bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding of ZnO‐Catalyzed Polyurethane Synthesis from Bisurea for Further Exploration of One‐Pot Synthesis and Property Evaluation Thereof
Authors: Yang Yiyin , Zhang Lei , Meng Fansen , Tang Donglin 
Published: February 2024

AbstractZnO is considered to be a good catalyst for the synthesis of polyurethanes (PUs) by alcoholysis of bisureas (BUs). ZnO tends to form Zn(NCO)2(NH3)2 in the presence of urea at high temperature, so does it in the alcoholysis of BUs. Here, attempt is made to understand the role Zn(NCO)2(NH3)2 plays in the alcoholysis of BUs. A loading of Zn(NCO)2(NH3)2 at 5 mol% is found to be sufficient to catalyze the polymerization and the reaction time is greatly cut from 40 h (catalyzed by ZnO) to 26 h, with similar chemical structures and properties. The tensile strength, elongation at break, and toughness for PU–Zn‐5 can reach 43.8 MPa, 330%, and 94.0 J cm−3, respectively. One‐pot synthetic strategy is then further introduced to improve the efficiency of the polymerization. Zn(NCO)2(NH3)2, BU, and PU can be synthesized in one‐pot, by adding ZnO, urea, diamine, LiBr, and diol sequentially. The feasibility of this one‐pot method is verified, indicated by the similar reaction time, chemical structures, molecular weight, thermal and mechanical properties. This one‐pot synthetic strategy offers an efficient way to synthesize PUs directly and simply from urea, diamines, and diols, which is beneficial for improving the molecular diversity of PUs.
Second sensor to improve near‐infrared spectroscopy flap monitor utility: A prospective study
Authors: Harper Jonathan , Slade Emily , Cornette Adrianne , Kejner Alexandra E. 
Published: February 2024

AbstractObjectiveThis study assesses whether use of continuous noninvasive near‐infrared spectroscopy (NIRS) sensor on head and neck free flap (FF) with a second sensor on nonoperated tissue improves distinction between systemic hypoperfusion and FF compromise.MethodsSingle‐institution, prospective study of patients undergoing head and neck FF reconstruction from December 2018 to April 2020. FFs were continuously monitored using NIRS on a monitor paddle with a second (control) sensor on the shoulder. Crude StO2 and percent change in StO2 were compared between the FF and control sensors on each patient, and percent change and percent difference between the control and the monitor paddle were documented to assess for congruity. Sentinel events (e.g., hypotension and hematoma) were documented to assess the association with change in StO2. These events and timing of StO2 changes were noted to assess associations with change in StO2.ResultsA total of 48 patients had complete data. Donor sites included 35 soft‐tissue FFs and 13 fibula FFs. Average StO2 was 73.7 ± 5.5 for FFs and 71.4 ± 5.0 for control sensors. There were seven sentinel events during the study. At the time of the events, StO2 dropped significantly more for the FF than the control sensor (FF = 52.2% drop; control = 6.2% drop; p = .016). NIRS signal denoted change prior to changes in implantable arterial Doppler in all cases.ConclusionsThe addition of a second sensor when using NIRS as a primary modality for FF monitoring may improve distinction between FF compromise events and systemic hypoperfusion. By increasing accuracy of the monitor, there is a potential for decreased resident burden and decreased use of higher level of care nursing, which could reduce overall costs.
Application of machine learning‐based read‐across structure‐property relationship (RASPR) as a new tool for predictive modelling: Prediction of power conversion efficiency (PCE) for selected classes of organic dyes in dye‐sensitized solar cells (DSSCs)
Authors: Pore Souvik , Banerjee Arkaprava , Roy Kunal 
Published: February 2024

