bluuebunny/crossref_metadata_2025_split huggingface dataset:
Distortionless, free‐breathing, and respiratory resolved 3D diffusion weighted imaging of the abdomen
Authors: Lee Philip K. , Zhou Xuetong , Wang Nan , Syed Ali B. , Brunsing Ryan L. , Vasanawala Shreyas S. , Hargreaves Brian A. 
Published: May 2024

AbstractPurposeAbdominal imaging is frequently performed with breath holds or respiratory triggering to reduce the effects of respiratory motion. Diffusion weighted sequences provide a useful clinical contrast but have prolonged scan times due to low signal‐to‐noise ratio (SNR), and cannot be completed in a single breath hold. Echo‐planar imaging (EPI) is the most commonly used trajectory for diffusion weighted imaging but it is susceptible to off‐resonance artifacts. A respiratory resolved, three‐dimensional (3D) diffusion prepared sequence that obtains distortionless diffusion weighted images during free‐breathing is presented. Techniques to address the myriad of challenges including: 3D shot‐to‐shot phase correction, respiratory binning, diffusion encoding during free‐breathing, and robustness to off‐resonance are described.MethodsA twice‐refocused, M1‐nulled diffusion preparation was combined with an RF‐spoiled gradient echo readout and respiratory resolved reconstruction to obtain free‐breathing diffusion weighted images in the abdomen. Cartesian sampling permits a sampling density that enables 3D shot‐to‐shot phase navigation and reduction of transient fat artifacts. Theoretical properties of a region‐based shot rejection are described. The region‐based shot rejection method was evaluated with free‐breathing (normal and exaggerated breathing), and respiratory triggering. The proposed sequence was compared in vivo with multishot DW‐EPI.ResultsThe proposed sequence exhibits no evident distortion in vivo when compared to multishot DW‐EPI, robustness to B0 and B1 field inhomogeneities, and robustness to motion from different respiratory patterns.ConclusionAcquisition of distortionless, diffusion weighted images is feasible during free‐breathing with a b‐value of 500 s/mm2, scan time of 6 min, and a clinically viable reconstruction time.
Tetraspanin immunoassay for the detection of extracellular vesicles and renal cell carcinoma
Authors: Khan Misba , Islam Md. Khirul , Rahman Mafiur , Dhondt Bert , Quintero Ileana , Puhka Maija , Jaakkola Panu M. , Lamminmäki Urpo , Leivo Janne 
Published: May 2024

AbstractHalf of patients with renal cell carcinoma (RCC) develop metastases. New and noninvasive biomarkers are needed for the diagnosis of RCC. The study aims to develop an EV‐based assay for the detection of RCC using a highly sensitive nanoparticle‐aided time‐resolved fluorescence immunoassay (NP‐TRFIA). To confirm the presence of tetraspanins on EVs, size exclusion chromatography is used to separate EV‐ and PE‐fractions from RCC4, 786‐O, and HEK293 cell lines. EV‐ and PE‐fractions are quantified using NP‐TRFIA assays established for CD9, CD63, CD81, and CD151. Tetraspanins are measured from RCC CCM and serum samples of RCC (n = 14), benign (n = 17), and healthy (n = 9) individuals. Among the tetraspanins, CD63 exhibits 3‐5‐fold higher expression on RCC4 and 786‐O CCM compared to HEK293. A sandwich CD63‐CD63 assay demonstrates significant discrimination of RCC patients from benign (p = 0.0003), and healthy (p = 0.005) individuals, respectively. Similarly, the CD81‐CD81 assay also enables significant separation of RCC patients compared to benign (p = 0.014), and healthy (p = 0.003) controls, respectively. This suggests that RCC cell lines and serum of RCC patients show higher amounts of CD63‐ and CD81‐EVs compared to controls. Detection of these EVs using NP‐TRFIA approach may play a vital role in the detection of RCC.
Poly(ethylene‐thiosuccinate)/carbon allotrope/cubic nickel‐cobalt hexacyanoferrate nanoparticles nanocomposites as supercapacitor materials
Authors: Zarei‐Gharehbaba Laya , Najjar Reza , Hosseini Mir Ghasem , YardaniSefidi Pariya 
Published: May 2024

