Information retrieval from spaceborne GNSS Reflectometry observations using physics- and learning-based techniques

This dissertation proposes a learning-based, physics-aware soil moisture (SM) retrieval algorithm for NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission. The proposed methodology has been built upon the literature review, analyses, and findings from a number of published studies throughout the dissertation research. Namely, a Sig- nals of Opportunity Coherent Bistatic scattering model (SCoBi) has been first developed at MSU and then its simulator has been open-sourced. Simulated GNSS-Reflectometry (GNSS-R) analyses have been conducted by using SCoBi. Significant findings have been noted such that (1) Although the dominance of either the coherent reflections or incoher- ent scattering over land is a debate, we demonstrated that coherent reflections are stronger for flat and smooth surfaces covered by low-to-moderate vegetation canopy; (2) The influ- ence of several land geophysical parameters such as SM, vegetation water content (VWC), and surface roughness on the bistatic reflectivity was quantified, the dynamic ranges of reflectivity changes due to SM and VWC are much higher than the changes due to the surface roughness. Such findings of these analyses, combined with a comprehensive lit- erature survey, have led to the present inversion algorithm: Physics- and learning-based retrieval of soil moisture information from space-borne GNSS-R measurements that are taken by NASA’s CYGNSS mission. The study is the first work that proposes a machine learning-based, non-parametric, and non-linear regression algorithm for CYGNSS-based soil moisture estimation. The results over point-scale soil moisture observations demon- strate promising performance for applicability to large scales. Potential future work will be extension of the methodology to global scales by training the model with larger and diverse data sets

Prealbumin is a more sensitive marker than albumin to assess the nutritional status in patients undergoing radiotherapy for head and neck cancer

AIM OF THE STUDY: The aim of this prospective study was to determine the prevalence of malnutrition and to evaluate a more sensitive marker to assess the nutritional status in patients undergoing RT for head and neck cancer. MATERIAL AND METHODS: The prospective study included 51 (mean age of 57.6 ±11.2 years) patients undergoing RT for head and neck cancer. Malnutrition was defined as weight loss > 5% of baseline. RESULTS: Forty-six (90.2%) of 51 patients were male. Malnutrition developed in 33 (64.7%) patients during RT. Mean prealbumin level was significantly lower in patients with malnutrition than in those without malnutrition (17 ±5 g/dl vs. 22 ±5 g/dl, respectively, p = 0.004). On the other hand, there was no significant difference between the two groups in terms of other nutrition parameters including total protein, albumin, total cholesterol, triglyceride, and glucose (p > 0.05). The percentage of weight loss negatively correlated with prealbumin (r = –0.430, p = 0.002), but not with other nutrition parameters including total protein, albumin, triglyceride, total cholesterol, HDL cholesterol, LDL cholesterol, and glucose (p > 0.05). CONCLUSIONS: The prevalence of malnutrition was high in patients with head and neck cancer. Prealbumin was a more sensitive marker than albumin to assess the nutritional status in these patients

Development of a Coherent Bistatic Vegetation Model for Signal of Opportunity Applications at VHF UHF-Bands

A coherent bistatic vegetation scattering model, based on a Monte Carlo simulation, is being developed to simulate polarimetric bi-static reflectometry at VHF/UHF-bands (240-270 MHz). The model is aimed to assess the value of geostationary satellite signals of opportunity to enable estimation of the Earth's biomass and root-zone soil moisture. An expression for bistatic scattering from a vegetation canopy is derived for the practical case of a ground-based/low altitude platforms with passive receivers overlooking vegetation. Using analytical wave theory in conjunction with distorted Born approximation (DBA), the transmit and receive antennas effects (i.e., polarization, orientation, height, etc.) are explicitly accounted for. Both the coherency nature of the model (joint phase and amplitude information) and the explicit account of system parameters (antenna, altitude, polarization, etc) enable one to perform various beamforming techniques to evaluate realistic deployment configurations. In this paper, several test scenarios will be presented and the results will be evaluated for feasibility for future biomass and root-zone soil moisture application using geostationary communication satellite signals of opportunity at low frequencies

High Spatio-Temporal Resolution CYGNSS Soil Moisture Estimates Using Artificial Neural Networks

