUM that can be tolerated in an interval type proportional–integral (PI) controlled system so that the whole system remains robustly stable. In order to show the validity of the proposed approach, an example of interval type load frequency control (LFC) system is considered to determine the PUM numerically. The proposed approach utilizes the concept of Kharitonov’s theorem for the modeling of interval type systems and stability boundary locus (SBL) technique for the designing of PI controller. The PUM obtained using the proposed approach is compared by that achieved by Kharitonov’s rectangles and zero exclusion principle.

Abstract PD7-03: Ultra-accelerated photon, proton, and brachytherapy partial breast irradiation: Primary results of the Mayo 3-fraction trial

Abstract Background: Partial breast irradiation (PBI) is an established option for selected patients with early stage breast cancer. The optimal technique, target volume and dose/fractionation for PBI has yet to be defined. The most studied regimen in North America (38.5 Gy in 10 fractions twice daily) has been associated with cosmetic deterioration. We hypothesized that condensing treatment and reducing the total administered dose could improve the therapeutic ratio in luminal breast cancer and DCIS based on emerging evidence that breast cancer is more sensitive than surrounding normal tissues to high dose fractions. Herein, we report cosmetic, tolerability, disease control, and patient reported outcomes of a novel ultra-accelerated PBI regimen. Methods: We conducted a single arm, three cohort trial of photon, proton, and brachytherapy PBI. Technique was selected at physician and patient discretion. Eligible women were age ≥ 50 years with estrogen receptor positive (ER+), sentinel lymph node negative invasive or in-situ breast cancer measuring ≤ 2.5 cm. The regimen was designed to have comparable biologically equivalent effect as 40 Gy in 15 fractions, assuming an α/β ratio of 3.5. Intracavitary brachytherapy target volume was lumpectomy cavity plus 1 cm and prescribed 21 Gy in 3 fractions. Photon and proton target volumes were post-operative tumor bed plus 1 cm and a 3 mm setup uncertainty margin, prescribed 21.9 Gy (RBE) in 3 fractions, and delivered with image guidance. The primary outcome was the percentage difference in patients with adverse cosmesis (defined as fair or poor cosmesis) at 3 years compared to baseline pre-PBI, as assessed by trained nurses using the 4-point Harvard breast cosmesis scale. Patients also completed quality of life surveys and self-reported cosmesis using the 4-point scale. Locoregional and distant recurrence-free survival was determined using the Kaplan-Meier method. Adverse events were assessed using CTCAE, v 4.0. Results: Between 2015 and 2017, 163 patients were treated: photons in 58, protons in 48, and brachytherapy in 57. Median patient age was 66 years. 129 (79%) patients had invasive breast cancer (all ER+) and 34 (21%) had DCIS (83% ER+). Median tumor size was 1.1 cm. Grade was 2-3 in 102 (63%). The median mean heart/ipsilateral lung doses were photons 0.1/1.6 Gy, protons &amp;lt;0.001/0.1 Gy, and brachytherapy 0.5/0.9 Gy. Median follow-up was 4.1 years (IQR 3.9-5.0). The proportion of patients with adverse cosmesis (by RN assessment) was 14.3% at baseline and 3.8% at 3 years, with four patients (1 photon, 1 proton, 2 brachytherapy) experiencing cosmetic deterioration at 3 years from baseline. The proportion with adverse cosmesis by self-report at 3 years was 2.4%, with three patients (1 photon, 1 proton, 1 brachytherapy) reporting cosmetic deterioration. Four patients developed locoregional recurrence (1 photons, 2 protons, 1 brachytherapy); three were local only and one was local and distant. 4-year locoregional recurrence and distant metastasis-free survival were 97.9% and 97.4%, respectively. There were 2 treatment related ≥ grade 2 late events (grade 2 fibrosis and grade 2 seroma, both brachytherapy associated), and no evidence of deterioration in patient-reported pain, fatigue, breast related or overall quality of life, as assessed by the patient reported outcomes version of the CTCAE, 10-point linear analog scales, and the breast cancer treatment outcomes scale. Conclusions: Ultra-accelerated 3-fraction PBI exquisitely spared normal tissues and was associated with favorable cosmetic outcomes, disease control, and excellent long-term tolerability. This ‘precision-radiotherapy’ approach may optimize the therapeutic ratio over more aggressive radiotherapy options as well as radiotherapy omission, particularly in patients with long life expectancies. Citation Format: Robert Mutter, Tina Hieken, Todd DeWees, Arslan Afzal, Stephanie Kenison, Laura Vallow, Christopher Deufel, Nicholas Remmes, Kathryn Ruddy, Judy Boughey, Keith Furutani, Amy Degnim, James Jakub, Tamara Vern-Gross, Dean Shumway, William Wong, Samir Patel, Lisa McGee, Minetta Liu, Carlos Vargas, Daniel Visscher, Bradley Stish, Deanna Pafundi, Mark Waddle, Michael Golafshar, Michele Halyard, Kimberly Corbin, Sean Park. Ultra-accelerated photon, proton, and brachytherapy partial breast irradiation: Primary results of the Mayo 3-fraction trial [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD7-03.

