Accuracy associated with MRI radiomics capabilities from the lean meats and hepatocellular carcinoma

Understanding the dynamics of harmful algal blooms is important to protect the aquatic ecosystem in regulated rivers and secure human health. In this study, artificial neural network (ANN) and support vector machine (SVM) models were used to predict algae alert levels for the early warning of blooms in a freshwater reservoir. Intensive water-quality, hydrodynamic, and meteorological data were used to train and validate both ANN and SVM models. The Latin-hypercube one-factor-at-a-time (LH-OAT) method and a pattern search algorithm were applied to perform sensitivity analyses for the input variables and to optimize the parameters of the models, respectively. The results indicated that the two models well reproduced the algae alert level based on the time-lag input and output data. In particular, the ANN model showed a better performance than the SVM model, displaying a higher performance value in both training and validation steps. Furthermore, a sampling frequency of 6- and 7-day were determined as efficient early-warning intervals for the freshwater reservoir. Therefore, this study presents an effective early-warning prediction method for algae alert level, which can improve the eutrophication management schemes for freshwater reservoirs.In this study, we used xanthate to modify two waste biomass materials (corn cob and chestnut shell) and prepared them as biosorbents in one step for effectively removing Pb(II) from aqueous solutions containing only Pb(II) or Pb(II), Cu(II) and Cd(II). The two biosorbents were characterized by SEM, EDS, FTIR and Zeta potential analysis, and the results of the characterization were used to explore the adsorption mechanism of Pb(II) on biosorbents. We compare the Pb(II) removal ability of the two biosorbents and the investigated factors that affect Pb(II) removal. The results show that the adsorption capacity of xanthate modified corn cob (X-CC) and xanthate modified chestnut shell (X-CS) for Pb(II) is related to pH, reaction time, temperature and initial concentrations of both adsorbent and adsorbate. The adsorption of Pb(II) on X-CC and X-CS follows Langmuir isotherm equation and quasi-secondary kinetic equation, and their fitted qm values are 166.39 and 124.84 mg g-1, respectively. The analysis shows that the biosorbent has high selectivity to Pb(II) rather than Cu(II) and Cd(II), and still maintains a high removal rate of Pb(II) in actual wastewater. selleck kinase inhibitor The biosorbents remove metal ions mainly through ion exchange reaction and the functional group in the material complexes with the metal to form micro-precipitation. The high adsorption capacity in aqueous solution and low costs in the manufacturing process of the present biosorbents ensure that they have great potential in practical applications for treating heavy-metal contaminated surface water.Pharmaceuticals and their by-products are recalcitrant contaminants in water. Moreover, the high consumption of these drugs has many detrimental effects on body waters and ecosystems. In this timely review, the advances in molecular engineering of layered double hydroxides (LDH) that have been used for the removal of pharmaceutical pollutants are discussed. The approach starts from the strategies to obtain homogeneous synthesis of LDH that allow the doping and/or surface functionalization of different metals and oxides, producing heterojunction systems as well as composites with carbon and silica-based materials with high surface area. Adsorption is considered as a traditional removal of pharmaceutical pollutants, so the kinetic and mechanism of this phenomenon are analyzed based on pH, temperature, ionic strength, in order to obtain new insights for the formation of multifunctional LDH. Advanced oxidation methodologies, mainly heterogeneous photocatalysis and Fenton-like processes, stand out as the more effitedly, the LDH have a unique flexible structure with adsorption capacity and catalytic activity, facts that explain the important reasons for their extensive use in the environmental remediation of pharmaceutical pollutants from water.Contamination-based obsessive-compulsive disorder (OCD) is thought to develop and be maintained by excessive propensity to experience disgust, particularly in response to perceived contaminants, and dysfunctional threat appraisals pertaining to illness. The present studies attempted to integrate these lines of research by testing the degree to which contamination-based OCD is associated with individual differences in disgust propensity and sensitivity, affective distress in response to perceived contaminants, and perceived threat of illness. In Study 1, a convenience sample of 185 adults completed self-report scales assessing obsessive-compulsive symptoms, disgust propensity and sensitivity, germ aversion, and perceived infectability. Multivariate regression showed that disgust propensity and germ aversion were the only significant predictors of contamination-based obsessions and compulsions. Exploratory analyses suggested that there was a significant indirect effect of disgust propensity on contamination-based obsessions and compulsions via germ aversion. Findings from Study 1 were replicated using a sample of twenty-six obsessive-compulsive participants. Despite the substantially smaller sample, the proportion of the total effects attributable to the mediating effect of germ aversion was comparable, consistent with a significant partial mediation in both samples. These results together suggest that contamination-based OCD symptoms are likely maintained and motivated by basic affective processes.
To compare the efficacy and acceptability of internet-delivered exposure therapy for panic disorder, to multi-component internet-delivered cognitive behavioral therapy (iCBT) that included controlled breathing, cognitive restructuring and exposure.
Participants with panic disorder, with or without agoraphobia, were randomized to internet-delivered exposure therapy (n = 35) or iCBT (n = 34). Both programs were clinician guided, with six lessons delivered over eight weeks. Outcomes included panic disorder and agoraphobia symptom severity, as well as depression symptom severity, functional impairment and days out of role.
Participants in both conditions displayed a large reduction in panic disorder symptom severity (ds >1.30) from pre- to post-treatment. Participants in both conditions displayed medium to large reduction in agoraphobia and depression symptom severity, functional impairment and days out of role. Effects were maintained at three- and six-month follow-up. There was no significant difference between the interventions in clinical outcomes, adherence or treatment satisfaction.