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Currently, microwave absorbers have received much attention in the military and civil fields on account of electromagnetic radiation and stealth technology. Herein, NiCo2O4/Graphite nanosheets/NiCo2O4 (GNC) hybrid composites with sandwich-like heterostructures were carefully constructed using a hydrothermal method and subsequent annealing process. The morphology and microwave absorption performance are investigated by changing the additive amount of GNS to regulate the ratio of GNS/NiCo2O4. The results show that varying the ratio of GNS/NiCo2O4 has a tiny effect on its structure, nanoband-like NiCo2O4 with the width of 100 nm attaches to the surface of GNS, while it can well tune the microwave absorption properties. When the additive amount of GNS increases from 0.02 g to 0.04 g, the microwave absorption performance first improves and subsequently worsens, which is attributed to the effect of impedance matching and attenuation capacity that resulted from conductive loss, interface polarization, and charge polarization. When the additive amount of GNS is 0.03 g, the maximum reflection loss and effective absorption bandwidth of GNC-2 composites are −47.01 dB and 2.98 GHz (14.51–17.49 GHz) with a thickness of 1 mm. Our results can provide more information for the design and manufacture of composites based on graphite nanosheets as high-performance microwave absorbers.

In meta-analysis, heterogeneity often exists between studies. Knowledge about study features (i.e., moderators) that can explain the heterogeneity in effect sizes can be useful for researchers to assess the effectiveness of existing interventions and design new potentially effective interventions. When there are multiple moderators, they may amplify or attenuate each other’s effect on treatment effectiveness. However, in most meta-analysis studies, interaction effects are neglected due to the lack of appropriate methods. The method meta-CART was recently proposed to identify interactions between multiple moderators. The analysis result is a tree model in which the studies are partitioned into more homogeneous subgroups by combinations of moderators. This paper describes the R-package metacart, which provides user-friendly functions to conduct meta-CART analyses in R. This package can fit both fixed- and random-effects meta-CART, and can handle dichotomous, categorical, ordinal and continuous moderators. In addition, a new look ahead procedure is presented. The application of the package is illustrated step-by-step using diverse examples. Electronic supplementary material The online version of this article (10.3758/s13428-020-01360-0) contains supplementary material, which is available to authorized users.

In recent years, the high-performance microwave absorbers with strong loss, broad frequency bandwidth, thin thickness and light weight have been intensively investigated to address the problem of electromagnetic pollution and improve stealth technology. Considering the fact that microwave absorption performance is quite sensitive to morphology, studying NiCo2O4 with different morphologies is a valuable step towards developing a high-performance microwave absorber. The different morphologies are prepared by adjusting the addition of the structure-directing agent NH4F. When the amount of added NH4F is 1 mmol, a flower-like NiCo2O4 morphology (NC–F1) is obtained with a large specific surface area of 158.97 m2/g and pore volume of 0.3525 cm3g-1, which easily generates conductive loss, polarization loss, and multiple scattering, thereby enhancing its microwave absorption performance. The maximum reflection loss reaches −50.3 dB at 3 mm, and the effective bandwidth is 4 GHz with the matching thickness of 2 mm when the fill ratio is only 30 wt% in the epoxy resin. As the thicknesses range from 1.5 mm to 5 mm, the effective bandwidth is 14.2 GHz (3.8 GHz–18 GHz) and covers the entire C, X, and Ku bands. Therefore, the defined-morphology NiCo2O4 is expected to be a novel wide-band and strong-loss microwave absorber.

Recurrent event data are commonly encountered in biomedical studies. In many situations, they are subject to an informative terminal event, for example, death. Joint modeling of recurrent and terminal events has attracted substantial recent research interests. On the other hand, there may exist a large number of covariates in such data. How to conduct variable selection for joint frailty proportional hazards models has become a challenge in practical data analysis. We tackle this issue on the basis of the "minimum approximated information criterion" method. The proposed method can be conveniently implemented in SAS Proc NLMIXED for commonly used frailty distributions. Its finite-sample behavior is evaluated through simulation studies. We apply the proposed method to model recurrent opportunistic diseases in the presence of death in an AIDS study.

Perturbation training, built upon motor adaptation and learning, has been increasingly used as a fall prevention paradigm in older adults. This training paradigm involves repeated externally-induced perturbations (like slips) to facilitate the error-driven learning of necessary motor skills for preventing falls. It remains unknown if people with multiple sclerosis can adapt to large-scale slip perturbations, which impedes the application of perturbation training in persons with multiple sclerosis. This study explored whether people with multiple sclerosis can adapt to large-scale repeated gait-slips.Thirteen individuals with multiple sclerosis (the mean ± standard deviation of the Patient Determined Disability Steps: 2.27 ± 1.42) were exposed unexpectedly to a block of five repeated standard slips while walking on a treadmill. The outcome (fall or recovery) for each slip, as our primary outcome measure, was determined. A battery of secondary variables, including dynamic gait stability and gait parameters, were also calculated. Both primary and secondary variables were compared across trials.Our participants showed a rapidly reduced slip-fall rate (from 92.3% on the first slip to 30.8% on the fifth, p0.001). They mainly adopted proactive, assisted by reactive, strategies to improve dynamic gait stability, thus reducing the risk of slip-falls. The proactive adjustments, including shortened step, reduced foot landing angle, and flexed knee, shifted the center of mass anteriorly to be closer to the base of support. Such changes in center of mass position improved dynamic gait stability before the slip. Dynamic gait stability after the slip was also improved across trials, as a reactive strategy.With practice, people with multiple sclerosis can adapt to large-scale, high-speed, gait-slips and acquire necessary skills against falls. Such skills primarily involve proactive strategy which is assisted by reactive strategy. The proactive strategy would shift the body's center of mass closer to the base of support, improving dynamic gait stability and reducing falls. Our findings could provide a theoretical foundation for deploying perturbation training to prevent falls in people with multiple sclerosis.

