Hypercomplex cross-correlation of DNA sequences

A hypercomplex representation of DNA is proposed to facilitate comparing DNA sequences with fuzzy composition. With the hypercomplex number representation, the conventional sequence analysis method, such as, dot matrix analysis, dynamic programming, and cross-correlation method have been extended and improved to align DNA sequences with fuzzy composition. The hypercomplex dot matrix analysis can provide more control over the degree of alignment desired. A new scoring system has been proposed to accommodate the hypercomplex number representation of DNA and integrated with dynamic programming alignment method. By using hypercomplex cross-correlation, the match and mismatch alignment information between two aligned DNA sequences are separately stored in the resultant real part and imaginary parts respectively. The mismatch alignment information is very useful to refine consensus sequence based motif scanning

Quality of life in Parkinson’s disease: Italian validation of the Parkinson’s Disease Questionnaire (PDQ-39-IT)

Translation and cross-cultural adaptation of the 39-item Parkinson’s Disease Questionnaire (PDQ-39) to the Italian culture was performed by Oxford University Innovation in 2008, but this version has never been validated. Therefore, we performed the process of validation of the Italian version of the PDQ-39 (PDQ-39-IT) following the “Consensus-Based Standards for the Selection of Health Status Measurement Instruments” checklist. The translated PDQ-39-IT was tested with 104 patients diagnosed with Parkinson’s disease (PD) who were recruited between June and October 2017. The mean age of the participants was 65.7 ± 10.2 years, and the mean duration of symptoms was 7.4 ± 5.3 years. The internal consistency of the PDQ-39-IT was assessed by Cronbach’s alpha and ranged from 0.69 to 0.92. In an assessment of test-retest reliability in 35 of the 104 patients, the infraclass correlation coefficient (ICC) ranged from 0.85 to 0.96 for the various subitems of the PDQ-39-IT (all p < 0.01). Spearman’s rank correlation coefficient for the validity of the PDQ-39-IT and the Italian version of the 36-Item Short Form (SF-36) was − 0.50 (p < 0.01). The results show that the PDQ-39-IT is a reliable and valid tool to assess the impact of PD on functioning and well-being. Thus, the PDQ-39-IT can be used in clinical and research practice to assess this construct and to evaluate the overall effect of different treatments in Italian PD patients

University Malaya Medical Centre (UMMC) Service Quality: A Pilot Study on Transformational Leadership and Empathy

This pilot study observed the correlation between transformational leadership and a healthcare service provider's service quality. The research used two sets of cross-sectional questionnaire surveys designed to measure the Consumer Assessment of Healthcare Providers and Systems and a Leadership Inventory Index of the services rendered by the University Malaya Medical Centre (UMMC) to their patients to classify the quality of services delivered to patients at UMMC. The results emphasized a significant correlation between transformational leadership and empathy but no significant relationship between leadership effectiveness and service quality because of a lack of consensus and empirical support around which leadership types are significant. Transformational leadership has empirical support and is principles-based, relationship-oriented, intuitively appealing, and potentially “transformative. The study further stressed that the patients were pleased with the services rendered by UMMC staff. Also, additional education for physicians and physicians in training in transformational leadership is warranted

Beyond BAO: improving cosmological constraints from BOSS with measurement of the void-galaxy cross-correlation

We present a measurement of the anisotropic void-galaxy cross-correlation function in the CMASS galaxy sample of the BOSS DR12 data release. We perform a joint fit to the data for redshift space distortions (RSD) due to galaxy peculiar velocities and anisotropies due to the Alcock-Paczynski (AP) effect, for the first time using a velocity field reconstruction technique to remove the complicating effects of RSD in the void centre positions themselves. Fits to the void-galaxy function give a 1% measurement of the AP parameter combination $D_A(z)H(z)/c = 0.4367\pm 0.0045$ at redshift $z=0.57$, where $D_A$ is the angular diameter distance and $H$ the Hubble parameter, exceeding the precision obtainable from baryon acoustic oscillations (BAO) by a factor of ~3.5 and free of systematic errors. From voids alone we also obtain a 10% measure of the growth rate, $f\sigma_8(z=0.57)=0.501\pm0.051$. The parameter degeneracies are orthogonal to those obtained from galaxy clustering. Combining void information with that from BAO and galaxy RSD in the same CMASS sample, we measure $D_A(0.57)/r_s=9.383\pm 0.077$ (at 0.8% precision), $H(0.57)r_s=(14.05\pm 0.14)\;10^3$ kms$^{-1}$Mpc$^{-1}$ (1%) and $f\sigma_8=0.453\pm0.022$ (4.9%), consistent with cosmic microwave background (CMB) measurements from Planck. These represent a factor \sim2 improvement in precision over previous results through the inclusion of void information. Fitting a flat cosmological constant $\Lambda$CDM model to these results in combination with Planck CMB data, we find up to an 11% reduction in uncertainties on $H_0$ and $\Omega_m$ compared to use of the corresponding BOSS consensus values. Constraints on extended models with non-flat geometry and a dark energy of state that differs from $w=-1$ show an even greater improvement.Comment: 22 pages, 15 figures. Accepted for publication in Phys.Rev.D. v2 corrects small error in likelihood analysis; minor changes to figures and text, cosmological results unchanged. Reconstruction and void-finding code available at https://github.com/seshnadathur/Revolver, likelihood analysis code available at https://github.com/seshnadathur/void-galaxy-cosmo-fitte

