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The metal-organic frameworks-derived carbon-based electromagnetic wave (EMW) absorbing (EMWA) materials have attracted extensive attention. However, it still maintains a challenge to design the kind of materials with wide effective absorption bandwidth (EAB). Herein, a series of reduced graphene oxide (RGO) supported symmetrical lotus-like cobalt/manganese oxide/porous carbon (Co/MnO/PC/RGO) composites were synthesized by hydrothermal method and subsequent carbonization process. Impressively, the symmetrical porous structure and the special component could synergistically improve EMWA capacity. On the one hand, the symmetrical porous structure and magnetic component could optimize impedance matching, which were conducive to more EMW entering into the sample. On the other hand, the abundant heterointerfaces enhanced the interface polarization and the EMWA performance of the sample could be also regulated by the change of GO content in the mixture. When the GO content was 9 wt%, a minimum reflection loss value of −50.1 dB and the corresponding EAB value of 5.1 GHz (11.9–17.0 GHz) was achieved at a thickness of 2.0 mm. The excellent EMW performance of the sample stemmed from the increased dielectric loss and magnetic loss as well as improved impedance matching. As a consequence, this work authenticated a novel pathway to construct the carbon-based EMW absorbers with broad EAB. [Display omitted] [ABSTRACT FROM AUTHOR]

The tunable multicomponent synergistic loss mechanism and multiple heterogeneous interfaces of magnetic carbon-based composites have emerged as the efficient electromagnetic wave absorbing (EMWA) materials. Herein, the Ni(OH) 2 /ZIF-67 precursors were synthesized via the hydrothermal and liquid-phase deposition methods, and then carbonized at different temperature under N 2 atmosphere to obtain Co@nitrogen-doped carbon/Ni (Co@NC/Ni) nanocomposites. The metallic components with good dispersion property provided magnetic loss and improved impedance matching. Meanwhile, they also acted as catalysts to induce the formation of graphitized carbon, enhancing the conductive loss. Furthermore, more heterogeneous interfaces and defects were generated inside the sample, which promotes dielectric loss. Therefore, the Co@NC/Ni nanocomposite (carbonized at 600 °C) exhibited excellent EMWA performance with a minimum reflection loss (RL) of −47.10 dB, and the effective absorption bandwidth (RL ≤ −10 dB) can reach 6.84 GHz at 2.5 mm with a filling ratio of 30%. This work provides a heterogeneous interface construction strategy for the future application of high-performance magnetic carbon based EMWA materials. [Display omitted] • The Co@NC/Ni nanocomposites were prepared by the facile methods. • The structural, magnetic and microwave absorption properties of composites were investigated. • The Co@NC/Ni nanocomposites exhibited excellent microwave absorption properties. [ABSTRACT FROM AUTHOR]

Low-frequency electromagnetic wave absorption (EMWA) materials were crucial for addressing electromagnetic pollution and radar stealth. However, achieving low-frequency and broadband absorption still faces challenges. In this work, a succession of CoO/Co 9 S 8 /N-doped carbon (NC) composites were fabricated via a partial sulfidation strategy of Co-Prussian blue analogue (Co-PBA). The as-prepared CoO/Co 9 S 8 /NC composites featured a porous architecture. The electromagnetic parameters were effectively modulated via varying the sulfidation time. When the sulfidation time was 9 h, the minimum reflection loss (RL min) value was −50.40 dB at 2.93 mm and a maximum effective absorption bandwidth value was 5.76 GHz (12.24–18.00 GHz) at 1.80 mm. Notably, when the sulfidation time was 12 h, the composites exhibited enhanced EMWA capability in the low-frequency S-band (3.52 GHz) with an RL min value of −28.91 dB. The superior EMWA performance of composites were primarily attributed to appropriate dielectric constants and optimized impedance matching due to magnetic loss. Moreover, the radar cross section simulation consequences further verified that dissipation capability of electromagnetic wave of the CoO/Co 9 S 8 /NC composites in the actual far field. This work afforded novel perspectives into the rational develop of PBA-derived carbon-based EMWA materials with the low-frequency and broadband absorption. [Display omitted] • The CoO/Co 9 S 8 /NC composites were obtained using a partial sulfidation strategy. • The electromagnetic parameters were effectively adjusted by varying the sulfidation time. • The composites showed an RL min value of −28.91 dB at low-frequency (3.52 GHz), and a maximum effective absorption bandwidth value was 5.76 GHz. [ABSTRACT FROM AUTHOR]

