Logarithm Of Ratio Research Articles

Seismic Attenuation Estimation Using an Enhanced Log Spectral Ratio Method

Seismic attenuation estimation is a significant task for characterizing reservoirs and improving the resolution of seismic data. The logarithmic spectral ratio (LSR) is one of the widely used tools for seismic attenuation estimation. However, how to select a suitable frequency bandwidth for the LSR is a difficult task, especially for field data. Moreover, field data are often contained kinds of noises, which makes seismic attenuation estimation difficult and unstable. We proposed an enhanced LSR (ELSR) workflow to estimate seismic attenuation. First, we built a sparse S-transform (SST) to obtain a sparse time-frequency (TF) spectrum of the analyzed seismic trace. Then, based on the SST spectrum, we introduced an ELSR workflow to estimate seismic attenuation. It should be noticed that we provided an adaptive frequency band selection for the LSR. To demonstrate the effectiveness of the proposed workflow, we apply it on both synthetic and field data. Compared with the results from several traditional attenuation estimation methods, the proposed ELSR provides a more stable and more accurate attenuation estimation result and offers the potentials in improving the resolution of post-stacked seismic data.

Evaluation and performance of satellite-derived bathymetry algorithms in turbid coastal water: a case study of Vengurla rocks

The coastal region bathymetry is increasingly becoming necessary for emerging needs of navigation and development along coasts. Satellite-Derived Bathymetry (SDB) has been examined as a viable alternative for hydrographic surveys for the past few decades to reduce the data acquisition efforts in coastal regions and augmentation of periodic updating of Electronic Navigational Charts (ENCs). The previous studies have applied SDB algorithms in less complex waters due to the limitations of SDB algorithms in turbid and varying shallow waters. This paper analyses three different medium-resolution satellite imagery data to derive bathymetry in a navigably very complex and highly turbid region, Vengurla rocks, situated on the west coast of India. The objective of the study was to evaluate the best suitable technique for SDB in turbid water. The bathymetry product images have been derived using the two most commonly utilized log ratio, and linear ratio transformation; three semi-automated methods, Principal Component Analysis (PCA), Independent Component Analysis (ICA), and ratio transform; and Machine Learning (ML) regression algorithms. Among the applied transform and algorithms, the ML algorithm using 561 nm band data performed the best, resulting in R2 of 0.77, RMSE of 3.4 m, and MAE of 2.8 m. This work established that open source images of sensor OLI/Landsat-8 satellite provide the best results of SDB estimation in complex turbid water by applying ML algorithms. However, extreme turbid and complex regions resulted in more erroneous SDB estimation specifying the need for refining algorithms using bio-optical parameters.

Applying grain-size and compositional data analysis for interpretation of the Quaternary oxbow lake sedimentation processes: Eastern Great Hungarian Plain

Grain size distribution is one of the paleoenvironmental proxies that provide insight statistical distribution of size fractions within the sediments. Multivariate statistics have been used to investigate the depositional process from the grain size distribution. Still, the direct application of the standard multivariate methods is not straightforward and can yield misleading interpretations due to the compositional nature of the raw grain size data. This paper is a methodological framework for grain size data characterization through the centered log ratio transformation and euclidean data, coupled with principal component analysis, cluster analysis, and linear discriminant analysis to examine Quaternary sediments from Tövises bed in the southeast Great Hungarian Plain. These approaches provide statistically significant and sedimentologically interpretable results for both datasets. However, the details by which they supplemented the conceptual model were significantly different, and this discrepancy resulted in a different temporal model of the depositional history.

Number of Positive Lymph Nodes Combined with the Logarithmic Ratio of Positive Lymph Nodes predicts Survival in Patients with Non-Metastatic Larynx Squamous Cell Carcinoma.