Possible changes in Sudan's future precipitation under the high and medium emission scenarios based on bias adjusted GCMs

Prospecting our future climate behavior under a wide range of possible scenarios is one of the most challenging issues in climate science. This study examines changes in monsoon's (June–September) future precipitation over three zones distributed across Sudan based on GCMs from CMIP5 and (CMIP6). The models are GISS-E2-H, IPSL-CM5A-MR, and MPI-ESM-LR (BCC-CSM2-MR, INM-CM4-9 MPI-ESM1-2-LR) in addition to the ensemble mean of each group. Given systematic errors in the GCMs simulations, we applied the Quantile Mapping bias correction technique to rectify the bias toward the real-occurred field. The bias coefficients were calculated for 1946–1975 and validated for 1976–2005. The improvement was quantified using the Skills Score technique. Overall, the GCMs simulations improved by 0–15% (45–90%) for CMIP6 (CMIP5) after bias correction (BC) was involved. BC has led to a remarkable breakthrough in the GCMs simulations manifested by a considerable improvement in the simulated precipitation, particularly in southern parts of Sudan. Furthermore, we applied the bias adjustments of the future period 2030–2099 to reduce the uncertainty margins when assessing the possible changes. The future period was divided as (i) Near Future 2025–2049, (ii) Middle Future 2050–2074, and (iii) Far Future 2075–2099. The changes were examined based on two Representative Concentration Pathways (Shared Socioeconomic Pathway) scenarios, namely: RCP4.5(SSP2–4.5) and RCP8.5(SSP5–8.5) for CMIP5 (CMIP6). In both scenarios, June–September is projected to remain the rainy season in all analyzed zones. Among all studied periods for both scenarios, the most severe changes are expected in the far future with a positive change of 60 to >80% shown in CMIP6 projection under the high emission scenario in zone3. However, the highest negative bias is expected in the near future period under the high emission scenario in CMIP5 projections in the same zone. Higher uncertainty is associated with the future projections, particularly in zone3 under the high emission scenario for both CMIP5 and CMIP6 projections. Higher agreement between the models, on the other hand, is shown in zone2 under the high emission scenario for both simulations.

Epistemología de la medición

Measuring designates the process by which a system is interacted with in order to represent some of its aspects by means of abstract terms or those that have a merely ideal character, establishing common references that allow comparison with a predetermined pattern and bounded by predetermined margins of uncertainty. Obviously, measurement is an essential component of science; one of its hallmarks, a primary source of knowledge and the essential link between theory and experimentation, allowing them to feed off each other and continuously improve. In the scientific study of any phenomenon, the intervention of the observer and the very fact of the observation disturb the phenomenon studied. For this reason, it is always necessary to take into consideration the degree of disturbance it produces, something that in clinical research can be particularly complex due to the multiplicity and variability of human manifestations. The complexity of the observed subject (human being), given his condition as a thinking, emotional, moral and social entity, multiplies the uncertainty of his responses, both individual and collective, and extreme methodological and ethical demands of the scientist; In addition, the response of each individual to a clinical intervention incorporates multiple other factors unrelated to the effects objectively attributable to the intervention, but which must be duly weighed. For all these reasons, in order to scientifically measure the effect of an intervention in a clinical trial, it is essential to previously define and justify the minimum magnitude of the change that can give rise to an effect that is clinically relevant for the patient and for the observer.

Quantifying fish catches and fish consumption in the Amazon Basin

Abstract The Amazon Basin is the largest in the world and for many of its inhabitants fishing is a crucially important source of food and income. However, the benefits derived from mostly informal, part time, seasonal, and subsistence-based activities such as fishing are largely invisible to policy-makers, and addressing the threats to aquatic habitats, ecosystem functioning, and fisheries is frequently given low priority in national development agendas. To estimate the total extraction of fish in the Amazon Basin, we reviewed various publications and databases with quantitative data related to the landings, trade, and consumption of fish. We estimated the total landings to be between 422,000 and 473,000 t yr-1 in live weight, near to previous estimates. Almost 75%, however, represented landings in the Brazilian part of the basin, and there is a very large margin of uncertainty given that, among other issues, there are no recent official statistics on commercial landings. Conversely, landings in Bolivia, Colombia, and Ecuador seem to be considerably higher than previously thought. In all Amazonian countries, from 50% up to almost 100% of the fishing takes place for personal consumption, implying that it is not recorded in official landing statistics. Available time series data indicate that fish consumption in Brazil, as well as commercial fish landings in Peru and Colombia, have declined in recent years. Local case studies, national household consumption and expenditure surveys (HCES), and market surveys, all have their benefits and drawbacks. Some minor modifications of HCES procedures could considerably improve their usefulness for estimating fish landings in the Amazon Basin. To improve such estimates, we propose that local case studies be used to calibrate HCES data, thus combining the high precision of local case studies with the wide coverage and representativity of HCES data

Internal Validity Index for Fuzzy Clustering Based on Relative Uncertainty

Unsupervised clustering and clustering validity are used as essential instruments of data analytics. Despite clustering being realized under uncertainty, validity indices do not deliver any quantitative evaluation of the uncertainties in the suggested partitionings. Also, validity measures may be biased towards the underlying clustering method. Moreover, neglecting a confidence requirement may result in over-partitioning. In the absence of an error estimate or a confidence parameter, probable clustering errors are forwarded to the later stages of the system. Whereas, having an uncertainty margin of the projected labeling can be very fruitful for many applications such as machine learning. Herein, the validity issue was approached through estimation of the uncertainty and a novel low complexity index proposed for fuzzy clustering. It involves only uni-dimensional membership weights, regardless of the data dimension, stipulates no specific distribution, and is independent of the underlying similarity measure. Inclusive tests and comparisons returned that it can reliably estimate the optimum number of partitions under different data distributions, besides behaving more robust to over partitioning. Also, in the comparative correlation analysis between true clustering error rates and some known internal validity indices, the suggested index exhibited the highest strong correlations. This relationship has been also proven stable through additional statistical acceptance tests. Thus the provided relative uncertainty measure can be used as a probable error estimate in the clustering as well. Besides, it is the only method known that can exclusively identify data points in dubiety and is adjustable according to the required confidence level.