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Exploring the effects of climatic variables on monthly precipitation variation using a continuous wavelet-based multiscale entropy approach

Highlights: • Developed a wavelet transform entropy approach to study precipitation. • Multiscale entropy values were the basis for precipitation regionalization. • Various entropy-based bands were introduced to segregate the CWME values for each cluster. • The relationship between changes of CWME and mean monthly precipitation were investigated. • Central rain gauges of each cluster were used for further analysis. Understanding precipitation on a regional basis is an important component of water resources planning and management. The present study outlines a methodology based on continuous wavelet transform (CWT) and multiscale entropy (CWME), combined with self-organizing map (SOM) and k-means clustering techniques, to measure and analyze the complexity of precipitation. Historical monthly precipitation data from 1960 to 2010 at 31 rain gauges across Iran were preprocessed by CWT. The multi-resolution CWT approach segregated the major features of the original precipitation series by unfolding the structure of the time series which was often ambiguous. The entropy concept was then applied to components obtained from CWT to measure dispersion, uncertainty, disorder, and diversification of subcomponents. Based on different validity indices, k-means clustering captured homogenous areas more accurately, and additional analysis was performed based on the outcome of this approach. The 31 rain gauges in this study were clustered into 6 groups, each one having a unique CWME pattern across different time scales. The results of clustering showed that hydrologic similarity (multiscale variation of precipitation) was not based on geographic contiguity. According to the pattern of entropy across the scales, each cluster was assigned an entropy signature that provided an estimation of the entropy pattern of precipitation data in each cluster. Based on the pattern of mean CWME for each cluster, a characteristic signature was assigned, which provided an estimation of the CWME of a cluster across scales of 1–2, 3–8, and 9–13 months relative to other stations. The validity of the homogeneous clusters demonstrated the usefulness of the proposed approach to regionalize precipitation. Further analysis based on wavelet coherence (WTC) was performed by selecting central rain gauges in each cluster and analyzing against temperature, wind, Multivariate ENSO index (MEI), and East Atlantic (EA) and North Atlantic Oscillation (NAO), indeces. The results revealed that all climatic features except NAO influenced precipitation in Iran during the 1960–2010 period.

54 ENVIRONMENTAL SCIENCES↗

NCAPH drives breast cancer progression and identifies a gene signature that predicts luminal a tumour recurrence

Luminal A tumours generally have a favourable prognosis but possess the highest 10-year recurrence risk among breast cancers. Additionally, a quarter of the recurrence cases occur within 5 years post-diagnosis. Identifying such patients is crucial as long-term relapsers could benefit from extended hormone therapy, while early relapsers might require more aggressive treatment. We conducted a study to explore non-structural chromosome maintenance condensin I complex subunit H’s (NCAPH) role in luminal A breast cancer pathogenesis, both in vitro and in vivo, aiming to identify an intratumoural gene expression signature, with a focus on elevated NCAPH levels, as a potential marker for unfavourable progression. Our analysis included transgenic mouse models overexpressing NCAPH and a genetically diverse mouse cohort generated by backcrossing. A least absolute shrinkage and selection operator (LASSO) multivariate regression analysis was performed on transcripts associated with elevated intratumoural NCAPH levels. We found that NCAPH contributes to adverse luminal A breast cancer progression. The intratumoural gene expression signature associated with elevated NCAPH levels emerged as a potential risk identifier. Transgenic mice overexpressing NCAPH developed breast tumours with extended latency, and in Mouse Mammary Tumor Virus (MMTV)-NCAPH ErbB2 double-transgenic mice, luminal tumours showed increased aggressiveness. High intratumoural Ncaph levels correlated with worse breast cancer outcome and subpar chemotherapy response. A 10-gene risk score, termed Gene Signature for Luminal A 10 (GSLA10), was derived from the LASSO analysis, correlating with adverse luminal A breast cancer progression. The GSLA10 signature outperformed the Oncotype DX signature in discerning tumours with unfavourable outcomes, previously categorised as luminal A by Prediction Analysis of Microarray 50 (PAM50) across three independent human cohorts. This new signature holds promise for identifying luminal A tumour patients with adverse prognosis, aiding in the development of personalised treatment strategies to significantly improve patient outcomes.

