Analysis Of Experiments Research Articles

Simulation studies for methodological research in psychology: A standardized template for planning, preregistration, and reporting.

Simulation studies are widely used for evaluating the performance of statistical methods in psychology. However, the quality of simulation studies can vary widely in terms of their design, execution, and reporting. In order to assess the quality of typical simulation studies in psychology, we reviewed 321 articles published in Psychological Methods, Behavior Research Methods, and Multivariate Behavioral Research in 2021 and 2022, among which 100/321 = 31.2% report a simulation study. We find that many articles do not provide complete and transparent information about key aspects of the study, such as justifications for the number of simulation repetitions, Monte Carlo uncertainty estimates, or code and data to reproduce the simulation studies. To address this problem, we provide a summary of the ADEMP (aims, data-generating mechanism, estimands and other targets, methods, performance measures) design and reporting framework from Morris et al. (2019) adapted to simulation studies in psychology. Based on this framework, we provide ADEMP-PreReg, a step-by-step template for researchers to use when designing, potentially preregistering, and reporting their simulation studies. We give formulae for estimating common performance measures, their Monte Carlo standard errors, and for calculating the number of simulation repetitions to achieve a desired Monte Carlo standard error. Finally, we give a detailed tutorial on how to apply the ADEMP framework in practice using an example simulation study on the evaluation of methods for the analysis of pre-post measurement experiments. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Cluster Perturbation Theory for Core Excited States and Core Ionization Potentials Using Core-Valence Separation.

The development of accurate and fast computational procedures for the ab initio calculation of X-ray spectroscopies is paramount to facilitate theoretical analysis of modern X-ray experiments on molecules. Herein, we present the extension of Cluster Perturbation theory to comprehend the calculation of core excited states and core ionization potentials using the core-valence separation approximation, which has seen widespread success for various quantum chemistry methods. We derive the theoretical framework for introducing core-valence separation into Cluster Perturbation series for excitation energies and display the performance of the methodology in S(D) orbital excitation spaces. The obtained core excitation energies on a test set of medium sized organic molecules show that carbon, nitrogen, and oxygen K-edge excitation energies can be determined with errors below 2 eV relative to the CCSD reference results using the developed CPS(D) excitation energy models which can be used for systems way beyond the reach of conventional CCSD.

Predictive modeling of CO2 capture efficiency using piperazine solutions: a comparative study of white-box algorithms

The urgency to mitigate carbon dioxide (CO2) emissions and combat climate change has spurred the development of effective CO2 capture technologies. One of the industry’s most well-known CO2 collection processes is CO2 absorption utilizing amine solvents. However, designing a successful amine scrubbing system in power plants requires precise prediction of CO2 absorption in aqueous amine solutions under various operating circumstances. Using aqueous piperazine (PZ) solutions for chemical absorption is promising due to the favorable reactivity of PZ with CO2. In this study, a comprehensive evaluation of PZ solution performance in CO2 capturing, employing the white-box algorithms, namely, Genetic Programming (GP), Gene Expression Programming (GEP), and Group Method of Data Handling (GMDH), was performed. Through extensive experimentation and data analysis, several correlations were developed with high and acceptable R2 values, such as 0.933 for GP, 0.949 for GEP, and 0.889 for GMDH, which shows high accuracy and reliability in predicting the CO2 capture efficiency of PZ solutions under varying operating conditions. The results of sensitivity analysis revealed that CO2 partial pressure increased CO2 absorption, while PZ concentration and temperature had negative and decreasing effects. These insights provide essential guidance for optimizing process conditions to enhance the CO2 capture efficiency. Finally, the leverage method was used to assess the reliability of both experimental and predicted data from white-box algorithms. This analysis identified potential outliers and validated the accuracy of the model’s predictions, enhancing the credibility of developed correlations and demonstrating the robustness of the approach.