Background: Logarithmic ratio of positive lymph nodes (LODDS), number of positive lymph nodes (NPLN), and number of lymph nodes to positive lymph nodes (pLNR) are three lymph node classifications; however, their function in prognosis is unclear.Purpose: To establish and validate an optimal nomogram according to the comparison among the 7th TNM stage of American Joint Committee on Cancer (AJCC) and the three lymph node classifications.Methods: A total of 881 patients from the Surveillance, Epidemiology and End Result (SEER database) with T1-4N1-3M0 in laryngeal squamous cell carcinoma from 2000 to 2018 were involved. The enrolled patients were allocated randomly into a training cohort and a validation cohort. Univariate cox regression analysis and multivariable cox regression analysis were applied to explore the predictors. The Akaike Information Criterion (AIC) and Harrell's concordance index (C-index) were to measure the predictive value and the accuracy of the prognostic models. Moreover, integrated discrimination improvement (IDI) and net reclassification index (NRI) were also used to assess the predictive abilities to models. According to the optimal model, nomograms were established and compared with 7th TNM stage of AJCC via the decision curve analysis.Results: NPLN, LODDS, and pLNR were three predictors for the overall and cancer-specific survival in the larynx squamous cell carcinoma. According to the AIC, C-index, IDI, and NRI, the model of NPLN combined with LODDS was assumed as the optimal prognostic model. Moreover, the decision curve analysis suggested that the nomogram demonstrated a better predictive performance, compared with the 7th AJCC TNM stage.Conclusion: The proposed nomograms we constructed for larynx squamous cell carcinoma has potential in the prediction of patients after surgery.

Statistical Analyses of the Energies of X-Ray Plateaus and Flares in Gamma-Ray Bursts

Abstract Distinct X-ray plateau and flare phases have been observed in the afterglows of gamma-ray bursts (GRBs), and most of them should be related to central engine activities. In this paper, we collect 174 GRBs with X-ray plateau phases and 106 GRBs with X-ray flares. There are 51 GRBs that overlap in the two selected samples. We analyze the distributions of the proportions of the plateau energy E plateau and the flare energy E flare relative to the isotropic prompt emission energy E γ,iso. The results indicate that they well meet the Gaussian distributions and the medians of the logarithmic ratios are ∼−0.96 and −1.39 in the two cases. Moreover, strong positive correlations between E plateau (or E flare ) and E γ,iso with slopes of ∼0.95 (or ∼0.80) are presented. For the overlapping sample, the slope is ∼0.80. We argue that most of X-ray plateaus and flares might have the same physical origin but appear with different features because of the different circumstances and radiation mechanisms. We also test the applicabilities of two models, i.e., black holes surrounded by fractured hyperaccretion disks and millisecond magnetars, on the origins of X-ray plateaus and flares.

Размер и содержание органических частиц в копролитах Aporrectodea caliginosa и Lumbricus rubellus

Размер и содержание органических частиц в копролитах Aporrectodea caliginosa и Lumbricus rubellus

Assessment of iron status in regular blood donors in a tertiary care hospital in Southern India.

Regular blood donation depletes iron stores. The assertion is that the vulnerable donor population requires a predictive standard operative procedure for early detection of iron store depletion, preventing them from developing iron-deficiency anemia. This study aims to study the potential effects of blood donation in the regular donor group using hematological and biochemical estimation of iron status parameters. This was a prospective cross-sectional study on regular blood donors, defined as those who have donated at least 3 times, the last donation being within the last 12 months and continues to donate at least once a year, at a tertiary care teaching hospital in Southern India. The complete blood count (CBC) was performed on the Sysmex coulter, and the red cell indices were calculated. The ferritin and the soluble transferrin receptor (sTfR) assays were performed using Enzyme Immunoassays. The comparison of CBC, serum ferritin, and sTfR assay with donation frequency and time since the last donation was carried out using an independent student's t-test for two groups. The statistical analysis was performed using SPSS for Windows version 20. A total of 323 regular blood donors (6 were females) were included in the study of which they were categorized into three, 211 donors with less than or equal to 10 donations, 84 those who had donated between 11 and 20 times and 28 who had donated more than 20 times. The red cell indices were reduced and different in the groups but not statistically significant except for mean corpuscular volume. About 15% of the study population had a transferrin level of <15 ng/ml. The Ferritin levels showed a statistically significant negative correlation with the number of donations, the correlation coefficient being -0.27. Logarithmic ratios of sTfR/ferritin also correlated with a coefficient of 0.156 with the number of donations and were statistically significant. Our study found that regular blood donors had low iron stores, as shown by ferritin levels and other iron indicators. Using the current guidelines (hemoglobin >12.5 g/dL) for donation, or the red cell indices alone do not reflect the donor's actual iron status.