This paper presents a learning-based, physics-aware soil moisture (SM) retrieval algorithm for NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission. The goal of the proposed novel method is to advance CYGNSS-based SM estimations, exploiting the spatio-temporal resolution of the GNSS reflectometry (GNSS-R) signals to its highest potential within a machine learning framework. The methodology employs a fully connected Artificial Neural Network (ANN) regression model to perform SM predictions through learning the nonlinear relations of SM and other land geophysical parameters to the CYGNSS observables. In situ SM measurements from several International SM Network (ISMN) sites are used as reference labels; CYGNSS incidence angles, derived reflectivity and trailing edge slope (TES) values, as well as ancillary data, are exploited as input features for training and validation of the ANN model. In particular, the utilized ancillary data consist of normalized difference vegetation index (NDVI), vegetation water content (VWC), terrain elevation, terrain slope, and h-parameter (surface roughness). Land cover classification and inland water body masks are also used for the intermediate derivations and quality control purposes. The proposed algorithm assumes uniform SM over a 0.0833 ∘ × 0.0833 ∘ (approximately 9 km × 9 km around the equator) lat/lon grid for any CYGNSS observation that falls within this window. The proposed technique is capable of generating sub-daily and high-resolution SM predictions as it does not rely on time-series or spatial averaging of the CYGNSS observations. Once trained on the data from ISMN sites, the model is independent from other SM sources for retrieval. The estimation results obtained over unseen test data are promising: SM predictions with an unbiased root mean squared error of 0.0544 cm 3 /cm 3 and Pearson correlation coefficient of 0.9009 are reported for 2017 and 2018

Comparison of Endovenous Laser and Radiofrequency Ablation in Treating Varices in the Same Patient

Conclusion: EVLA procedure may be superior to RFA in certain respects

Effect of Serum Selenium Levels on Radiotherapy-related Toxicity in Patients Undergoing Radiotherapy for Head and Neck Cancer

Aim: To investigate whether there is a difference in selenium levels before and after radiotherapy (RT) and to study the effects of serum selenium levels on RT-related toxicity in patients undergoing RT for head and neck cancer. Patients and Methods: A population of 47 consecutive patients was enrolled in the study. RT was given by conventional fractionation. RT-related acute toxicity was evaluated once a week. Blood samples were obtained before and after RT to evaluate selenium levels. Results: There was no significant difference between the levels of selenium before and after RT (58.09 +/- 1.36 mu g/l and 56.34 +/- 1.11 mu g/l, p-value=0.747, respectively). Grade mucositis, dysphagia, radiodermatitis, and nausea were seen in 6 (12.7%), 32 (68.2%), 24 (51.1%), and 3 (6.4%) patients, respectively. It was found that there was no statistically significant difference in the levels of selenium before and after RT, and no observed diferrences in regard to RT-related toxicities. Conclusion: The serum selenium levels do not affect RT-related toxicities

The effect of being overweight on survival in patients with gastric cancer undergoing adjuvant chemoradiotherapy

The aim of this study was to examine the effect of being overweight on survival in patients with gastric cancer undergoing adjuvant chemoradiotherapy and chemotherapy. In this study 152 patients were evaluated. Radiotherapy dose was 45 Gy given in 5 weeks. 5-FU 425 mg/m(2) and folinic acid 20 mg/m(2) were administered weekly during the radiotherapy and four cycles with 4-week intervals as consolidation chemotherapy after radiotherapy. Patients were assigned into two groups according to their body mass index: overweight (body mass index >= 5 kg/m(2)) and normal weight (body mass index <25.0 kg/m(2)). The median overall survival was 39 months vs. 18 months and median disease-free survival was 27 months vs. 13 months in the overweight and normal-weight groups respectively (P = 0.004 and P = 0.006 respectively). The 5-year survival was better in the patients with overweight than those with normal weight (42% vs. 17%; P = 0.004). The overall survival was significantly better with being overweight and early pathological stage (P = 0.016 and P = 0001 respectively). Overall survival, disease-free survival and long-term survival in patients with gastric cancer undergoing adjuvant treatment were better in overweight than normal-weight patients. Moreover, it was shown that body mass index and pathological stage were associated to survival and prognosis

The effect of different types of honey on healing infected wounds

KISA, Ucler/0000-0002-8131-6810WOS: 000447063700004PubMed: 30307813Objective: To investigate the effects of treatments of 'mad honey', blossom honey and nitrofurazone on infected wound healing. Method: Male albino Wistar rats were randomly divided into four groups: 'mad honey' (MH), blossom honey (BH), nitrofurazone (N) and control (C). All rats were anaesthetised intraperitoneally. A circular skin incision was made to the back regions. Grafts containing slime-producing Staphylococcus epidermidis were placed on the incision area and then sutured to the skin. Infection in the wound area was confirmed after 48 hours. Wounds were dressed twice daily with the various treatment materials. Rats were randomly euthanised on days 7 or 14, and tissue samples taken. Tissue samples were assessed for hydroxyproline (HP), tensile strength (TS) and macroscopic measurement (area and intensity). Results: HP levels were higher in the treatment groups (MH, BH, N) at days 7 and 14 compared with the control group. 'Group x day' interaction was found in the HP levels (p=0.015). Increases in HP levels in the MH and N groups between days 7 and 14 were significantly higher than those in the other groups (p<0.05). Intensity was significantly lower in the control group and significantly higher in group MH compared with the other groups. Significant 'group x day' interaction was observed in intensity (p=0.006). TS was significantly lower on day 7 than on day 14 (p=0.022). No marked difference was observed between the groups, nor any 'group x day' interaction, in terms of TS. Conclusion: Honey administration successfully healed infected wounds. However, there was no significant difference between the effect of MH and that of N in terms of wound healing