Effectiveness of a dispatcher-assisted CPR using an animated image: Simulation study.

INTRODUCTION: Considering the few studies evaluating bystander cardiopulmonary resuscitation (CPR) performance, we sought to analyze differences in bystander CPR performance with and without the use of our self-developed animated GIFs based on dispatcher-assisted CPR simulation. METHODS: A total of 80 adults who had not received CPR training over the past two years participated in the study. Among them, 40 people were classified into the auditory group (receiving CPR instructions only over the phone), and the other 40 people were classified into the audiovisual group (receiving CPR instructions over the phone after receiving images on a smartphone). All participants were asked to perform adult and infant CPR for 2 min. CPR performance was recorded using two video cameras (front and side) and analyzed by two emergency physicians, whereas CPR quality was measured using Resusci Anne & Baby QCPR Mk II (Laerdal). RESULTS: In the adult CPR study, the audiovisual group had higher performance scores for adequacy of "knee position," "hand posture," "elbow extension," and "vertical compression," as well as higher Standard Posture Completeness and Instruction Performance scores (p < 0.001). No significant difference in CPR quality was observed between the two groups. In the infant CPR study, audiovisual group had higher performance scores in adequacy of "compression site," "finger posture," and "vertical compression," as well as higher Standard Posture Completeness and Instruction Performance scores (p < 0.001). Regarding CPR quality, the audiovisual group had higher scores for "adequate compression rate ratio" (p = 0.047). CONCLUSION: Audiovisual guidance using animated GIFs more effectively improved CPR Standard Posture Completeness and Instruction Performance than did traditional auditory guidance.

Prognostic and Diagnostic Power of Delta Neutrophil Index and Mean Platelet Component in Febrile Patients with Suspected Sepsis.

BACKGROUND: The delta neutrophil index (DNI), a prognostic and diagnostic marker for sepsis, is based on the leukocyte count. Platelet activation, similar to leukocyte activation, plays a crucial role in host defense against pathogens and may serve as a predictor of sepsis outcome. However, the combined evaluation of mean platelet component (MPC) and DNI has rarely been used to assess sepsis. METHODS: To assess the prognostic and diagnostic validity of the simultaneous evaluation of DNI and MPC in cases of human febrile sepsis, we conducted measurements of cellular indices, including DNI and MPC, as well as molecular biomarkers, including procalcitonin (PCT) and C-reactive protein (CRP). This study was carried out in patients admitted to the emergency department with suspected sepsis. RESULTS: Using a cutoff value of 2.65%, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the DNI in sepsis were found to be 69%, 73.9%, 77.9%, and 64.1%, respectively. Furthermore, significant differences in DNI and MPC levels were observed between the sepsis and non-sepsis groups (6.7 ± 7.8% versus 2.1 ± 2.2% (p = 0.000) and 26.0 ± 1.9 g/dL versus 26.8 ± 1.4 g/dL (p = 0.002), respectively). Notably, there was a negative correlation between DNI and MPC, with the strength of the correlation varying based on the cause of sepsis. By setting the cutoff value of the DNI to 6.2%, its sensitivity, specificity, and NPV improved to 100%, 80.3%, and 100%, respectively, although the PPV remained at 10.6%. CONCLUSIONS: In our study, the DNI demonstrates superior effectiveness compared with other molecular biomarkers, such as CRP and procalcitonin, in distinguishing septic febrile patients from non-septic febrile patients. Additionally, a negative correlation exists between MPC and DNI, making MPC a valuable marker for differentiating the etiology of sepsis. These findings hold significant clinical implications, as DNI/MPC evaluation is a cost-effective and readily applicable approach in various impending sepsis scenarios. Notably, this study represents the first examination of the prognostic and diagnostic validity of employing the simultaneous evaluation of DNI and MPC in human cases of febrile sepsis.

Characteristics and Effectiveness of Mobile- and Web-Based Tele-Emergency Consultation System between Rural and Urban Hospitals in South Korea: A National-Wide Observation Study.