60 APPLIED LIFE SCIENCES↗

Characterizing Tumor Heterogeneity With Functional Imaging and Quantifying High-Risk Tumor Volume for Early Prediction of Treatment Outcome: Cervical Cancer as a Model

Purpose: Treatment response in cancer has been monitored by measuring anatomic tumor volume (ATV) at various times without considering the inherent functional tumor heterogeneity known to critically influence ultimate treatment outcome: primary tumor control and survival. This study applied dynamic contrast-enhanced (DCE) functional MRI to characterize tumors' heterogeneous subregions with low DCE values, at risk for treatment failure, and to quantify the functional risk volume (FRV) for personalized early prediction of treatment outcome. Methods and Materials: DCE-MRI was performed in 102 stage IB{sub 2}-IVA cervical cancer patients to assess tumor perfusion heterogeneity before and during radiation/chemotherapy. FRV represents the total volume of tumor voxels with critically low DCE signal intensity (<2.1 compared with precontrast image, determined by previous receiver operator characteristic analysis). FRVs were correlated with treatment outcome (follow-up: 0.2-9.4, mean 6.8 years) and compared with ATVs (Mann-Whitney, Kaplan-Meier, and multivariate analyses). Results: Before and during therapy at 2-2.5 and 4-5 weeks of RT, FRVs >20, >13, and >5 cm{sup 3}, respectively, significantly predicted unfavorable 6-year primary tumor control (p = 0.003, 7.3 Multiplication-Sign 10{sup -8}, 2.0 Multiplication-Sign 10{sup -8}) and disease-specific survival (p = 1.9 Multiplication-Sign 10{sup -4}, 2.1 Multiplication-Sign 10{sup -6}, 2.5 Multiplication-Sign 10{sup -7}, respectively). The FRVs were superior to the ATVs as early predictors of outcome, and the differentiating power of FRVs increased during treatment. Discussion: Our preliminary results suggest that functional tumor heterogeneity can be characterized by DCE-MRI to quantify FRV for predicting ultimate long-term treatment outcome. FRV is a novel functional imaging heterogeneity parameter, superior to ATV, and can be clinically translated for personalized early outcome prediction before or as early as 2-5 weeks into treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Weekly Dose-Volume Parameters of Mucosa and Constrictor Muscles Predict the Use of Percutaneous Endoscopic Gastrostomy During Exclusive Intensity-Modulated Radiotherapy for Oropharyngeal Cancer

Purpose: To define predictors of percutaneous endoscopic gastrostomy (PEG) use during intensity-modulated radiotherapy (IMRT) for oropharyngeal cancer. Methods and Materials: Data for 59 consecutive patients treated with exclusive IMRT at a single institution were recovered. Of 59 patients, 25 were treated with hyperfractionation (78 Gy, 1.3 Gy per fraction, twice daily; 'HYPER'); and 34 of 59 were treated with a once-daily fractionation schedule (66 Gy, 2.2 Gy per fraction, or 70 Gy, 2 Gy per fraction; 'no-HYPER'). On the basis of symptoms during treatment, a PEG tube could have been placed as appropriate. A number of clinical/dosimetric factors, including the weekly dose-volume histogram of oral mucosa (OM DVHw) and weekly mean dose to constrictors and larynx, were considered. The OM DVHw of patients with and without PEG were compared to assess the most predictive dose-volume combinations. Results: Of 59 patients, 22 needed a PEG tube during treatment (for 15 of 22, {>=}3 months). The best cutoff values for OM DVHw were V9.5 Gy/week <64 cm{sup 3} and V10 Gy/week <54 cm{sup 3}. At univariate analysis, fractionation, mean weekly dose to OM and superior and middle constrictors, and OM DVHw were strongly correlated with the risk of PEG use. In a stepwise multivariate logistic analysis, OM V9.5 Gy/week ({>=}64 vs. <64 cm{sup 3}) was the most predictive parameter (odds ratio 30.8, 95% confidence interval 3.7-254.2, p = 0.0015), confirmed even in the no-HYPER subgroup (odds ratio 21, 95% CI 2.1 confidence interval 210.1, p = 0.01). Conclusions: The risk of PEG use is drastically reduced when OM V9.5-V10 Gy/week is <50-60 cm{sup 3}. These data warrant prospective validation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Functional Data Analysis in NTCP Modeling: A New Method to Explore the Radiation Dose-Volume Effects

