Surface changes on comet 67P/Churyumov-Gerasimenko suggest a more active past.

The Rosetta spacecraft spent ~2 years orbiting comet 67P/Churyumov-Gerasimenko, most of it at distances that allowed surface characterization and monitoring at submeter scales. From December 2014 to June 2016, numerous localized changes were observed, which we attribute to cometary-specific weathering, erosion, and transient events driven by exposure to sunlight and other processes. While the localized changes suggest compositional or physical heterogeneity, their scale has not resulted in substantial alterations to the comet's landscape. This suggests that most of the major landforms were created early in the comet's current orbital configuration. They may even date from earlier if the comet had a larger volatile inventory, particularly of CO or CO2 ices, or contained amorphous ice, which could have triggered activity at greater distances from the Sun.

Rosetta's comet 67P/Churyumov-Gerasimenko sheds its dusty mantle to reveal its icy nature.

The Rosetta spacecraft has investigated comet 67P/Churyumov-Gerasimenko from large heliocentric distances to its perihelion passage and beyond. We trace the seasonal and diurnal evolution of the colors of the 67P nucleus, finding changes driven by sublimation and recondensation of water ice. The whole nucleus became relatively bluer near perihelion, as increasing activity removed the surface dust, implying that water ice is widespread underneath the surface. We identified large (1500 square meters) ice-rich patches appearing and then vanishing in about 10 days, indicating small-scale heterogeneities on the nucleus. Thin frosts sublimating in a few minutes are observed close to receding shadows, and rapid variations in color are seen on extended areas close to the terminator. These cyclic processes are widespread and lead to continuously, slightly varying surface properties.

Shape-preserving preprocessing for human pulse signals based on adaptive parameter determination.

The use of the human pulse signal for medical diagnosis is a mainstay in the practice of traditional Chinese medicine. Computer processing of this signal may be used to automate diagnostic procedures and to reveal sources of information in the waveform that have been used by both eastern and western physicians for more than two millennia. A new method for preprocessing of the human pulse signal significantly improves feature extraction and classification of the waveform. Baseline distortion is first removed using the dual-tree complex wavelet transform (DT-CWT) and cubic spline interpolation, then a novel filtering method removes the residual background noise. Filtering is implemented in two stages. In the initial pass, a majority of the noise is eliminated by an adaptive mean filter whose sliding window duration is selected automatically based on a chain code and the DT-CWT. In the second pass, residual high frequency noise is removed using the DT-CWT with a new threshold determination. Experimental results demonstrate effective removal of background disturbances with excellent preservation of pulse peak information essential for proper parametric representation and classification of the waveform.

Biologically-motivated system identification: application to microbial growth modeling.

This paper presents a new method for identification of system models that are linear in parametric structure, but arbitrarily nonlinear in signal operations. The strategy blends traditional system identification methods with three modeling strategies that are not commonly employed in signal processing: linear-time-invariant-in-parameters models, set-based parameter identification, and evolutionary selection of the model structure. This paper reports recent advances in the theoretical foundation of the methods, then focuses on the operation and performance of the approach, particularly the evolutionary model determination. The method is applied to the modeling of microbial growth by Monod Kinetics.

Exploiting identifiability and intergene correlation for improved detection of differential expression.

Accurate differential analysis of microarray data strongly depends on effective treatment of intergene correlation. Such dependence is ordinarily accounted for in terms of its effect on significance cutoffs. In this paper, it is shown that correlation can, in fact, be exploited to share information across tests and reorder expression differentials for increased statistical power, regardless of the threshold. Significantly improved differential analysis is the result of two simple measures: (i) adjusting test statistics to exploit information from identifiable genes (the large subset of genes represented on a microarray that can be classified a priori as nondifferential with very high confidence], but (ii) doing so in a way that accounts for linear dependencies among identifiable and nonidentifiable genes. A method is developed that builds upon the widely used two-sample t-statistic approach and uses analysis in Hilbert space to decompose the nonidentified gene vector into two components that are correlated and uncorrelated with the identified set. In the application to data derived from a widely studied prostate cancer database, the proposed method outperforms some of the most highly regarded approaches published to date. Algorithms in MATLAB and in R are available for public download.

Nonlinear dependence in the discovery of differentially expressed genes.

Microarray data are used to determine which genes are active in response to a changing cell environment. Genes are "discovered" when they are significantly differentially expressed in the microarray data collected under the differing conditions. In one prevalent approach, all genes are assumed to satisfy a null hypothesis, ℍ 0, of no difference in expression. A false discovery (type 1 error) occurs when ℍ 0 is incorrectly rejected. The quality of a detection algorithm is assessed by estimating its number of false discoveries, 𝔉. Work involving the second-moment modeling of the z-value histogram (representing gene expression differentials) has shown significantly deleterious effects of intergene expression correlation on the estimate of 𝔉. This paper suggests that nonlinear dependencies could likewise be important. With an applied emphasis, this paper extends the "moment framework" by including third-moment skewness corrections in an estimator of 𝔉. This estimator combines observed correlation (corrected for sampling fluctuations) with the information from easily identifiable null cases. Nonlinear-dependence modeling reduces the estimation error relative to that of linear estimation. Third-moment calculations involve empirical densities of 3 × 3 covariance matrices estimated using very few samples. The principle of entropy maximization is employed to connect estimated moments to 𝔉 inference. Model results are tested with BRCA and HIV data sets and with carefully constructed simulations.