Nowadays, the studying of high-performance microwave absorber with the features of broad bandwidth and strong absorption to address the electromagnetic wave pollution is still a challenge. Thus, based on the careful design of structure and composition, a novel high-performance microwave absorber of hierarchical 1D–2D NiCo2O4 integrating one-dimension nanofibers and two-dimension microsheets is prepared via facile hydrothermal method and subsequent annealing process. The formed NiCo2O4 can be well adjusted under the different annealing temperature. Particularly, varying the annealing temperature from 280 to 600 °C regulates the composition and physicochemical property, further optimizing the microwave absorption performance of hierarchical 1D–2D NiCo2O4. Therefore, when the annealing temperature is 320 °C and the fill ratio in the paraffin is 30%, maximum reflection loss and efficient frequency bandwidth below − 10 dB are − 41.8 dB and 5.35 GHz at a thickness of 2 mm respectively. The superior absorption performance is due to conductive loss, dipole polarization loss, multiple scattering and multiple reflection, which illustrates that hierarchical 1D–2D NiCo2O4 could be regarded as a strong-loss, broadband, and lightweight microwave absorber.

Prostate cancer (PCa) screening using serum prostate-specific antigen (PSA) testing has caused unnecessary biopsies and overdiagnosis owing to its low accuracy and reliability. Therefore, there is an increased interest in identifying better PCa biomarkers. Studies showed that trained dogs can discriminate patients with PCa from unaffected men by sniffing urine. We hypothesized that urinary volatile organic compounds (VOCs) may be the source of that odor and could be used to develop urinary VOC PCa diagnosis models.Urine samples from 55 and 53 biopsy proven PCa-positive and -negative patients respectively were initially obtained for diagnostic model development. Urinary metabolites were analyzed by gas chromatography-mass spectrometry. A PCa diagnosis model was developed and validated using innovative statistical machine-learning techniques. A second set of samples (53 PCa-positive and 22 PCa-negative patients) were used to evaluate the previously developed PCa diagnosis model.The analysis resulted in 254 and 282 VOCs for their significant association (P .05) with either PCa-positive or -negative samples respectively. Regularized logistic regression analysis and the Firth method were then applied to predict PCa prevalence, resulting in a final model that contains 11 VOCs. Under cross-validation, the area under the receiver operating characteristic curve (AUC) for the final model was 0.92 (sensitivity, 0.96; specificity, 0.80). Further evaluation of the developed model using a testing cohort yielded an AUC of 0.86. As a comparison, the PSA-based diagnosis model only rendered an AUC of 0.54.The study describes the development of a urinary VOC-based model for PCa detection.

Objectives: To examine the concurrent use of self-report questionnaires and hormonal biomarkers, specifically levels of testosterone and cortisol, along with demographic variables and corrected age (CA) in the assessment of mental health and healthy behaviors among mothers of very-low-birthweight (VLBW, BW < 1,500 g) infants at five time points over 2 years post birth. Method: Data on 40 mothers from a neonatal intensive care unit of a tertiary medical center in the southeast United States were collected from the medical record, standard questionnaires for the mother (depressive symptoms, perceived stress, anxiety, mental health status, parenting stress, and healthy lifestyle behaviors), and biochemical measurement of maternal testosterone and cortisol using enzyme immunoassay at birth, 40 weeks’ postmenstrual age, and 6, 12, and 24 months CA. Results: Maternal self-report of mental health improved from birth to 6 or 12 months then worsened at 24 months. Mixed linear models showed that mothers with higher testosterone levels had more depressive symptoms and smoked more, whereas mothers with higher cortisol levels had healthier behaviors and exercised more. Testosterone levels were negatively correlated with cortisol levels. Marital status, education, and health insurance were the most predictive demographic variables for the levels of hormonal biomarkers, mental health, and healthy behaviors. Conclusions: The use of self-report and biochemical measurement was effective in assessing maternal mental health and healthy behaviors over 2 years post birth, when mothers of VLBW infants tend to experience more mental health problems and parenting difficulties than mothers of normal-BW full-term infants.

Background Mobility impairment is common in people with multiple sclerosis (MS). Gait speed has shown strong correlations with other mobility measures in MS. The purpose of this study was to assess the relative importance of a battery of factors in determining gait speed among people with MS. Methods Thirty-one individuals with MS (the mean (standard deviation) of the Patient Determined Disability Steps: 3.68(1.70)) participated in this cross-sectional observational study. Their gait speed was assessed using the Timed-25-Foot Walking test. Six factors which could slow gait speed in MS, including the strength capacity at knee joints, functional mobility, body balance, dorsiflexion range of motion of ankle joints, bilateral foot cutaneous sensation level, and the fear of falling, were also assessed. Multiple regression and relative weight analysis were used to identify the relative importance of each factor in explaining the gait speed variation. Results All six factors together accounted for about 86% of the observed variation in gait speed; each explaining a statistically significant amount. The most important factor was the strength measurement (relative weight = 0.321) which accounted for 37.2% of the explained variation in gait speed. Conclusion : Muscle strength, particularly the knee joint strength capacity, could be a principal factor determining gait speed in people with mild to moderate MS. Other factors also significantly affect gait speed in this population. The findings from this study could provide guidance in terms of prioritizing actions to improve gait speed in people with MS.

