Adsorption and desorption of gases in porous silicon

This research was undertaken to provide an understanding of the nature, origin and desorption mechanism of species found on the porous silicon (PS) surface and the changes that occur when PS is stored under varying conditions. The PS used in this work was produced from p-, high-resistivity FZ c-Si substrates.Three types of commonly used HF-based electrolytes were chosen for anodisation, under the same process conditions. With the resulting samples, temperature programmed desorption (TPD) coupled with mass spectrometry were used to identify species liberated at different temperatures. FTIR was also used to investigate the nature of surface species on PS and hence to infer how these give rise to the observed volatile products. After various modifications, the TPD system with the custom-made heating unit and the appropriate methodology were developed to suit the present work. Freshly anodised PS in the vacuum chamber at room temperatures gave somewhat enhanced peaks due to air components (0 ⁺, N₂⁺ and/or CO⁺, O₂⁺ and CO₂⁺) and, most significantly, an increase in F-containing species (e.g. F ⁺), derived from the electrolyte. On heating, the main desorbed species were found be hydrogen, silane, Si-Fx species, and Hx-Fx species. TPD spectra for hydrogen showed two peak maxima with a "hump". This implies two types of hydrogen environments; these were assigned as Si-H (lower temperature peak) and Si-H₂ (higher temperature peak) species on the PS surface. The temperature difference between the two peaks was similar (~100K) in all three cases. This shows that hydrogen desorption occurs similarly from PS prepared using the three different electrolytes. It also suggests that hydrogen adsorption during PS formation occurs analogously in the three electrolytes. Silane was observed to desorb at 575K. It is proposed that this comes from -SiH3 groups on the PS surface, possibly after reaction with sorbed water. A mechanism is suggested. In contrast, desorption of Si-Fx species was found to be sensitive to the nature of the electrolyte. The lower temperature peaks from the TPD experiments are assigned to H₂SiF₆ , SiF ₄ and perhaps H₂SiF₂ (by-products from anodisation) sorbed on PS. They are held relatively weakly by electrostatic and/or van der Waals forces. The higher temperature peak assigned to SiF₃ + may be explained in terms of migration of F atoms followed by Si-SiF₃ bond breakage. The various Hx-Fy products derive from species present in the HF electrolytes. To investigate changes in PS under typical storage conditions, samples were kept in (i) a blue wafer box, (ii) a screw-top white box and (iii) a similar box in a vacuum desiccator. The PS was then analysed by FTIR after various time intervals. After one month, only PS stored under condition (iii) was unchanged. The other samples showed evidence of oxidation, attributed to hydrolysis, fonnation of silanol (SiO-H) species, and back-bond oxidation of Si-Hx groups. Further ageing revealed inclusion of C-H species on PS. This work is a contribution to understanding of PS behaviour, and is relevant to its applications in electronic devices and sensors

Reproducibility in Radiomics: A Comparison of Feature Extraction Methods and Two Independent Datasets

Radiomics involves the extraction of information from medical images that are not visible to the human eye. There is evidence that these features can be used for treatment stratification and outcome prediction. However, there is much discussion about the reproducibility of results between different studies. This paper studies the reproducibility of CT texture features used in radiomics, comparing two feature extraction implementations, namely the MATLAB toolkit and Pyradiomics, when applied to independent datasets of CT scans of patients: (i) the open access RIDER dataset containing a set of repeat CT scans taken 15 min apart for 31 patients (RIDER Scan 1 and Scan 2, respectively) treated for lung cancer; and (ii) the open access HN1 dataset containing 137 patients treated for head and neck cancer. Gross tumor volume (GTV), manually outlined by an experienced observer available on both datasets, was used. The 43 common radiomics features available in MATLAB and Pyradiomics were calculated using two intensity-level quantization methods with and without an intensity threshold. Cases were ranked for each feature for all combinations of quantization parameters, and the Spearman’s rank coefficient, rs, calculated. Reproducibility was defined when a highly correlated feature in the RIDER dataset also correlated highly in the HN1 dataset, and vice versa. A total of 29 out of the 43 reported stable features were found to be highly reproducible between MATLAB and Pyradiomics implementations, having a consistently high correlation in rank ordering for RIDER Scan 1 and RIDER Scan 2 (rs > 0.8). 18/43 reported features were common in the RIDER and HN1 datasets, suggesting they may be agnostic to disease site. Useful radiomics features should be selected based on reproducibility. This study identified a set of features that meet this requirement and validated the methodology for evaluating reproducibility between datasets