(1) Background: The government of South Korea has established a nationwide web- and mobile-based emergency teleconsultation network by designating urban and rural hospitals. The purpose of this study is to analyze the characteristics and effectiveness of the tele-emergency system in South Korea. (2) Methods: Tele-emergency consultation cases from May 2015 to December 2018 were analyzed in the present study. The definition of a tele-emergency in the present study is an emergency consultation between doctors in rural and urban hospitals via a web- and mobile-based remote emergency consultation system (RECS). Consultations through an RECS are grouped into three categories: medical procedure or treatment guidance, image interpretation, and transportation requests. The present study analyzed the characteristics of the tele-emergency system and the reduction in unnecessary transportation (RUT). (3) Results: A total of 2604 cases were analyzed in the present study from 2985 tele-emergency consultation cases. A total of 381 cases were excluded for missing data. Consultations for image interpretation were the most common in trauma cases (71.3%), while transfer requests were the most common in non-trauma cases (50.3%). Trauma patients were more frequently admitted to rural hospitals or discharged and followed up with at rural hospitals (20.3% vs. 40.5%) after consultations. In terms of disease severity, non-severe cases were statistically higher in trauma cases (80.6% vs. 59.4%; p < 0.001). The RUT was statistically highly associated with trauma cases (60.8% vs. 42.8%; p < 0.001). In an analysis that categorized cases by region, a statistically higher proportion of transportation was used in island regions (69.9% vs. 49.5%; p < 0.003). More RUT was associated with non-island regions (30.1% vs. 50.5%; p = 0.001). (4) Conclusions: The tele-emergency system had a great role in reducing unnecessary patient transportation in non-severe trauma cases and non-island rural area emergency cases. Further research is needed for a cost/benefit analysis and clinical outcomes.

Sol-Gel-Processed Y2O3 Multilevel Resistive Random-Access Memory Cells for Neural Networks.

Yttrium oxide (Y2O3) resistive random-access memory (RRAM) devices were fabricated using the sol-gel process on indium tin oxide/glass substrates. These devices exhibited conventional bipolar RRAM characteristics without requiring a high-voltage forming process. The effect of current compliance on the Y2O3 RRAM devices was investigated, and the results revealed that the resistance values gradually decreased with increasing set current compliance values. By regulating these values, the formation of pure Ag conductive filament could be restricted. The dominant oxygen ion diffusion and migration within Y2O3 leads to the formation of oxygen vacancies and Ag metal-mixed conductive filaments between the two electrodes. The filament composition changes from pure Ag metal to Ag metal mixed with oxygen vacancies, which is crucial for realizing multilevel cell (MLC) switching. Consequently, intermediate resistance values were obtained, which were suitable for MLC switching. The fabricated Y2O3 RRAM devices could function as a MLC with a capacity of two bits in one cell, utilizing three low-resistance states and one common high-resistance state. The potential of the Y2O3 RRAM devices for neural networks was further explored through numerical simulations. Hardware neural networks based on the Y2O3 RRAM devices demonstrated effective digit image classification with a high accuracy rate of approximately 88%, comparable to the ideal software-based classification (~92%). This indicates that the proposed RRAM can be utilized as a memory component in practical neuromorphic systems.

Sol-Gel-Processed Y2O3-Al2O3 Mixed Oxide-Based Resistive Random-Access-Memory Devices.

Herein, sol-gel-processed Y2O3-Al2O3 mixed oxide-based resistive random-access-memory (RRAM) devices with different proportions of the involved Y2O3 and Al2O3 precursors were fabricated on indium tin oxide/glass substrates. The corresponding structural, chemical, and electrical properties were investigated. The fabricated devices exhibited conventional bipolar RRAM characteristics without requiring a high-voltage forming process. With an increase in the percentage of Al2O3 precursor above 50 mol%, the crystallinity reduced, with the amorphous phase increasing owing to internal stress. Moreover, with increasing Al2O3 percentage, the lattice oxygen percentage increased and the oxygen vacancy percentage decreased. A 50% Y2O3-50% Al2O3 mixed oxide-based RRAM device exhibited the maximum high-resistance-state/low-resistance-state (HRS/LRS) ratio, as required for a large readout margin and array size. Additionally, this device demonstrated good endurance characteristics, maintaining stability for approximately 100 cycles with a high HRS/LRS ratio (>104). The HRS and LRS resistances were also retained up to 104 s without considerable degradation.