Triterpenoid saponins from the fruit pulp of Tetrapleura tetraptera (Fabaceae)

Tetrapleura tetraptera fruit, used as spice in West Africa was studied chemically; five previously undescribed triterpenoid saponins 1–5 and four known compounds 6–9 were isolated from the n-Butanol fraction. The chemical structures of all nine isolates were determined by comprehensive analysis of HRMS, 1D & 2D NMR experiments and by comparison with data in the literature. All nine compounds were evaluated for antibacterial activity by the broth microdilution through the rapid p-iodonitrotetrazolium chloride (INT) colorimetric technique. The results showed that only compounds 5 (MIC = 64 µg/mL against P. aeruginosa and P. stuartii) and 8 (MIC = 64 µg/mL against E. coli) exhibited moderate antibacterial activity. The rest of the compounds displayed weak antibacterial activity against the tested organisms. Molecular docking studies was used to comprehend antibacterial activities.

Numerical and Constitutive Analysis of Granular Column Collapse Experiments Under Reduced-Gravity Conditions

Numerical and Constitutive Analysis of Granular Column Collapse Experiments Under Reduced-Gravity Conditions

The Language That Drives Engagement: A Systematic Large-scale Analysis of Headline Experiments

We use a large-scale data set of thousands of field experiments conducted on Upworthy.com , an online media platform, to investigate the cognitive, motivational, affective, and grammatical factors implementable in messages that increase engagement with online content.

In Situ Experimental Analysis and Performance Evaluation of Airport Precast Concrete Pavement System Subjected to Environmental and Moving Airplane Loads.

The behavior of airport precast concrete pavement (APCP) involving new design and construction concepts was experimentally analyzed under environmental and moving airplane loads, and the long-term performance of the APCP was evaluated using fatigue failure analysis. The strain characteristics and curling behavior of the APCP under environmental loads were comprehensively analyzed. The APCP slabs exhibited a pronounced curling phenomenon similar to conventional concrete pavement slabs. The dynamic response of the APCP subjected to impact loads was analyzed by performing heavy weight deflectometer tests. The test results confirmed that the vertical deformation of the APCP was small and within the typical range of vertical deformation of conventional concrete pavement. The dynamic strain response of the APCP under moving airplane loads was then analyzed and the strain variation during day and night times was compared. The strains during the day were found to be significantly larger than those at night under airplane loads because of the curling phenomenon of the APCP slabs. Finally, the long-term performance of the APCP was evaluated using fatigue failure analysis based on the obtained behavior. Even using the most conservative fatigue failure prediction model, the service life of the APCP was ascertained to be more than 30 years. Based on the overall results of this study, it is concluded that the APCP, which is designed to reduce slab thickness by placing reinforcing bars in the slabs via reinforced concrete structural design, exhibits typical behavior of concrete pavements and can be successfully applied to airport pavement rehabilitation.

Locally increased dysferlin expression improves left-ventricular function by stabilizing membrane nanodomains of cardiomyocytes in the myocardial infarction border zone