This study examined the relationship between frequent social media use and subsequent mental health in a representative sample of US adolescents. Also investigated were sex differences in multiyear growth trajectories of mental health problem internalization relative to social media use. Four waves (2013–2018) of nationally representative, longitudinal Population Assessment of Tobacco and Health data were analyzed. A total of 5,114 US adolescents aged 12–14 years at baseline had repeated data across all waves. Statistical analysis involved testing a series of sequential-weighted single-group and multi-group latent growth curve models using R version 3.6.2. Of the 5,114 respondents, 2,491 were girls (48.7%). The percentage of frequent social media use was 26.4% at Wave 1 and 69.1% at Wave 4 for boys compared to 38.3% and 80.6% for girls (p <.001). Boys showed an improving (−0.218, p =.005) but girls showed a deteriorating linear trend (0.229, p =.028) for mental health at the full multigroup latent growth curve model. Social media use accounted for mental health conditions across Waves 1–3 for boys (p s<.01) but only at Wave 1 for girls (p =.035). With the addition of the social media use variable alone, model fit dramatically improved, and residual variances in growth patterns (i.e., random effect) became nonsignificant for boys. Substantial sex differences existed in baseline status, directionality, and shape of mental health growth trajectories as well as interplay of social media use with other factors. Findings of the study suggest that frequent social media use is associated with poorer subsequent mental health for adolescents. [ABSTRACT FROM AUTHOR]

Molybdenum selenide (MoSe 2) with the diverse crystal structures and unique electronic characteristics were restricted in field of the electromagnetic wave (EMW) absorbing (EMWA) owing to the poor electrical conductivity and easy agglomeration. Herein, a series of N-doped carbon (NC) coupled with MoSe 2 nanosheets composites were synthesized via a brief selenization process of the self-polymerized Mo-polydopamine precursor. The as-prepared MoSe 2 /NC composites with good dispersibility exhibited the shape of ball-flower-like with a diameter ranging from 400 to 900 nm. Significantly, the electromagnetic parameters, the electrical conductivity, and N-doped defect rate could be effectively adjusted by varying the selenization temperature. As the temperature increased, the EMWA property of MoSe 2 /NC composites revealed a trend of first increasing and then decreasing. At 800 °C, the MoSe 2 /NC composites showed a minimal reflections loss value of −50.56 dB at 2.53 mm and covered a maximum effective absorption band value of 5.76 GHz at 2.0 mm with a filling ratio of 30 wt%. The enhanced EMWA performance stemmed from reinforced conductive loss, enriched polarization relaxation processes, optimized impedance matching, and porous characteristics. Furthermore, the radar cross section simulation results confirmed the MoSe 2 /NC composites coatings possessed superb EMWA capacity. This work provided a straightforward approach for designing highly efficient MoSe 2 -based EMW absorbers. [Display omitted] • A series of N-doped carbon coupled with MoSe 2 nanosheets composites were synthesized. • The heterostructures boosted interfacial polarization and optimized impedance matching characteristic. • The composites showed a minimal RL value of −50.56 dB at 2.53 mm and covered a maximum EAB value of 5.76 GHz at 2.0 mm. [ABSTRACT FROM AUTHOR]