Interaction between a rising bubble and a stationary droplet immersed in a liquid pool using a ternary conservative phase-field lattice Boltzmann method.

When a stationary bubble and a stationary droplet immersed in a liquid pool are brought into contact, they form a bubble-droplet aggregate. Its equilibrium morphology and stability largely depend on the combination of different components' surface tensions, known as the "spreading factor." In this study, we look at the interaction between a rising bubble and a stationary droplet to better understand the dynamics of coalescence and rising and morphological changes for the bubble-droplet aggregate. A systematic study is conducted on the interaction processes with various bubble sizes and spreading factors in two dimensions. The current simulation framework consists of the ternary conservative phase-field lattice Boltzmann method (LBM) for interface tracking and the velocity-pressure LBM for hydrodynamics, which is validated by benchmark cases such as the liquid lens and parasitic currents around a static droplet with several popular surface tension formulations. We further test our LBM for the morphology changes of two droplets initially in contact with various spreading factors and depict the final morphologies in a phase diagram. The separated, partially engulfed, and completely engulfed morphologies can be replicated by systematically altering the sign of the spreading factors. The rising bubble and stationary droplet interaction are simulated based on the final morphologies obtained under stationary conditions by imposing an imaginary buoyancy force on the rising bubble. The results indicate that the bubble-droplet aggregate with double emulsion morphology can minimize the distortion of the bubble-droplet aggregate and achieve a greater terminal velocity than the aggregate with partially engulfed morphology.

Incremental Model Fit Assessment in the Case of Categorical Data: Tucker-Lewis Index for Item Response Theory Modeling.

The Tucker-Lewis index (TLI; Tucker & Lewis, 1973), also known as the non-normed fit index (NNFI; Bentler & Bonett, 1980), is one of the numerous incremental fit indices widely used in linear mean and covariance structure modeling, particularly in exploratory factor analysis, tools popular in prevention research. It augments information provided by other indices such as the root-mean-square error of approximation (RMSEA). In this paper, we develop and examine an analogous index for categorical item level data modeled with item response theory (IRT). The proposed Tucker-Lewis index for IRT (TLIRT) is based on Maydeu-Olivares and Joe's (2005) [Formula: see text] family of limited-information overall model fit statistics. The limited-information fit statistics have significantly better Chi-square approximation and power than traditional full-information Pearson or likelihood ratio statistics under realistic situations. Building on the incremental fit assessment principle, the TLIRT compares the fit of model under consideration along a spectrum of worst to best possible model fit scenarios. We examine the performance of the new index using simulated and empirical data. Results from a simulation study suggest that the new index behaves as theoretically expected, and it can offer additional insights about model fit not available from other sources. In addition, a more stringent cutoff value is perhaps needed than Hu and Bentler's (1999) traditional cutoff criterion with continuous variables. In the empirical data analysis, we use a data set from a measurement development project in support of cigarette smoking cessation research to illustrate the usefulness of the TLIRT. We noticed that had we only utilized the RMSEA index, we could have arrived at qualitatively different conclusions about model fit, depending on the choice of test statistics, an issue to which the TLIRT is relatively more immune.

Improved Environment Stability of Y2O3 RRAM Devices with Au Passivated Ag Top Electrodes.

In this study, we fabricated sol-gel-processed Y2O3-based resistive random-access memory (RRAM) devices. The fabricated Y2O3 RRAM devices exhibited conventional bipolar RRAM device characteristics and did not require the forming process. The long-term stability of the RRAM devices was investigated. The Y2O3 RRAM devices with a 20 nm thick Ag top electrode showed an increase in the low resistance state (LRS) and high resistance state (HRS) and a decrease in the HRS/LRS ratio after 30 days owing to oxidation and corrosion of the Ag electrodes. However, Y2O3 RRAM devices with inert Au-passivated Ag electrodes showed a constant RRAM device performance after 30 days. The 150 nm-thick Au passivation layer successfully suppressed the oxidation and corrosion of the Ag electrode by minimizing the chance of contact between water or oxygen molecules and Ag electrodes. The Au/Ag/Y2O3/ITO RRAM devices exhibited more than 300 switching cycles with a decent resistive window (>103). They maintained constant LRS and HRS resistances for up to 104 s, without significant degradation of nonvolatile memory properties for 30 days while stored in air.