Exploration of PET and MRI radiomic features for decoding breast cancer phenotypes and prognosis.

Radiomics is an emerging technology for imaging biomarker discovery and disease-specific personalized treatment management. This paper aims to determine the benefit of using multi-modality radiomics data from PET and MR images in the characterization breast cancer phenotype and prognosis. Eighty-four features were extracted from PET and MR images of 113 breast cancer patients. Unsupervised clustering based on PET and MRI radiomic features created three subgroups. These derived subgroups were statistically significantly associated with tumor grade (p = 2.0 × 10-6), tumor overall stage (p = 0.037), breast cancer subtypes (p = 0.0085), and disease recurrence status (p = 0.0053). The PET-derived first-order statistics and gray level co-occurrence matrix (GLCM) textural features were discriminative of breast cancer tumor grade, which was confirmed by the results of L2-regularization logistic regression (with repeated nested cross-validation) with an estimated area under the receiver operating characteristic curve (AUC) of 0.76 (95% confidence interval (CI) = [0.62, 0.83]). The results of ElasticNet logistic regression indicated that PET and MR radiomics distinguished recurrence-free survival, with a mean AUC of 0.75 (95% CI = [0.62, 0.88]) and 0.68 (95% CI = [0.58, 0.81]) for 1 and 2 years, respectively. The MRI-derived GLCM inverse difference moment normalized (IDMN) and the PET-derived GLCM cluster prominence were among the key features in the predictive models for recurrence-free survival. In conclusion, radiomic features from PET and MR images could be helpful in deciphering breast cancer phenotypes and may have potential as imaging biomarkers for prediction of breast cancer recurrence-free survival

A Survey on Multisensor Fusion and Consensus Filtering for Sensor Networks

Multisensor fusion and consensus filtering are two fascinating subjects in the research of sensor networks. In this survey, we will cover both classic results and recent advances developed in these two topics. First, we recall some important results in the development ofmultisensor fusion technology. Particularly, we pay great attention to the fusion with unknown correlations, which ubiquitously exist in most of distributed filtering problems. Next, we give a systematic review on several widely used consensus filtering approaches. Furthermore, some latest progress on multisensor fusion and consensus filtering is also presented. Finally, conclusions are drawn and several potential future research directions are outlined.the Royal Society of the UK, the National Natural Science Foundation of China under Grants 61329301, 61374039, 61304010, 11301118, and 61573246, the Hujiang Foundation of China under Grants C14002 and D15009, the Alexander von Humboldt Foundation of Germany, and the Innovation Fund Project for Graduate Student of Shanghai under Grant JWCXSL140

On the performance of US fiscal forecasts : government vs. private information

This paper contributes to shed light on the quality and performance of US fiscal forecasts. The first part inspects the causes of official (CBO) fiscal forecasts revisions between 1984 and 2016 that are due to technical, economic or policy reasons. Both individual and cumulative means of forecast errors are relatively close to zero, particularly in the case of expenditures. CBO averages indicate net average downward revenue and expenditure revisions and net average upward deficit revisions. Focusing on the causes of the technical component, we uncover that its revisions are quite unpredictable which casts doubts on inferences about fiscal policy sustainability that rely on point estimates. Comparing official with private-sector (Consensus) forecasts, despite the informational advantages CBO might have, one cannot unequivocally say that one or the other is more accurate. Evidence also seems to suggest that CBO forecasts are consistently heavily biased towards optimism while this is less the case for Consensus forecasts. Not only is the extent of information rigidity is more prevalent in CBO forecasts, but evidence also seems to indicate that Consensus forecasts dominate CBO’s in terms of information content.info:eu-repo/semantics/publishedVersio