PURPOSE: To compare two implementation telephone-based strategies of an evidence-based educational and support intervention to Rural Breast Cancer Survivor (RBCS) in which education was delivered early or after the support component. METHODS: Florida RBCS participated in a 12-month randomized clinical trial (RCT) with two arms: Early Education and Support (EE-S), and Support and Delayed Education (S-DE). Arms differed in the timing of 6 support and 3 education sessions. Main outcome was quality of life (QOL, SF-36 physical and mental composite scores [PCS, MCS]). Secondary outcomes were depressive symptoms (Centers for Epidemiologic Studies Depression Scale, CES-D), mood (Profile of Mood States, POMS), and social support (Medical Outcomes Study - Social Support Survey, MOS-SSS). Outcomes were analyzed longitudinally using repeated measures models fitted with linear mixed methods. RESULTS: Of 432 RBCS (mean 25.6 months from diagnosis), about 48% were 65+, 73% married/partnered, 28% with ≤high school education. There were no differences between EE-S and S-DE in demographics or outcomes at baseline (Mean (Standard deviation): SF-36 PCS: 44.88 (10.6) vs. 45.08 (10.6) ; MCS: 49.45 (11.1) vs. 48.1 (11.9); CES-D: 10.11 (9.8) vs. 10.86 (10.5) ; POMS-SF: 23.95 (38.6) vs. 26.35 (38.8); MOS-SSS: 79.2 (21.2) vs. 78.66 (21.2)) or over time. One exception was slightly worse mean scores at month 9 in MCS (Cohen’s d −0.22, 95% CI: −0.38, −0.06) and POMS (Cohen’s d 0.23, 95% CI: 0.07, 0.39) for EE-S vs. S-DE. CONCLUSIONS: The implementation strategies were equivalent. IMPLICATIONS FOR SURVIVORS: Enhancing support may be considered before delivering not-in-person interventions to RBCS.

In clinical studies, the treatment effect may be heterogeneous among patients. It is of interest to identify subpopulations which benefit most from the treatment, regardless of the treatment’s overall performance. In this study, we are interested in subgroup identification in longitudinal studies when nonlinear trajectory patterns are present. Under such a situation, evaluation of the treatment effect entails comparing longitudinal trajectories while subgroup identification requires a further evaluation of differential treatment effects among subgroups induced by moderators. To this end, we propose a tree-structured subgroup identification method, termed “interaction tree for longitudinal trajectories”, which combines mixed effects models with regression splines to model the nonlinear progression patterns among repeated measures. Extensive simulation studies are conducted to evaluate its performance and an application to an alcohol addiction pharmacogenetic trial is presented.

Assessing heterogeneous treatment effects has become a growing interest in advancing precision medicine. Individualized treatment effects (ITE) play a critical role in such an endeavor. Concerning experimental data collected from randomized trials, we put forward a method, termed random forests of interaction trees (RFIT), for estimating ITE on the basis of interaction trees (Su et al., 2009). To this end, we first propose a smooth sigmoid surrogate (SSS) method, as an alternative to greedy search, to speed up tree construction. RFIT outperforms the traditional `separate regression' approach in estimating ITE. Furthermore, standard errors for the estimated ITE via RFIT can be obtained with the infinitesimal jackknife method. We assess and illustrate the use of RFIT via both simulation and the analysis of data from an acupuncture headache trial., 32 pages, 6 figures

Multivariate survival trees require few statistical assumptions, are easy to interpret, and provide meaningful diagnosis and prediction rules. Trees can handle a large number of predictors with mixed types and do not require predictor variable transformation or selection. These are useful features in many application fields and are often required in the current era of big data. The aim of this article is to introduce the R package MST. This package constructs multivariate survival trees using marginal model and frailty model based approaches. It allows the user to control and see how the trees are constructed. The package can also simulate high-dimensional, multivariate survival data from marginal and frailty models.

Background Male infants are more prone to health problems and developmental delays than female infants. Objectives On the basis of theories of gender differences in brain development and social relationships, we explored associations between testosterone and cortisol levels with infant cognitive, motor, and language development (“infant development”) in very low birth weight (VLBW) infants, controlling for mother–infant interactions, characteristics of mothers and infants, and days of saliva collection after birth. Methods A total of 62 mother–VLBW infant pairs were recruited from the newborn intensive care unit of a tertiary medical center in the Southeast United States. Data were collected through infant medical record review, biochemical measurement, observation of mother–infant interactions, and standard questionnaires. Infant development was assessed at 6 months corrected age (CA), and mother–infant interactions were observed at 3 and 6 months CA. Results General linear regression with separate analyses for each infant gender showed that high testosterone levels were positively associated with language development of male infants after controlling for mother–infant interactions and other covariates, whereas high cortisol levels were negatively associated with motor development of female infants after controlling for mother–infant interactions. Conclusions Steroid hormonal levels may well be more fundamental factors for assessing infant development than infant gender or mother–infant interactions at 6 months CA.

The purpose of this study was to systematically examine the effect of an 8-week controlled whole-body vibration training on improving fall risk factors and the bone mineral density among people with multiple sclerosis (PwMS).This study adopted a single group pre-test-post-test design. Twenty-five PwMS (50.3 years SD 14.1) received vibration training on a side-alternating vibration platform. Each training session was repeated three times every week for 8 weeks. Prior to and following the 8-week training course, a battery of fall risk factors were evaluated: the body balance, functional mobility, muscle strength, range of motion, and fear of falling. Bone density at both calcanei was also assessed.Twenty-two participants completed the study. Compared with pre-test, almost all fall risk factors and the bone density measurement were significantly improved at post-test, with moderate to large effect sizes varying between 0.571 and 1.007.The 8-week vibration training was well accepted by PwMS and improved their fall risk factors. The important findings of this study were that vibration training may increase the range of motion of ankle joints on the sagittal plane, lower the fear of falling, and improve bone density. IMPLICATIONS FOR REHABILITATION An 8-week vibration training course could be well-accepted by people with multiple sclerosis (MS). Vibration training improves the risk factors of falls in people living with MS. Vibration training could be a promising rehabilitation intervention in individuals with MS.

