Patient-specific stopping power calibration for proton therapy planning based on single-detector proton radiography.

A simple robust optimizer has been developed that can produce patient-specific calibration curves to convert x-ray computed tomography (CT) numbers to relative stopping powers (HU-RSPs) for proton therapy treatment planning. The difference between a digitally reconstructed radiograph water-equivalent path length (DRRWEPL) map through the x-ray CT dataset and a proton radiograph (set as the ground truth) is minimized by optimizing the HU-RSP calibration curve. The function of the optimizer is validated with synthetic datasets that contain no noise and its robustness is shown against CT noise. Application of the procedure is then demonstrated on a plastic and a real tissue phantom, with proton radiographs produced using a single detector. The mean errors using generic/optimized calibration curves between the DRRWEPL map and the proton radiograph were 1.8/0.4% for a plastic phantom and -2.1/ - 0.2% for a real tissue phantom. It was then demonstrated that these optimized calibration curves offer a better prediction of the water equivalent path length at a therapeutic depth. We believe that these promising results are suggestive that a single proton radiograph could be used to generate a patient-specific calibration curve as part of the current proton treatment planning workflow

Bacteriologic and clinical efficacy of ofloxacin 0.3% versus ciprofloxacin 0.3% ophthalmic solutions in the treatment of patients with culture-positive bacterial keratitis.

PURPOSE: To compare the efficacy and safety of ofloxacin 0.3% ophthalmic solution with ciprofloxacin 0.3% ophthalmic solution in patients with culture-positive bacterial keratitis. METHODS: Patients with a microbiologic diagnosis of bacterial keratitis were included in this double-masked, parallel-group study and were randomized to treatment with either ofloxacin 0.3% or ciprofloxacin 0.3% ophthalmic solution. One drop of the study medication was instilled during the daytime according to the following schedule: every half-hour on study day 1, every hour on days 2 through 4, and every 2 hours on days 5 through 21. Healing, the primary outcome measure, was defined as complete reepithelialization, accompanied by nonprogression of stromal infiltrate for 2 days. Secondary outcome measures included signs and symptoms of infection. Patients were monitored throughout the study period for any adverse events. RESULTS: A total of 217 patients completed the study: 112 were treated with ofloxacin and 105 were treated with ciprofloxacin. Streptococcus pneumoniae was the most commonly encountered pathogen in all patients. Complete corneal reepithelialization occurred in 85% of those treated with ofloxacin and in 77% of those treated with ciprofloxacin (p = 0.32). The average time to corneal ulcer healing was 13.7 days in those treated with ofloxacin and 14.4 days in those treated with ciprofloxacin. Both treatments were well tolerated with no patient discontinuing the study because of side effects. CONCLUSION: Ofloxacin 0.3% and ciprofloxacin 0.3% ophthalmic solutions are effective and safe in the treatment of patients with culture-positive bacterial keratitis

Anti-inflammation activity and chemical composition of flower essential oil from Hedychium coronarium

Hedychium coronarium Koen. (Family Zingiberaceae), popularly named butterfly ginger, is widely available in tropical and subtropical regions. It has been used in folk medicine for many conditions, such as contusion inflammation, anti-rheumatic and so on. In this study, chemical compositions and anti-inflammatory activity of this flowers’ essential oil were investigated for the first time. Followed by GC–MS analysis, a total of 29 components were identified and the main constituents included -transocimenone (28.05%), linalool (18.52%), 1,8-cineole (11.35%), -terpineol (7.11%), 10-epi--eudesmol (6.06%), sabinene (4.59%) and terpinen-4-ol (3.17%). We measured the antioxidant activity of the essential oil in vitro (DPPH reduction assay and ferric reducing antioxidant power assay) and the antiinflammatory activity in vivo (carrageenan-induced hind paw edema in rats). The oil (100 mg/kg p.o.) produced significant inhibition of paw oedema, but showed poor antioxidant activity (with the DPPH IC50 value of 1091.00 g/ml and FRAP value of 0.22 mol Fe2+/mg). The results reveal that there is no direct correlation between anti-inflammatory effect and antioxidant activity of this essential oil

The effects on grain quality traits of a grain serpin protein and the VPM 1 segment in southern Australian wheat breeding

