Neutrophil to Lymphocyte Ratio (NLR)—A Useful Tool for the Prognosis of Sepsis in the ICU

Sepsis is a life-threatening medical emergency induced by the body¢s extreme response to an infection. Despite well-defined and constantly updated criteria for diagnosing sepsis, it is still underdiagnosed worldwide. Among various markers studied over time, the neutrophil to lymphocyte ratio (NLR) recently emerged as a good marker to predict sepsis severity. Our study was a single-center prospective observational study performed in our ICU and included 114 patients admitted for sepsis or septic shock. Neutrophil to lymphocyte ratio (NLR) is easy to perform, CBC being one of the standard blood tests routinely performed upon admission for all ICU patients. We found that NLR was increased in all patients with sepsis and significantly raised in those with septic shock. NLR correlates significantly with sepsis severity evaluated by the SOFA score (R = 0.65) and also with extensively studied sepsis prognosis marker presepsin (R = 0.56). Additionally, NLR showed good sensitivity (47%) and specificity (78%) with AUC = 0.631 (p < 0.05). NLR is less expensive and easier to perform compared with other specific markers and may potentially become a good alternate option for evaluation of sepsis severity. Larger studies are needed in the future to demonstrate the prognosis value of NLR.

A new method to specify the mitigated acoustic test conditions from flight telemetry based on the equivalence of vibro-acoustic response

Ground acoustic tests using stationary sound pressure level spectrum have been conducted to verify the spacecraft survivability against acoustic environment acting on a spacecraft during launch, which is a non-stationary and random dynamic load. In general, a stationary spectrum used in ground acoustic test is traditionally determined by a method called maximax spectrum, which is the enveloped spectrum of time varying non-stationary short-time Fourier transform. However, the maximax spectrum is more or less an excessively conservative test condition because this spectrum focuses on processing of a time-varying acoustic signal itself to extract maximum value, rather than on how the vibro-acoustic response of an excited structure is. In this paper, a new method is proposed to specify a stationary spectrum equivalent to a structural vibro-acoustic response under a non-stationary and random acoustic environment based on extreme response spectrum and fatigue damage spectrum. This proposed method was applied to flight telemetry of both liquid- and solid-propellant launch vehicles developed by JAXA, to show its effect to mitigate the acoustic test conditions compared to the maximax spectrum while maintaining the equivalence of the structural vibro-acoustic response. Furthermore, the maximum predicted environment, which is the statistical upper percentiles of the flight telemetry of eight liquid-propellant launch vehicles, by the proposed method achieved a mitigation of about 2.5 and 6.8 dB in the extreme stress and cumulative fatigue, respectively, compared to the that which is calculated by the conventional maximax spectrum.

A New Multiprocess IRT Model With Ideal Points for Likert-Type Items

For surveys of complex issues that entail multiple steps, multiple reference points, and nongradient attributes (e.g., social inequality), this study proposes a new multiprocess model that integrates ideal-point and dominance approaches into a treelike structure (IDtree). In the IDtree, an ideal-point approach describes an individual’s attitude and then a dominance approach describes their tendency for using extreme response categories. Evaluation of IDtree performance via two empirical data sets showed that the IDtree fit these data better than other models. Furthermore, simulation studies showed a satisfactory parameter recovery of the IDtree. Thus, the IDtree model sheds light on the response processes of a multistage structure.

The Gag Reflex: A Hurdle in Dentistry– Literature Review

Gagging reflex poses a hurdle in numerous dental procedures. It causes discomfort for the patient, extended procedure time for the clinician, compromised quality of treatment and along with a lot of physiological discomfort for both. The normal gag reflex is protective in nature, but few individuals elicit extreme response, leading to problems during the treatment procedures. It is extremely important for the clinician to identify the cause and severity of the condition so that it can be decided whether the patient can handle standard treatment techniques or whether alternative methods must be considered. There is no universal solution for successfully managing the gagging patient. Various modalities can be used according to the doctor’s assessment and patient’s conditions in order to control the gag reflex so that the patient can be comfortable and cope with the dental treatment. A wide range of management solutions are available, and many cases need a combination of therapeutic procedures. The main aim of the present article is to comprehensively report the clinical significance, etiology, symptoms and various management approaches used during prosthodontic treatments.