Abstract Introduction Dysferlin, a transmembrane protein with multiple Ca2+-binding C2-domains, is expressed in the sarcolemma and vesicle membranes of striated muscle cells. Upon Ca2+ entry, Dysferlin is thought to mediate vesicle fusion and membrane repair events in order to rapidly seal sarcolemmal lesions. Dysferlin mutations are associated with progressive muscular dystrophies and dilated cardiomyopathy. However, the precise role of Dysferlin in protection of membrane nanodomains in ventricular myocytes (VMs) after myocardial infarction (MI) remains elusive. Purpose We hypothesized that Dysferlin is crucial to prevent VMs from loss-of-function and cell death by stabilizing membrane nanodomains like the transverse-axial tubule (TAT) system and the intercalated disc (ICD) cell-cell contact sites post-MI. Methods and Results 1 week post-MI induced by LAD artery ligation, investigator-blinded echocardiography revealed increased infarct sizes and decreased left-ventricular (LV) ejection fraction of Dysferlin-knockout (KO) vs. WT mice (mean±SEM: 21±2 vs. 28±2%, n=20/30 mice, P<0.05). Immunoblotting of WT LV tissue lysates showed an upregulated Dysferlin expression to 148% compared to sham-operated controls. Importantly, immunohistology identified a maximal Dysferlin expression of 230% in the MI border zone that faces a high ischemic and mechanical stress. Hence, we used data-independent mass spectrometry (DIA-MS) to analyse the proteomic profile of the infarction zone, border zone and remote zone from WT vs. KO hearts 1 week post-MI (each n = 5 mice). Overall, we reproducibly quantified 4360 proteins across all LV samples, identifying local genotype-specific proteotypes post-MI. In WT vs. KO samples, DIA-MS revealed 725 differentially abundant proteins in the zone pairwise comparison, highlighting a vital role of Dysferlin for LV remodelling post-MI. In addition, superresolution stimulated emission depletion (STED) microscopy was applied to study the subcellular localization and function of Dysferlin in the MI border zone. Here, we observed VMs with disrupted TAT endomembrane networks and significantly extended ICD regions. Interestingly, STED imaging revealed Dysferlin clusters that highly decorated residual TAT structures and interdigitated ICD membrane folds in the MI border zone. DIA-MS analysis of anti-Dysferlin co-imunoprecipitation experiments from WT vs. KO LV tissues characterized the cardiac interactome of Dysferlin, confirming interactions with proteins of the TAT system and the gap junction hemichannel Connexin-43. Conclusions Our data demonstrate Dysferlin as an endogenous membrane repair protein necessary to stabilize sarcolemmal nanodomains in the MI border zone. Dysferlin not only prevents from loss of TAT structures, but also compensates for increased mechanical stress at the ICDs. Hence, Dysferlin emerges as a novel therapeutic target to control membrane integrity in VMs to prevent from loss-of-function and cell death post-MI.

Video Generative AI in Digital Marketing: A SWOT Analysis on E-Commerce

Artificial Intelligence (AI) is reshaping the way various business processes are performed, most rapidly in digital marketing, due to its advanced computational capabilities. ECommerce companies are in advantageous position to adopt and reap the benefits of AI for many reasons including the readily available computational infrastructure and big data related to their users and processes. Meanwhile, big tech companies and startups are competing to create and improve generative AI models, that create high-definition videos based on inputs in the form of text, image or videos. The current research specifically aims to analyse the video outputs of various video generating AI models available for digital marketing purposes in ecommerce businesses and to rationally analyse how those video generative AI models benefit or affect e-commerce companies. To meet the research objectives, mixed methodologies of experimentation and content analysis were deployed. It was observed that the video outputs from the tested models were not yet suitable for digital marketing and appeared underdeveloped. Additionally, the SWOT analysis revealed advantages like low costs, alongside concerns such as intellectual property issues.

Modelling and Transmission Characteristics Analysis of APU Pneumatic Servo System

The auxiliary power unit (APU), which is a compact gas turbine engine, is employed to provide a stable compressed air supply to the aircraft. This compressed air is introduced into the various aircraft components via the pneumatic servo system, thereby ensuring the normal operation of the aircraft’s systems. The objective of this study is to examine the impact of parameter variation on the transmission characteristics of an APU pneumatic servo system, with a particular focus on the aerodynamic moment associated with the operating process of a butterfly valve. To this end, a mathematical model of the pneumatic servo system has been developed. The accuracy of the mathematical model was verified by means of numerical simulation and comparative analysis of experiments. The simulation model was established in the Matlab/Simulink environment. Furthermore, the effects of throttling area ratio, fixed throttling hole diameter, rodless chamber volume of actuator cylinder and gas supply temperature on the transmission characteristics of the system were discussed in greater detail. The findings of the research indicate that the throttle area ratio is insufficiently sized, which results in a deterioration of the system’s linearity. Conversely, an excessively large throttle area ratio leads to a reduction in the controllable range of the load axis and is therefore detrimental to the servo mechanism of the flow control. An increase in the diameter of the fixed throttling hole or a decrease in the volume of the rodless cavity of the actuator cylinder facilitates a rapid change in flow rate within the rodless cavity and an increase in the response speed of the load-rotating shaft of the servomechanism. An increase in the temperature of the gas supply from 30 °C to 230 °C results in a reduction in the response time of the system by a mere 0.2 s, which has a negligible impact on the transmission characteristics of the system.