Introduction: Although risk factors often co-occur, previous studies examining lifestyle or psychosocial factors often treat these factors as individual predictors of health. This study aims to identify the underlying subgroups of women characterized by distinct lifestyle and psychosocial risk patterns and to investigate the prospective associations between risk patterns and mortality among postmenopausal women.Methods: A total of 64,812 postmenopausal women aged 50-79 years without prevalent diabetes, cardiovascular disease, and cancer at baseline (1993-1998) were followed until 2019 with a mean follow-up duration of 14.6 (SD=6.4) years. Latent class analysis was used to identify the latent classes of women with homogeneous combinations of lifestyle and psychosocial variables and to test whether the classes were prospectively associated with mortality. Analyses were stratified by race/ethnicity and were performed in 2020.Results: A total of 4 latent classes (Healthy Lifestyle and Psychosocial, Risky Psychosocial, Risky Lifestyle, and Risky Lifestyle and Risky Psychosocial) were identified for Hispanic, Black, and White women, and 2 classes (High Risk or Low Risk) were identified for American Indian and Asian women. Women in the Risky Lifestyle and Risky Psychosocial group had the highest hazard ratios for all outcomes studied for all race/ethnicity groups than those in the Healthy Lifestyle and Psychosocial group, followed by those in the Risky Lifestyle group. Risky Psychosocial class was significantly associated with an elevated risk of overall and cardiovascular disease mortality only in Black women.Conclusions: The class with concurrent risky lifestyle and psychosocial factors conveyed the greatest risk of all types of mortality than a low-risk ref group. Health promotion should address both behavioral and psychosocial risks concurrently. [ABSTRACT FROM AUTHOR]

Background and Aims: Little is known about how weight trajectories among women during menopausal transition and beyond may be related to risk of type 2 diabetes mellitus (T2DM). The aim of this study was to examine associations between body mass index (BMI) trajectories over 20 years, age of obesity onset, cumulative obese-years and incidence of T2DM among middle-aged women.Methods and Results: 12,302 women enrolled in the Australian Longitudinal Study on Women's Health (ALSWH) were surveyed in 1996 (Survey 1, age 45-50), 1998 and then every three years to 2016. Self-reported weight and height were collected for up to eight time points. Incident diabetes was assessed via validated self-report of physician-diagnosed diabetes. Growth mixture models were used to identify distinct BMI trajectories. A total of 1380 (11.2%) women newly developed T2DM over an average 16 years of follow-up. Seven distinct BMI trajectories were identified with differential risk of developing T2DM. Initial BMI was positively associated with T2DM risk. We also observed that risk of T2DM was positively associated with rapid weight increase, early age of obesity onset and greater obese-years.Conclusion: Slowing down weight increases, delaying the onset of obesity, or reducing cumulative exposure to obesity may substantially lower the risk of developing T2DM. [ABSTRACT FROM AUTHOR]

Abstract Background People experience multiple co-occurring exposures to environmental pollutants, but analyses of multiple exposures have rarely been reported. Objectives We used latent class analysis to estimate co-exposures to multiple polycyclic aromatic hydrocarbons (PAH), and tested the associations of latent classes to body mass index. Methods We analyzed National Health and Nutrition Examination Survey (NHANES) 2013–2014 data. The sample included 2354 people aged 6–80 years. Measures included seven urinary PAH metabolites, BMI, and demographic and behavioral covariates. People were classified into mutually exclusive latent classes characterized by unique profiles of multiple PAH exposures. These classes were used as categorical independent variables in weighted multiple regression models with BMI as the dependent measure. Models were analyzed overall and by age groups (6–19, 20–59, and 60 and over.) We compared results using latent classes to results using a summed PAH exposure measure. Results Five latent classes were identified. Two of these classes were significantly associated with higher BMI overall (p <.0001) and for the two youngest age groups. One of these classes was characterized by high multiple exposures across all PAHs, and one by moderate exposures but relatively high naphthalene and phenanthrene. The summed PAH score was associated with higher BMI only for the youngest age group. Conclusions Persons experience multiple co-exposures to PAHs that are related to BMI and obesity across age groups. Latent class analysis provides information on higher order interactions among multiple chemicals that a summed score does not. Future work may apply this approach to other outcomes or types of co-exposures. Highlights • Latent class analysis identified patterns of multiple co-occurring exposures to polycyclic aromatic hydrocarbons. • Five latent classes were identified characterized by unique exposure profiles. • Two classes representing multiple co-exposures were associated with higher body mass index in children and adults. • Latent class analysis provides a possible method for the study of multiple co-occurring environmental exposures. [ABSTRACT FROM AUTHOR]

