UNASSIGNED: Currently, the linkage between high-risk fertility behavior of birth and the occurrence of stunting among children under the age of 5 continues to be a significant public health problem in developing countries, including Ethiopia. This issue poses a threat to the health and overall wellbeing of under-five children. Thus, the main objective of this study was to examine the association between high-risk fertility behavior of birth and the stunting status of children and associated factors.
UNASSIGNED: The data used for this study were extracted from the recent Ethiopian Mini Demographic and Health Survey data in 2019. A total weighted sample of 4,969 under-five children was included in this study, and the relevant data were extracted from those samples. The multilevel bivariate analysis was used to assess the association between high-risk fertility behavior of birth and the stunting status of under-five children in Ethiopia.
UNASSIGNED: It was found that, out of 4,997 under-five children, 24% of under-five children experienced stunting as a result of high-risk fertility behavior of birth. Our study also revealed an intra-class correlation of 0.2, indicating that 20% of the variability in both high-risk fertility behaviors of birth and stunting can be attributed to differences between communities. Furthermore, there was a statistically significant association between high-risk fertility behavior of birth and the stunting status of children under the age of 5 years [AOR = 8.5, 95% CI: (5.58, 18.70)]. Similarly, the stunting status of birth among boys was 1.36 times greater than the estimated odds of the stunting status of birth among girls [AOR = 1.36, 95% CI: (1.19, 1.55)].
UNASSIGNED: This study found that there was a significant statistical association between high-risk fertility behavior of birth and stunting status of under-five children. Specifically, children born to mothers under 18 years and in households with high parity were identified as the main risk factors for child stunting. Furthermore, health-related education, improved access to maternal healthcare, and training interventions were associated with high-risk fertility behavior during birth and child stunting. The study suggests that regular health assessments and early interventions for infants born to mothers with high-risk reproductive characteristics are crucial to reducing the impact of child stunting under 5 years of age.

Ten novel spectrophotometric approaches were developed for the initial examination of the Hydroxychloroquine and Paracetamol medications. These procedures are straightforward, specific, easy to use, and provide exact and accurate results. The determination was conducted through the utilization of several approaches, including zero order (dual wavelength, zero crossing, advanced absorption subtraction and spectrum subtraction), derivative (first derivative of zero crossing), ratio (ratio difference, ratio derivative) and mathematical (bivariate, simultaneous equation, and Q-absorbance) techniques. After undergoing validation in accordance with ICH criteria, it was established that each of these methods achieved acceptable levels of precision, repeatability, robustness, and accuracy. The advantages and disadvantages of each method are demonstrated, and the proposed and reported methodologies were statistically compared.

Four simple, specific, easy, precise and accurate spectrophotometric methods were developed for the first time to examine ciprofloxacin and metronidazole in combination, without having been separated beforehand by the developed methods. Ciprofloxacin and metronidazole were determined by utilizing advanced absorbance subtraction (AAS), spectrum subtraction, bivariate and ratio difference methods. Precision, repeatability, robustness, and accuracy were all determined to be within acceptable levels after each of these procedures underwent validation in accordance with ICH recommendations. Each method\'s benefits and drawbacks are illustrated, and the proposed and reported methodologies were statistically compared.

There have been few studies on associations between age-related declines in fluid cognition and functional ability in population-representative samples of middle-aged and older adults. We used a two-stage process (longitudinal factor analysis followed by structural growth modeling) to estimate bivariate trajectories of age-related changes in general fluid cognition (numeracy, category fluency, executive functioning, and recall memory) and functional limitation (difficulties in daily activities, instrumental activities, and mobility). Data came from the Health and Retirement Study (Waves 2010-2016; N = 14,489; ages 50-85 years). Cognitive ability declined on average by -0.05 SD between ages 50-70 years, then -0.28 SD from 70-85 years. Functional limitation increased on average by +0.22 SD between ages 50-70 years, then +0.68 SD from 70-85 years. Significant individual variation in cognitive and functional changes was observed across age windows. Importantly, cognitive decline in middle age (pre-age 70 years) was strongly correlated with increasing functional limitation (r = -.49, p < .001). After middle age, cognition declined independently of change in functional limitation. To our knowledge, this is the first study to estimate age-related changes in fluid cognitive measures introduced in the HRS between 2010-2016.

