Random bounce algorithm: real-time image processing for the detection of bats and birds

Wind energy plants generate an impact on wildlife with significant fatality rates for various bat and bird species, e.g. due to a collision with the rotor blades. Monitoring approaches, such as vision-based systems, are needed to reduce their mortality by means of an optimized turbine control strategy as soon as flying animals are detected. Since manual analysis of the video data is ineffective, automatic video processing with real-time capabilities is required. In this paper, we propose the random bounce algorithm (RBA) as a novel real-time image processing method for vision-based detection of bats and birds. The RBA is combined with object tracking in order to extract flight trajectories. Its performance is compared with connected components object detection. Results from a laboratory flight tunnel as well as from a field study at a 2 MW wind energy plant in Southern Germany will be presented and discussed. We have successfully detected and tracked objects both in laboratory experiments with many animals and in field experiments with individual animals at a frame rate of 10 fps.     

Bayesian kernel methods for analysis of functional neuroimages

We propose an approach to analyzing functional neuroimages in which 1) regions of neuronal activation are described by a superposition of spatial kernel functions, the parameters of which are estimated from the data and 2) the presence of activation is detected by means of a generalized likelihood ratio test (GLRT). Kernel methods have become a staple of modern machine learning. Herein, we show that these techniques show promise for neuroimage analysis. In an on-off design, we model the spatial activation pattern as a sum of an unknown number of kernel functions of unknown location, amplitude, and/or size. We employ two Bayesian methods of estimating the kernel functions. The first is a maximum a posteriori (MAP) estimation method based on a Reversible-Jump Markov-chain Monte-Carlo (RJMCMC) algorithm that searches for both the appropriate model complexity and parameter values. The second is a relevance vector machine (RVM), a kernel machine that is known to be effective in controlling model complexity (and thus discouraging overfitting). In each method, after estimating the activation pattern, we test for local activation using a GLRT. We evaluate the results using receiver operating characteristic (ROC) curves for simulated neuroimaging data and example results for real fMRI data. We find that, while RVM and RJMCMC both produce good results, RVM requires far less computation time, and thus appears to be the more promising of the two approaches.     

Simulation of early-stage clustering in ternary metal alloys using the phase-field crystal method

Phase-field crystal methodology is applied, for the first time, to study the effect of alloy composition on the clustering behavior of a quenched/aged supersaturated ternary Al alloy system. An analysis of the work of formation is adapted from a methodology developed in Fallah et al. to describe the dislocation-mediated nucleation and growth mechanisms of early clusters in binary alloys [Phys Rev B 2012;86:134112]. Consistent with the experiments, we demonstrate that the addition of Mg to an Al–1.1Cu alloy increases the nucleation rate of clusters in the quenched/aged state by increasing the effective driving force for nucleation, enhancing the dislocation stress relaxation and decreasing the surface energy associated with the Cu-rich co-clusters of Cu–Mg. Furthermore, we show that it is thermodynamically favorable for small subcritical clusters to have higher affinity for Mg than larger post-critical Cu-rich clusters, particularly depicting a two-stage clustering phenomenon.     

Atomistic investigation of clustering phenomenon in the Al–Cu system: Three-dimensional phase-field crystal simulation and HRTEM/HRSTEM characterization

Early-stage clustering in quenched/aged supersaturated Al–Cu alloys is simulated and characterized at the atomic scale to study the structural and compositional evolution of clusters. A three-dimensional analysis of the nucleation and growth mechanisms of early clusters in binary alloys is built upon a phase-field crystal (PFC) methodology previously developed in two dimensions by Fallah et al. [Phys. Rev. B. 86, 134112 (2012)]. The dislocation-mediated nucleation of clusters, reproduced in three dimensions, is compared against new results of atomistic characterization using high-resolution transmission electron microscopy (HRTEM) and high-resolution scanning transmission electron microscopy (HRSTEM). Consistent with the simulation results, analysis of HRTEM micrographs reveals the association of quenched-in dislocations with the early clusters. Moreover, the PFC model and HRSTEM observations show remarkable agreement on the non-equilibrium evolution of composition within the early clusters as well as their preferred growth orientation and spherical-to-ellipsoidal morphological transition.     