AbstractThe application of various in‐silico‐based approaches for the prediction of various properties of materials has been an effective alternative to experimental methods. Recently, the concepts of Quantitative structure‐property relationship (QSPR) and read‐across (RA) methods were merged to develop a new emerging chemoinformatic tool: read‐across structure‐property relationship (RASPR). The RASPR method can be applicable to both large and small datasets as it uses various similarity and error‐based measures. It has also been observed that RASPR models tend to have an increased external predictivity compared to the corresponding QSPR models. In this study, we have modeled the power conversion efficiency (PCE) of organic dyes used in dye‐sensitized solar cells (DSSCs) by using the quantitative RASPR (q‐RASPR) method. We have used relatively larger classes of organic dyes–Phenothiazines (n=207), Porphyrins (n=281), and Triphenylamines (n=229) for the modelling purpose. We have divided each of the datasets into training and test sets in 3 different combinations, and with the training sets we have developed three different QSPR models with structural and physicochemical descriptors and validated them with the corresponding test sets. These corresponding modeled descriptors were used to calculate the RASPR descriptors using a Java‐based tool RASAR Descriptor Calculator v2.0 (https://sites.google.com/jadavpuruniversity.in/dtc‐lab‐software/home), and then data fusion was performed by pooling the previously selected structural and physicochemical descriptors with the calculated RASPR descriptors. Further feature selection algorithm was employed to develop the final RASPR PLS models. Here, we also developed different machine learning (ML) models with the descriptors selected in the QSPR PLS and RASPR PLS models, and it was found that models with RASPR descriptors superseded in external predictivity the models with only structural and physicochemical descriptors: RMSEP reduced for phenothiazines from 1.16–1.25 to 1.07–1.18, for porphyrins from 1.60–1.79 to 1.45–1.53, for triphenylamines from 1.27–1.54 to 1.20–1.47.
Block preconditioning strategies for generalized continuum models with micropolar and nonlocal damage formulations
Authors: Alkmim Nasser , Gamnitzer Peter , Neuner Matthias , Hofstetter Günter 
Published: February 2024

AbstractIn this work, preconditioning strategies are developed in the context of generalized continuum formulations used to regularize multifield models for simulating localized failure of quasi‐brittle materials. Specifically, a micropolar continuum extended by a nonlocal damage formulation is considered for regularizing both, shear dominated failure and tensile cracking. For such models, additional microrotation and nonlocal damage fields, and their interactions, increase the complexity and size of the arising linear systems. This increases the demand for specialized preconditioning strategies when iterative solvers are adopted. Herein, a block preconditioning strategy, employing algebraic multigrid methods (AMG) for approximating the application of sub‐block inverses, is developed and tested in three steps. First, a block preconditioner is introduced for linear systems resulting from micropolar models. For this case, a simple sparse Schur complement approximation, which is practical to compute, is proposed and analyzed. It is tested for three different discretizations. Second, the developed preconditioner is extended to reflect the additional nonlocal damage field. This extended three‐field preconditioner is tested on the simulation of a compression test on a sandstone sample. All numerical tests show an improved performance of the block preconditioning approach in comparison to a black‐box monolithic AMG approach. Finally, a problem‐adapted preconditioner setup strategy is proposed, which involves a reuse of the multigrid hierarchy during nonlinear iterations, and additionally accounts for the different stages occurring in the simulation of localized failure. The problem‐adapted preconditioning strategy has the potential to further reduce the total computation time.
The associations of “weekend warrior” and regularly active physical activity with abdominal and general adiposity in US adults
Authors: Lei Lubi , Li Jingkuo , Wang Wei , Yu Yanwu , Pu Boxuan , Peng Yue , Zhang Lihua , Zhao Zhenyan 
Published: February 2024

AbstractObjectiveThis study examined the association between physical activity patterns and abdominal and general adiposity.MethodsData were extracted among 20‐ to 59‐year‐old participants in the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018. Abdominal and general adiposity was assessed by dual‐energy x‐ray absorptiometry (DXA) and anthropometric measures. DXA‐measured indicators were further normalized into z scores. Physical activity levels were collected by questionnaire and classified as inactive, “weekend warrior” (WW), and regularly active (RA). Survey linear regression models were used to assess associations between physical activity patterns and adiposity indicators.ResultsAmong 9629 participants, 772 (8.2%) reported the WW pattern and 3277 (36.9%) reported the RA pattern. Compared with inactive, both WW and RA had lower DXA‐measured abdominal adiposity (WW: β: −0.24, 95% CI: −0.38 to −0.10; RA: −0.18, 95% CI: −0.29 to −0.07), waist circumference (WW: β: −1.94, 95% CI: −3.16 to −0.73; RA: −1.31, 95% CI: −2.32 to −0.29), whole‐body fat mass (WW: β: −0.16, 95% CI: −0.25 to −0.08; RA: −0.11, 95% CI: −0.18 to −0.04), and BMI (WW: β: −0.78, 95% CI: −1.27 to −0.28; RA: −0.47, 95% CI: −0.89 to −0.04).ConclusionsThe WW pattern was associated with similarly lower abdominal and general adiposity to the RA pattern versus the inactive pattern.
The impact of parental benefits on disadvantaged households
Authors: Havet Nathalie , Lacroix Guy , Plantier Morgane 
Published: February 2024