Fractional centralities on networks: Consolidating the local and the global.

We propose a new centrality incorporating two classical node-level centralities, the degree centrality and the information centrality, which are considered as local and global centralities, respectively. These two centralities have expressions in terms of the graph Laplacian L, which motivates us to exploit its fractional analog L^{γ} with a fractional parameter γ. As γ varies from 0 to 1, the proposed fractional version of the information centrality makes intriguing changes in the node centrality rankings. These changes could not be generated by the fractional degree centrality since it is mostly influenced by the local aspect. We prove that these two fractional centralities behave similarly when γ is close to 0. This result provides its complete understanding of the boundary of the interval in which γ lies since the fractional information centrality with γ=1 is the usual information centrality. Moreover, our computation for the correlation coefficients between the fractional information centrality and the degree centrality reveals that the fractional information centrality is transformed from a local centrality into being a global one as γ changes from 0 to 1.

Dirac-source diode with sub-unity ideality factor.

An increase in power consumption necessitates a low-power circuit technology to extend Moore's law. Low-power transistors, such as tunnel field-effect transistors (TFETs), negative-capacitance field-effect transistors (NC-FETs), and Dirac-source field-effect transistors (DS-FETs), have been realised to break the thermionic limit of the subthreshold swing (SS). However, a low-power rectifier, able to overcome the thermionic limit of an ideality factor (η) of 1 at room temperature, has not been proposed yet. In this study, we have realised a DS diode based on graphene/MoS2/graphite van der Waals heterostructures, which exhibits a steep-slope characteristic curve, by exploiting the linear density of states (DOSs) of graphene. For the developed DS diode, we obtained η < 1 for more than four decades of drain current (ηave_4dec < 1) with a minimum value of 0.8, and a rectifying ratio exceeding 108. The realisation of a DS diode represents an additional step towards the development of low-power electronic circuits.

Two cases of extraluminal migration of fishbones into the thyroid gland and submandibular gland.

Laryngopharyngeal or cervical pain following ingestion of foreign bodies is one of the most frequently encountered emergencies in otolaryngologic practice. Although most of these foreign bodies can be easily removed under laryngoscopic examination without any complications, surgical removal may be required when foreign bodies migrate extraluminally. This report describes two rare cases of ingested fishbones that had migrated, one each to the thyroid gland and submandibular gland. Extraluminal migration fishbones should always be considered in otolaryngologic clinics.

Positive Role of Delta Neutrophil Index (DNI) as a Prodiagnostic Marker in Cecal Ligation and Puncture (CLP)-Induced Sepsis Murine Model.

Sepsis is an emergent infectious disease and a leading cause of death despite immediate intervention. While Delta neutrophil index (DNI) and myeloperoxidase (MPO) are known as a prodiagnostic marker of sepsis, the preclinical evidence of the best marker of sepsis is unclear. For this, using a well-designed cecal ligation and puncture (CLP)-induced sepsis mouse model, we comparatively measured the level and cost-effectiveness of sepsis biomarkers such as DNI, myeloperoxidase (MPO), procalcitonin (PCT), and tumor necrosis factor-alpha (TNF-α). First, we found that the optimal time point for early detection is at 6 h, 24 h post-CLP. Strikingly, the peak level and fold change of DNI was revealed at 24 h, further showing the best fold change as compared with other biomarker levels. Given the fold change at 6, 24 h, PCT was next to DNI. Third, a cost-effectiveness survey showed that DNI was the best, with PCT next. Further, DNI level was moderate positively associated with PCT (ρ = 0.697, p = 0.012) and TNF-α (ρ = 0.599, p = 0.040). Collectively, these data indicate that DNI in CLP-induced sepsis mice is as effective as the existent inflammatory biomarkers such as MPO, PCT and TNF-α to predict the prognosis of sepsis. This might have clinically important implications that DNI is cost effective, thus quickly and rationally applying to diverse types of imminent sepsis regardless of species. This might be the first report on the validity of DNI in preclinical CLP-induced murine sepsis.