Atherogenic Index of Plasma Associates With Epicardial Adipose Tissue Volume on Coronary Computed Tomography Angiography

The atherogenic index of plasma (AIP) is a novel biomarker of atherogenic dyslipidaemia (AD) but its relationship with cardiac adipose tissue depots—epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT)—is unknown. We aimed to assess the association of AD with cardiac adipose tissue parameters quantified on coronary computed tomography angiography (CCTA). We studied 161 patients who underwent CCTA between 2008 and 2011 (age 59.0±14.0 yrs). AD was defined as triglyceride (TG)>1.7mmol/L and HDL<1.0mmol/L (n=34). AIP was defined as the base 10 logarithmic ratio of TG to HDL. Plaque burden was assessed using the CT-Leaman score (CT-LeSc). We studied volume and attenuation of EAT (EAT-v and EAT-a) and PCAT (PCAT-v and PCAT-a) on CCTA using semi-automated software. Patients with AD had higher PCAT-v (p=0.042) and EAT-v (p=0.041). AIP was associated with EAT-v (p=0.006), type II diabetes (p=0.009) and male sex (p<0.001), and correlated with CT-LeSc (p=0.040). EAT-v progressively increased across quartiles of AIP (p=0.029). On multivariable analysis, AIP was associated with EAT-v≥52.3cm3, age, male sex and type II diabetes when corrected for traditional risk factors and plaque burden. EAT-v≥52.3cm3 was associated with AIP, age and obesity when corrected for traditional risk factors and plaque burden. AIP is associated with increased EAT volume, but not PCAT-a, after multivariable adjustment. These findings indicate AIP is associated with adverse adipose tissue changes which may increase coronary risk.

Natural Changes in Radiological and Radiomics Features on MRIs of Soft‐Tissue Sarcomas Naïve of Treatment: Correlations With Histology and Patients' Outcomes

Because of long diagnostic intervals, soft-tissue sarcoma (STS) patients can undergo several MRIs before treatments. However, only the latest pre-treatment MRI is used in clinical practice and the natural changes in MRI presentations of STS occurring before any medical procedure remain unknown. To qualitatively and quantitatively depict the natural history of MRI presentations of STS prior to medical intervention, to investigate their prognostic value, and to compare methods to calculate the changes in radiomics features (named delta-radiomics features). Retrospective. Sixty-eight patients with locally advanced histologically proven STS and two pre-treatment contrast-enhanced (CE) MRIs (median age: 64 years, median delay between MRIs: 77 days). Two-dimensional (2D) turbo spin echo (TSE) T1-weighted-imaging (WI) and T2-WI; 2D TSE or 3D gradient echo CE-T1-WI at 1.5T. Radiomics analysis was performed on 2D TSE CE-T1-WI. Three radiologists independently reported morphological features, evaluating changes in STS dimensions, intra-tumoral necrotic and hemorrhagic signals and heterogeneity, and changes in the tumor peritumoral enhancement, edema, and tail sign. After homogenizing the MRIs to account for differences in acquisition parameters, STS were 3D-segmented on both CE-T1-WI MRIs and radiomic features (RFs) were extracted. Changes in RFs between the two MRIs were calculated according to five methods: absolute, absolute/time between MRIs, relative, relative/time between MRIs, and log ratio. Histopathological samples were reviewed to count mitosis and Ki67 immunostaining. Survival data regarding local relapse, metastatic relapse, and disease-related deaths were collected. Reproducibility analysis (using intra-class correlation coefficient and [weighted] kappa), hierarchical clusterings based on changes in RFs, survival analyses (using Cox regressions), and association with histopathology (using Student's t-test, Wilcoxon, or Chi-squared test). A P-value of <0.05 was considered to be statistically significant. There were 15 and 26 local and metastatic progressions, respectively. Average tumor size increase between scans was +39.8%. Metastatic relapse-free survival (MFS) was associated with: increases in size, tumor heterogeneity on T1-WI, T2-WI, and CE-T1-WI, necrotic signal, peritumoral enhancement, and tail sign. Local relapse-free survival (LFS) was associated with: increase in tumor heterogeneity on T1-WI, necrotic signal, hemorrhagic signal and peritumoral edema, and clusters based on the logarithmic changes in RFs (Log-RF). Increase in heterogeneity on CE-T1-WI and Log-RF clusters were independent predictors for MFS and LFS, respectively, in stepwise multivariate Cox regression (hazard ratio [HR]=2.78 and HR=+∞ respectively). Associations were found between changes in necrotic signal, heterogeneity on CE-T1-WI and peritumoral enhancement, and histological markers of proliferation. Changes in MRI presentation of STS before any treatment are frequent, associated with histopathology, and could help in patients' prognostication, in addition to baseline MRI feature. 3 TECHNICAL EFFICACY: Stage 3.

