‘: Digital native’ has been a buzzword within the last decade particularly in educational research. Learners born after the 1980s are presumed somehow different just because they were born in a digital world. Although scholars have labelled these young generations as digital natives or millennials as a homogenous construct, the questions of how and for what purpose(s) these younger generations use these newer technologies remain unresolved. Acknowledging the abundance of literature documenting adults’ viewing their younger ones different throughout history, this study investigates the relationship between socioeconomic level variables, paternal and maternal education level, household income, and their internet use frequency and purposes. Data were gathered from 327 undergraduate students, born between 1997 and 2000, enrolled at a Turkey state university. Findings indicate that maternal and paternal education levels significantly influence the internet use duration of the younger generation, yet observe no significant effect on household income. The results also reveal significant differences in participants’ internet use for academic and a variety of non-academic purposes concerning socioeconomic status variables. Overall, simply being born into a technological world does not make the younger generation a monolithic group of tech-savvy individuals as their adults assume them to be.
The physician assignment process consists of coverage of shifts and duties allocated to physicians in a planning period, taking into account work regulations, individual preferences, and organizational rules, which mostly conflict with each other. In this work, we propose a reformulated mixed-integer programming model based on the literature to tackle fairness in physician scheduling in Emergency Rooms (ERs). In particular, we propose two mixed-integer quadratic programming formulations that consider quadratic costs and two models with linear costs. Our approaches provide balanced schedules concerning target hours and weekends in terms of fairness. Our models also provide a high degree of demand coverage, providing decision-makers a significant advantage.
A new operator for handling the joint risk of different sources has been presented and its various properties are investigated. The problem of risk evaluation of multivariate risk sources has been studied, and a multivariate risk measure, so-called multivariate average-value-at-risk,, is proposed to quantify the total risk. It is shown that the proposed operator satisfies the four axioms of a coherent risk measure while reducing to one variable average-value-at-risk,, in case N = 1. In that respect, it is shown thatis the natural extension ofto N -dimensional case maintaining its axiomatic properties. We further showis flexible by giving the investor the option to choose the risk levelof each random loss i differently. This flexibility is novel and can not be achieved applying univariatewith corresponding risk level α to the sum of the risk marginals. The framework is applicable for Gaussian mixture models with dependent risk factors that are naturally used in financial and actuarial modelling. A multivariate tail variance and its connection withis also presented via Chebyshev inequality for tail events. Examples with numerical simulations are also illustrated throughout.
We aimed to identify a rapid, accurate, and accessible biomarker in the early stages of COVID-19 that can determine the prognosis of the disease in cancer patients. A total number of 241 patients with solid cancers who had a COVID-19 diagnosis between March 2020 and February 2022 were included in the study. Factors and ten different markers of inflammation were analyzed by year of diagnosis of COVID-19 and grouped by severity of infection. Hospitalization, referral to the intensive care unit (ICU), mechanical ventilation, and death were more frequent in 2020 than in 2021 and 2022 (mortality rates, respectively, were 18.8%, 3.8%, and 2.5%). Bilateral lung involvement and chronic lung disease were independent risk factors for severe disease in 2020. In 2021–2022, only bilateral lung involvement was found as an independent risk factor for severe disease. The neutrophil-to-lymphocyte platelet ratio (NLPR) with the highest area under the curve (AUC) value in 2020 had a sensitivity of 71.4% and specificity of 73.3% in detecting severe disease (cut-off > 0.0241, Area Under the Curve (AUC) = 0.842, p <.001). In 2021–2022, the sensitivity of the C-reactive protein-to-lymphocyte ratio (CRP/L) with the highest AUC value was 70.0%, and the specificity was 73.3% (cut-off > 36.7, AUC = 0.829, p = .001). This is the first study to investigate the distribution and characteristics of cancer patients, with a focus on the years of their COVID-19 diagnosis. Based on the data from our study, bilateral lung involvement is an independent factor for severe disease, and the CRP/L inflammation index appears to be the most reliable prognostic marker.