Purpose/Objective(s): To describe a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding (RB) for patients irradiated in the prostatic bed by 3-dimensional conformal radiation therapy. Methods and Materials: Kernel density estimation was used to estimate the individual probability density functions from each of the 141 rectum differential dose-volume histograms. Functional principal component analysis was performed on the estimated probability density functions to explore the variation modes in the dose distribution. The functional principal components were then tested for association with RB using logistic regression adapted to functional covariates (FLR). For comparison, 3 other normal tissue complication probability models were considered: the Lyman-Kutcher-Burman model, logistic model based on standard dosimetric parameters (LM), and logistic model based on multivariate principal component analysis (PCA). Results: The incidence rate of grade ≥2 RB was 14%. V{sub 65Gy} was the most predictive factor for the LM (P=.058). The best fit for the Lyman-Kutcher-Burman model was obtained with n=0.12, m = 0.17, and TD50 = 72.6 Gy. In PCA and FLR, the components that describe the interdependence between the relative volumes exposed at intermediate and high doses were the most correlated to the complication. The FLR parameter function leads to a better understanding of the volume effect by including the treatment specificity in the delivered mechanistic information. For RB grade ≥2, patients with advanced age are significantly at risk (odds ratio, 1.123; 95% confidence interval, 1.03-1.22), and the fits of the LM, PCA, and functional principal component analysis models are significantly improved by including this clinical factor. Conclusion: Functional data analysis provides an attractive method for flexibly estimating the dose-volume effect for normal tissues in external radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Imaging Changes in Pediatric Intracranial Ependymoma Patients Treated With Proton Beam Radiation Therapy Compared to Intensity Modulated Radiation Therapy

Purpose: The clinical significance of magnetic resonance imaging (MRI) changes after radiation therapy (RT) in children with ependymoma is not well defined. We compared imaging changes following proton beam radiation therapy (PBRT) to those after photon-based intensity modulated RT (IMRT). Methods and Materials: Seventy-two patients with nonmetastatic intracranial ependymoma who received postoperative RT (37 PBRT, 35 IMRT) were analyzed retrospectively. MRI images were reviewed by 2 neuroradiologists. Results: Sixteen PBRT patients (43%) developed postradiation MRI changes at 3.8 months (median) with resolution by 6.1 months. Six IMRT patients (17%) developed changes at 5.3 months (median) with 8.3 months to resolution. Mean age at radiation was 4.4 and 6.9 years for PBRT and IMRT, respectively (P=.06). Age at diagnosis (>3 years) and time of radiation (≥3 years) was associated with fewer imaging changes on univariate analysis (odds ratio [OR]: 0.35, P=.048; OR: 0.36, P=.05). PBRT (compared to IMRT) was associated with more frequent imaging changes, both on univariate (OR: 3.68, P=.019) and multivariate (OR: 3.89, P=.024) analyses. Seven (3 IMRT, 4 PBRT) of 22 patients with changes had symptoms requiring intervention. Most patients were treated with steroids; some PBRT patients also received bevacizumab and hyperbaric oxygen therapy. None of the IMRT patients had lasting deficits, but 2 patients died from recurrent disease. Three PBRT patients had persistent neurological deficits, and 1 child died secondarily to complications from radiation necrosis. Conclusions: Postradiation MRI changes are more common with PBRT and in patients less than 3 years of age at diagnosis and treatment. It is difficult to predict causes for development of imaging changes that progress to clinical significance. These changes are usually self-limiting, but some require medical intervention, especially those involving the brainstem.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Measuring Nd(III) Solution Concentration in the Presence of Interfering Er(III) and Cu(II) Ions: A Partial Least Squares Analysis of Ultraviolet–Visible Spectra