Renal outcomes associated with glucose-lowering agents: Systematic review and meta-analysis of randomized outcome trials

Although the clinical questions of the recent glucose-lowering trials are principally oriented towards preventing macrovascular events, an updated review regarding renal outcome prevention is lacking. We assessed the impact of different antihyperglycemic classes on kidney damage progression. A systematic review and meta-analysis was performed by searching PubMed, Cochrane Collaboration Library, Medline, and previous overviews through June 2021 (any language) for earlier and contemporary glucose-lowering trials, including patients with, but not limited to, type 2 diabetes mellitus vs. placebo or less intense treatment. Incidences of kidney function worsening and macroalbuminuria development was extracted, and risk ratios and 95% confidence intervals (CI) under the random-effects model were calculated. The association between outcome reductions and glycohemoglobin (HBA1c) reductions was investigated through the meta-regression analyses. Among 27 eligible trials (n = 198,532 patients) an averaged HBA1c reduction of 0.6 ± 0.3% was followed by a reduction of 17% (95% CI, 8–25%) in worsening of kidney function, and of 25% (95% CI, 19–32%) in macroalbuminuria. Analog of human glucagon-like peptide 1 (GLP1)-agonists, and sodium-glucose cotransporter (SGLT2)-inhibitors, considered separately, compared with placebo, were associated with a significant reduction of both renal outcomes, at variance with dipeptidyl peptidase 4 (DPP4)-inhibitors, where no outcome change was observed. Logarithmic risk ratios of macroalbuminuria were related to HBA1c reductions, in contrast to the worsening of kidney function related to systolic blood pressure reduction. Worsening of kidney function and macroalbuminuria development were reduced following glucose-lowering. GLP1 agonists and SGLPT2 inhibitors were associated with protection against both outcomes, while DPP4 inhibitors do not provide renal protection.

Change Detection in Water reservoir using Image Fusion and Supervised Classifier

The research provides a method for improving change detection in SAR images using a fusion object and a supervised classification system. To remove noise from the input image, we use the DnCNN denoising approach. The data from the first image is then processed with the mean ratio operator. The log ratio operator is used to process the second image. These two images are fused together using SWT-based image fusion, and the output is sent to a supervise classifier for change detection.

Why do calcareous microfossils preferentially occur in tuffaceous sandstones of the Santa Marta formation (James Ross Island, Antarctica)?

The Santa Marta Formation (James Ross Island, Antarctica) presents one of the most complete Santonian-Campanian high-latitude marine records in the Southern Hemisphere. Recent micropaleontological studies pointed to an unusual preferential preservation of calcareous microfossils, such as foraminifera and nannofossils, in tuffaceous sandstone levels of the Santa Marta Formation. Here we aim to characterize depositional and early diagenetic conditions that influenced preservation of calcareous microfossils within the succession of the Santa Marta Formation (Alpha Member). We used X-ray fluorescence (FRX)-derived elemental ratios, as well as carbonate (CaCO3), total organic carbon (TOC), and total sulfur (TS) contents to characterize sediment properties, as well as X-ray diffraction (XRD)-derived mineralogical analysis. Elemental ratios suggest hydrothermal influence during diagenesis throughout the stratigraphic succession, as indicated by (Fe + Mn)/Ti values > 20. This interpretation is supported by the occurrence of typical low-temperature hydrothermal minerals, such as garronite and heulandite. Contribution of volcanic ashes in the tuffaceous sandstone levels is evidenced by high values of the log (Zr/Ti) ratio, and the presence of volcanogenic minerals. Since stratigraphic levels characterized by the highest abundances and richnesses of calcareous microfossils also present high log (Zr/Ti) values and CaCO3 contents, we hypothesize that the input and subsequent alteration of volcanogenic material (e.g., ashes) acted as a buffer, increasing porewater alkalinity during early diagenesis. Such a chemical mechanism was already described for modern marine sediments deposited under the influence of significant input of volcanogenic materials, and can explain the preferential preservation of calcareous microfossils in tuffaceous sandstones of the Upper Cretaceous Santa Marta Formation.

HIV incidence, viremia, and the national response in Eswatini: Two sequential population-based surveys.