[Post-retirement activity in Germany]. / Berufliche Aktivität von Ruheständlern.

During recent years, a discussion on work activity of retirees has commenced also in Germany. First, this contribution presents a survey of the North American phenomenon of bridge employment and, second, complements leadoff empirical results on individual motives and favored basic conditions in Germany. Individual and structural preconditions for work activity during retirement are presented as well as possible manifestations of retirement activities. This paper quantifies the extent of work activity of retirees in Germany into their upper seventies. Potential follow-up actions for the three levels individuals, organizations, as well as politics and society are recommended.

RP1 protein truncating mutations predominate at the RP1 adRP locus.

PURPOSE: Recent reports have shown that the autosomal dominant retinitis pigmentosa (adRP) phenotype linked to the pericentric region of chromosome 8 is associated with mutations in a gene designated RP1. Screening of the whole gene in a large cohort of patients has not been undertaken to date. To assess the involvement and character of RP1 mutations in adRP, the gene was screened in a panel of 266 unrelated patients of British origin and a Pakistani family linked to this locus. METHODS: Patients exhibiting the adRP phenotype were screened for mutations in the four exons of the RP1 gene by heteroduplex analysis and direct sequencing. Linkage of the Pakistani family was achieved using microsatellite markers. Polymerase chain reaction (PCR) products were separated by nondenaturing polyacrylamide gel electrophoresis. Alleles were assigned to individuals, which allowed calculation of LOD scores. Microsatellite marker haplotyping was used to determine ancestry of patients carrying the same mutation. RESULTS: In the 266 British patients and 1 Pakistani family analyzed, 21 loss-of-function mutations and 7 amino acid substitutions were identified, some of which may also be disease-causing. The mutations, many of which were deletion or insertion events, were clustered in the 5' end of exon 4. Most mutations resulted in a premature termination codon in the mRNA. Haplotype analysis of nine patients carrying an R677X mutation suggested that these patients are not ancestrally related. CONCLUSIONS: RP1 mutations account for 8% to 10% of the mutations in our cohort of British patients. The most common disease-causing mechanism is deduced to be one involving the presence of a truncated protein. Mutations in RP1 have now been described in adRP patients of four ethnically diverse populations. The different disease haplotype seen in the nine patients carrying the same mutation suggests that this mutation has arisen independently many times, possibly due to a mutation hot spot in this part of the gene.

On the use of hidden Markov modelling for recognition of dysarthric speech.

Recognition of the speech of severely dysarthric individuals requires a technique which is robust to extraordinary conditions of high variability and very little training data. A hidden Markov model approach to isolated word recognition is used in an attempt to automatically model the enormous variability of the speech, while signal preprocessing measures and model modifications are employed to make better use of the existing data. Two findings are contrary to general experience with normal speech recognition. The first is that an ergodic model is found to outperform a standard left-to-right (Bakis) model structure. The second is that automated clipping of transitional acoustics in the speech is found to significantly enhance recognition. Experimental results using utterances of cerebral palsied persons with an array of articulatory abilities are presented.

An AI-based communication system for motor and speech disabled persons: design methodology and prototype testing.

An intelligent communication device is developed to assist the nonverbal, motor disabled in the generation of written and spoken messages. The device is centered on a knowledge base of the grammatical rules and message elements. A "belief" reasoning scheme based on both the information from external sources and the embedded knowledge is used to optimize the process of message search. The search for the message elements is conceptualized as a path search in the language graph, and a special frame architecture is used to construct and to partition the graph. Bayesian "belief" reasoning from the Dempster-Shafer theory of evidence is augmented to cope with time-varying evidence. An "information fusion" strategy is also introduced to integrate various forms of external information. Experimental testing of the prototype system is discussed.

Ineffectiveness of human chorionic gonadotropin in weight reduction: a double-blind study.

Our investigation was designed to retest the hypothesis of the efficacy of human chorionic gonadotropin (HCG) on weight reduction in obese women in a clinic setting. We sought to duplicate the Asher-Harper study (1973) which had found that the combination of 500 cal diet and HCG had a statistically significant benefit over the diet and placebo combination as evidenced by greater weight loss and decrease in hunger. Fifty-one women between the ages of 18 and 60 participated in our 32-day prospective, randomized, double-blind comparison of HCG versus placebo. Each patient was given the same diet (the one prescribed in the Asher-Harper study), was weighed daily Monday through Saturday and was counselled by one of the investigators who administered the injections. Laboratory studies were performed at the time of initial physical examinations and at the end of the study. Twenty of 25 in the HCG and 21 of 26 patients in the placebo groups completed 28 injections. There was no statistically significant difference in the means of the two groups in number of injections received, weight loss, percent of weight loss, hip and waist circumference, weight loss per injections, or in hunger ratings. HCG does not appear to enhance the effectiveness of a rigidly imposed regimen for weight reduction.