To more precisely evaluate the effects of nurse staffing on hospital-acquired pressure injury (HAPI) development, data on nursing care hours per patient day (NCHPPD), nursing skill mix, patient turnover (i.e., admissions, transfers, and discharges), and patient acuity were merged with patient information from pressure injury prevalence surveys that were collected annually for the Military Nursing Outcomes Database (MilNOD) project. The MilNOD included staffing and adverse events from 56 medical-surgical, stepdown, and critical care units in 13 military hospitals over a 4-year-period. Data on 1,643 patients were analyzed with Cox proportional hazards models and generalized estimating equations. Staffing was not associated with pressure injuries in stepdown or critical care patients. However, among the 1,104 medical-surgical patients, higher licensed practical nurse (LPN) nursing care hours per patient day (NCHPPD) 3 days and 1 week prior to the HAPI discovery date were associated with fewer HAPI (HR 0.27, p < .001), after controlling for patient age, Braden mobility score, and albumin level. Neither total staff number, nor RN NCHPPD, nor the proportion of staff who were RNs (RN skill mix) were associated with HAPI. These findings suggest that on military medical-surgical units, LPNs play a major role in HAPI prevention. Although the national trend in acute care is to staff hospital units with more RNs and patient care technicians, and fewer LPNs, hospitals should reconsider LPNs as valuable members of the nursing care team. © 2016 Wiley Periodicals, Inc.

This paper reports a Ka-band sheet beam traveling wave tube (TWT) focused by a 0.2 T closed periodic cusped magnet (PCM) system. The TWT with one section of staggered double-vane slow-wave structure (SWS) is driven by a 0.8-A sheet beam with rectangular cross-sectional area of 3.2 mm × 0.6 mm. This sheet beam TWT can produce 100 W output power, and the 3 dB band is 33–38.5 GHz. In order to improve the output power, an optimized sheet beam TWT with two sections of SWSs focused by a novel closed PCM system is proposed. The new closed PCM system is with annular magnetic blocks and can be fabricated and adjusted easily. The simulation shows that the optimized sheet beam TWT can produce 2000 W output power and the 3 dB band ranging from 33 to 40 GHz.

Understanding how resources are used provides guidance to disseminating effective interventions. Here, we report data on implementation resources needed for the Rural Breast Cancer Survivors (RBCS) study that tested a telephone-delivered psychoeducational education and support intervention to survivors in rural Florida. Intervention resources included interventionists’ time on one intake assessment (IA) call, three education calls (ED), one follow-up education call (FUE), six support (SUP) calls, and documentation time per survivor. Interventionists logged start and end times of each type of call. Average interventionist time in minutes was calculated by call type. Associations between interventionists’ time and participants’ characteristics including age, race/ethnicity, time since treatment, cancer treatment, depressive symptoms, education, income, employment, and support, was assessed using linear mixed models with repeated measures. Among 328 survivors, IA calls lasted 66.9 min (SD 21.7); ED lasted 50.6 (SD 16.7), 48.1 (SD 15.9), and 39.6 (SD 14.8); FUE lasted 24.7 (SD 14.8); and SUP 42.8 (SD 29.6) min. Documentation time was 18.4 min for IA, 23–27 for ED, 12.3 for FUE, and 23.0 for SUP. Interventionists spent significantly more time with participants with depressive symptoms, who already used other support, and who received SUP calls before the ED vs. after. There were no significant differences by time since or type of cancer treatment, or other personal characteristics. Resources vary by survivor characteristics. Careful consideration of mental health status or support available is warranted for planning implementation and dissemination of effective survivorship interventions on a broad scale.

Background Identification of patient subgroups to enhance treatment effects is an important topic in personalized (or tailored) alcohol treatment. Recently, several recursive partitioning methods have been proposed to identify subgroups benefiting from treatment. These novel data mining methods help to address the limitations of traditional regression-based methods that focus on interactions. Methods We propose an exploratory approach, using recursive partitioning methods, for example, interaction trees (IT) and virtual twins (VT), to flexibly identify subgroups in which the treatment effect is likely to be large. We apply these tree-based methods to a pharmacogenetic trial of ondansetron. Results Our methods identified several subgroups based on patients' genetic and other prognostic covariates. Among the 251 subjects with complete genotype information, the IT method identified 118 with specific genetic and other prognostic factors, resulting in a 17.2% decrease in the percentage of heavy drinking days (PHDD). The VT method identified 88 subjects with a 21.8% decrease in PHDD. Overall, the VT subgroup achieved a good balance between the treatment effect and the group size. Conclusions A data mining approach is proposed as a valid exploratory method to identify a sufficiently large subgroup of subjects that is likely to receive benefit from treatment in an alcohol dependence pharmacotherapy trial. Our results provide new insights into the heterogeneous nature of alcohol dependence and could help clinicians to tailor treatment to the biological profile of individual patients, thereby achieving better treatment outcomes.

Background Pressure ulcers are associated with a nearly three-fold increase in in-hospital mortality. It is essential to investigate how other factors besides the Braden scale could enhance the prediction of pressure ulcers. Data mining modeling techniques can be beneficial to conduct this type of analysis. Data mining techniques have been applied extensively in health care, but are not widely used in nursing research. Purpose To remedy this methodological gap, this paper will review, explain, and compare several data mining models to examine patient level factors associated with pressure ulcers based on a four year study from military hospitals in the United States. Methods The variables included in the analysis are easily accessible demographic information and medical measurements. Logistic regression, decision trees, random forests, and multivariate adaptive regression splines were compared based on their performance and interpretability. Results The random forests model had the highest accuracy (C-statistic) with the following variables, in order of importance, ranked highest in predicting pressure ulcers: days in the hospital, serum albumin, age, blood urea nitrogen, and total Braden score. Conclusion Data mining, particularly, random forests are useful in predictive modeling. It is important for hospitals and health care systems to use their own data over time for pressure ulcer risk prediction, to develop risk models based upon more than the total Braden score, and specific to their patient population.