AbstractThis paper reports the synthesis of poly(ethylene‐thiosuccinate) (PETS) using succinic anhydride and 1,2‐ethanedithiol monomers and investigates its electrochemical behavior as supercapacitor electrode material. The synthesized polymer's structure is designed so that to contain sulfur atoms in the main chain of polymer, as the sulfur containing polymers are among the interesting active compounds for fabricating of novel devices for energy storage with wider voltage window and increase the energy density. The cyclic voltammetry (CV) graphs show the supercapacitor behavior of the materials with the faradic charge storage mechanism. The triangular shape of the charge–discharge curves indicate the reversible performance of the PETS as an electrode material. To enhance the supercapacitive action of PETS, its nanocomposites including PETS/Norit (1:1), PETS/MWCNT (1:1) and PTES/MWCNT (1:1)/(1.5%, 3% and 5%) Ni2CoHCF (nickel‐cobalt hexacyanoferrate) is prepared. The results indicate that the PETS/MWCNT/0.15% Ni2CoHCF nanocomposite exhibits a specific capacity which is 7 times higher than that of the PETS/MWCNT (1:1) nanocomposite, when the current density is 0.05 mA.cm−2. Also, according to the Nyquist diagrams, by incorporating of 1.5% of Ni2CoHCF in the PETS/MWCNT (1:1) nanocomposite, its electrical resistance decreases significantly by about two times.Highlights
Poly(ethylene‐thiosuccinate) (PETS) made by succinic anhydride & ethanedithiol
PETS/Norit or MWCNT/cubic Ni2CoHCF nanoparticles composites are prepared
PETS/MWCNT composites as supercapacitor materials by Faradic storage mechanism
PETS/1.5% Ni2CoHCF showed 0.0449 mF.cm−2 specific capacity at 0.01 mA.cm−2
Comparing the morphological evolution of reactive and nonreactive Polystyrene/Polypropylene polymer blends: Processing phase inversion
Authors: Ramakrishnan Shashank , Lencar Calin , Mohseni Majid , Sundararaj Uttandaraman 
Published: May 2024

AbstractThis paper discusses the evolution of morphology in 80/20 (vol/vol) (polypropylene‐maleic anhydride)/polypropylene (PP)/(polystyrene‐oxazoline)/polystyrene (PS) reactive blends and nonreactive 80/20 PP/PS blends. For both the blends, the PS forms the continuous phase initially, traps the PP‐maleic anhydride or PP pellets within, and gradually deforms these pellets to lamellar sheets and elongated fibers. Eventually, the irregular domains of PP coalesce and invert to form the continuous phase in a transition known as the “processing phase inversion.” The nonreactive PP/PS blend needed much higher torque to be deformed from pellets to a viscoelastic melt than their reactive counterparts. Despite the significant differences in their processing energy, the reactive and nonreactive blends have similar morphologies during the inversion process. The changes in the structure of the blends were captured on video by a custom‐built visualization system and correlated with scanning electron microscopy of the fractured surfaces, along with monitoring the changes in the torque levels during the processing. The solid‐state properties of the minor phase were crucial for deforming the major phase pellets and, consequentially, the work required to process the blends. Due to a suppression of coalescence due to the presence of in situ formed copolymers at the interface of the PP/PS, a finer dispersion was obtained in the case of the reactive blend systems.Highlights
Visualization of polymer melt blending.
In situ reaction during processing.
Processing energy requirements during blending.
Development of a physiologically based pharmacokinetic model of fostemsavir and its pivotal application to support dosing in pregnancy
Authors: Salem Farzaneh , Nguyen Dung , Bush Mark , Moore Katy P. , Mudunuru Jennypher , Stamatopoulos Konstantinos , Thakkar Nilay , Taskar Kunal S. 
Published: May 2024