Expanding and improving analyses of nucleotide recoding RNA-seq experiments with the EZbakR suite.

Nucleotide recoding RNA sequencing methods (NR-seq; TimeLapse-seq, SLAM-seq, TUC-seq, etc.) are powerful approaches for assaying transcript population dynamics. In addition, these methods have been extended to probe a host of regulated steps in the RNA life cycle. Current bioinformatic tools significantly constrain analyses of NR-seq data. To address this limitation, we developed EZbakR, an R package to facilitate a more comprehensive set of NR-seq analyses, and fastq2EZbakR, a Snakemake pipeline for flexible preprocessing of NR-seq datasets, collectively referred to as the EZbakR suite. Together, these tools generalize many aspects of the NR-seq analysis workflow. The fastq2EZbakR pipeline can assign reads to a diverse set of genomic features (e.g., genes, exons, splice junctions, etc.), and EZbakR can perform analyses on any combination of these features. EZbakR extends standard NR-seq mutational modeling to support multi-label analyses (e.g., s 4 U and s 6 G dual labeling), and implements an improved hierarchical model to better account for transcript-to-transcript variance in metabolic label incorporation. EZbakR also generalizes dynamical systems modeling of NR-seq data to support analyses of premature mRNA processing and flow between subcellular compartments. Finally, EZbakR implements flexible and well-powered comparative analyses of all estimated parameters via design matrix-specified generalized linear modeling. The EZbakR suite will thus allow researchers to make full, effective use of NR-seq data.

Experimental Study on Human Kinetic Energy Harvesting with Wearable Lifejackets to Assist Search and Rescue

This study explores the integration of a human kinetic energy-harvesting mechanism into lifejackets to address the energy needs of aid search and rescue operations in aquatic environments. Due to the limited data on the movement patterns of drowning individuals, a human motion model has been developed to identify optimal design parameters for energy harvesting. This model is developed from computer vision analysis of underwater footage and motion capture laboratory experiments and is used to quantify the potential for power generation. The field testing experiment is conducted underwater, replicating the environment used for footage collection and analysis for the modelling. During the field testing, the participant wears a lifejacket integrated with the energy-harvesting device. Field testing data are then collected to verify the model. The efficacy of this approach is demonstrated with observed power outputs ranging from 0 mW to 754 mW in simulations and experiments. Despite challenges such as the “dead zone” in a drowning person’s motion, the success of the experiments underscores the potential of the proposed energy-harvesting mechanism to efficiently harness the kinetic energy generated by a drowning person’s movements. This study contributes to the development of sustainable, energy-efficient solutions for search and rescue operations, particularly in remote and challenging aquatic environments.

Quasi-static and dynamic responses of gradient hexachiral auxetics: Experimental and numerical analysis

In the current paper, the mechanical responses of polymer gradient hexachiral auxetic metamaterials were experimentally and numerically investigated under quasi-static and intermediate strain rate loadings. Five gradient design strategies were explored, including uniform, positive, negative, center positive, and center negative gradients. The deformation/failure mechanism, Poisson's ratio, and energy absorption capability were experimentally analyzed, together with the effects of impact velocity and gradient distribution. Experimental results revealed that the gradient design can mitigate the shear deformation of hexachiral auxetics, which efficiently remain its negative Poisson's ratio effect under dynamic loading. Compare with the quasi-static loading, earlier failure of auxetics was observed under dynamic loads due to the strain rate and inertial effect, which diluted their negative Poisson's ratio effect and energy absorption capability. Among the designs, auxetics with negative gradient configurations showed the best energy absorption under dynamic loading. Numerical analysis further supported the experimental findings and provided insights into the influence of geometric parameters. It shows that thicker configurations and non-uniform node gradient series with coefficients of 1.15 (positive, center positive) and 0.87 (negative, center negative) provided optimal energy absorption under the dynamic loading. This work offers profound insights into enhanced performance mechanisms and provides avenues for optimizing structural design of auxetic metamaterials.