In Situ Defect Engineering Route to Optimize the Cationic Redox Activity of Layered Double Hydroxide Nanosheet via Strong Electronic Coupling with Holey Substrate.

A defect engineering of inorganic solids garners great deal of research activities because of its high efficacy to optimize diverse energy-related functionalities of nanostructured materials. In this study, a novel in situ defect engineering route to maximize electrocatalytic redox activity of inorganic nanosheet is developed by using holey nanostructured substrate with strong interfacial electronic coupling. Density functional theory calculations and in situ spectroscopic analyses confirm that efficient interfacial charge transfer takes place between holey TiN and Ni-Fe-layered double hydroxide (LDH), leading to the feedback formation of nitrogen vacancies and a maximization of cation redox activity. The holey TiN-LDH nanohybrid is found to exhibit a superior functionality as an oxygen electrocatalyst and electrode for Li-O2 batteries compared to its non-holey homologues. The great impact of hybridization-driven vacancy introduction on the electrochemical performance originates from an efficient electrochemical activation of both Fe and Ni ions during electrocatalytic process, a reinforcement of interfacial electronic coupling, an increase in electrochemical active sites, and an improvement in electrocatalysis/charge-transfer kinetics.

Evaluating SEM Model Fit with Small Degrees of Freedom.

Research has revealed that the performance of root mean square error of approximation (RMSEA) in assessing structural equation models with small degrees of freedom (df) is suboptimal, often resulting in the rejection of correctly specified or closely fitted models. This study investigates the performance of standardized root mean square residual (SRMR) and comparative fit index (CFI) in small df models with various levels of factor loadings, sample sizes, and model misspecifications. We find that, in comparison with RMSEA, population SRMR and CFI are less susceptible to the effects of df. In small df models, the sample SRMR and CFI could provide more useful information to differentiate models with various levels of misfit. The confidence intervals and p-values of a close fit were generally accurate for all three fit indices. We recommend researchers use caution when interpreting RMSEA for models with small df and to rely more on SRMR and CFI.

Defect-mediated ab initio thermodynamics of metastable γ-MoN(001).

Refractory transition metal nitrides exhibit a plethora of polymorphic expressions and chemical stoichiometries. To afford a better understanding of how defects may play a role in the structural and thermodynamics of these nitrides, using density-functional theory calculations, we investigate the influence of point and pair defects in bulk metastable γ-MoN and its (001) surface. We report favorable formation of Schottky defect pairs of neighboring Mo and N vacancies in bulk γ-MoN and apply this as a defect-mediated energy correction term to the surface energy of γ-MoN(001) within the ab initio atomistic thermodynamics approach. We also inspect the structural distortions in both bulk and surfaces of γ-MoN by using the partial radial distribution function, g(r), of Mo-N bond lengths. Large atomic displacements are found in both cases, leading to a broad spread of Mo-N bond length values when compared to their idealized bulk values. We propose that these structural and thermodynamic analyses may provide some insight into a better understanding of metastable materials and their surfaces.

A comparison of full information maximum likelihood and multiple imputation in structural equation modeling with missing data.