AbstractIt is critical to understand the impact of significant physiological changes during pregnancy on the extent of maternal and fetal drug exposure. Fostemsavir (FTR) is a prodrug of temsavir (TMR) and is approved in combination with other antiretrovirals for multi‐drug‐resistant human immunodeficiency virus (HIV) infections. This physiologically based pharmacokinetic model (PBPK) study was used to estimate TMR PK in pregnant populations during each trimester of pregnancy to inform FTR dosing. A PBPK model was developed and validated for TMR using PK data collected following intravenous TMR and oral FTR dosing (immediate‐release and extended‐release tablets) in healthy volunteers. Predicted TMR concentration–time profiles accurately predicted the reported clinical data and variability in healthy (dense data) and pregnant (sparse data) populations. Predicted versus observed TMR geometric mean (CV%) clearance following intravenous administration was 18.01 (29) versus 17 (21) (L/h). Predicted versus observed TMR AUC0–inf (ng.h/mL) in healthy volunteers following FTR administration of the extended‐release tablet were 9542 (66) versus 7339 (33). The validated TMR PBPK model was then applied to predict TMR PK in a population of pregnant individuals during each trimester. Simulations showed TMR AUC in pregnant individuals receiving FTR 600 mg twice daily was decreased by 25% and 38% in the second and third trimesters, respectively. However, TMR exposure remained within the range observed in nonpregnant adults with no need for dose adjustment. The current PBPK model can also be applied for the prediction of local tissue concentrations and drug–drug interactions in pregnancy.
Improving subseasonal forecast of precipitation in Europe by combining a stochastic weather generator with dynamical models
Authors: Krouma Meriem , Specq Damien , Magnusson Linus , Ardilouze Constantin , Batté Lauriane , Yiou Pascal 
Published: May 2024

AbstractWe propose a forecasting tool for precipitation based on analogues of circulation defined from 5‐day hindcasts and a stochastic weather generator that we call “HC–SWG.” In this study, we aim to improve the forecast of European precipitation for subseasonal lead times (from 2 to 4 weeks) using the HC–SWG. We designed the HC–SWG to generate an ensemble precipitation forecast from the European Centre of Medium‐range Weather Forecasts (ECMWF) and Centre National de la Recherche Météorologique (CNRM) subseasonal‐to‐seasonal ensemble reforecasts. We define analogues from 5‐day ensemble reforecast of Z500 from the ECMWF (11 members) and CNRM (10 members) models. Then, we generate a 100‐member ensemble for precipitation over Europe. We evaluate the skill of the ensemble forecast using probabilistic skill scores such as the continuous ranked probability skill score (CRPSS) and receiver operating characteristic curve. We obtain reasonable forecast skill scores within 35 days for different locations in Europe. The CRPSS shows positive improvement with respect to climatology and persistence at the station level. The HC–SWG shows a capacity to distinguish between events and non‐events of precipitation within 15 days at the different stations. We compare the HC–SWG forecast with other precipitation forecasts to further confirm the benefits of our method. We found that the HC–SWG shows improvement against the ECMWF precipitation forecast until 25 days.
Prospects and status of forecasting monthly mean subregional rainfall during the Indian summer monsoon using the coupled Unified Model
Authors: Gupta Ankur , Mitra Ashis K. , Pandey Avinash C. 
Published: May 2024

AbstractWhile there is huge demand for regional forecasts, information needed for selection of the most appropriate temporal and spatial scales is not available. The objective of this study is to demonstrate the basis of forecasting monthly mean rainfall over homogeneous regions by analyzing the forecasting skill and source of predictability. Reforecasts generated at the National Center for Medium Range Weather Forecasting (NCMRWF) for the period 1993–2015 using the coupled Unified Model are used in this study. Analysis of the forecasting skill over increasingly large lead times, averaging periods and spatial scales, is carried out to compare the skill at different time‐scales and to highlight the effect of spatial averaging over regions of coherent rainfall characteristics. Analysis of probabilistic forecasts is carried out to further demonstrate the usefulness of monthly mean forecasts. The influence of forcings on rainfall is studied both in model and in observations to understand the model's skill in representing interannual variability of monthly mean rainfall. Multiple regression analyses carried out for rainfall using climate indices as independent variables shows that the extent of forcings can largely explain the high variability of rainfall during the onset and withdrawal phase compared to the peak phase of monsoons. ENSO‐related subsidence is found to influence mainly the southern peninsular region, while tropical sea surface temperatures (SSTs) in the Indian Ocean are found to influence rainfall over northwest and central India by forcing circulation patterns typically associated with circumglobal teleconnections (CGTs) which are strongest during the month of June. Interestingly, the influence of CGTs on rainfall in the northeast is opposite to its influence on other homogeneous regions, which explains the contrast in influence of the North Indian Ocean SSTs on rainfall over the northeast and over All India. The model representation of influence of forcings and strength of teleconnections is better for specific region–month pairs, which is seen to influence the monthly variations in skill of forecasting rainfall over homogeneous regions.
Individualized image region detection with total variation
Authors: Wu Sanyou , Wang Fuying , Feng Long 
Published: May 2024