In this paper, La-Ni substituted barium ferrite nanoparticles were prepared by a co-precipitation method. The morphology, structure, magnetic and microwave absorption properties of samples were accomplished by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), transmission electron microscope (TEM), vibrating sample magnetometer (VSM) and vector network analysis. From the results evaluation, it can be seen that the magnetoplumbite structure for all of the samples have been formed and the average crystallite sizes of Ba 1−x La x Fe 12−x Ni x O 19 nanoparticles within in the range of 50.9–65.5 nm. Ba 0.9 La 0.1 Fe 11.9 Ni 0.1 O 19 exhibits a remarkable reflection loss of −13.5 dB at 13.05 GHz with a matching thickness of 1.5 mm. The reflection loss results indicate that Ba 0.9 La 0.1 Fe 11.9 Ni 0.1 O 19 nanoparticles may be used as a potential for thin microwave absorbers. [ABSTRACT FROM AUTHOR]

With the increasing problem of eutrophication, lacustrine ecosystem can undergo complex changes, often resulting in a shift from a clear macrophyte-dominated state to a turbid phytoplankton-dominated state. However, it's not clear how lake transitions occur at regional and global scales. This is due to a lack of long-term monitoring and an effective algorithm that can distinguish floating/emergent aquatic vegetation (FEAV), submerged aquatic vegetation (SAV) and algal bloom (AB). This paper presents a novel three-step classification algorithm based on Landsat imagery, (ie., vegetation and bloom indices (VBI) algorithm): (1) to distinguish between aquatic vegetation (AV) and non-aquatic vegetation (non-AV) extents by an aquatic vegetation index (AVI) derived from tasseled cap transformation; (2) to identify FEAV and SAV within AV extent by using the normalized difference vegetation index (NDVI), and (3) to extract AB from non-AV extent with floating algae index (FAI). The performance of the VBI algorithm was validated using 1307 field samples collected across 22 lakes in the middle and lower reaches of the Yangtze River (MLY) in China, with a pooled overall accuracy of 84.49%. Finally, the VBI algorithm was applied to Landsat data from 1985 to 2021 to quantify the temporal changes of FEAV, SAV and AB in large lakes (i.e., > 50 km2) along the MLY. Within these lakes, AV showed a significant decrease over the past 37 years, mainly due to the decrease of SAV; while AB occurred with higher frequency and in more lakes. The transition from a macrophyte-dominated state to a phytoplankton-dominated aquatic systems is still ongoing in the MLY area. This study shows outstanding innovation in the construction of a new classification index (i.e., AVI), and the method of calculating the adaptive threshold, which makes VBI algorithm have great potential in mapping long-term changes and capturing transformation between lake communities on a global scale. • A novel Landsat-based algorithm was developed for quantifying aquatic communities. • An index for aquatic vegetation (AV) was proposed to classify AV and non-AV. • Long-term algal blooms and AV (floating/emergent/submerged) in MLY lakes were mapped. • AV decreased while algal blooms increased in most MLY lakes from 1985 to 2021. • Shift from macrophyte- to phytoplankton-dominated state is ongoing in MLY lakes. [ABSTRACT FROM AUTHOR]