The purpose of this study was to determine whether maternal mental and physical health is associated with maternal testosterone and cortisol levels, parenting of very low birth weight infants, physical exercise, and White vs non-White race. A total of 40 mothers of very low birth weight infants were recruited from a neonatal intensive care unit at a University Hospital in the Southeast United States. Data were collected through a review of medical records, standardized questionnaires, and biochemical measurement. Maternal mental and physical health status using questionnaires as well as maternal testosterone and cortisol levels using an enzyme immunoassay were measured four times (birth, 40 weeks postmenstrual age [PMA], and 6 and 12 months [age of infant, corrected age]). General linear models showed that higher testosterone levels were associated with greater depressive symptoms, stress, and poorer physical health at 40 weeks PMA, and at 6 and 12 months. High cortisol levels were associated with greater anxiety at 40 weeks PMA; however, with better mental and physical health at 40 weeks PMA, and 6 and 12 months. Physical activity was associated with lower maternal perceived stress at 12 months. Maternal health did not differ by race, except anxiety, which was higher in White than non-White mothers after birth. As very low birth weight infants grew up, maternal physical health improved but mental health deteriorated. Testosterone and cortisol levels were found to be positively correlated in women but testosterone was more predictive of maternal mental and physical health than cortisol. Indeed testosterone consistently showed its associations with maternal health. Maternal stress might be improved through regular physical exercise.

Objective: Although the roles of testosterone and cortisol in various health problems have been extensively investigated, little is known about their associations with health outcomes in mothers and their very-low-birthweight (VLBW) infants when maternal testosterone and cortisol are examined together during the postpartum period. Method: The 101 mother–VLBW infant pairs were recruited from the neonatal intensive care unit of a tertiary medical center in the southeastern United States. Demographic information, pregnancy and labor complications of mothers, and health and growth outcomes of infants were obtained from medical records and interviews with mothers. Maternal salivary testosterone and cortisol levels were determined using enzyme immunoassay. Results: Linear regression showed that mothers who were older and had a larger body mass index experienced more pregnancy complications, whereas mothers who were single and had a cesarean section experienced more labor complications. Generalized linear models showed that mothers with high cortisol levels had more antepartum hemorrhage, whereas infants of mothers with high cortisol levels had fewer neurological insults and shorter hospitalizations than other infants. More mothers experienced premature prolonged rupture of membranes (PPROM) than chorioamnionitis, and maternal medical complications were negatively associated with infant health outcomes except PPROM, which was positively associated with infant outcomes. Conclusions: High maternal cortisol levels were associated with maternal health problems during pregnancy. Beneficial effects of PPROM and high maternal cortisol levels on infant health outcomes were important findings, and understanding the mechanisms of these relationships may be of practical value for clinicians and researchers.

The paper introduce a W-band folded waveguide traveling wave tube(TWT), the test result show the impulse wave output power is above 100W within 2GHz bandwidth from 94GHz to 96GHz. The peak power is 120W and the maximum gain is 41.6dB. The electron efficiency is more than 3.7 % and the total efficiency is more than 18% with two stage depression collector. The tube is tested under the electron gun voltage is 19.1 KV and beam current is 145 mA.

Little is known about the influence of sleep quality, stress, and caregiver burden on quality of life in maternal caregivers of young children with bronchopulmonary dysplasia (BPD). In 61 maternal caregivers (mean age 29.59 years) of young children with BPD (mean age 13.93 months), caregivers reported sleeping a mean of 5.8 hours, and significant correlations were found between sleep quality and depressive symptoms and stress, as well as an inverse correlation with quality of life. Sleep quality was found to be the most significant predictor of quality of life in maternal caregivers.

Folded waveguide (FWG) traveling wave tubes (TWTs) are potential sources of wideband, high-power millimeter and terahertz wave radiation. However, low efficiency limits its application. In this paper, we discuss a design strategy to improve efficiency of the FWG TWT meanwhile how to avoid instability is also discussed. The critical factors for the slow-wave structure design and the sever design are analyzed. A phase velocity taper profile incorporating a positive period followed by a negative period is introduced into the design to improve the efficiency. A Ka-band FWG TWT was developed, which demonstrated the output power up to in 2-GHz bandwidth and electronic efficiency up to .

Attrition can jeopardize both internal and external validity. The goal of this secondary analysis was to examine predictors of attrition using baseline data of 432 participants in the Rural Breast Cancer Survivors study. Attrition predictors were conceptualized based on demographic, social, cancer treatment, physical health, and mental health characteristics. Baseline measures were selected using this conceptualization. Bivariate tests of association, discrete-time Cox regression models and recursive partitioning techniques were used in analysis. Results showed that 100 participants (23%) dropped out by Month 12. Non-linear tree analyses showed that poor mental health and lack of health insurance were significant predictors of attrition. Findings contribute to future research efforts to reduce research attrition among rural underserved populations.

The importance of quality of life (QOL) measurement among breast cancer survivors (BCS) is well-recognized by researchers and clinicians. With data from 427 rural BCS, the authors used a combination of clinical expertise and statistical analysis to revise a 48-item measure of QOL specific to BCS. The revised 15-item measure showed adequate psychometric properties and provides the basis for a brief yet comprehensive multidimensional measure of QOL applicable to most BCS. Future work includes fine-tuning the measurement model and examining its generalizability among non-rural BCS.