AbstractMedical image data have emerged to be an indispensable component of modern medicine. Different from many general image problems that focus on outcome prediction or image recognition, medical image analysis pays more attention to model interpretation. For instance, given a list of medical images and corresponding labels of patients' health status, it is often of greater importance to identify the image regions that could differentiate the outcome status, compared to simply predicting labels of new images. Moreover, medical image data often demonstrate strong individual heterogeneity. In other words, the image regions associated with an outcome could be different across patients. As a consequence, the traditional one‐model‐fits‐all approach not only omits patient heterogeneity but also possibly leads to misleading or even wrong conclusions. In this article, we introduce a novel statistical framework to detect individualized regions that are associated with a binary outcome, that is, whether a patient has a certain disease or not. Moreover, we propose a total variation‐based penalization for individualized image region detection under a local label‐free scenario. Considering that local labeling is often difficult to obtain for medical image data, our approach may potentially have a wider range of applications in medical research. The effectiveness of our proposed approach is validated by two real histopathology databases: Colon Cancer and Camelyon16.
The analysis of association rules: Latent class analysis
Authors: Kenett Ron S. , Gotwalt Chris 
Published: May 2024

AbstractAssociation rules are used to extract information from transactional databases with a collection of items also called “tokens” or “words.” The aim of association rule analysis is to indicate what and how items go with what items in a set of transactions called “documents.” This approach is used in the analysis of text records, of blogs in social media and of shopping baskets. We present here an approach to analyze documents using latent class analysis (LCA) clustering of document term matrices. A document term matrix (DTM) consists of rows referring to documents and columns corresponding to items. In binary weights, “1” indicates the presence of a term in a document and “0” otherwise. The clustering of similar documents provides stratified data sets used to enhance the interpretability of measures of interest such as lift, odds ratios and relative linkage disequilibrium. The article demonstrates the approach with two case studies. A first example consists of comments recorded in a survey aimed at pet owners. A second, much larger example, is based on online reviews to crocs sandals. Association rules describe combinations of terms in the pet survey and crocs reviews. In Section 3, we compute, for these case studies, association rule measures of interest defined in Section 2. We first introduce the case studies to motivate the methods proposed here. In Section 4, we provide a new approach with an enhanced interpretations of measures such as lift by comparing them across clusters derived from an LCA of the DTM. A key result is the application of clustered data in analyzing observational data. This enhances generalizability and interpretability of findings from text analytics. The article concludes with a discussion in Section 5.
Iodination of Substituted Alkynes in the Presence of Cadmium(II) Acetate
Authors: Sargsyan Hmayak B. , Balyan Kristine V. , Pogosyan Haykanush R. , Movsisyan Lusine A. , Hovsepyan Varduhi S. , Ayvazyan Armen G. , Hobosyan Nina G. 
Published: May 2024

AbstractA convenient and selective method for the preparation of substituted iodoalkynes, iodoalkenes based on the interaction of propargylic compounds with iodine in the presence of readily available cadmium (II) acetate in some solvents was developed. The highest yields of iodoalkynes and iodoalkenes were recorded using DMSO as the solvent. An excess of the alkylpropargyl substrate unambiguously led to iodolkynes. By varying the reaction conditions using a twofold excess of iodine in DMSO, methanol or ethanol it was possible to achieve a one‐pot preparation of triiodoalkenes. The interaction of iodine with propargyl substrates could be represented in two ways: formation and further nucleophilic transformation of the iodonium complex under the influence of the acetate ion and generation of π‐coordinated species and elimination of acetic acid.
Highly Porous Carbon Materials Prepared Through KOH‐Assisted CO2‐Activation of Carbonized Waste Tires for Removal of Cr(VI) and Cd(II) from Water
Authors: Ahi Zeinab , Roshanravan Bita , Younesi Habibollah , Bahramifar Nader 
Published: May 2024