STAREG: Statistical replicability analysis of high throughput experiments with applications to spatial transcriptomic studies.

Replicable signals from different yet conceptually related studies provide stronger scientific evidence and more powerful inference. We introduce STAREG, a statistical method for replicability analysis of high throughput experiments, and apply it to analyze spatial transcriptomic studies. STAREG uses summary statistics from multiple studies of high throughput experiments and models the the joint distribution of p-values accounting for the heterogeneity of different studies. It effectively controls the false discovery rate (FDR) and has higher power by information borrowing. Moreover, it provides different rankings of important genes. With the EM algorithm in combination with pool-adjacent-violator-algorithm (PAVA), STAREG is scalable to datasets with millions of genes without any tuning parameters. Analyzing two pairs of spatially resolved transcriptomic datasets, we are able to make biological discoveries that otherwise cannot be obtained by using existing methods.

B-162 Evaluation of two commercially available stable isotope labeled whole-protein infliximab as internal standard for a clinical infliximab LC-MS/MS assay

Abstract Background Liquid chromatography tandem mass spectrometry (LC-MS/MS) based quantitation of infliximab has been successfully introduced in the clinical laboratory for therapeutic drug monitoring in recent years. Although stable isotope labeled (SIL)-peptide or non-labeled analog protein internal standards have been utilized, SIL-whole protein infliximab is generally considered to be the ideal internal standard for the correction of variations during sample preparation and analysis. In this study, we compared two commercially available SIL infliximab proteins, Sigma SILu™MAb and Promise Proteomics, for use in a clinical infliximab assay. Methods Both labeled infliximab proteins incorporate [13C6, 15N4]-arginine and [13C6, 15N2]-lysine in their sequence and are designed for use as an internal standard for LC-MS/MS based quantitative analysis of infliximab. For the comparison of their performance, a laboratory-developed LC-MS/MS clinical method was utilized. Linearity at 6 levels in triplicate with Remicade and 3 biosimilars (-abda, -axxq, and -dyyb), intra-assay precision at 2 levels (n=10/level), and method comparison (n=15) experiments were performed using each labeled infliximab as the internal standard. For sample preparation, internal standard was mixed with the serum sample, followed by protein precipitation with ammonium sulfate, protein denaturation, and tryptic digestion. The peptides YASESMSGIPSR (YASE) from infliximab and YASESMSGIPSR [13C6, 15N4] (SIL-YASE) from labeled infliximab were monitored by LC-MS/MS (Transcend TLX and TSQ Atlis, Thermo Scientific) and utilized for the quantitation of infliximab. Results For the linearity experiment (1-50 µg/mL), while utilizing the Promise Proteomics internal standard to assay had an accuracy range of 103.4% to 114.1% for Remicade, 100.6% to 108.2% for Infliximab-axxq, 103.0% to 110.9% for Infliximab-abda, 102.7% to 108.3% for Infliximab-dyyb. For the Sigma SILu™Mab SIL infliximab, the accuracy range was 92.1% to 99.6% for Remicade, 94.5% to 107.2% for Infliximab-axxq, 99.0% to 104.2% for Infliximab-abda, and 105.1% to 112.0% for Infliximab-dyyb. The mean overall error for Remicade and biosimilars was 0.203 µg/mL (2.0%) for Sigma SILu™Mab SIL infliximab and 0.193 µg/mL (2.0%) for Promise Proteomics internal standardization. Intra-day precision using each SIL infliximab was evaluated with Remicade at low and high levels (5 and 20 µg/mL). Using Promise Proteomics, the coefficient of variation (CV) was 2.8 and 2.2%, while using Sigma SILu™Mab the precision was 6.8 and 6.5% for the low and high levels, respectively. The regression analysis for the method comparison experiment had a correlation coefficient (r) of 0.9996 with a slope of 1.050 (95% confidence interval, 1.030-1.070) and intercept of -0.318 (95% confidence interval, -0.842 to 0.205). Conclusions The mean overall error for the linearity experiment was the same using Sigma SILu™Mab or Promise Proteomics as the internal standard. The Promise Proteomics product demonstrated a lower intra-assay CV compared to the Sigma SILu™Mab. The 2 products displayed a strong correlation during the method comparison experiment. Both Sigma SILu™Mab and Promise Proteomics labeled standards showed acceptable performance as an internal standard for LC-MS/MS based quantitative analysis of infliximab. Having both products available increases the robustness of LC-MS/MS clinical assays in the event of supply issues.