A bivariate genome-wide association study was conducted in 137 pairs of twins to explore the shared genetic loci between cognition and blood pressure (BP). Before SNPs imputation, rs72815554 is significantly (P < 5 × 10-8) associated with the cognition-pulse pressure (PP) phenotype, while after imputation, 4 and 9 SNPs are significantly associated with the cognition-SBP phenotype, and cognition-PP phenotype, respectively, including rs72815554. There existed SNPs with highly linkage disequilibrium (LD) of rs10998339, rs72815554, rs11665292, and rs10823231. Besides, rs10998347, rs12153038, and rs10998295 had higher RegulomeDB scores and are located in the transcription factors binding regions. Rs7574283 and rs58113664 are located in the super-enhancer regions which are expressed highly in the adrenal gland, artery, atrial tissue, brain, nerves, etc. There are 1108, 1154, 1071, and 1102 genes associated with cognition-SBP, cognition-DBP, cognition-PP, and cognition-mean arterial pressure (MAP) phenotypes at the suggestive significant association level (P < 0.05), respectively. Furthermore, 641, 630, 900, and 555 pathways are associated with cognition-SBP, cognition-DBP, cognition-PP, and cognition-MAP phenotypes at the suggestive significant association level (P < 0.05), respectively.

Assessing power-law cross-correlations between a pair - or among a set - of processes is of great significance in diverse fields of analyses ranging from neuroscience to financial markets. In most cases such analyses are computationally expensive and thus carried out offline once the entire signal is obtained. However, many applications - such as mental state monitoring or financial forecasting - call for fast algorithms capable of estimating scale-free coupling in real time. Detrended cross-correlation analysis (DCCA), a generalization of the detrended fluctuation analysis (DFA) to the bivariate domain, has been introduced as a method designed to quantify power-law cross-correlations between a pair of non-stationary signals. Later, in analogy with the Pearson cross-correlation coefficient, DCCA was adapted to the detrended cross-correlation coefficient (DCCC), however as of now no online algorithms were provided for either of these analysis techniques. Here we introduce a new formula for obtaining the scaling functions in real time for DCCA. Moreover, the formula can be generalized via matrix notation to obtain the scaling relationship between not only a pair of signals, but also all possible pairs among a set of signals at the same time. This includes parallel estimation of the DFA scaling function of each individual process as well, thus allowing also for real-time acquisition of DCCC. The proposed algorithm matches its offline variants in precision, while being substantially more efficient in terms of execution time. We demonstrate that the method can be utilized for mental state monitoring on multi-channel electroencephalographic recordings obtained in eyes-closed and eyes-open resting conditions.

Investigating scale-free (i.e., fractal) functional connectivity in the brain has recently attracted increasing attention. Although numerous methods have been developed to assess the fractal nature of functional coupling, these typically ignore that neurophysiological signals are assemblies of broadband, arrhythmic activities as well as oscillatory activities at characteristic frequencies such as the alpha waves. While contribution of such rhythmic components may bias estimates of fractal connectivity, they are also likely to represent neural activity and coupling emerging from distinct mechanisms. Irregular-resampling auto-spectral analysis (IRASA) was recently introduced as a tool to separate fractal and oscillatory components in the power spectrum of neurophysiological signals by statistically summarizing the power spectra obtained when resampling the original signal by several non-integer factors. Here we introduce multiple-resampling cross-spectral analysis (MRCSA) as an extension of IRASA from the univariate to the bivariate case, namely, to separate the fractal component of the cross-spectrum between two simultaneously recorded neural signals by applying the same principle. MRCSA does not only provide a theoretically unbiased estimate of the fractal cross-spectrum (and thus its spectral exponent) but also allows for computing the proportion of scale-free coupling between brain regions. As a demonstration, we apply MRCSA to human electroencephalographic recordings obtained in a word generation paradigm. We show that the cross-spectral exponent as well as the proportion of fractal coupling increases almost uniformly over the cortex during the rest-task transition, likely reflecting neural desynchronization. Our results indicate that MRCSA can be a valuable tool for scale-free connectivity studies in characterizing various cognitive states, while it also can be generalized to other applications outside the field of neuroscience.