Trabalho final do 6º ano médico com vista à atribuição do Grau de Mestre no âmbito do ciclo de estudos de mestrado integrado em medicina da Faculdade de Medicina de Coimbra.Introdução: Estudos prévios estabeleceram que até 12% dos doentes com enfarte agudo do miocárdio não demonstravam lesão coronária aparente ao exame angiográfico. Contudo, existe muito pouca informação disponível acerca deste fenómeno em enfartes agudos do miocárdio sem elevação do segmento ST. O objectivo deste estudo foi avaliar uma população de doentes com esse diagnóstico sujeitos a angiografia coronária, analisando e comparando as características clínicas e os prognósticos entre os que não revelaram lesão coronária aparente e os que apresentavam doença coronária epicárdica. Métodos: O nosso estudo avaliou 270 doentes com enfarte agudo do miocárdio sem elevação do segmento ST que foram sujeitos a angiografia coronária nas primeiras 72 horas de enfarte. Foram valorizadas as características demográficas, clínicas, parâmetros analíticos, achados electrocardiográficos, fracção de ejecção ventricular esquerda, duração do internamento e prognóstico.Previous studies established that up to 12% of patients with acute myocardial infarction did not present coronary atherosclerotic disease demonstrable with angiographic exam. However, little information is available about this phenomenon in acute non-STelevation myocardial infarction. We examined a population of patients with this diagnosis who had undergone coronary angiography, assessing and comparing the clinical characteristics and prognosis between the subset of patients with angiographically normal coronary arteries and the subset of patients with coronary disease

A Novel Power-Band based Data Segmentation Method for Enhancing Meter Phase and Transformer-Meter Pairing Identification

This paper presents a novel power-band-based data segmentation (PBDS) method to enhance the identification of meter phase and meter-transformer pairing. Meters that share the same transformer or are on the same phase typically exhibit strongly correlated voltage profiles. However, under high power consumption, there can be significant voltage drops along the line connecting a customer to the distribution transformer. These voltage drops significantly decrease the correlations among meters on the same phase or supplied by the same transformer, resulting in high misidentification rates. To address this issue, we propose using power bands to select highly correlated voltage segments for computing correlations, rather than relying solely on correlations computed from the entire voltage waveforms. The algorithm's performance is assessed by conducting tests using data gathered from 13 utility feeders. To ensure the credibility of the identification results, utility engineers conduct field verification for all 13 feeders. The verification results unequivocally demonstrate that the proposed algorithm surpasses existing methods in both accuracy and robustness.Comment: Submitted to the IEEE Transactions on Power Delivery. arXiv admin note: text overlap with arXiv:2111.1050

A Modified Sequence-to-point HVAC Load Disaggregation Algorithm

This paper presents a modified sequence-to-point (S2P) algorithm for disaggregating the heat, ventilation, and air conditioning (HVAC) load from the total building electricity consumption. The original S2P model is convolutional neural network (CNN) based, which uses load profiles as inputs. We propose three modifications. First, the input convolution layer is changed from 1D to 2D so that normalized temperature profiles are also used as inputs to the S2P model. Second, a drop-out layer is added to improve adaptability and generalizability so that the model trained in one area can be transferred to other geographical areas without labelled HVAC data. Third, a fine-tuning process is proposed for areas with a small amount of labelled HVAC data so that the pre-trained S2P model can be fine-tuned to achieve higher disaggregation accuracy (i.e., better transferability) in other areas. The model is first trained and tested using smart meter and sub-metered HVAC data collected in Austin, Texas. Then, the trained model is tested on two other areas: Boulder, Colorado and San Diego, California. Simulation results show that the proposed modified S2P algorithm outperforms the original S2P model and the support-vector machine based approach in accuracy, adaptability, and transferability

An ICA-Based HVAC Load Disaggregation Method Using Smart Meter Data

This paper presents an independent component analysis (ICA) based unsupervised-learning method for heat, ventilation, and air-conditioning (HVAC) load disaggregation using low-resolution (e.g., 15 minutes) smart meter data. We first demonstrate that electricity consumption profiles on mild-temperature days can be used to estimate the non-HVAC base load on hot days. A residual load profile can then be calculated by subtracting the mild-day load profile from the hot-day load profile. The residual load profiles are processed using ICA for HVAC load extraction. An optimization-based algorithm is proposed for post-adjustment of the ICA results, considering two bounding factors for enhancing the robustness of the ICA algorithm. First, we use the hourly HVAC energy bounds computed based on the relationship between HVAC load and temperature to remove unrealistic HVAC load spikes. Second, we exploit the dependency between the daily nocturnal and diurnal loads extracted from historical meter data to smooth the base load profile. Pecan Street data with sub-metered HVAC data were used to test and validate the proposed methods.Simulation results demonstrated that the proposed method is computationally efficient and robust across multiple customers