Optical spectroscopy is a powerful characterization tool with applications ranging from fundamental studies to real-time process monitoring. However, it can be difficult to apply to complex samples that contain interfering analytes which are common in processing streams. Multivariate (chemometric) analysis has been examined for providing selectivity and accuracy to the analysis of optical spectra and expanding its potential applications. Here we will discuss chemometric modeling with an in-depth comparison to more simplistic analysis approaches and outline how chemometric modeling works while exploring the limits on modeling accuracy. Understanding the limitations of the chemometric model can provide better analytical assessment regarding the accuracy and precision of the analytical result. This will be explored in the context of UV–Vis absorbance of neodymium (Nd 3+ ) in the presence of interferents, erbium (Er 3+ ) and copper (Cu 2+ ) under conditions simulating the liquid–liquid extraction approach used to recycle plutonium (Pu) and uranium (U) in used nuclear fuel worldwide. Finally, the selected chemometric model, partial least squares regression, accurately quantifies Nd 3+ with a low percentage error in the presence of interfering analytes and even under conditions that the training set does not describe.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Maximizing MWh: A statistical analysis of the performance of utility-scale photovoltaic projects in the United States

Despite significant cost declines utility-scale solar projects have to perform well over their lifetime in order to return profits in a low-PPA environment of under $50/MWh. Using multivariate regression analysis this paper examines the 2014 Net Capacity Factors for 128 utility-scale projects that came online before the end of 2013 and explores the impact (in decreasing order of importance) of global horizontal irradiance, tracking technology, inverter loading ratios and project vintage plus three other interactive variables on performance. The model complies with the assumptions of OLS regressions and explains 93% of the observed NCF variation.

Bolinger, M↗

Baseline Metabolic Tumor Volume and Total Lesion Glycolysis Are Associated With Survival Outcomes in Patients With Locally Advanced Pancreatic Cancer Receiving Stereotactic Body Radiation Therapy

Purpose: Although previous studies have demonstrated the prognostic value of positron emission tomography (PET) parameters in other malignancies, the role of PET in pancreatic cancer has yet to be well established. We analyzed the prognostic utility of PET for patients with locally advanced pancreatic cancer (LAPC) undergoing fractionated stereotactic body radiation therapy (SBRT). Materials and Methods: Thirty-two patients with LAPC in a prospective clinical trial received up to 3 doses of gemcitabine, followed by 33 Gy in 5 fractions of 6.6 Gy, using SBRT. All patients received a baseline PET scan prior to SBRT (pre-SBRT PET). Metabolic tumor volume (MTV), total lesion glycolysis (TLG), and maximum and peak standardized uptake values (SUV{sub max} and SUV{sub peak}) on pre-SBRT PET scans were calculated using custom-designed software. Disease was measured at a threshold based on the liver SUV, using the equation Liver{sub mean} + [2 × Liver{sub sd}]. Median values of PET parameters were used as cutoffs when assessing their prognostic potential through Cox regression analyses. Results: Of the 32 patients, the majority were male (n=19, 59%), 65 years or older (n=21, 66%), and had tumors located in the pancreatic head (n=27, 84%). Twenty-seven patients (84%) received induction gemcitabine prior to SBRT. Median overall survival for the entire cohort was 18.8 months (95% confidence interval [CI], 15.7-22.0). An MTV of 26.8 cm{sup 3} or greater (hazard ratio [HR] 4.46, 95% CI 1.64-5.88, P<.003) and TLG of 70.9 or greater (HR 3.08, 95% CI 1.18-8.02, P<.021) on pre-SBRT PET scan were associated with inferior overall survival on univariate analysis. Both pre-SBRT MTV (HR 5.13, 95% CI 1.19-22.21, P=.029) and TLG (HR 3.34, 95% CI 1.07-10.48, P=.038) remained independently associated with overall survival in separate multivariate analyses. Conclusions: Pre-SBRT MTV and TLG are potential predictive factors for overall survival in patients with LAPC and may assist in tailoring therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