Whereas the theory of confirmatory adaptive designs is well understood for uncensored data, implementation of adaptive designs in the context of survival trials remains challenging. Commonly used adaptive survival tests are based on the independent increments structure of the log-rank statistic. This implies some relevant limitations: On the one hand, essentially only the interim log-rank statistic may be used for design modifications (such as data-dependent sample size recalculation). Furthermore, the treatment arm allocation ratio in these classical methods is assumed to be constant throughout the trial period. Here, we propose an extension of the independent increments approach to adaptive survival tests that addresses some of these limitations. We present a confirmatory adaptive two-sample log-rank test that allows rejection regions and sample size recalculation rules to be based not only on the interim log-rank statistic, but also on point-wise survival rate estimates, simultaneously. In addition, the possibility is opened to adapt the treatment arm allocation ratio after each interim analysis in a data-dependent way. The ability to include point-wise survival rate estimators in the rejection region of a test for comparing survival curves might be attractive, e.g., for seamless phase II/III designs. Data-dependent adaptation of the allocation ratio could be helpful in multi-arm trials in order to successively steer recruitment into the study arms with the greatest chances of success. The methodology is motivated by the LOGGIC Europe Trial from pediatric oncology. Distributional properties are derived using martingale techniques in the large sample limit. Small sample properties are studied by simulation.

Sclerotinia sclerotiorum is a necrotrophic fungus causing devastating stem rot and associated yield losses of canola/rapeseed (Brassica napus) worldwide, including in Australia. Developing host resistance against Sclerotinia stem rot is critical if this disease in canola/rapeseed is to be successfully managed, as cultural or chemical control options provide only partial or sporadic control. Three B. napus breeding populations, C2, C5 and C6, including the parents, F1, F2, BC1P1 and BC2P2, were utilised in a field study with an objective of exploring the inheritance pattern of disease resistance (based on stem lesion length, SLL), the genetic relationships of disease with stem diameter (SD) or days to flowering (DTF), and to compare these new adult plant stem resistances against S. sclerotiorum with those of seedling (cotyledon and leaf) resistances in earlier studies. Heritability (broad-sense) of SLL, was 0.57 and 0.73 for populations C2 at 3 and 5 weeks post-inoculation, and was 0.21 for C5 at 5 weeks post-inoculation. Additive genetic variance was evident within all three populations for DTF but not for SD. Narrow sense heritability for DTF was 0.48 (C2), 0.42 (C5) and 0.32 (C6). SD, DTF and SLL were all inherited independently with no significant genetic covariance between traits in bivariate analysis. Genetic variance for SLL in populations C2 and C5 was entirely non-additive, and there was significant non-additive genetic covariance of SLL at 3 and 5 weeks post-inoculation. Generation means analysis in population C2 supported the conclusion that complex epistatic interactions controlled SLL. Several C2 and C5 progeny showed high adult plant stem resistance which may be critical in developing enhanced stem resistance in canola/rapeseed. While population C6 showed no genetic variation for SLL resistance in this study, it showed significant non-additive genetic variance at the cotyledon and leaf stages in earlier studies. We conclude that host resistance varies across different plant growth stages and breeding must be targeted for resistance at each growth stage. In populations C2, C5 and C6, resistance to S. sclerotiorum in stem, leaf and cotyledon is always controlled by non-additive effects such as complex epistasis or dominance. Overall, our findings in relation to the quantitative inheritance of Sclerotinia stem rot resistance, together with the new, high-level resistances identified, will enable breeders to select/develop genotypes with enhanced resistances to S. sclerotiorum.

Flumethasone pivalate (FP) and clioquinol (CL) formulation was developed as a prodigious remedy to cure the external ear inflammatory disorders. So, the current research introduces five smart and novel UV-spectrophotometric platforms relying on minimal mathematical manipulation steps for simultaneous green analysis of FP and CL with no preliminary separation in their formulation that suffered from the high difference of their ratio and severe spectral overlapping. These platforms involved dual-wavelength, first derivative ratio, Fourier self-deconvolution, area under the curve, and bivariate methods. The suggested platform\' linearity was observed over the concentration range of 3-42 µg/ml for FP and 1.5-8 µg/ml for CL. All suggested platforms were validated according to ICH recommendations regarding accuracy, precision, repeatability, and selectivity producing satisfactory results within the accepted limits. These platforms were represented as rapid, green, and cheap alternatives to the reported chromatographic method due to lower solvent consumption and waste generation. Furthermore, they improved the determination sensitivity of the studied drugs and enhanced the recorded data signals or its spectral resolution by the newly introduced Fourier self-deconvoluted method. The statistical comparison between the results of the suggested platforms with each other and with those of the reported method showed no significant differences between them.