AbstractOver the past 25 years, the Government of Quebec (Canada) has introduced a number of relatively novel policies aimed at fighting poverty such as the Universal Child Care Program (UCCP) in 1997 and the Quebec Parental Insurance Program (QPIP) in 2006. Since its inception, the QPIP has provided a means‐tested supplementary benefits scheme for disadvantaged households. The scheme yields a well‐defined kink in the benefits schedule with respect to two entirely exogenous criteria. Using the QPIP administrative data files from 2006 to 2017, we estimate the causal impact of the supplemental benefits on leave duration and participation of poor households within a sharp Regression Kink Design (RKD) approach. Our results indicate that single mothers are relatively responsive to additional benefits. Conversely, partnered mothers are not found to respond to the supplemental benefits, irrespective of fathers’ own participation in the parental leave. The Canadian government is currently considering introducing a similar parental leave program. Our results may prove useful for the design of the program.
Preparation and properties of PC/PCTG blends with excellent optical properties and solvent resistance
Authors: Yu DaYang , Zhong Jiachun , Wu Fang , Zheng Pan , Xiang Yu , Zhu Rongli , Wang Xu , Yue Mengjie , Pu Zejun 
Published: February 2024

AbstractBlends of polycarbonate (PC) and poly(1,4‐cyclohexylene dimethylene terephthalate glycol) (PCTG) were synthesized using a twin‐screw extruder. Four distinct PC/PCTG blends were produced with PCTG constituting 10%, 20%, 30%, and 40% of the total weight. Comprehensive evaluations were performed to investigate their thermal properties, solvent resistance, light transmittance, mechanical characteristics, and melt flow index. Differential scanning calorimetry and thermogravimetric analysis demonstrated a single glass transition temperature in the PC/PCTG blends, indicating high compatibility. The incorporation of PCTG was observed to affect the blends' thermal stability. The data revealed a progressive increase in solvent resistance, light transmittance, and melt flow index with increasing PCTG content. The light transmittance of the blend reached 87.5%, and the melt flow index was recorded at 124.2 g (10 min)−1. Mechanical tests showed that the tensile and bending strengths were relatively stable with the addition of PCTG, but there was a noticeable reduction in notched impact strength as the proportion of PCTG increased. © 2024 Society of Industrial Chemistry.
The effect of hybrid thermal fillers on thermal conductivity of carbon fiber reinforced polybutylene terephthalate composites
Authors: Yenier Zafer , Seki Yoldas , Aker Sibel , Öner Ferhat , Altay Lutfiye , Sarikanat Mehmet 
Published: February 2024

AbstractThe use of functional polymeric composites with superior thermal properties, capable of replacing conventional polymers, has increased in recent years, particularly in the electrical‐electronics sector where thermal management is crucial. Carbon fiber (CF) polymer–matrix structural composites have relatively high in‐plane thermal conductivity but low through‐plane conductivity. In order to further enhance the through‐plane and in‐plane conductivity of CF‐reinforced polybutylene terephthalate (PBT) composite, a hybrid loading approach was employed, incorporating synthetic graphite (SG), boron nitride (hBN), aluminium nitride (AlN) and graphene (G) in composite formulations. It was found that the in‐plane conductivity of PBT‐20CF‐20SG‐3G and the through‐plane conductivity of PBT‐20CF‐20SG‐3AlN are 69% and 25% higher, respectively, than those of PBT‐40CF. However, the mechanical properties of hybrid composites exhibit lower values compared to those of CF‐reinforced PBT composites. The tensile strength value of PBT‐40CF is about 33% and 57% higher than those of PBT‐20CF‐20SG‐3G and PBT‐20CF‐20SG‐3AlN. Moreover, the flexural strength of PBT‐40CF is about 48% and 38% higher than those of PBT‐20CF‐20SG‐3G and PBT‐20CF‐20SG‐3AlN, respectively. The density value of PBT‐40CF is lower than that of the composites of PBT‐20CF‐20SG. From TGA it was observed that the thermal stability of PBT‐40CF is comparable to that of the composites PBT‐20CF‐20SG. From the conducted study, it can be proposed that the hybrid combination of SG, hBN, AlN and G can be utilized to achieve higher thermal conductivity values, instead of relying solely on CF in the composites. © 2024 The Authors. Polymer International published by John Wiley & Sons Ltd on behalf of Society of Industrial Chemistry.
Photooxidation of organic compounds by mesoporous silica functionalized with rose bengal
Authors: Bittencourt Catiunaiara R. , Gomes Julia C. , Bazani Heitor A. G. , Gerola Adriana P. 
Published: February 2024