Male vulnerability in health and growth outcomes has often been reported in very low birth weight (VLBW) preterm neonates. On the basis of gender-difference theories, possible associations were explored between the levels of postnatal salivary testosterone/cortisol and the outcomes of neonatal health/growth.This study used an exploratory and comparative research design. One-hundred-one mother-VLBW preterm neonate pairs were recruited from the neonatal intensive care unit (NICU) of a tertiary medical center in the Southeastern, US. Demographic information, health and growth variables of neonates, and pregnancy and labor variables of mothers were obtained from the medical record reviews and interviews of mothers. Saliva samples from each pair were collected between 9 and 60 days of age. The levels of testosterone and cortisol were determined by using an enzyme immunoassay methodology.Linear regression analysis showed that neonatal health problems were positively associated with the levels of postnatal salivary testosterone and cortisol, while growth delays were positively associated with the levels of postnatal salivary testosterone after adjusting for the characteristics of neonates and mothers and day of saliva sampling. The salivary levels of testosterone and cortisol were higher in neonates than in mothers. A positive correlation between the levels of testosterone and cortisol was found in neonates and in mothers.The level of postnatal salivary testosterone is a more reliable marker in assessing neonatal health and growth outcomes compared to salivary cortisol. Further research on both testosterone and cortisol measurements at various stages during the neonatal period may elucidate further these associations.

The development of an accurate prognosis is an integral component of treatment planning in the practice of periodontics. Prior work has evaluated the validity of using various clinical measured parameters for assigning periodontal prognosis as well as for predicting tooth survival and change in clinical conditions over time. We critically review the application of multivariate Classification And Regression Trees (CART) for survival in developing evidence-based periodontal prognostic indicators. We focus attention on two distinct methods of multivariate CART for survival: the marginal goodness-of-fit approach, and the multivariate exponential approach. A number of common clinical measures have been found to be significantly associated with tooth loss from periodontal disease, including furcation involvement, probing depth, mobility, crown-to-root ratio, and oral hygiene. However, the inter-relationships among these measures, as well as the relevance of other clinical measures to tooth loss from periodontal disease (such as bruxism, family history of periodontal disease, and overall bone loss), remain less clear. While inferences drawn from any single current study are necessarily limited, the application of new approaches in epidemiologic analyses to periodontal prognosis, such as CART for survival, should yield important insights into our understanding, and treatment, of periodontal diseases.

Intelligent transportation systems–based lane management technologies were introduced to work zones in an attempt to reduce congestion and diminish queue lengths. Two forms of lane merging—the early merge and the late merge—were designed to advise drivers on definite merging locations. This study suggests two SDLMS—early merge and late merge—to supplement the current Florida Maintenance of Traffic (MOT) plans. Data were collected in work zones on I-95, Florida using three different traffic maintenance treatments. The first MOT plan treatment was the standard MOT used by the Florida Department of Transportation. The second MOT plan was the early SDLMS, and the third MOT was the late SDLMS. Results showed that the maximum queue discharge rate (or capacity) of the work zone was significantly higher for the early SDLMS compared to the conventional Florida Department of Transportation MOT plans. The late SDLMS did not result in significant increase in the work zone capacity. Moreover, results showed that early...

Although most cancer survivors are at risk for being lost in the transition from treatment to survivorship, rural breast cancer survivors face special challenges that might place them at particular risk. This small-scale preliminary study had 2 specific aims: (aim 1) establish the feasibility of rural breast cancer survivors participation in a longitudinal quality of life (QOL) intervention trial and (aim 2) determine the effects of the Breast Cancer Education Intervention (BCEI) on overall QOL. Fifty-three rural breast cancer survivors were randomized to either an experimental (n = 27) or a wait-control arm (n = 26). Participants in the experimental arm received the BCEI consisting of 3 face-to-face education and support sessions and 2 face-to-face and 3 telephone follow-up sessions, along with supplemental written and audiotape materials over a 6-month period. Breast Cancer Education Intervention modules and interventions are organized within a QOL framework. To address the possible effects of attention, wait-control participants received 3 face-to-face sessions and 3 telephone sessions during the first 6 months of participation in the study, but not the BCEI intervention. Research questions addressing aim 1 were as follows: (a) can rural breast cancer survivors be recruited into a longitudinal intervention trial, and (b) can their participation be retained. Research questions for aim 2 were as follows: (a) do participants who received the BCEI show improvement in overall QOL, and (b) is the QOL improvement sustained over time. Data were analyzed using repeated-measures general linear mixed models. Results demonstrated the ability to recruit and retain 53 rural breast cancer survivors, that the experimental arm showed improvement in overall QOL (P = .013), and that there were significant differences in overall QOL between the experimental and wait-control groups at both months 3 and 6. Thus, it appears that at least some rural breast cancer survivors can and will participate in a larger trial and will maintain their participation and that those that do participate experience significant QOL benefit.

Taking evasive actions vis-à-vis critical traffic situations impending to motor vehicle crashes endows drivers an opportunity to avoid the crash occurrence or at least diminish its severity. This study explores the drivers, vehicles, and environments' characteristics associated with crash avoidance maneuvers (i.e., evasive actions or no evasive actions). Rear-end collisions, head-on collisions, and angle collisions are analyzed separately using decision trees and the significance of the variables on the binary response variable (evasive actions or no evasive actions) is determined. Moreover, the random forests method is employed to rank the importance of the drivers/vehicles/environments characteristics on crash avoidance maneuvers. According to the exploratory analyses' results, drivers' visibility obstruction, drivers' physical impairment, drivers' distraction are associated with crash avoidance maneuvers in all three types of accidents. Moreover, speed limit is associated with rear-end collisions' avoidance maneuvers and vehicle type is correlated with head-on collisions and angle collisions' avoidance maneuvers. It is recommended that future research investigates further the explored trends (e.g., physically impaired drivers, visibility obstruction) using driving simulators which may help in legislative initiatives and in-vehicle technology recommendations.