With the highest HIV incidence and prevalence globally, the government of Eswatini started a substantial scale-up of HIV treatment and prevention services in 2011. Two sequential large population-based surveys were conducted before and after service expansion to assess the impact of the national response. Cross-sectional, household-based, nationally representative samples of adults, ages 18 to 49 years, were sampled in 2011 and 2016. We measured HIV prevalence, incidence (recent infection based on limiting antigen ≤1.5 optical density units and HIV RNA ≥1000 copies/mL), viral load suppression (HIV RNA <1000 copies/mL among all seropositive adults) and unsuppressed viremia (HIV RNA ≥1000 copies/mL among all, regardless of HIV status) and assessed for temporal changes by conducting a trend analysis of the log ratio of proportions, using a Z statistic distribution. HIV prevalence remained stable from 2011 to 2016 [32% versus 30%, p = 0.10]. HIV incidence significantly declined 48% [2.48% versus 1.30%, p = 0.01]. Incidence remained higher among women than men [2011: 3.16% versus 1.83%; 2016: 1.76% versus 0.86%], with a smaller but significant relative reduction among women [44%; p = 0.04] than men [53%; p = 0.09]. The proportion of seropositive adults with viral load suppression significantly increased from 35% to 71% [p < .001]. The proportion of the total adult population with unsuppressed viremia decreased from 21% to 9% [p < .001]. National HIV incidence in Eswatini decreased by nearly half and viral load suppression doubled over a five-year period. Unsuppressed viremia in the total population decreased 58%. These population-based findings demonstrate the national impact of expanded HIV services in a hyperendemic country.

Epithelial-Cadherin Expression Is Associated With Better Recurrence-Free and Overall Survival in Invasive Lobular Breast Cancer in Mexican Women.

BackgroundThere are different clinicopathological characteristics that are associated with the prognosis in patients with breast cancer. To date, the prognostic valor of for epithelial cadherin (E cadherin) expression in invasive lobular breast cancer remains unknown.MethodsA retrospective single-center study that included 207 patients with primary invasive lobular breast cancer was conducted. The primary outcome was to report the correlation of the different clinical pathological characteristics including the expression of epithelial-cadherin (E-cadherin) in invasive lobular breast cancer in Mexican women with recurrence-free survival (RFS) and overall survival (OS).ResultsAfter 11 years of follow-up of patients with invasive lobular breast cancer, RFS was 89.4% and OS of 96.1%. The best prognosis in RFS was in patients with negative nodes 95.2% (P = 0.0001) and OS was 98.6-100% (P = 0.0001). Regarding tumor size, an RFS of 98.3% was observed in those measuring ≤ 2 cm (P = 0.0001) and OS of 99.2% (P = 0.0001). Negative Her2 was related to an RFS of 92.1% (P = 0.0001), and had better OS of 98.3% (P = 0.0001). Ki67 proliferation index ≤ 14% was associated with an RFS of 93.2% (P = 0.005). Negative lymph vascular invasion (LVI) increases the RFS of 91.8% (P = 0.032). The rate of positive expression of E-cadherin was associated with an increase in the RFS of 97.4%, with a mean of 128.6 ± 2.4 months (95% confidence interval (CI): 123.75 - 133.45 months) compared to the absence of expression E-cadherin: signal log ratio (SLR) 68.9%, a mean of 95 ± 6 months (95% CI: 83.28 - 106.88 months), P <0.001. When the OS was analyzed, the presence of E-cadherin expression increased the OS of 100% vs. 86.9% with the absence, P = 0.015.ConclusionsThe prognostic impact of the different clinicopathological characteristics known worldwide was confirmed. Results of the analysis in the presented study indicate that positive expression of E-cadherin correlates with an improvement in OS and RFS in invasive lobular breast cancer in Mexican women.

Abstract 14407: Effect of Initial Defibrillation on Chest Compression Artifact in the ECG