High Nuclear Hypoxia-Inducible Factor 1 Alpha Expression Is a Predictor of Distant Recurrence in Patients With Resected Pancreatic Adenocarcinoma

Purpose: To evaluate nuclear hypoxia-inducible factor 1α (HIF-1α) expression as a prognostic factor for distant recurrence (DR) and local recurrence (LR) after pancreatic adenocarcinoma resection. Methods and Materials: Tissue specimens were collected from 98 patients with pancreatic adenocarcinoma who underwent resection without neoadjuvant therapy between January 2000 and December 2011. Local recurrence was defined as radiographic or pathologic evidence of progressive disease in the pancreas, pancreatic bed, or associated nodal regions. Distant recurrence was defined as radiographically or pathologically confirmed recurrent disease in other sites. Immunohistochemical staining was performed and scored by an independent pathologist blinded to patient outcomes. High HIF-1α overall expression score was defined as high percentage and intensity staining and thus score >1.33. Univariate analysis was performed for HIF-1α score with LR alone and with DR. Multivariate logistic regression was used to determine predictors of LR and DR. Results: Median follow-up time for all patients was 16.3 months. Eight patients (8%) demonstrated isolated LR, 26 patients (26.5%) had isolated DR, and 13 patients had both LR and DR. Fifty-three patients (54%) had high HIF-1α expression, and 45 patients (46%) had low HIF-1α expression. High HIF-1α expression was significantly associated with DR (P=.03), and low HIF-1α expression was significantly associated with isolated LR (P=.03). On multivariate logistic regression analysis, high HIF-1α was the only significant predictor of DR (odds ratio 2.46 [95% confidence interval 1.06-5.72]; P=.03). In patients with a known recurrence, an HIF-1α score ≥2.5 demonstrated a specificity of 100% for DR. Conclusions: High HIF-1α expression is a significant predictor of distant failure versus isolated local failure in patients undergoing resection of pancreatic adenocarcinoma. Expression of HIF-1α may have utility in determining candidates for adjuvant local radiation therapy and systemic chemotherapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Prognostic value of left ventricular dyssynchrony evaluated by gated myocardial perfusion imaging in patients with chronic kidney disease and normal perfusion defect scores

Background: This study aimed to investigate whether indices of left ventricular (LV) dyssynchrony by gated myocardial perfusion SPECT (GMPS) could be useful to predict prognosis in chronic kidney disease (CKD) patients with normal perfusion defect scores. Methods: One hundred and sixty-seven CKD patients with normal perfusion defect scores on adenosine-stress {sup 201}Tl GMPS and no previous history of overt heart diseases were enrolled. Phase standard deviation (PSD) and bandwidth (BW) were automatically calculated from GMPS. The major adverse cardiac events (MACEs) for a mean of 560 days were defined as sudden cardiac death, fatal arrhythmias, and acute coronary syndrome requiring urgent coronary revascularization. Patients were divided into two groups according to the presence or absence of MACEs. Results: The MACEs occurred in 12 patients (7.1%). Patients who experienced MACEs showed significantly higher PSD and wider BW than those who did not. In the Kaplan-Meier event-free survival analysis, cardiac event rate was significantly higher in the high-PSD and wide-BW group (n = 81) than in the low-PSD and narrow-BW group (n = 71) (P = .002). The multivariate regression analysis revealed that the PSD was associated with MACEs (odds ratio 1.33, 95% confidence interval 1.05-1.69, P = .01). Conclusion: The LV dyssynchrony indices from GMPS may be novel prognostic predictors in CKD patients with normal perfusion defect scores.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