Factor structure of the Children’s Perception of Interparental Conflict Scale for studies of youths with externalizing behavior problems.

The assessment of children’s perception of marital conflict is an important area of research related to family relations, children’s cognitions about self, and the development of psychopathology. The leading instrument in this domain is the Children’s Perception of Interparental Conflict Scale (CPIC; J. H. Grych, M. Seid, & F. D. Fincham, 1992). It has 48 items organized into 9 conceptual designed subscales, with reports of 3-factor higher order structure to the 9 subscales. However, the 3-factor solution does not capture all 9 subscales well. Further, items have never been subjected to factor analysis to evaluate the best fitting factor structure at the item level. Doing so is particularly important when bringing the scale into new populations such as children with attention-deficit/hyperactivity disorder (ADHD) or disruptive behavior disorders. In the present study, 2 samples of children (total N = 1,190; ages 6–18 years) completed the CPIC. An exploratory factor analysis in Sample 1 (from a clinical study of ADHD and non-ADHD youths) yielded 4 interpretable factors. A confirmatory factor analysis in Sample 2 (a population sample of twins) confirmed the generalizability of the solution with an acceptable fit, although 1 item was dropped. The final solution used 38 of the 48 items. The 4-factor solution captured a Conflict Properties factor, two appraisal factors labeled Threat to Self and Self-Blame, and a Triangulation/Stability factor that included elements of appraisal and content. The authors concluded that the item-based 4-factor solution to the CPIC is preferable to the 9-factor or 3-factor formulation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Tailored Systemic Therapy for Colorectal Cancer Liver Metastases

Liver metastases are the most common site of metastatic spread in colorectal cancer. Current treatment approaches involve effective systemic therapies in combination with surgical and/or interventional strategies. Multimodal strategies greatly improved clinical outcomes of patients with metastatic colorectal cancer over the last decades. Identification of predictive and prognostic biomarkers helped to comprehensively refine individual targeted treatment approaches and resulted in median overall survival rates of 30 months or longer. Current guidelines, thus, recommend treatment selection according to patients’ performance status, tumor localization and stage as well as the tumor’s molecular and genetic status. Here, we outline the latest developments in molecular decision-making for patients with upfront resectable, potentially or initially unresectable and non/never-resectable colorectal cancer liver metastases.     

Effect of long‐term dietary administration of oregano and rosemary on the antioxidant status of rat serum,liver, kidney and heart after carbon tetrachloride‐induced oxidative stress

BACKGROUND: This study was performed on female Wistar rats allocated to eight groups of six animals each. Groups 1 and 2 were fed the basal diet, groups 3 and 4 were fed the basal diet supplemented with ground oregano at 20 g kg^?1 level, groups 5 and 6 were fed the basal diet supplemented with ground rosemary at 20 g kg^?1 level, while groups 7 and 8 were fed the basal diet supplemented with both oregano and rosemary, each at 20 g kg^?1 level. Following 6 weeks feeding, groups 2, 4, 6 and 8 were injected with CCl₄ at 1 mL kg^?1 body weight, and 6 h thereafter all animals were sacrificed. RESULTS: Administration of CCl₄ to the control rats enhanced (P < 0.05) aspartate transaminase (AST), alanine transaminase (ALT) and alkaline phosphatase (ALP) activities, decreased cholesterol and triglycerides content in serum, increased (P < 0.05) lipid peroxidation and decreased (P < 0.05) the ABTS radical cation, the hydroxyl anion radical, the superoxide anion radical, and the hydrogen peroxide scavenging activities in all tested tissues, as compared to the control. Feeding oregano, rosemary or both before CCl₄ treatment resulted in decline (P < 0.05) of the increase in AST, ALT and ALP activities, increase (P < 0.05) of cholesterol and triglycerides in serum, decrease (P < 0.05) of lipid peroxidation, and increase (P < 0.05) of the ABTS radical cation, hydroxyl anion radical, superoxide anion radical and hydrogen peroxide scavenging activity. CONCLUSION: The results of this study suggest that long‐term dietary administration of oregano and rosemary has the potential to quench free radicals and alleviate CCl₄‐induced oxidative stress in rats. Copyright © 2009 Society of Chemical Industry     