Purpose/objectives To describe quality-of-life (QOL) changes in older women with early-stage breast cancer in the first year of survivorship and report on the effectiveness of a psychoeducational intervention on survivors' QOL. Design Secondary analysis, descriptive, repeated measure. Setting An academic setting in the southeastern United States. Sample 50 early-stage breast cancer survivors, aged 65 years and older. Methods Data were drawn from the Breast Cancer Education Intervention (BCEI) research study. Data for a six-month time period within the survivors' first year were available for an experimental group participating in a psychoeducational intervention and a control group. Main research variables Overall QOL and physical, psychological, social, and spiritual well-being subscales. Findings Older women reported positive overall QOL within the first year of survivorship, but overall QOL declined slightly over time. Physical and psychological well-being declined over time. Social well-being initially improved over time, but then declined. Spiritual well-being initially declined over time, then improved. Survivors had a downward trend in overall QOL during the study time period; however, experimental group participants had a smaller decline in QOL compared to control group participants. Conclusions QOL in older breast cancer survivors within the first year is positive. However, overall QOL declines over time. The BCEI attenuated decline of QOL in the experimental group compared to the control group. Implications for nursing Few studies focus on older breast cancer survivors. This descriptive study is one of the first to describe changes in QOL and report the effect of interventions for older breast cancer survivors. Oncology nurses are in a position to recognize QOL issues and help older women maintain QOL in the first year of survivorship after treatment.

Purpose/Objectives: To examine the effectiveness of a psychoeducational intervention on quality of life (QOL) in breast cancer survivors in post-treatment survivorship. Design: A randomized controlled trial. Setting: An academic center collaborating with a regional cancer center in the southeastern United States. Sampie: 256 breast cancer survivors. iVIethods: Women were randomly assigned to the experimental or wait control group. The Breast Cancer Education Intervention (BCEI) study was delivered in three face-to-face sessions and five monthly follow-up sessions (three by telephone and two in person). The control group received four monthly attention control telephone calls and the BCEI at month 6. Data were collected at baseline, three and six months after the BCEI for the experimental group, and one month after the BCEI (at month 7) for the wait control group. Main Research Variabies: Primary endpoints were overall QOL and physical, psychological, social, and spiritual well-being. Findings: No differences in QQL were reported at baseline between groups. The experimental group reported improved QOL at three months, whereas the wait control group reported a significant decline in QOL. The experimental group reported continued maintenance of QQL at six months. Although the wait control group reported improved QQL at six months, significant differences continued to exist between the groups. Conclusions: The BCEI was an effective intervention in improving QOL during the first year of breast cancer survivorship. Treatment effects were durable overtime. Impiications for Nursing: Post-treatment survivorship has not been ennpirically studied to a large degree. The BCEI is one of the few interventions demonstrating effectiveness among survivors after primary treatment, suggesting that oncology nurses may be uniquely positioned to provide safe passage using education and support.

A Q-band FWG TWT was developed with some special design strategies and techniques. The test result shows it can operate at continuous wave state. The saturated output power of the TWT is above 200 watts within 2GHz bandwidth and the overall efficiency is above 25%.

The primary purpose of this study was to systematically examine the effects of an 8-week controlled whole-body vibration training on reducing the risk of falls among community-dwelling adults. Eighteen healthy elderlies received vibration training which was delivered on a side alternating vibration platform in an intermittent way: five repetitions of 1 min vibration followed by a 1 min rest. The vibration frequency and amplitude were 20 Hz and 3.0mm respectively. The same training was repeated 3 times a week, and the entire training lasted for 8 weeks for a total of 24 training sessions. Immediately prior to (or pre-training) and following (or post-training) the 8-week training course, all participants' risk of falls were evaluated in terms of body balance, functional mobility, muscle strength and power, bone density, range of motion at lower limb joints, foot cutaneous sensation level, and fear of falling. Our results revealed that the training was able to improve all fall risk factors examined with moderate to large effect sizes ranging between 0.55 and 1.26. The important findings of this study were that an 8-week vibration training could significantly increase the range of motion of ankle joints on the sagittal plane (6.4° at pre-training evaluation vs. 9.6° at post-training evaluation for dorsiflexion and 45.8° vs. 51.9° for plantar-flexion, p0.05 for both); reduce the sensation threshold of the foot plantar surface (p0.05); and lower the fear of falling (12.2 vs. 10.8, p0.05). These findings could provide guidance to design optimal whole-body vibration training paradigm for fall prevention among older adults.

We propose a method of constructing regression trees within the framework of maximum likelihood. It inherits the backward fitting idea of classification and regression trees (CART) but has more rigorous justification. Simulation studies show that it provides more accurate tree model selection compared to CART. The analysis of a baseball dataset is given as an illustration.

A Q-band Traveling-Wave Tube was fabricated with folded waveguide (FWG) as its slow wave structure (SWS). The device can deliver 200 Watts power from 43.5 to 45.5 GHz. The electron efficiency is more than 8 % and the total efficiency is more than 25% with one stage depression collector. The test result shows it will be a promising high power millimeter wave source.