NMR-Based Stable Isotope Tracing of Cancer Metabolism.

NMR is widely used for metabolite profiling (metabolomics, metabonomics) particularly of various readily obtainable biofluids such as plasma and urine. It is especially valuable for stable isotope tracer studies to track metabolic pathways under control or perturbed conditions in a wide range of cell models as well as animal models and human subjects. NMR has unique properties for utilizing stable isotopes to edit or simplify otherwise complex spectra acquired in vitro and in vivo, while quantifying the level of enrichment at specific atomic positions in various metabolites (i.e., isotopomer distribution analysis).In this protocol, we give an overview with specific protocols for NMR-based stable isotope-resolved metabolomics, or SIRM, with a workflow from administration of isotope-enriched precursors, via sample preparation through to NMR data collection and reduction. We focus on indirect detection of common NMR-active stable isotopes including 13C, 15N, 31P, and 2H, using a variety of 1H-based two-dimensional experiments. We also include the application and analyses of multiplex tracer experiments.

A-114 Protective effect of leukocytes in preventing Cold Induced Hyperkalemia

Abstract Background Cellular components, especially PRBC units stored in blood banks show progressively increasing extracellular potassium because ATP dependent Na+/ K+ATPase that pumps potassium into cells is slowed at cold but K+ leak continues. The extracellular potassium levels in these units may go well above the range of linearity of some electrolyte analyzers and may need dilution to measure accurately. We wanted to see effect of Leukocytes on this progressive cold-storage hyperkalemia. Buffy-Coat, the leukocyte rich layer of spun whole blood, a discard product of blood banks using buffy-coat-method for components, was used as the source of leukocytes. Methods Buffy-Coat-bags (from Terumo Quadruple-bag-set, in CPD) were separated from 32 donations from male donors (with IRB, consent). Eight ABO,Rh compatible pools of four buffy each, were prepared and divided into 2 groups of four pools each:Leukoreduced pools (LR group): Each pool leukoreduced by a clinical-grade commercial Leukofilter (Mitra).Non-leukoreduced pools (NLR group) rich in leukocytes. Potassium/VBG on Cobas B221(Roche), and CBC were done on days 0, 3, 7 on each pool stored at 4oC. Results Potassium was significantly lower in NLR than LR pools on days 3 & 7, and potassium had significant negative correlation with WBC count. Multiple-linear-regression and analysis of additional control experiments consistently showed that independent of days of storage, pH, and Hct, WBC-Count had significant negative correlation with Potassium. Conclusions Preanalytic artefacts like “seasonal-pseudohypokalemia” and pseudohypokalemia in a subset of AMLs (opposite of pseudohyperkalemia in fragile hyperleukocytosis) suggest that leukocytes may be capable of reducing extracellular potassium. Our in-vitro closed-system controlled experiments show that leukocyte-rich/Non-Leuko-Reduced (NLR) pools were relatively protected from hyperkaleimia than filtered leukocyte-poor/Leuko-Reduced (LR) buffy pools, and potassium has significant negative correlation with leukocyte count independent of storage-time, pH & Hct. Though considered otherwise bad/aggravator for “PRBC-storage-lesion”, leukocytes may help abate progressive cold-storage-hyperkalemia.