Cognitive impairment imposes substantial psychological, emotional, and economic burdens on affected individuals, families and society. A better understanding of potentially modifiable risk factors that may be used in the prevention of cognitive impairment is therefore a high priority in aging research. This study included 9268 community-dwelling women aged 65 years or older from the Study of Osteoporotic Fractures launched between 1986 and 1988 in the US. Participants were followed for 20 years. Modified Mini-Mental State Examination (m-MMSE) was administered up to 6 times. Six updated measurements of gait speed and handgrip strength at the same visit time when m-MMSE was administered were used. The m-MMSE score was used to define cognitive impairment states (normal, mild, and severe impairment). A multi-state model (MSM) was used to estimate the transitions between different states of cognitive function. Faster gait speed (one unit increase of meter/s) was associated with lower risk of transition from cognitively normal status to mild cognitive impairment (HR = 0.50, 95 % CI: 0.37–0.67), and from mild impairment to severe impairment (HR = 0.52, 95 % CI: 0.37–0.72). Higher gait speed was associated with increased risk of cognitive transition from severe impairment to mild impairment (HR = 2.56 95 % CI: 0.97–6.77), although the result did not reach statistical significance. Similarly, we observed greater handgrip strength (per kg increase) was associated with lower risk of transition of cognitive status from normal to mild impairment (HR = 0.96 95 % CI: 0.95–0.97), and from mild to severe impairment (HR = 0.98, 95 % CI: 0.96–0.99). Greater handgrip strength was associated with increased risk of cognitive transition from severe to mild cognitive impairment (HR = 1.05, 95 % CI: 1.01–1.09). In addition, we also observed that both faster gait speed and greater handgrip strength were associated with lower risk of transitions from normal or mild cognitive impairment status to death. Our results confirmed that screening for slow gait speed or weak handgrip strength may be useful for identifying older adults at risk for cognitive decline when they are still cognitively normal or only mildly impaired. Exercise programs to improve gait speed and muscle strength may delay or prevent transitions into cognitive impairment in older adults. • Faster gait speed was associated with lower progression of cognitive impairment. • Slow gait speed may be used as an early sign for cognitive decline in older adults. • Greater handgrip strength was also associated with lower progression. • Exercise programs to improve gait speed and muscle strength are recommended. [ABSTRACT FROM AUTHOR]

Remote sensing images are widely used to map leaf area index (LAI) continuously over landscape. The objective of this study is to explore the ideal image features from Chinese HJ-1 A/B CCD images for estimating winter wheat LAI in Beijing. Image features were extracted from such images over four seasons of winter wheat growth, including five vegetation indices (VIs), principal components (PC), tasseled cap transformations (TCT) and texture parameters. The LAI was significantly correlated with the near-infrared reflectance band, five VIs [normalized difference vegetation index, enhanced vegetation index (EVI), modified nonlinear vegetation index (MNLI), optimization of soil-adjusted vegetation index, and ratio vegetation index], the first principal component (PC1) and the second TCT component (TCT2). However, these image features cannot significantly improve the estimation accuracy of winter wheat LAI in conjunction with eight texture measures. To determine the few ideal features with the best estimation accuracy, partial least squares regression (PLSR) and variable importance in projection (VIP) were applied to predict LAI values. Four remote sensing features (TCT2, PC1, MNLI and EVI) were chosen based on VIP values. The result of leave-one-out cross-validation demonstrated that the PLSR model based on these four features produced better result than the ten features’ model, throughout the whole growing season. The results of this study suggest that selecting a few ideal image features is sufficient for LAI estimation. [ABSTRACT FROM AUTHOR]

