Lung cancer is categorized into two main types: non-small cell lung cancer (NSCLC) and small cell lung cancer. Of these, NSCLC accounts for approximately 85% of all cases and encompasses varieties ...such as squamous cell carcinoma and adenocarcinoma. For patients with advanced NSCLC that do not have oncogene addiction, the preferred treatment approach is a combination of immunotherapy and chemotherapy. However, the progression-free survival (PFS) typically ranges only from about 6 to 8 months, accompanied by certain adverse events. In order to carry out individualized treatment more effectively, it is urgent to accurately screen patients with PFS for more than 12 months under this treatment regimen. Therefore, this study undertook a retrospective collection of pulmonary CT images from 60 patients diagnosed with NSCLC treated at the First Affiliated Hospital of Wenzhou Medical University. It developed a machine learning model, designated as bSGSRIME-SVM, which integrates the rime optimization algorithm with self-adaptive Gaussian kernel probability search (SGSRIME) and support vector machine (SVM) classifier. Specifically, the model initiates its process by employing the SGSRIME algorithm to identify pivotal image features. Subsequently, it utilizes an SVM classifier to assess these features, aiming to enhance the model's predictive accuracy. Initially, the superior optimization capability and robustness of SGSRIME in IEEE CEC 2017 benchmark functions were validated. Subsequently, employing color moments and gray-level co-occurrence matrix methods, image features were extracted from images of 60 NSCLC patients undergoing immunotherapy combined with chemotherapy. The developed model was then utilized for analysis. The results indicate a significant advantage of the model in predicting the efficacy of immunotherapy combined with chemotherapy for NSCLC, with an accuracy of 92.381% and a specificity of 96.667%. This lays the foundation for more accurate PFS predictions and personalized treatment plans.
•PProposes bSGSRIME-SVM, a novel model to predict progression-free survival in NSCLC patients under chemo and immunotherapy.•Validates SGSRIME's superior optimization and robustness using IEEE CEC 2017 benchmarks, proving its reliability in predicting PFS for NSCLC patients.•Extracts 118 features from CT images of 60 NSCLC patients using color moments and gray-level co-occurrence matrix methods, offering a comprehensive dataset for analysis.•Demonstrates bSGSRIME-SVM's effectiveness with 92.381% accuracy and 96.667% specificity in predicting NSCLC patients' response to chemo-immunotherapy.
Petrarch's fragmenta Peterson, Thomas E
Petrarch's fragmenta,
2016, 20160613, 2016, 2016-01-01, 2016-06-16
eBook
"Building on recent Petrarch scholarship and broader studies of medieval poetics, poetic narrativity and biblical intertextuality, this study argues that Petrarch's Rerum vulgarium fragmenta is an ...ordered and coherent work unified by narrative and theological structures. The author begins with the premise that the multiple voices of the Petrarchan figure (or subject) call for a reading informed by historical and autobiographical considerations. Within such a reading, the internal chronology of the work coincides with a temporal framework provided by Petrarch's Latin prose and poetry. Drawing on this material, he argues that Petrarch's derivations from early poets in the Italian vernacular, his Augustineanism and his humanism are manifest in the Fragmenta and contribute to its narrative and theological unity."--
The authors report a systematic meta-analytic review of the relationships among 3 of the most widely studied measures of children's phonological skills (phonemic awareness, rime awareness, and verbal ...short-term memory) and children's word reading skills. The review included both extreme group studies and correlational studies with unselected samples (235 studies were included, and 995 effect sizes were calculated). Results from extreme group comparisons indicated that children with dyslexia show a large deficit on phonemic awareness in relation to typically developing children of the same age (pooled effect size estimate: -1.37) and children matched on reading level (pooled effect size estimate: -0.57). There were significantly smaller group deficits on both rime awareness and verbal short-term memory (pooled effect size estimates: rime skills in relation to age-matched controls, -0.93, and reading-level controls, -0.37; verbal short-term memory skills in relation to age-matched controls, -0.71, and reading-level controls, -0.09). Analyses of studies of unselected samples showed that phonemic awareness was the strongest correlate of individual differences in word reading ability and that this effect remained reliable after controlling for variations in both verbal short-term memory and rime awareness. These findings support the pivotal role of phonemic awareness as a predictor of individual differences in reading development. We discuss whether such a relationship is a causal one and the implications of research in this area for current approaches to the teaching of reading and interventions for children with reading difficulties.