Analysis of the Mammalian Lipidome by DMS Shotgun Lipidomics.

Shotgun Lipidomics is a robust methodology for the characterization of the lipidome of complex biological samples. This assay is among the most quantitative lipidomics methods and is capable of surveying a wide breadth of lipid subclasses, both neutral and polar. The shortfalls of the technique include limitations in lipid species characterization and computationally demanding data analysis requiring isotopic and isobaric overlap correction. Differential Mobility Spectrometry (DMS) has demonstrated its utility in enabling acyl tail characterization within a Shotgun Lipidomics experiment. Here, we present a workflow for DMS Shotgun Lipidomics that measures 1400 possible lipid species. It utilizes the Shotgun Lipidomics Assistant (SLA) application, an open-source application that supervises the data analysis for an expansive Shotgun Lipidomics experiment.

A Two-Phase Methodology leveraging X-DenseNet for Multi-Organ Segmentation in Abdominal CT Scans

Introduction: Multi organ segmentation (MOS) is crucial for various medical applications such as disease diagnosis, treatment planning, and surgery. Manual segmentation of CT organs is inefficient, laborious and time-consuming, necessitating the development of automated techniques. To address these challenges, automatic techniques based on deep learning models are explored in this field. These techniques require improvements to deal with patient-to-patient variability in organ size, location, and shape. Despite the transformative potential of deep learning techniques, research studies often inadequately address low contrast and overlapping structures within CT scans. This paper proposes a novel two phase methodology to integrate deep learning models and image enhancement strategies. Methods: Our framework contributes in two stages named (a) Optimized Contrast Limited Adaptive Histogram Equalization-Weighted Grey Wolf Optimization (optiCLAHE-Weighted GWO), where the organs contrast is enhanced by employing weighted GWO for CLAHE clip limit selection (b) X-DenseNet architecture, where segmented regions of interest are produced with X-DenseNet model from the enhanced CT. Results: For validation of proposed multi organ segmentation (PMOS) technique, experimentation and comparative analysis with existing models has been conducted on FLARE 22 challenge dataset. The Dice Score (DSC) of liver, aorta and spleen for proposed Multi organ segmentation (PMOS) approach is 90.4%, 99.38% and 98.33% respectively. The mean of Precision (Pre), Accuracy (Acc), F-score and DSC of the proposed approach are 95.05%, 95.55%, 95.29% and 96.06% respectively.

Bimetal-organic framework derived single-atom-like Co/Fe catalysts for peroxydisulfate activation: The dual amplification of radical and nonradical pathways

A novel single-atom-like Co/Fe catalyst (i.e., Co/Fe-N-C) was synthesized by pyrolysis of a Zn/Co/Fe zeolitic imidazolate framework, and applied in peroxydisulfate (PDS) activation for removal of organic contaminants from wastewater. The isolated diatomic metal-nitrogen sites were detected by X-ray adsorption fine-structure. The degradation of four contaminants (i.e., phenol, bisphenol A, 2,4-dichlorophenol, and N-methyl-2-pyrrolidone) with a concentration of 100 mg/L could be degraded separately within 20 min by the Co/Fe-N-C system with 10 mmol/L of PDS, 0.5 g/L of catalyst dosage, and initial pH of 3. Besides, 79.2 % of phenol could be mineralized in 120 min, and the turn-over frequency value of the catalyst was calculated to be 27.17 min−1, which was higher than the commonly reported homogeneous PS-AOPs. Moreover, the Co/Fe-N-C exhibited high stability (mineralization rate over 70 % after 5 cycles), a wide initial pH range (3−9), and high catalytic performance at 5–20 mmol/L of PDS concentrations. Based on the analysis of radical scavenging experiments and electron spin resonance spectra, the radical and non-radical pathways for PDS activation were proved in the system, and the contribution of phenol degradation by each pathway was clarified.