Knowledge of the composition and areal distribution of aquatic vegetation types, as well as their seasonal and interannual variations, is crucial for managing and maintaining the balance of lake ecosystems. In this study, a series of remotely sensed images with a resolution of 30 m (HJ-CCD and Landsat TM) were collected and used to map the distribution of aquatic vegetation types in Taihu Lake, China. Seasonal and interannual dynamics of aquatic vegetation types were explored and analyzed. The distribution areas of Type I (emergent, floating-leaved and floating vegetation) and Type II (submerged vegetation) were used to model their growing season phenology by double logistic functions. The resulting double logistic models showed, the area of Type I reached its peak in mid-August, and the maximum area for Type II occurred in mid-September. From 1984 to 2013, Type I area increased continuously from 59.75 km 2 to 148.00 km 2 ( R 2 = 0.84), whereas the area covered by Type II first increased and then decreased, with a trend conforming to a significant quadratic curve ( R 2 = 0.83). The eutrophication and stable state of Taihu Lake was assessed using a simple indicator which was expressed as a ratio of Type II area to Type I area. The results showed that the eutrophication in the lake might have been increasing in the area studied since 2000. Additionally, the results showed that air temperature had likely a direct effect on the growth of Type I ( R 2 = 0.66) and a significant, but delayed, effect on the growth of Type II. [ABSTRACT FROM AUTHOR]

A ternary composite which was composed of reduced graphene oxide (R-GO), Fe 3 O 4 porous nanospheres (P–Fe 3 O 4 ) and polyaniline (PANI) was synthesized by a facile route. The microstructure of the composite was characterized by XRD, FT-IR, FESEM and TEM. The results indicated that the uniform Fe 3 O 4 porous nanospheres with the average size of 250–400 nm were grown on R-GO sheets and the coating layer of PANI covered over the surface of R-GO/P–Fe 3 O 4 composite. With the decreasing content of Fe 3 O 4 , the saturation magnetization of this ternary composite declined while the coercivity showed the opposite trend. The composite showed excellent microwave absorption properties due to the good impedance match characteristic between dielectric loss and magnetic loss. The minimum reflection loss value reached −29.51 dB at 14.69 GHz with thickness of 1.0 mm. [ABSTRACT FROM AUTHOR]

M-type strontium ferrite substituted by RE (RE=Sm 3+ , Er 3+ ) were prepared via a sol–gel method. Polypyrrole (PPy)/ferrite nanocomposites (with 20 wt% ferrite) were prepared by in situ polymerization method in the presence of ammonium persulfate. Effect of the substituted RE ions on structure, magnetic properties and microwave absorption properties were investigated by X-ray diffraction (XRD), vibrating sample magnetometer (VSM) and vector network analyzer. All XRD patterns show the single phase of strontium hexaferrite without other intermediate phases. The crystallite size of synthesized particle is within the range of 22.2–38.1 nm. The structural in character of the composites were investigated with FT-IR analysis. It shows that the ferrite successfully packed by PPy. TEM photographs show that the particle size had grown up to 50–100 nm after coating with PPy. In the magnetization for the PPy/SrSm 0.3 Fe 11.7 O 19 (SrEr 0.3 Fe 11.7 O 19 ) composites, the coercivity ( H c ) of the composites both increased compared with the undoped composite while the saturation magnetization ( M s ) appeared opposite change with different RE ions. Considering the electromagnetic loss and impedance matching comprehensively, the Er-doped ferrite/PPy composite got the better microwave absorption performance with the maximum RL value of −24.01 dB in 13.8 GHz at 3.0 mm. And its width (<−10 dB) has reached 7.2 GHz which has covered the whole Ku band. [ABSTRACT FROM AUTHOR]

Sm-doped strontium ferrite nanopowders (SrSm 0.3 Fe 11.7 O 19 ) and their composites of polyaniline (PANI)/SrSm 0.3 Fe 11.7 O 19 with 10 wt% and 20 wt% ferrite were prepared by a sol–gel method and an in-situ polymerization process, respectively. The structure, magnetic properties and microwave absorption properties of the samples were characterized by means of X-ray diffraction (XRD), Fourier transform infrared spectra (FT-IR), transmission electron microscope (TEM), vibrating sample magnetometer (VSM) and vector network analyzer, respectively. The particle size of SrSm 0.3 Fe 11.7 O 19 was about 35 nm by using XRD. The ferrite successfully packed by PANI. PANI/SrSm 0.3 Fe 11.7 O 19 possessed the best absorption property with the optimum matching thickness of 3 mm in the frequency of 2–18 GHz. The value of the maximum reflection loss (RL) were −26.0 dB at 14.2 GHz with the 6.5 GHz bandwidth and −24.0 dB at 13.8 GHz with the 7.9 GHz bandwidth for the samples with 10 wt% and 20 wt% ferrite, respectively. [ABSTRACT FROM AUTHOR]

