A Model of the Influence of Neutral Air Dynamics on the Seasonal Variation in the Low Ionosphere

Recently it has become clear that the phenomena in the ionospheric D-region are determined to a great extent by dynamical processes in the strato-mesosphere D-region. In this respect much attention is paid to the study of the winter anomaly (WA) phenomenon on medium and short radiowaves, in which the meteorological character of the lower ionosphere is most prominent. Significant experimental data about the variations of the electron concentration, N, ion composition, temperature and dynamic regime during WA permit a better understanding of the character of the physical processes in the middle atmosphere. The influence of the neutral wind on the seasonal variation of the electron concentration N for the altitude interval 90 or = z or = 120 km, where the ratio upsilon sub in/omega sub i, of the ion-neutral collision frequency, upsilon sub in and the ion gyrofrequency, omega sub i decreases from 40 to 1 was evaluated. CIRA-72 is used as a model of the zonal wind

The Effect of Tumbling, Sodium Chloride and Polyphosphates on the Microstructure and Appearance of Whole-Muscle Processed Meats

The properties of a whole-muscle processed meat were determined. The complex action of socium chloride, polyphosphates and mechanical agitation caused extraction of myofibrillar protein, swelling of fibers and loss of cross-strations. A new functional ability was found for the extracted proteins to form a fine cover or membrane on the surface of the whole muscle during cooking. These changes produced a product with improved cooking yield and color appearance

A Generalized Approach to Optimization of Relational Data Warehouses Using Hybrid Greedy and Genetic Algorithms

As far as we know, in the open scientific literature, there is no generalized framework for the optimization of relational data warehouses which includes view and index selection and vertical view fragmentation. In this paper we are offering such a framework. We propose a formalized multidimensional model, based on relational schemas, which provides complete vertical view fragmentation and presents an approach of the transformation of a fragmented snowflake schema to a defragmented star schema through the process of denormalization. We define the generalized system of relational data warehouses optimization by including vertical fragmentation of the implementation schema (F), indexes (I) and view selection (S) for materialization. We consider Genetic Algorithm as an optimization method and introduce the technique of "recessive bits" for handling the infeasible solutions that are obtained by a Genetic Algorithm. We also present two novel hybrid algorithms, i.e. they are combination of Greedy and Genetic Algorithms. Finally, we present our experimental results and show improvements of the performance and benefits of the generalized approach (SFI) and show that our novel algorithms significantly improve the efficiency of the optimization process for different input parameters

Mutations in the Gene DNAJC5 Cause Autosomal Dominant Kufs Disease in a Proportion of Cases: Study of the Parry Family and 8 Other Families

Background: The Neuronal Ceroid Lipofuscinoses (NCL) comprise at least nine progressive neurodegenerative genetic disorders. Kufs disease, an adult-onset form of NCL may be recessively or dominantly inherited. Our study aimed to identify genetic mutations associated with autosomal dominant Kufs disease (ADKD). Methodology and Principal Findings We have studied the family first reported with this phenotype in the 1970s, the Parry family. The proband had progressive psychiatric manifestations, seizures and cognitive decline starting in her mid 20s. Similarly affected relatives were observed in seven generations. Several of the affected individuals had post-mortem neuropathological brain study confirmatory for NCL disease. We conducted whole exome sequencing of three affected family members and identified a pLeu116del mutation in the gene DNAJC5, which segregated with the disease phenotype. An additional eight unrelated affected individuals with documented autosomal dominant or sporadic inheritance were studied. All had diagnostic confirmation with neuropathological studies of brain tissue. Among them we identified an additional individual with a p.Leu115Arg mutation in DNAJC5. In addition, a pAsn477Ser change in the neighboring gene PRPF6, a gene previously found to be associated with retinitis pigmentosa, segregated with the ADKD phenotype. Interestingly, two individuals of the Parry family did report visual impairment. Conclusions: Our study confirmed the recently reported association of DNAJC5 mutations with ADKD in two out of nine well-defined families. Sequence changes in PRPF6 have not been identified in other unrelated cases. The association of vision impairment with the expected PRPF6 dysfunction remains possible but would need further clinical studies in order to confirm the co-segregation of the visual impairment with this sequence change

Bayesian Inference for Structural Vector Autoregressions Identified by Markov-Switching Heteroskedasticity

In this study, Bayesian inference is developed for structural vector autoregressive models in which the structural parameters are identified via Markov-switching heteroskedasticity. In such a model, restrictions that are just-identifying in the homoskedastic case, become over-identifying and can be tested. A set of parametric restrictions is derived under which the structural matrix is globally or partially identified and a Savage-Dickey density ratio is used to assess the validity of the identification conditions. The latter is facilitated by analytical derivations that make the computations fast and numerical standard errors small. As an empirical example, monetary models are compared using heteroskedasticity as an additional device for identification. The empirical results support models with money in the interest rate reaction function.Comment: Keywords: Identification Through Heteroskedasticity, Bayesian Hypotheses Assessment, Markov-switching Models, Mixture Models, Regime Chang

De novo mutations of KIAA2022 in females cause intellectual disability and intractable epilepsy

Background Mutations in the KIAA2022 gene have been reported in male patients with X-linked intellectual disability, and related female carriers were unaffected. Here, we report 14 female patients who carry a heterozygous de novo KIAA2022 mutation and share a phenotype characterised by intellectual disability and epilepsy. Methods Reported females were selected for genetic testing because of substantial developmental problems and/or epilepsy. X-inactivation and expression studies were performed when possible. Results All mutations were predicted to result in a frameshift or premature stop. 12 out of 14 patients had intractable epilepsy with myoclonic and/or absence seizures, and generalised in 11. Thirteen patients had mild to severe intellectual disability. This female phenotype partially overlaps with the reported male phenotype which consists of more severe intellectual disability, microcephaly, growth retardation, facial dysmorphisms and, less frequently, epilepsy. One female patient showed completely skewed X-inactivation, complete absence of RNA expression in blood and a phenotype similar to male patients. In the six other tested patients, X-inactivation was random, confirmed by a non-significant twofold to threefold decrease of RNA expression in blood, consistent with the expected mosaicism between cells expressing mutant or normal KIAA2022 alleles. Conclusions Heterozygous loss of KIAA2022 expression is a cause of intellectual disability in females. Compared with its hemizygous male counterpart, the heterozygous female disease has less severe intellectual disability, but is more often associated with a severe and intractable myoclonic epilepsy