A stochastic mathematical model of 4D tumour spheroids with real-time fluorescent cell cycle labelling

In vitro tumour spheroids have been used to study avascular tumour growth and drug design for over 50 years. Tumour spheroids exhibit heterogeneity within the growing population that is thought to be related to spatial and temporal differences in nutrient availability. The recent development of real-time fluorescent cell cycle imaging allows us to identify the position and cell cycle status of individual cells within the growing spheroid, giving rise to the notion of a four-dimensional (4D) tumour spheroid. We develop the first stochastic individual-based model (IBM) of a 4D tumour spheroid and show that IBM simulation data compares well with experimental data using a primary human melanoma cell line. The IBM provides quantitative information about nutrient availability within the spheroid, which is important because it is difficult to measure these data experimentally.     

First Trimester Maternal Plasma Aberrant miRNA Expression Associated with Spontaneous Preterm Birth

Spontaneous Preterm Delivery (sPTD) is one of the leading causes of perinatal mortality and morbidity worldwide. The present case–control study aims to detect miRNAs differentially expressed in the first trimester maternal plasma with the view to identify predictive biomarkers for sPTD, between 32^0/7 and 36^6/7 weeks, that will allow for timely interventions for this serious pregnancy complication. Small RNA sequencing (small RNA-seq) of five samples from women with a subsequent sPTD and their matched controls revealed significant down-regulation of miR-23b-5p and miR-125a-3p in sPTD cases compared to controls, whereas miR-4732-5p was significantly overexpressed. Results were confirmed by qRT-PCR in an independent cohort of 29 sPTD cases and 29 controls. Statistical analysis demonstrated that miR-125a is a promising early predictor for sPTL (AUC: 0.895; 95% CI: 0.814-0.972; p < 0.001), independent of the confounding factors tested, providing a useful basis for the development of a novel non-invasive predictive test to assist clinicians in estimating patient-specific risk.     

µ-Opioid Receptors Expressed by Intrinsically Photosensitive Retinal Ganglion Cells Contribute to Morphine-Induced Behavioral Sensitization

Opioid drugs are the most effective tools for treating moderate to severe pain. Despite their analgesic efficacy, long-term opioid use can lead to drug tolerance, addiction, and sleep/wake disturbances. While the link between opioids and sleep/wake problems is well-documented, the mechanism underlying opioid-related sleep/wake problems remains largely unresolved. Importantly, intrinsically photosensitive retinal ganglion cells (ipRGCs), the cells that transmit environmental light/dark information to the brain’s sleep/circadian centers to regulate sleep/wake behavior, express μ-opioid receptors (MORs). In this study, we explored the potential contribution of ipRGCs to opioid-related sleep/circadian disruptions. Using implanted telemetry transmitters, we measured changes in horizontal locomotor activity and body temperature in mice over the course of a chronic morphine paradigm. Mice lacking MORs expressed by ipRGCs (McKO) exhibited reduced morphine-induced behavioral activation/sensitization compared with control littermates with normal patterns of MOR expression. Contrastingly, mice lacking MORs globally (MKO) did not acquire morphine-induced locomotor activation/sensitization. Control mice also showed morphine-induced hypothermia in both the light and dark phases, while McKO littermates only exhibited morphine-induced hypothermia in the dark. Interestingly, only control animals appeared to acquire tolerance to morphine’s hypothermic effect. Morphine, however, did not acutely decrease the body temperature of MKO mice. These findings support the idea that MORs expressed by ipRGCs could contribute to opioid-related sleep/wake problems and thermoregulatory changes.