In the current research, lornoxicam-loaded in situ gels were developed, and their potential usage in ocular inflammation was evaluated. Lornoxicam cyclodextrin complex prepared with hydroxypropyl methylcellulose and poloxamer P407 because of the low viscosity of in situ gels to provide easy application. However, washing and removing it from the ocular surface becomes difficult due to the gelation formation with heat. A three-level factorial experimental design was used to evaluate the effects of poloxamer 407 concentration, polymer type, and polymer concentration on viscosity, pH, gelation capacity, gelation time, and gelation temperature, which were considered the optimal indicators of lornoxicam-containing formulations. As a result of the three-level factorial experimental design, the optimized formulation contained 15 (%w/v) poloxamer 407 and 1 (%w/v) hydroxypropyl methylcellulose. The optimize formulation viscosity 25 °C = 504 ± 49cP, viscosity 35 °C = 11247 ± 214cP, pH = 6.80 ± 0.01, gelation temprature = 35 ± 0.2 °C, and gelation time= 34 ± 0.2 s was obtained. In the in vitro release studies, 68% of lornoxicam was released with a burst effect in the first three hours; then, the release continued for eight hours with controlled release. Release kinetics of the formulations were modeled mathematically, and it was found to be compatible with the Korsemeyer-Peppas and Weibull models. In cell culture studies, cell viability at 100 µg/mL was 83% and 96% for NL6 and NL6-CD, respectively. In Draize’s in vivo test, no negative conditions occurred in rats. Therefore, the NL6-CD formulation has the potential to be a favorable option for treating ocular inflammation.
Modeling and estimating autocorrelated discrete data can be challenging. In this article, we use an autoregressive panel ordered probit model where the serial correlation in the discrete variable is driven by the autocorrelation in the latent variable. In such a nonlinear model, the presence of a lagged latent variable results in an intractable likelihood containing high-dimensional integrals. To tackle this problem, we use composite likelihoods that involve a much lower order of integration. However, parameter identification might potentially become problematic since the information employed in lower dimensional distributions may not be rich enough for identification. Therefore, we characterize types of composite likelihoods that are valid for this model and study conditions under which the parameters can be identified. Moreover, we provide consistency and asymptotic normality results for two different composite likelihood estimators and conduct Monte Carlo studies to assess their finite-sample performances. Finally, we apply our method to analyze corporate bond ratings. Supplementary materials for this article are available online.
To investigate the effects of functional electrical stimulation cycling (FES-C) training in addition to conventional physical therapy on gait, muscle strength, gross motor function, and energy expenditure in ambulatory children with spastic diplegic cerebral palsy. Twenty children with diplegic cerebral palsy were randomly assigned to FES-C group ( n = 10) or control group ( n = 10). Subjects trained 3 days/week for 8 weeks. Control group received conventional physical therapy. The FES-C group additionally received FES-C training. The functional muscle test was used for muscle strength assessment. Vicon-3D system was used for gait analysis. Gross Motor Function Measure (GMFM-88) was used for motor function assessment and calorimeter was used for energy expenditure. Measurements were performed at the baseline, at the eight week and at the sixteenth week. Functional muscle strength, gross motor function, and energy expenditure improved more in the FES-C group after training and follow up ( p < 0.05). There was no significant difference found between the changes in gait parameters of the two groups after treatment and follow up ( p > 0.05). Pelvic tilt while walking decreased after training in the FES-C group ( p < 0.05). FES-C applied in addition to conventional physical therapy in children with diplegic cerebral palsy is more effective than conventional physical therapy for increasing functional muscle strength, improving gross motor function functions, and reducing energy expenditure.HighlightsFES-C improves lower extremity functional muscle strength, gross motor function, and energy expenditure in ambulatory children with spastic dCP.The use of FES-C in combination with conventional physiotherapy methods may be beneficial in outpatients with spastic dCP. FES-C improves lower extremity functional muscle strength, gross motor function, and energy expenditure in ambulatory children with spastic dCP. The use of FES-C in combination with conventional physiotherapy methods may be beneficial in outpatients with spastic dCP.
Children with hemiplegic cerebral palsy (CP) are at risk of reduced upper limb function and poorer quality of life than their typically developing peers. Although upper limb impairments have potential negative impact on the health-related quality of life (HRQOL) in children with hemiplegic CP, the efficacy of upper limb rehabilitation approaches aiming to improve upper limb impairments on HRQOL has not been adequately investigated. This study compares the efficacy of two modes of activity-based upper limb rehabilitation (modified constraint-induced movement therapy [mCIMT] and bimanual training [BIM]) on HRQOL outcomes in children with hemiplegic CP mainstreamed in regular schools. Thirty children with hemiplegic CP aged between 7 and 11 years (mean age 8.53 ± 1.54 years) who had functional ability levels of I–III according to the Manual Ability Classification System (MACS), Gross Motor Classification System (GMFCS), and Communication Function Classification System (CFCS) were randomly assigned to receive mCIMT or BIM training. Result : Both mCIMT and BIM yielded statistically significant improvements in all HRQOL domains immediately after the 10-week interventions ( P < .001), which were retained at 16 weeks. While there were some differences in the intervention effects, both of these upper limb rehabilitation approaches based on intensive unimanual or bimanual activity may be beneficial for improving perceived life satisfaction related to physical activity, general mood, family, friends, and school among children with hemiplegic CP mainstreamed in regular schools.