AbstractThe reuse of waste and the use of renewable materials are of great environmental and economic interest. With that in mind, the synthesis of mesoporous silica can be performed using rice husk ash, which is an industrial waste generated in large quantities. This mesoporous material can be functionalized with photoactive molecules, enabling application in photocatalysis. In this work, we used mesoporous silica nanoparticles functionalized with rose bengal dye (RB) for photooxidation reactions of organic molecules, such as the antibiotic cefuroxime 1‐acetoxyethyl ester (cefuroxime axetil). The characterization results showed the formation of one‐dimensional channels with uniform size and two‐dimensional hexagonal arrangement, with surface area and pore diameter of 230 m2 g−1 and 5 nm, respectively. The infrared and UV‐Vis spectroscopy indicated the functionalization of silica with photoactive molecules. Finally, SBA‐15/RB was applied for the photooxidation of ascorbic acid and antibiotic cefuroxime axetil under irradiation with green light, proving to be efficient for the degradation of cefuroxime axetil. Investigation of the reactive oxygen species involved in photodegradation showed that the photooxidation mechanism mainly involves singlet oxygen.
Modeling matrix variate time series via hidden Markov models with skewed emissions
Authors: Gallaugher Michael P. B. , Zhu Xuwen 
Published: February 2024

AbstractData collected today have increasingly become more complex and cannot be analyzed using regular statistical methods. Matrix variate time series data is one such example where the observations in the time series are matrices. Herein, we introduce a set of three hidden Markov models using skewed matrix variate emission distributions for modeling matrix variate time series data. Compared to the hidden Markov model with matrix variate normal emissions, the proposed models present greater flexibility and are capable of modeling skewness in time series data. Parameter estimation is performed using an expectation maximization algorithm. We then look at both simulated data and salary data for public Texas universities.
Triphasic Ni2P–Ni12P5–Ru with Amorphous Interface Engineering Promoted by Co Nano‐Surface for Efficient Water Splitting
Authors: Malhotra Deepanshu , Nguyen Thanh Hai , Tran Duy Thanh , Dinh Van An , Kim Nam Hoon , Lee Joong Hee 
Published: February 2024

AbstractThis research designs a triphasic Ni2P–Ni12P5–Ru heterostructure with amorphous interface engineering strongly coupled by a cobalt nano‐surface (Co@NimPn–Ru) to form a hierarchical 3D interconnected architecture. The Co@NimPn–Ru material promotes unique reactivities toward hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in alkaline media. The material delivers an overpotential of 30 mV for HER at 10 mA cm−2 and 320 mV for OER at 50 mA cm−2 in freshwater. The electrolyzer cell derived from Co@NimPn–Ru(+,−) requires a small cell voltage of only 1.43 V in alkaline freshwater or 1.44 V in natural seawater to produce 10 mA cm−2 at a working temperature of 80 °C, along with high performance retention after 76 h. The solar energy‐powered electrolyzer system also shows a prospective solar‐to‐hydrogen conversion efficiency and sufficient durability, confirming its good potential for economic and sustainable hydrogen production. The results are ascribed to the synergistic effects by an exclusive combination of multi‐phasic crystalline Ni2P, Ni12P5, and Ru clusters in presence of amorphous phosphate interface attached onto cobalt nano‐surface, thereby producing rich exposed active sites with optimized free energy and multi open channels for rapid charge transfer and ion diffusion to promote the reaction kinetics.
Blockchain and explainable AI for enhanced decision making in cyber threat detection
Authors: Kumar Prabhat , Javeed Danish , Kumar Randhir , Islam A.K.M Najmul 
Published: February 2024

SummaryArtificial Intelligence (AI) based cyber threat detection tools are widely used to process and analyze a large amount of data for improved intrusion detection performance. However, these models are often considered as black box by the cybersecurity experts due to their inability to comprehend or interpret the reasoning behind the decisions. Moreover, AI‐based threat hunting is data‐driven and is usually modeled using the data provided by multiple cloud vendors. This is another critical challenge, as a malicious cloud can provide false information (i.e., insider attacks) and can degrade the threat‐hunting capability. In this paper, we present a blockchain‐enabled eXplainable AI (XAI) for enhancing the decision‐making capability of cyber threat detection in the context of Smart Healthcare Systems. Specifically, first, we use blockchain to validate and store data between multiple cloud vendors by implementing a Clique Proof‐of‐Authority (C‐PoA) consensus. Second, a novel deep learning‐based threat‐hunting model is built by combining Parallel Stacked Long Short Term Memory (PSLSTM) networks with a multi‐head attention mechanism for improved attack detection. The extensive experiment confirms its potential to be used as an enhanced decision support system by cybersecurity analysts.
Acute decompensation of cirrhosis versus acute‐on‐chronic liver failure: What are the clinical implications?
Authors: Xu Manman , Chen Yu , Artru Florent 
Published: February 2024