Rapid immunoprecipitation mass spectrometry of endogenous protein (RIME) is a method that allows the study of protein complexes, in particular chromatin and transcription factor complexes, in a rapid ...and robust manner by mass spectrometry (MS). The method can be used in parallel with chromatin immunoprecipitation-sequencing (ChIP-seq) experiments to provide information on both the cistrome and interactome for a given protein. The method uses formaldehyde fixation to stabilize protein complexes. By using antibodies against the endogenous target, the cross-linked complex is immunoprecipitated, rigorously washed, and then digested into peptides while avoiding antibody contamination (on-bead digestion). By using this method, MS identification of the target protein and several dozen interacting proteins is possible using a 100-min LC-MS/MS run. The protocol does not require substantial proteomics expertise, and it typically takes 2-3 d from the collection of material to results.
Nitrogen (N) deposition, a key process of atmospheric self-cleaning, represents an important pathway for nutrients and pollutants to ecosystems. Enhanced N deposition flux contributes to ...acidification, eutrophication and loss of biodiversity. N-NO3− concentrations in rime and snow were measured at 10 Czech plots situated in borderline mountains in 2009–2011 winters. The results were put in context with data-driven geostatistical modelling results of annual wet vertical and horizontal deposition. Our hypotheses were that: (i) rime and snow would be more polluted in the highly industrialized north than in the south, (ii) the N-NO3− concentrations would differ in the three winters studied, and (iii), that N-NO3− rime deposition is not negligible in Central European mountain ranges. Our results indicated that winter N-NO3− concentrations were significantly higher in rime than in snow and that there were much larger between-site differences in N-NO3− concentrations for rime than for snow. Relatively large differences were found between individual years. Atmospheric input of N-NO3− in winter was dominated by vertical deposition, i.e., snow. Modelled results showed that mean winter rime deposition corresponded to about 6–25 %, and mean winter snow deposition made up 25–72.5 % of mean annual N-NO3− wet-only deposition. Model N-NO3−occult deposition estimated from throughfall and total (wet and dry) deposition is highly uncertain, however: N throughfall is not a relevant proxy for estimation of realistic total N deposition due to N exchange between the tree canopy and atmosphere.
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•N_NO3− measured in rime and snow at ten plots compared to modelled deposition.•Winter N_NO3− concentrations significantly higher in rime than in snow.•Between site differences in N_NO3− concentrations much larger for rime than snow.•Relatively large differences between years.•Atmospheric input of N_NO3− in winter dominated by vertical deposition (snow).•Mean rime deposition makes about 6–25 % of mean annual N_NO3− wet-only deposition.
Microplastics in rime-ice observed at a remote mountain NAGAFUCHI, Osamu; NAKAZAWA, Koyomi; SHINOZUKA, Ken’ichi
Journal of the Japanese Society of Snow and Ice,
2022/01/15, 2022-1-15, Letnik:
84, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Microplastics (MPs) have been found not only atmospheric deposition in urban areas, but also the snow obtained from Mt. Everest and Arctic, sediments in the deepest part of the Mariana ...Trench.However, the pathway of the MPs to the atmosphere has not been clear. Here, we collected rime-ice and snowpack samples at Mt. Karakunidake in winter season to clarify the existence of atmospheric MPs deposition in rime-ice and snowpack, using FTIR imaging. MPs were detected in the range of 8.34×106 m－3 to 12.3×106 m－3 in rime-ice, and 1.34×106 m－3 in snowpack. The concentration of MPs in rime-ice was about 10 times higher than that in snowpack. The particle size distribution of MPs in rime-ice showed more than 90.1 % of MPs were present below 100 µm fraction, and most of them were fragments. The predominant plastic found in the samples is polyethylene (as fragments). Mt. Karakunidake is isolated from the impact of human activities. This indicates that MPs can be transported from other area.