Background and purpose of the study The goal was to evaluate and compare the effects of aqueous extract of the seeds of chicory, Cichorium intybus L., on glucose tolerance test (GTT) and blood biochemical indices of experimentally-induced hyperglycemic rats. Methods Late stage and early stage of Type 2 diabetes mellitus (T2DM) were induced in rats by streptozotocin (STZ) and a combination of STZ and niacinamide (NIA/STZ), respectively. Within each group, one subgroup received daily i. p. injections of chicory extract (125 mg/kg body weight, for 28 days). Body weight and fasting blood sugar (FBS) were measured weekly. Blood was analyzed for glycosylated hemoglobin (HbA1c) and sera for alanine aminotransferase (ALT), aspartate aminotransferase (AST), nitric oxide (NO), triacylglycerol (TG), total cholesterol (TC), total protein, and insulin on days 10 and 28 after treatment. Intraperitoneal glucose tolerance test (IPGTT) along with insulin determination was performed on a different set of rats in which the chicory-treated groups received the extract for 10 days. Results During 4 weeks of treatment, chicory prevented body-weight loss and decreased FBS. ALT activities and levels of TG, TC and HbA1c decreased, and concentration of NO increased in the chicory treated groups (p < 0.05). Unlike late-stage diabetes, fasting serum insulin concentrations were higher and GTT pattern approximated to normal in chicory-treated early-stage diabetic rats. Conclusions Chicory appeared to have short-term (about 2 hours, as far as GTT is concerned) and long-term (28 days, in this study) effects on diabetes. Chicory may be useful as a natural dietary supplement for slowing down the pace of diabetes progress, and delaying the development of its complications.

GLP-1 and its analog have been used in diabetes treatment; however, the direct alteration of gene expression profile in human islets induced by GLP-1 has not been reported. In present study, transcriptional gene expression in the liraglutide-treated human islets was analyzed with 12 human U133A chips including 23000 probe sets. The data compared between liraglutide and control groups showed a significant difference on glucose-induced insulin secretion, rather than viability. Microarray analysis identified 7000 genes expressed in human islets. Eighty genes were found to be modulated by liraglutide treatment. Furthermore, the products of these genes are proteins involved in binding capability, enzyme activity, transporter function, signal transduction, cell proliferation, apoptosis, and cell differentiation. Our data provides a set of information in the complex events, following the activation of the GLP-1 receptor in the islets of Langerhans.

Endotracheal tube cuff pressure must be kept within an optimal range that ensures ventilation and prevents aspiration while maintaining tracheal perfusion.To test the effect of an intervention (adding or removing air) on the proportion of time that cuff pressure was between 20 and 30 cm H(2)O and to evaluate changes in cuff pressure over time.A repeated-measure crossover design was used to study 32 orally intubated patients receiving mechanical ventilation for two 12-hour shifts (randomized control and intervention conditions). Continuous cuff pressure monitoring was initiated, and the pressure was adjusted to a minimum of 22 cm H(2)O. Caregivers were blinded to cuff pressure data, and usual care was provided during the control condition. During the intervention condition, cuff pressure alarm or clinical triggers guided the intervention.Most patients were men (mean age, 61.6 years). During the control condition, 51.7% of cuff pressure values were out of range compared with 11.1% during the intervention condition (P.001). During the intervention, a mean of 8 adjustments were required, mostly to add air to the endotracheal tube cuff (mean 0.28 [SD, 0.13] mL). During the control condition, cuff pressure decreased over time (P.001).The intervention was effective in maintaining cuff pressure within an optimal range, and cuff pressure decreased over time without intervention. The effect of the intervention on outcomes such as ventilator-associated pneumonia and tracheal damage requires further study.

This paper applies a nonparametric statistical method, hierarchical tree-based regression (HTBR), to explore train-vehicle crash prediction and analysis at passive highway-rail grade crossings. Using the Federal Railroad Administration (FRA) database, the research focuses on 27 years of train-vehicle accident history in the United States from 1980 through 2006. A cross-sectional statistical analysis based on HTBR is conducted for public highway-rail grade crossings that were upgraded from crossbuck-only to stop signs without involvement of other traffic-control devices or automatic countermeasures. In this study, HTBR models are developed to predict train-vehicle crash frequencies for passive grade crossings controlled by crossbucks only and crossbucks combined with stop signs respectively, and assess how the crash frequencies change after the stop-sign treatment is applied at the crossbuck-only-controlled crossings. The study results indicate that stop-sign treatment is an effective engineering countermeasure to improve safety at the passive grade crossings. Decision makers and traffic engineers can use the HTBR models to examine train-vehicle crash frequency at passive crossings and assess the potential effectiveness of stop-sign treatment based on specific attributes of the given crossings.

We propose an interaction tree (IT) procedure to optimize the subgroup analysis in comparative studies that involve censored survival times. The proposed method recursively partitions the data into two subsets that show the greatest interaction with the treatment, which results in a number of objectively defined subgroups: in some of them the treatment effect is prominent while in others the treatment may have a negligible or even negative effect. The resultant tree structure can be used to explore the overall interaction between treatment and other covariates and help identify and describe possible target populations on which an experimental treatment demonstrates desired efficacy. We follow the standard CART (Breiman, et al., 1984) methodology to develop the interaction tree structure. Variable importance information is extracted via random forests of interaction trees. Both simulated experiments and an analysis of the primary billiary cirrhosis (PBC) data are provided for evaluation and illustration of the proposed procedure.

This paper provides explicit sample size determination formulas for planning a long-term trial in patients with chronic disease by using available results from existing short-term studies that may predict long-term disease progression patterns. The sample size calculation formulas are flexible to incorporate different nonlinear disease progression patterns. Various within-patient correlation structures are considered. By using the proposed formulas, sample size sensitivity can be easily explored for possible choices of study duration, assumed nonlinear disease progression patterns, randomization ratio, and expected clinical meaningful difference in the end of study. In addition, sample size calculation formulas are provided when the primary endpoint is change from baseline. Discussions on the relationship among required sample size, study duration, randomization ratio are also included.