AbstractIn this study, waste tires (WTs) were carbonized under an N2 atmosphere. Subsequently, KOH/WTs‐char with KOH‐assisted CO2 activation was used to prepare activated carbon (AC) as a highly porous carbon material for the removal of Cr(VI) and Cd(II) from water. Various techniques such as elemental analysis, Fourier‐transform infrared spectroscopy, scanning electron microscopy, and N2 adsorption/desorption were employed to investigate the physical and chemical characteristics of the prepared carbons. The WTs‐char activated with KOH under CO2 exhibited a microstructure with a high BET surface area and pore volume of 1841 m2/g and 0.869 cm3/g, respectively, demonstrating excellent adsorbent performance. The maximum removal efficiencies of 99.91 % for Cd(II) and 99.81 % for Cr(VI) were achieved using AC2 carbon under the following conditions: pH 2 for Cr(VI) and pH 5 for Cd(II), contact time of 120 min, adsorbent dose of 0.4 g/100 mL, and temperature of 298 K. The adsorption kinetics followed the pseudo‐second‐order equation, and the equilibrium data fit well with the Redlich–Peterson isotherm equation. The positive values of ▵G indicated that the uptake process for both ions was nonspontaneous and nonfeasible over the temperature studied. Both ions showed negative values of ΔH and ΔS on carbon, suggesting exothermic adsorption and a decrease in disorder. Regeneration studies showed that NaOH was a better desorbing agent than HCl. Cr(VI) desorption resulted in over 90 % removal recovery by AC2 using 1.0 M NaOH even after the fifth cycle. However, the low activation energy indicated that the adsorption was favorable kinetically. Overall, this study demonstrated the effective preparation of highly porous carbon and its successful performance in removing Cr(VI) and Cd(II) ions.
Unveiling the Electronic Structure of SnS for Photocatalytic Applications: A DFT Approach†
Authors: Ali Munawar , Rauf Ali , Ali Amjad 
Published: May 2024

AbstractPhotocatalytic materials are of great scientific interest due to their potential applications in sustainable energy sources. Band gap and optical absorption of the materials are two core characteristics for photocatalysis that eventually depend on electronic structure. In order to accurately compute (predict) the electronic‐scale properties of a crystalline solid using first principles calculations, which might be costly to measure experimentally, large‐scale atomic level calculation frameworks have been made possible through the use of density functional theory (DFT). We have used DFT with many body perturbation theory (MBPT) by solving the bethe‐salpeter equation (BSE) to priorly predict the properties of bulk tin sulfide (SnS) as it meets the necessary requirements for photocatalytic applications. We fixed the DFT band gap underestimation by including the Hubbard parameter (U) and used projector augmented wave pseudo‐potentials with generalized‐gradient approximation (GGA) to calculate the electronic and optical properties of SnS. Optical properties were computed using independent particle approximation (IPA) and BSE with DFT+U wave functions. Our theoretical results align with experimental data for this material, demonstrating the potential for further research in validating experimental results with theoretical approximations and empirical relations.
Optimization and Bioactive Properties of Nanoemulsion Formulated with Hemp (Cannabis sativa L.) Seed Oil and Aloe vera (Barbadensis miller Stockton) Gel
Authors: Kara Ayse , Caglak Emre , Karsli Baris 
Published: May 2024

AbstractThe use of nanoemulsions, a nanotechnology technique, is very popular in the food industry to extend the shelf life of foods and preserve their quality. In this study, it was aimed to develop, optimize, and determine the bioactive properties of nanoemulsion containing Aloe vera gel (AVG) and hemp seed oil (HSO) for use in the food industry. Nanoemulsions containing different ratios of AVG (1 %, 2 %, and 3 %) and HSO: Tween 80(T80) (1 : 4; 20, 25, 30 %) were formulated by ultrasonication. Bioactive properties of nanoemulsions were determined by droplet size, polydispersity index (PDI), zeta potential, Transmission electron microscopy (TEM) imaging, Fourier transform infrared spectroscopy (FT‐IR), viscosity, color, whiteness index, turbidity, conductivity, pH, antioxidant (DPPH), and antimicrobial activity analyses. The pH of the nanoemulsions was between 4.74 and 4.88 due to the acidic nature of AVG. PDI was determined in the 0.17 (HA8) range to 0.26 (HA1). According to the FT‐IR spectrum, it was determined that the entire nanoemulsion formulation did not undergo any chemical degradation and their particle sizes (range between 118.9 nm and 170.5 nm) were <200 nm. The small droplet size and PDI values obtained showed that the nanoemulsions had a homogeneous and stable structure in their dispersions. TEM results determined that all nanoemulsions showed a spherical shape, but the structure detected in the HA8 group had a more homogeneous appearance. The antioxidant activity of the nanoemulsions increased depending on the increasing HSO and AVG percentages. Unfortunately, no antibacterial activity of the nanoemulsions was detected against any of the bacterial strains tested. According to the analysis results, it was determined that the best nanoemulsion formulation belonged to the HA8 group containing 3 % Aloe vera gel and 5 % HSO in terms of TEM and PDI analyses.