Reproducibility in Radiomics: A Comparison of Feature Extraction Methods and Two Independent Datasets

Radiomics involves the extraction of information from medical images that are not visible to the human eye. There is evidence that these features can be used for treatment stratification and outcome prediction. However, there is much discussion about the reproducibility of results between different studies. This paper studies the reproducibility of CT texture features used in radiomics, comparing two feature extraction implementations, namely the MATLAB toolkit and Pyradiomics, when applied to independent datasets of CT scans of patients: (i) the open access RIDER dataset containing a set of repeat CT scans taken 15 min apart for 31 patients (RIDER Scan 1 and Scan 2, respectively) treated for lung cancer; and (ii) the open access HN1 dataset containing 137 patients treated for head and neck cancer. Gross tumor volume (GTV), manually outlined by an experienced observer available on both datasets, was used. The 43 common radiomics features available in MATLAB and Pyradiomics were calculated using two intensity-level quantization methods with and without an intensity threshold. Cases were ranked for each feature for all combinations of quantization parameters, and the Spearman’s rank coefficient, rs, calculated. Reproducibility was defined when a highly correlated feature in the RIDER dataset also correlated highly in the HN1 dataset, and vice versa. A total of 29 out of the 43 reported stable features were found to be highly reproducible between MATLAB and Pyradiomics implementations, having a consistently high correlation in rank ordering for RIDER Scan 1 and RIDER Scan 2 (rs > 0.8). 18/43 reported features were common in the RIDER and HN1 datasets, suggesting they may be agnostic to disease site. Useful radiomics features should be selected based on reproducibility. This study identified a set of features that meet this requirement and validated the methodology for evaluating reproducibility between datasets

Oral Apixaban for the Treatment of Acute Venous Thromboembolism

BACKGROUND: Apixaban, an oral factor Xa inhibitor administered in fixed doses, may simplify the treatment of venous thromboembolism. METHODS: In this randomized, double-blind study, we compared apixaban (at a dose of 10 mg twice daily for 7 days, followed by 5 mg twice daily for 6 months) with conventional therapy (subcutaneous enoxaparin, followed by warfarin) in 5395 patients with acute venous thromboembolism. The primary efficacy outcome was recurrent symptomatic venous thromboembolism or death related to venous thromboembolism. The principal safety outcomes were major bleeding alone and major bleeding plus clinically relevant nonmajor bleeding. RESULTS: The primary efficacy outcome occurred in 59 of 2609 patients (2.3%) in the apixaban group, as compared with 71 of 2635 (2.7%) in the conventional-therapy group (relative risk, 0.84; 95% confidence interval [CI], 0.60 to 1.18; difference in risk [apixaban minus conventional therapy], -0.4 percentage points; 95% CI, -1.3 to 0.4). Apixaban was noninferior to conventional therapy (P<0.001) for predefined upper limits of the 95% confidence intervals for both relative risk (<1.80) and difference in risk (<3.5 percentage points). Major bleeding occurred in 0.6% of patients who received apixaban and in 1.8% of those who received conventional therapy (relative risk, 0.31; 95% CI, 0.17 to 0.55; P<0.001 for superiority). The composite outcome of major bleeding and clinically relevant nonmajor bleeding occurred in 4.3% of the patients in the apixaban group, as compared with 9.7% of those in the conventional-therapy group (relative risk, 0.44; 95% CI, 0.36 to 0.55; P<0.001). Rates of other adverse events were similar in the two groups. CONCLUSIONS: A fixed-dose regimen of apixaban alone was noninferior to conventional therapy for the treatment of acute venous thromboembolism and was associated with significantly less bleeding (Funded by Pfizer and Bristol-Myers Squibb; ClinicalTrials.gov number, NCT00643201)