Introduction: Chest compressions (CCs) during CPR cause electrical artifacts in the ECG. Prior work has found that the severity of CC artifact, quantified by the signal-to-noise ratio (SNR), affects the diagnostic sensitivity of defibrillator algorithms designed to detect shockable rhythms during CCs. Whether SNR is altered by defibrillation is unknown. We therefore compared SNR before and after defibrillation shocks. Methods: We evaluated patients with out-of-hospital cardiac arrest who received at least 1 defibrillation shock, had subsequent ventricular fibrillation (VF), and had a calculable SNR before and after initial shock. We measured the CC artifact during VF before and after the initial shock (and up to 3 subsequent shocks) using CC amplitude and SNR. CC amplitude was defined as the median peak-to-peak voltage of the ECG during CCs. SNR was calculated as the log ratio of the power of the CC-free VF signal to the power of the estimated noise caused by CC artifact (Figure). Differences in medians before and after the first 4 shocks were evaluated using Wilcoxon signed-rank test with Bonferroni correction (alpha = 0.0125). Results: A total of 192 patients had a calculable SNR during VF before and after initial shock. Of these, the median CC amplitude decreased after the initial shock (0.93 vs. 0.75 mV, p&lt;0.001), and SNR improved (-2.30 vs. -1.07 dB, p=0.004). In contrast to the initial shock, both CC amplitude and SNR did not differ significantly before and after shock 2 (n=107), shock 3 (n=54), or shock 4 (n=32). Conclusion: Measures of CC artifact in the ECG were greater before initial shock than afterward. This could potentially be due to changes in CC characteristics, variations in physical perturbation of the defibrillator electrodes, degradation of VF over time, or effects of tissue electroporation on paddle conductivity and noise. These findings may have implications for selection of decision thresholds in algorithms to detect shockable rhythm during CCs.

NIMG-36. VISUALIZATION OF TUMOR HETEROGENEITY AND PREDICTION OF ISOCITRATE DEHYDROGENASE MUTATION STATUS FOR HUMAN GLIOMAS BY USING MULTIPARAMETRIC PHYSIOLOGIC AND METABOLIC MRI

Abstract Preoperative prediction of isocitrate dehydrogenase mutation status is clinically meaningful, but remains challenging. This study aimed to predict the isocitrate dehydrogenase (IDH) status of gliomas by using the machine learning voxel-wise clustering method of multiparametric physiologic and metabolic magnetic resonance imaging (MRI) and to show the association of the created cluster labels with the glucose metabolism status of the tumors. Sixty-nine patients with diffuse glioma were scanned by pH-sensitive MRI, diffusion-weighted imaging, fluid-attenuated inversion recovery, and contrast-enhanced T1-weighted imaging at 3 T. An unsupervised two-level clustering approach, including the generation of a self-organizing map followed by the K-means clustering, was used for voxel-wise feature extraction from the acquired images. The logarithmic ratio of the labels in each class within tumor regions was applied to a support vector machine to differentiate IDH mutation status. Bootstrapping and leave-one-out cross-validation were used to calculate the area under the curve (AUC) of receiver operating characteristic curves, accuracy, sensitivity, and specificity for evaluating performance. Targeted biopsies were performed for 14 patients to explore the relationship between clustered labels and the expression of key glycolytic proteins determined using immunohistochemistry. The highest prediction performance to differentiate IDH status was found for 10-class clustering, with a mean AUC, accuracy, sensitivity, and specificity of 0.94, 0.91, 0.90, and 0.91, respectively. The tissues with labels 7 + 8 + 9 + 10 showed high expression levels of hypoxia-inducible factor 1-alpha, glucose transporter 3, and hexokinase 2, which are typical of IDH wild-type glioma, whereas those with labels 1 showed low expression of these proteins. Our machine learning model successfully predicted the IDH mutation status of gliomas, and the resulting clusters properly reflected the metabolic status of the tumors.

16p Deletion Involving BCMA Locus Is Frequent and Predominantly Observed with del17p

16p Deletion Involving BCMA Locus Is Frequent and Predominantly Observed with del17p

Light absorption enhancement due to mixing in black carbon and organic carbon generated during biomass burning

We report the direct observation of the light absorption enhancement effect due to the mixing of black carbon (BC) and organic carbon (OC) aerosols generated during biomass combustion. The biomass fuels viz. mango tree wood (Mangifera indica) and dung cake were burned and the dry absorption of the aerosol stream was measured using the 7-wavelength aethalometer. The absorption coefficients were measured for thermally denuded and undenuded aerosols. The measurements provided an enhancement ratio for black carbon in presence of organic carbon at seven different wavelengths. The near-source enhancement ratio for wood and dung cake at 880 nm was found to be 1.35 ± 0.06 and 1.59 ± 0.08, respectively. The enhancement effect was found to increase with the decrease in wavelength for both the fuels, indicating absorption by the brown carbon. The organic coating on the black carbon was estimated using the mie theory modelling. The organic coating factor on the black carbon was found to be 1.37 and 1.69 for wood and dung cake, respectively. The enhancement ratio at 370 nm increased with the increase in the absorption angstrom exponent (AAE). The enhancement ratio depicted negative linear dependence (r = −0.91) on the logarithmic ratio of black carbon and absorption coefficients of brown carbon at 370 nm across both fuels and burn conditions.