The occurrence and prevalence of wheat aphid has severe impact on wheat quality and bring about wheat yield loss. Infestation models commonly based on in situ meteorological data can be effective, but are usually lacking spatialized information, which could be provided using multispectral remote sensing datasets. The purpose of this study was to develop a prediction model for aphid occurrence probability by combining remote sensing images and meteorological data in a logistic regression based framework. In such framework, the predictor variables are: land surface temperature (LST), normalized difference vegetation index (NDVI) and perpendicular drought index (PDI) derived from satellite remote sensing image and temperature, precipitation and wind speed coming from meteorological stations. Logistic regression estimated predictor coefficients showed that LST was the most important factor inducing aphid occurrence, followed by NDVI, temperature, precipitation, wind speed and PDI. The prediction accuracy of the model was evaluated by calculating receiver operating characteristics (ROC) against reference data, scoring a value of area under the ROC curve of 0.993, and resulting in an overall predicted accuracy of 94.4% for the estimated subset. In addition, the results suggested that the probability of aphid occurrence obtained by the logistic regression model had a positive correlation with aphid damage level from field data. Based on the validation subset, it was observed that there were lower omission error with 23.68 and commission error with 23.81% and higher overall accuracy with 75.61% when the cut-off probability ( p ) value was 0.45. The model developed can be a useful tool to predict aphid occurrence and incidence over winter wheat with some advance, and it could be effective in protecting winter wheat from aphid infestation. [ABSTRACT FROM AUTHOR]

Abstract: The preparation and magnetic properties of nanosize Ce3+ added MgCuZn ferrite powders have been investigated. The obtained powders were investigated by using X-ray diffraction (XRD), scanning electron microscope (SEM) and vibrating sample magnetometer (VSM) techniques. High energy ball milling enabled result in direct formation of single phase MgCuZn ferrite powders at a low temperature (700°C). Lattice constants (a) and crystallite size were calculated from the XRD data. The values of lattice constants increased with an increase of Ce2O3. The crystallite sizes were in the range of 35–50nm. The saturation magnetization (M s) increased with the addition of Ce2O3. [Copyright &y& Elsevier]

Abstract: Diabetes has been consistently linked to many forms of cancers, such as liver, colorectal, pancreatic, and breast cancer, however, the role of diabetes in outcome among cancer patients remains unclear. In this study, we retrospectively reviewed electronic medical records of 342 inpatients newly diagnosed with NSCLC referred by a teaching hospital cancer center in southern Taiwan between 2005 and 2007 to examine the effects of fasting glucose levels at time of cancer diagnosis on overall survival in patients with non-small cell lung cancer (NSCLC). All patients were followed up until the end of 2010. The Kaplan–Meier method was used to compare survival curves for patients with and without diabetes. The Cox proportional hazards model was used to estimate hazard ratios for the association between diabetes, other prognostic factors and patient survival. We observed that significant prognostic factors for poor overall survival in patients with NSCLC included older age, smoking, poor performance status, advanced stage (stage IIIB or IV), and no cancer-directed surgery treatment. Particularly, we identified that diabetic state defined by fasting blood glucose level ≥126mg/dl was another independent prognostic factor for these patients. Compared with those who had normal range of fasting glucose level (70–99mg/dl), patients with high fasting glucose level (≥126mg/dl) had 69% excess risk of all-cause mortality in patients with NSCLC. In conclusion: Diabetes as indicated by elevated fasting blood glucose was independently associated with a significantly higher risk of all-cause mortality in patients with NSCLC, indicating that diabetes or hyperglycemia effectively controlled may present an opportunity for improving prognosis in NSCLS patients with abnormal glucose level. [Copyright &y& Elsevier]