This study investigated the relative role of sub-syllabic components (initial consonant, rime, and tone) in spoken word recognition of Mandarin Chinese using an eye-tracking experiment with a visual ...world paradigm. Native Mandarin speakers (all born and grew up in Beijing) were presented with four pictures and an auditory stimulus. They were required to click the picture according to the sound stimulus they heard, and their eye movements were tracked during this process. For a target word (e.g.,
"candy"), nine conditions of competitors were constructed in terms of the amount of their phonological overlap with the target: consonant competitor (e.g.,
"ladder"), rime competitor (e.g.,
"wave"), tone competitor (e.g.,
"cow"), consonant plus rime competitor (e.g.,
"soup"), consonant plus tone competitor (e.g.,
"head"), rime plus tone competitor (e.g.,
"sheep"), cohort competitor (e.g.,
"tower"), cohort plus tone competitor (e.g.,
"peach"), and baseline competitor (e.g.,
"snow"). A growth curve analysis was conducted with the fixation to competitors, targets, and distractors, and the results showed that (1) competitors with consonant or rime overlap can be adequately activated, while tone overlap plays a weaker role since additional tonal information can strengthen the competitive effect only when it was added to a candidate that already bears much phonological similarity with the target. (2) Mandarin words are processed in an incremental way in the time course of word recognition since different partially overlapping competitors could be activated immediately; (3) like the pattern found in English, both cohort and rime competitors were activated to compete for lexical activation, but these two competitors were not temporally distinctive and mainly differed in the size of their competitive effects. Generally, the gradation of activation based on the phonological similarity between target and candidates found in this study was in line with the continuous mapping models and may reflect a strategy of native speakers shaped by the informative characteristics of the interaction among different sub-syllabic components.
In this study, five ice shapes generated at NASA Glenn's Icing Research Tunnel (IRT) are simulated at multiple angles of attack 1. These geometries target different icing environments, both ...early-time and longer-duration glaze and rime ice exposure events, including a geometry that results from using a thermal ice-protection system. Using the laser-scanned geometries, detailed representations of the three-dimensional ice geometries are resolved on the grid and simulated using wall-modeled LES. Integrated loads (lift, drag, and moment coefficients) and pressure distributions are compared against experimental measurements in both clean and iced conditions for several angles of attack in both pre- and post-stall regions. The relevant comparisons to the experimental results show that qualitative and acceptable quantitative agreement with the data is observed across all geometries.
Glaze ice formations exhibit larger and highly nonuniform ice features, such as ‘horns’, in contrast to rime ice formations characterized by smaller, uniformly distributed roughness elements. In wall-modeled LES, it was observed that larger roughness scales in the glaze ice that trigger transition can be accurately resolved. Therefore, it is possible for WMLES to accurately capture the aerodynamics of glaze ice shapes without the need for additional modeling. In contrast, rime ice geometries required additional resolution to accurately represent the aerodynamic loads. This study demonstrates the effectiveness of the wall-modeled LES technique in simulating the complex aerodynamic effects of iced airfoils, providing valuable insights for aircraft design in icing environments and highlighting the importance of accurately representing ice geometries and roughness scales in simulations.
We present the results of a short-term longitudinal study. Children in the early stages of learning to read (5 and 6 year olds) were administered three different tasks (deletion, oddity, and ...detection) tapping awareness of four phonological units (initial phoneme, final phoneme, onset, and rime). Measures of phoneme awareness were the best concurrent and longitudinal predictors of reading skill with onset-rime skills making no additional predictive contribution once phonemic skills were accounted for. The findings are related to recent controversy over the role of large versus small phonological units as predictors of children's reading skills.
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