Application of a Longitudinal IRTree Model: Response Style Changes Over Time

Traditional psychometric models focus on studying observed categorical item responses, but these models often oversimplify the respondent cognitive response process, assuming responses are driven by a single substantive trait. A further weakness is that analysis of ordinal responses has been primarily limited to a single substantive trait at one time point. This study applies a significant expansion of this modeling framework to account for complex response processes across multiple waves of data collection using the item response tree (IRTree) framework. This study applies a novel model, the longitudinal IRTree, for response processes in longitudinal studies, and investigates whether the response style changes are proportional to changes in the substantive trait of interest. To do so, we present an empirical example using a six-item sexual knowledge scale from the National Longitudinal Study of Adolescent to Adult Health across two waves of data collection. Results show an increase in sexual knowledge from the first wave to the second wave and a decrease in midpoint and extreme response styles. Model validation revealed failure to account for response style can bias estimation of substantive trait growth. The longitudinal IRTree model captures midpoint and extreme response style, as well as the trait of interest, at both waves.

TRUMP AND THE FOREIGN POLICY CRISIS IN THE UNITED STATES

Under Donald Trump's administration, American foreign policy's controversial and anti-traditional path has already disrupted decades of U.S strategy, conveying an extreme response from both allies and enemies. This steady decline not only confuses the close allies of the USA in Europe and Asia but also brings new insight to the growing and revival powers that the age of historic global dominance in the United States is over. The decline in US superpower status was, however, accidentally not due to "national below-reach," but through a gradual loss of power and authority including the sacrifice of power. Under Trump's administration, U.S. foreign policy is shifting the U.S. relationship with former friends and harming their potential to achieve the expected results.

Accounting for Item Response Process and Response Styles Using the Unfolding Item Response Tree (UIRTree) Model

Many researchers have found that unfolding models may better represent how respondents answer Liker-type items and response styles (RSs) often have moderate to strong presence in responses to such items. However, the two research lines have been growing largely in parallel. The present study proposed an unfolding item response tree (UIRTree) model that can account for unfolding response process and RSs simultaneously. An empirical illustration showed that the UIRTree model could fit a personality dataset well and produced more reasonable parameter estimates. Strong presence of the extreme response style (ERS) was also revealed by the UIRTree model. We further conducted a Monte Carlo simulation study to examine the performance of the UIRTree model compared to three other models for Likert-scale responses: the Samejima’s graded response model, the generalized graded unfolding model, and the dominance item response tree (DIRTree) model. Results showed that when data followed unfolding response process and contained the ERS, the AIC was able to select the UIRTree model, while BIC was biased towards the DIRTree model in many conditions. In addition, model parameters in the UIRTree model could be accurately recovered under realistic conditions, and wrongly assuming the item response process or ignoring RSs was detrimental to the estimation of key parameters. In general, the UIRTree model is expected to help in better understanding of responses to Liker-type items theoretically and contribute to better scale development practically. Future studies on multi-trait UIRTree models and UIRTree models accounting for different types of RSs are expected.

Optimization of Damage Equivalent Accelerated Test Spectrum Derivation Using Multiple Non-Gaussian Vibration Data

The response spectra are widely used in the damage assessment of non-Gaussian random vibration environments and the derivation of damage equivalent accelerated test spectrum. The effectiveness of the latter is strongly affected by modal parameter uncertainties, multiple field data processing, and the nonsmooth shape of the derived power spectral density (PSD). Optimization of accelerated test spectrum derivation based on dynamic parameter selection and iterative update of spectrum envelope is presented in this paper. The extreme response spectrum (ERS) envelope of the field data is firstly taken as the limiting spectrum, and the corresponding relationship between damping coefficient, fatigue exponent, and damage equivalent PSD under different test times is constructed to achieve the dynamic selection of uncertain parameters in the response spectrum model. Then, an iterative update model based on the weighted sum of fatigue damage spectrum (FDS) error is presented to reduce the error introduced by the nonsmooth shape of the derived PSD. The case study shows that undertest can be effectively avoided by the dynamic selection of model parameters. The weighted error is reduced from 80.1% to 7.5% after 7 iterations. Particularly, the error is close to 0 within the peak and valley frequency band.

Kernel Causality Among Teacher Self-Efficacy, Job Satisfaction, School Climate, and Workplace Well-Being and Stress in TALIS

Teachers play an important role in the educational system. Teacher self-efficacy, job satisfaction, school climate, and workplace well-being and stress are four individual characteristics shown to be associated with tendency to turnover. In this article, data from the Teaching and Learning International Survey (TALIS) 2018 teacher questionnaire are analyzed, with the goal to understand the interplay amongst these four individual characteristics. The main purposes of this study are to (1) measure extreme response style for each scale using unidimensional nominal response models, and (2) investigate the kernel causal paths among teacher self-efficacy, job satisfaction, school climate, and workplace well-being and stress in the TALIS-PISA linked countries/economies. Our findings support the existence of extreme response style, the rational non-normal distribution assumption of latent traits, and the feasibility of kernel causal inference in the educational sector. Results of the present study inform the development of future correlational research and policy making in education.