Spatial interpolation of coal properties using geographic quantile regression forest

Inaccuracies in spatial modelling of coal properties can impact coal resource and reserve estimates. Geostatistical methods which account for compositional data have previously been recommended as a preferred method for modelling of coal properties. These methods can quantify uncertainty, can use auxiliary information to improve estimates, and ensure that compositional data (such as coal proximate analysis) is modelled in a mathematically consistent way. However, geostatistical methods have drawbacks in that have rigid statistical assumptions about the distribution and stationarity of the target variable and require variogram interpretation which can be onerous when then number of domains and target variables are numerous. Due to these drawback, inverse distance weighting (a simple deterministic method) remains the most popular method for modelling coal properties in Australian resource estimates. To address the drawbacks of geostatistical methods, a machine learning approach based on the quantile regression forest algorithm is proposed as an alternative method to spatially model coal properties. This newly proposed method, accounts for spatial arrangement of data, requires minimal pre-processing steps, can quantify uncertainty and can easily incorporate auxiliary information of various types. To evaluate the performance of this method, the accuracy of predictions of coal proximate analysis properties, and coal density are compared to the predictions of inverse distance weighting and regression kriging. All methods incorporate isometric log ratio transform and back-transform of data in order to account for the compositional nature of coal proximate analysis. Data from an active coal mine in the Bowen Basin, Queensland Australia was used as basis of the results. A unique feature of the mine site in this basin is the presence of intrusion which impacts coal quality properties to various degrees. Using evaluation metrics from leave-one-out cross-validation, this paper demonstrates that quantile regression forest has higher accuracy, lower bias and higher precision than inverses distance weighting across all coal properties. The paper also shows that results of the new method are very similar or better than regression kriging. It is also demonstrated that the prediction maps produced by quantile regression forest could be used to more accurately map out coal impacted by intrusion compared to inverse distance weighting, and that inverse distance weighting overestimates the impact of intrusion and intrusion extent. A drawback of the method compared to inverse distance weighting, is that it is more computationally demanding, less intuitive and is currently not available in existing geological packages.

Meta-Analysis illustrates possible role of lipopolysaccharide (LPS)-induced tissue injury in nasopharyngeal carcinoma (NPC) pathogenesis.

Nasopharyngeal carcinoma (NPC) is a cancer of epithelial origin with a high incidence in certain populations. While NPC has a high remission rate with concomitant chemoradiation, recurrences are frequent, and the downstream morbidity of treatment is significant. Thus, it is imperative to find alternative therapies. We employed a Search Tag Analyze Resource (STARGEO) platform to conduct a meta-analysis using the National Center for Biotechnology's (NCBI) Gene Expression Omnibus (GEO) to define NPC pathogenesis. We identified 111 tumor samples and 43 healthy nasopharyngeal epithelium samples from NPC public patient data. We analyzed associated signatures in Ingenuity Pathway Analysis (IPA), restricting genes that showed statistical significance (p<0.05) and an absolute experimental log ratio greater than 0.15 between disease and control samples. Our meta-analysis identified activation of lipopolysaccharide (LPS)-induced tissue injury in NPC tissue. Additionally, interleukin-1 (IL-1) and SB203580 were the top upstream regulators. Tumorigenesis-related genes such as homeobox A10 (HOXA10) and prostaglandin-endoperoxide synthase 2 (PTGS2 or COX-2) as well as those associated with extracellular matrix degradation, such as matrix metalloproteinases 1 and 3 (MMP-1, MMP-3) were also upregulated. Decreased expression of genes that encode proteins associated with maintaining healthy nasal respiratory epithelium structural integrity, including sentan-cilia apical structure protein (SNTN) and lactotransferrin (LTF) was documented. Importantly, we found that etanercept inhibits targets upregulated in NPC and LPS induction, such as MMP-1, PTGS2, and possibly MMP-3. Our analysis illustrates that nasal epithelial barrier dysregulation and maladaptive immune responses are key components of NPC pathogenesis along with LPS-induced tissue damage.