This article compares two missing data procedures, full information maximum likelihood (FIML) and multiple imputation (MI), to investigate their relative performances in relation to the results from analyses of the original complete data or the hypothetical data available before missingness occurred. By expressing the FIML estimator as a special MI estimator, we predicted the expected patterns of discrepancy between the two estimators. Via Monte Carlo simulation studies where we have access to the original complete data, we compare the performance of FIML and MI estimators to that of the complete data maximum likelihood (ML) estimator under a wide range of conditions, including differences in sample size, percent of missingness, and degrees of model misfit. Our study confirmed well-known knowledge that the two estimators tend to yield essentially equivalent results to each other and to those from analysis of complete data when the postulated model is correctly specified. However, some noteworthy patterns of discrepancies were found between the FIML and MI estimators when the hypothesized model does not hold exactly in the population: MI-based parameter estimates, comparative fit index (CFI), and the Tucker Lewis index (TLI) tend to be closer to the counterparts of the complete data ML estimates, whereas FIML-based chi-squares and root mean square error of approximation (RMSEA) tend to be closer to the counterparts of the complete data ML estimates. We explained the observed patterns of discrepancy between the two estimators as a function of the interplay between the parsimony and accuracy of the imputation model. We concluded by discussing practical and methodological implications and issues for further research. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Fitting Ordinal Factor Analysis Models With Missing Data: A Comparison Between Pairwise Deletion and Multiple Imputation.

This study compares two missing data procedures in the context of ordinal factor analysis models: pairwise deletion (PD; the default setting in Mplus) and multiple imputation (MI). We examine which procedure demonstrates parameter estimates and model fit indices closer to those of complete data. The performance of PD and MI are compared under a wide range of conditions, including number of response categories, sample size, percent of missingness, and degree of model misfit. Results indicate that both PD and MI yield parameter estimates similar to those from analysis of complete data under conditions where the data are missing completely at random (MCAR). When the data are missing at random (MAR), PD parameter estimates are shown to be severely biased across parameter combinations in the study. When the percentage of missingness is less than 50%, MI yields parameter estimates that are similar to results from complete data. However, the fit indices (i.e., χ2, RMSEA, and WRMR) yield estimates that suggested a worse fit than results observed in complete data. We recommend that applied researchers use MI when fitting ordinal factor models with missing data. We further recommend interpreting model fit based on the TLI and CFI incremental fit indices.

Structure and Measurement Invariance of Ethnic Identity for Native American College Students.

With a specific focus on the Native American population, the current study investigated the structure of ethnic identity, measured by the Multigroup Ethnic Identity Measure, using a bifactor model across Native American (n = 307), Asian (n = 348), and White (n = 549) undergraduate students. We further investigated measurement invariance across ethnic groups that shared the same factor structure. The results indicated that ethnic identity can be modeled by a bifactor structure with a general factor and two group factors, affective pride and exploration, for Native American and Asian respondents but not White respondents. In addition, measurement invariance tests supported partial weak invariance between the Native American group and the Asian group. The current findings suggest that comparisons of ethnic identity scores across ethnic groups should be treated with caution.

Polymorphic expressions of ultrathin oxidic layers of Mo on Au(111).

Ultrathin oxidic layers of Mo (i.e. O/Mo) on the Au(111) substrate are investigated using first-principles density-functional theory calculations. Various polymorphic structural models of these O/Mo layers are proposed and compared with previous experimental results - covering both spectroscopic and microscopic approaches of characterization. We find that, through the control of metal-oxygen coordination in these ultrathin oxidic O/Mo films on Au(111), the oxidation state of Mo atoms in the O/Mo layers can be modulated and reduced without intentional creation of oxygen vacancies. This is also assisted by a charge transfer mechanism from the Au substrate to these oxidic films, providing a direct means to tune the surface electronic properties of ultrathinoxide films on metal substrates.

Understanding the Model Size Effect on SEM Fit Indices.

This study investigated the effect the number of observed variables (p) has on three structural equation modeling indices: the comparative fit index (CFI), the Tucker-Lewis index (TLI), and the root mean square error of approximation (RMSEA). The behaviors of the population fit indices and their sample estimates were compared under various conditions created by manipulating the number of observed variables, the types of model misspecification, the sample size, and the magnitude of factor loadings. The results showed that the effect of p on the population CFI and TLI depended on the type of specification error, whereas a higher p was associated with lower values of the population RMSEA regardless of the type of model misspecification. In finite samples, all three fit indices tended to yield estimates that suggested a worse fit than their population counterparts, which was more pronounced with a smaller sample size, higher p, and lower factor loading.