High throughput crystal structure and composition mapping of crystalline nanoprecipitates in alloys by transmission Kikuchi diffraction and analytical electron microscopy

Statistically significant crystal structure and composition identification of nanocrystalline features such as nanoparticles/nanoprecipitates in materials chemistry and alloy designing using electron microscopy remains a grand challenge. In this paper, we reveal that differing crystallographic phases of nanoprecipitates in alloys can be mapped with unprecedented statistics using transmission Kikuchi diffraction (TKD), on typical carbon-based electron-transparent samples. Using a case of multiphase, multicomponent nanoprecipitates extracted from an improved version of 9% chromium Eurofer-97 reduced-activation ferritic-martensitic steel we show that TKD successfully identified more than thousand M 23 C 6 , MX, M 7 C 3 , and M 2 X ( M =Fe, Cr, W, V, Ta; X = C, N) nanoprecipitates in a single scan, something that is currently unachievable using a transmission electron microscope (TEM) without incorporating a precision electron diffraction (PED) system. Precipitates as small as ~20–25 nm were successfully phase identified by TKD. We verified the TKD phase identification using high-resolution transmission electron microscopy (HRTEM) and convergent beam electron diffraction (CBED) pattern analysis of a few precipitates that were identified by TKD on same sample. TKD study was combined with state-of-art analytical scanning transmission electron microscopy (STEM)-energy dispersive X-ray (EDX) spectroscopy and multivariate statistical analysis (MVSA) which provided the complete crystal structure and distinct chemistries of the precipitates in the steel in a high throughput automated way. This technique should be applicable to characterizing any multiphase crystalline nanoparticles or nanomaterials. Furthermore the results highlight that combining phase identification by TKD with analytical STEM and modern data analytics may open new pathways in big data material characterization at nanoscale that may be highly beneficial for characterizing existing materials and in designing new materials.

36 MATERIALS SCIENCE↗

Chemometrics and Experimental Design for the Quantification of Nitrate Salts in Nitric Acid: Near-Infrared Spectroscopy Absorption Analysis

Implementing remote, real-time spectroscopic monitoring of radiochemical processing streams in hot cell environments requires efficiency and simplicity. The success of optical spectroscopy for the quantification of species in chemical systems highly depends on representative training sets and suitable validation sets. Selecting a training set (i.e., calibration standards) to build multivariate regression models is both time- and resource-consuming using standard one-factor-at-a-time approaches. This study describes the use of experimental design to generate spectral training sets and a validation set for the quantification of sodium nitrate (0–1 M) and nitric acid (0.1–10 M) using the near-infrared water band centered at 1440 nm. Partial least squares regression models were built from training sets generated by both D- and I-optimal experimental designs and a one-factor-at-a-time approach. The prediction performance of each model was evaluated by comparing the bias and standard error of prediction for statistical significance. D- and I-optimal designs reduced the number of samples required to build regression models compared with one-factor-at-a-time while also improving performance. Models must be confirmed against a validation sample set when minimizing the number of samples in the training set. The D-optimal design performed the best when considering both performance and efficiency by improving predictive capability and reducing number of samples in the training set by 64% compared with the one-factor-at-a-time approach. The experimental design approach objectively selects calibration and validation spectral data sets based on statistical criterion to optimize performance and minimize resources.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Does Unintentional Splenic Radiation Predict Outcomes After Pancreatic Cancer Radiation Therapy?