AbstractIt is essential to identify the subgroup of patients who experience poorer outcomes in order to adapt clinical management effectively. In the context of liver disease, the earlier the identification occurs, the greater the range of therapeutic options that can be offered to patients. In the past, patients with acute decompensation (AD) of chronic liver disease were treated as a homogeneous group, with emphasis on identifying those at the highest risk of death. In the last 15 years, a differentiation has emerged between acute‐on‐chronic liver failure syndrome (ACLF) and AD, primarily due to indications that the latter is linked to a less favorable short‐term prognosis. Nevertheless, the definition of ACLF varies among the different knowledge societies, making it challenging to assess its true impact compared with AD. Therefore, the purpose of this review is to provide a detailed analysis emphasizing the critical importance of identifying ACLF in the field of advanced liver disease. We will discuss the differences between Eastern and Western approaches, particularly in relation to the occurrence of liver failure and disease onset. Common characteristics, such as the dynamic nature of the disease course, will be highlighted. Finally, we will focus on two key clinical implications arising from these considerations: the prevention of ACLF before its onset and the clinical management strategies once it develops, including liver transplantation and withdrawal of care.
Symptomatic gallstone disease: Recurrence patterns and risk factors for relapse after first admission, the RELAPSTONE study
Authors: Velamazán Raúl , López‐Guillén Pablo , Martínez‐Domínguez Samuel J. , Abad Baroja Daniel , Oyón Daniel , Arnau Anna , Ruiz‐Belmonte Lara M. , Tejedor‐Tejada Javier , Zapater Raul , Martín‐Vicente Noelia , Fernández‐Esparcia Pedro José , Julián Gomara Ana Belén , Sastre Lozano Violeta , Manzanares García Juan José , Chivato Martín‐Falquina Irene , Andrés Pascual Laura , Torres Monclus Nuria , Zaragoza Velasco Natividad , Rojo Eukene , Lapeña‐Muñoz Berta , Flores Virginia , Díaz Gómez Arantxa , Cañamares‐Orbís Pablo , Vinzo Abizanda Isabel , Marcos Carrasco Natalia , Pardo Grau Laura , García‐Rayado Guillermo , Millastre Bocos Judith , Garcia Garcia de Paredes Ana , Vaamonde Lorenzo María , Izagirre Arostegi Arantzazu , Lozada‐Hernández Edgard Efrén , Velarde‐Ruiz Velasco José Antonio , de‐Madaria Enrique 
Published: February 2024

AbstractBackgroundDelayed cholecystectomy in patients with symptomatic gallstone disease is associated with recurrence. Limited data on the recurrence patterns and the factors that determine them are available.ObjectiveWe aimed to determine the pattern of relapse in each symptomatic gallstone disease (acute pancreatitis, cholecystitis, cholangitis, symptomatic choledocholithiasis, and biliary colic) and determine the associated factors.MethodsRELAPSTONE was an international multicenter retrospective cohort study. Patients (n = 3016) from 18 tertiary centers who suffered a first episode of symptomatic gallstone disease from 2018 to 2020 and had not undergone cholecystectomy during admission were included. The main outcome was relapse‐free survival. Kaplan–Meier curves were used in the bivariate analysis. Multivariable Cox regression models were used to identify prognostic factors associated with relapses.ResultsMean age was 76.6 [IQR: 59.7–84.1], and 51% were male. The median follow‐up was 5.3 months [IQR 2.1–12.4]. Relapse‐free survival was 0.79 (95% CI: 0.77–0.80) at 3 months, 0.71 (95% CI: 0.69–0.73) at 6 months, and 0.63 (95% CI: 0.61–0.65) at 12 months. In multivariable analysis, older age (HR = 0.57; 95% CI: 0.49–0.66), sphincterotomy (HR = 0.58, 95% CI: 0.49–0.68) and higher leukocyte count (HR = 0.79; 95% CI: 0.70–0.90) were independently associated with lower risk of relapse, whereas higher levels of alanine aminotransferase (HR = 1.22; 95% CI: 1.02–1.46) and multiple cholelithiasis (HR = 1.19, 95% CI: 1.05–1.34) were associated with higher relapse rates.ConclusionThe relapse rate is high and different in each symptomatic gallstone disease. Our independent predictors could be useful for prioritizing patients on the waiting list for cholecystectomies.