Berthelsenhodge5924

Cu0-Cu2O@CNTs composite can be used as an efficient catalyst to activate PDS for the degradation of toxic organic pollutants in water and wastewater.An important step in understanding the nature of the brain is to identify "cores" in the brain network, where brain areas strongly interact with each other. Cores can be considered as essential sub-networks for brain functions. In the last few decades, an information-theoretic approach to identifying cores has been developed. In this approach, interactions between parts are measured by an information loss function, which quantifies how much information would be lost if interactions between parts were removed. Then, a core called a "complex" is defined as a subsystem wherein the amount of information loss is locally maximal. Although identifying complexes can be a novel and useful approach, its application is practically impossible because computation time grows exponentially with system size. Here we propose a fast and exact algorithm for finding complexes, called Hierarchical Partitioning for Complex search (HPC). HPC hierarchically partitions systems to narrow down candidates for complexes. The computation time of HPC is polynomial, enabling us to find complexes in large systems (up to several hundred) in a practical amount of time. We prove that HPC is exact when an information loss function satisfies a mathematical property, monotonicity. We show that mutual information is one such information loss function. We also show that a broad class of submodular functions can be considered as such information loss functions, indicating the expandability of our framework to the class. We applied HPC to electrocorticogram recordings from a monkey and demonstrated that HPC revealed temporally stable and characteristic complexes.We consider the large sum of DC (Difference of Convex) functions minimization problem which appear in several different areas, especially in stochastic optimization and machine learning. Two DCA (DC Algorithm) based algorithms are proposed stochastic DCA and inexact stochastic DCA. We prove that the convergence of both algorithms to a critical point is guaranteed with probability one. Furthermore, we develop our stochastic DCA for solving an important problem in multi-task learning, namely group variables selection in multi class logistic regression. The corresponding stochastic DCA is very inexpensive, all computations are explicit. Numerical experiments on several benchmark datasets and synthetic datasets illustrate the efficiency of our algorithms and their superiority over existing methods, with respect to classification accuracy, sparsity of solution as well as running time.Osteoarthritis (OA) is the most common type of joint-related diseases, which affects millions of people worldwide. Expensive and time-consuming medical imaging can provide precise structural description of knee joints, but lacks the functional descriptions. Gait analysis can provide functional descriptions of knee joints. However, orthopedic surgeons always observe the patient's gait qualitatively and perform subjective assessments through rating scales at present due to the lack of a quantitative gait analysis system. To solve these problems, a gait acquisition and analysis system is developed to provide a cheap, easy-to-use solution for quantitative recording and functional description of OA patients. Firstly, an automatic gait acquisition platform is designed for the clinical setting based on the RGB-D camera and the developed software of gait data recording. In addition, the effective working space of gait acquisition platform is evaluated for clinical applications by comparing with the ground-truth from infrared optical trackers. Secondly, the acquired gait data is analyzed with a novel hybrid prediction model to assess the gait anomalies quantitatively and objectively. In the hybrid model, the extracted features of gait data contain the manually-extracted features and the automatically-extracted features from Long Short-Term Memory network. Experimental results on real patients demonstrate that the proposed gait analysis system can quantitatively predict gait anomalies with a high accuracy of 98.77 %. Therefore, this gait acquisition and analysis system achieves quantitative recording and objective assessment of gait anomalies for clinical OA treatments.Preeclampsia-eclampsia syndrome (PES) is associated with severe obstetric complications and there are no efficient methods available for an early detection. We studied blood concentration of some immunological and metabolic markers in association with obstetric outcome in healthy pregnant women and patients with obstetric risk factors, by ELISA and biochemical tests. Patients with complications showed higher levels of CRP and C4 positively correlated with Triglycerides and Cholesterol concentrations. Our results provide evidence that Immunological and metabolic alterations contribute to obstetric complications and that biomarkers linked to these alterations could be useful for an early detection of these problems.In the Merino ram, it is unclear whether cryopreserved sperm function and fertility is compromised when collected during the non-breeding season, when Merino ewes are seasonally anestrus. It was therefore investigated whether treatment with melatonin could improve sperm function or fertility when semen was collected during the period Merino ewes were seasonally anestrus. There were 16 Merino rams treated or not treated with melatonin implants during the non-breeding season of ewes (September). Ejaculates were collected before melatonin treatment (Week 0), during the period of melatonin release (Week 7) and subsequent breeding season (Week 23). In vitro sperm function was assessed before freezing, and at 0- and 3 -hs post-thaw. Fertility was determined through intrauterine insemination of ewes (n = 966) with frozen-thawed samples, during the breeding season. Compared to Week 0 values, spermatozoa from melatonin-treated rams had greater progressive motility at Week 7 (P = 0.019) and less DNA fragmentation (P = 0.003) at Weeks 7 and 23, whilst spermatozoa from non-treated rams were unchanged during these time-periods. There were no other treatment effects on sperm function or fertility (P > 0.05). PND-1186 in vitro In ejaculates collected during Week 23, there were no effects of treatment either before freezing or post-thawing. Sperm from ejaculates collected at Week 23, however, had lesser pre-freezing/post-thawing total motility and resulted in lower pregnancy rates (P  less then  0.05). It is concluded there are no effects of season on sperm quality or fertility of Merino rams and that melatonin treatment subtly improves quality of spermatozoa following cryopreservation.