Purpose: To determine whether severity of lymphopenia is dependent on radiation dose and fractional volume of spleen irradiated unintentionally during definitive chemoradiation (CRT) in patients with locally advanced pancreatic cancer (LAPC). Methods: 177 patients with LAPC received induction chemotherapy (mainly gemcitabine-based regimens) followed by CRT (median 50.4 Gy with concurrent capecitabine) from January 2006 to December 2012. Absolute lymphocyte count (ALC) was recorded at baseline, before CRT, and 2 to 10 weeks after CRT. Splenic dose-volume histogram (DVH) parameters were reported as mean splenic dose (MSD) and percentage of splenic volume receiving at least 5- (V5), 10- (V10), 15- (V15), and 20-Gy (V20) dose. Overall survival (OS) was analyzed with use of the Cox model, and development of post-CRT severe lymphopenia (ALC <0.5 K/UL) was assessed by multivariate logistic regression with use of baseline and treatment factors. Results: The median post-CRT ALC (0.68 K/UL; range, 0.13-2.72) was significantly lower than both baseline ALC (1.42 K/UL; range, 0.34-3.97; P<.0001) and pre-CRT ALC (1.32 K/UL, range 0.36-4.82; P<.0001). Post-CRT ALC <0.5 K/UL was associated with inferior OS on univariate analysis (median, 11.1 vs 15.3 months; P=.01) and multivariate analysis (hazard ratio = 1.66, P=.01). MSD (9.8 vs 6 Gy, P=.03), median V10 (32.6 vs 16%, P=.04), V15 (23.2 vs 9.5%, P=.03), and V20 (15.4 vs 4.6%, P=.02) were significantly higher in patients with severe lymphopenia than in those without. On multivariate analysis, postinduction lymphopenia (P<.001; odds ratio [OR] = 5.25) and MSD (P=.002; OR= 3.42) were independent predictors for the development of severe post-CRT lymphopenia. Conclusion: Severe post-CRT lymphopenia is an independent predictor of poor OS in LAPC patients receiving CRT. Higher splenic doses increase the risk for the development of severe post-CRT lymphopenia. When clinically indicated, assessment of splenic DVHs before the acceptance of treatment plans may minimize the risk of severe post-CRT lymphopenia.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Analysis of Multilayer Devices for Superconducting Electronics by High-Resolution Scanning Transmission Electron Microscopy and Energy Dispersive Spectroscopy

We used a focused ion beam to obtain cross-sectional specimens from both magnetic multilayer and Nb/Al-AlOx/Nb Josephson junction devices for characterization by scanning transmission electron microscopy (STEM) and energy dispersive X-ray spectroscopy (EDX). An automated multivariate statistical analysis of the EDX spectral images produced chemically unique component images of individual layers within the multilayer structures. STEM imaging elucidated distinct variations in film morphology, interface quality, and/or etch artifacts that could be correlated to magnetic and/or electrical properties measured on the same devices.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Land quality, sustainable development and environmental degradation in agricultural districts: A computational approach based on entropy indexes

Land Degradation (LD) in socio-environmental systems negatively impacts sustainable development paths. This study proposes a framework to LD evaluation based on indicators of diversification in the spatial distribution of sensitive land. We hypothesize that conditions for spatial heterogeneity in a composite index of land sensitivity are more frequently associated to areas prone to LD than spatial homogeneity. Spatial heterogeneity is supposed to be associated with degraded areas that act as hotspots for future degradation processes. A diachronic analysis (1960–2010) was performed at the Italian agricultural district scale to identify environmental factors associated with spatial heterogeneity in the degree of land sensitivity to degradation based on the Environmentally Sensitive Area Index (ESAI). In 1960, diversification in the level of land sensitivity measured using two common indexes of entropy (Shannon's diversity and Pielou's evenness) increased significantly with the ESAI, indicating a high level of land sensitivity to degradation. In 2010, surface area classified as “critical” to LD was the highest in districts with diversification in the spatial distribution of ESAI values, confirming the hypothesis formulated above. Entropy indexes, based on observed alignment with the concept of LD, constitute a valuable base to inform mitigation strategies against desertification. - Highlights: • Spatial heterogeneity is supposed to be associated with degraded areas. • Entropy indexes can inform mitigation strategies against desertification. • Assessing spatial diversification in the degree of land sensitivity to degradation. • Mediterranean rural areas have an evident diversity in agricultural systems. • A diachronic analysis carried out at the Italian agricultural district scale.

54 ENVIRONMENTAL SCIENCES↗