Mathematical programming for piecewise linear regression analysis

In data mining, regression analysis is a computational tool that predicts continuous output variables from a number of independent input variables, by approximating their complex inner relationship. A large number of methods have been successfully proposed, based on various methodologies, including linear regression, support vector regression, neural network, piece-wise regression, etc. In terms of piece-wise regression, the existing methods in literature are usually restricted to problems of very small scale, due to their inherent non-linear nature. In this work, a more efficient piece-wise linear regression method is introduced based on a novel integer linear programming formulation. The proposed method partitions one input variable into multiple mutually exclusive segments, and fits one multivariate linear regression function per segment to minimise the total absolute error. Assuming both the single partition feature and the number of regions are known, the mixed integer linear model is proposed to simultaneously determine the locations of multiple break-points and regression coefficients for each segment. Furthermore, an efficient heuristic procedure is presented to identify the key partition feature and final number of break-points. 7 real world problems covering several application domains have been used to demonstrate the efficiency of our proposed method. It is shown that our proposed piece-wise regression method can be solved to global optimality for datasets of thousands samples, which also consistently achieves higher prediction accuracy than a number of state-of-the-art regression methods. Another advantage of the proposed method is that the learned model can be conveniently expressed as a small number of if-then rules that are easily interpretable. Overall, this work proposes an efficient rule-based multivariate regression method based on piece-wise functions and achieves better prediction performance than state-of-the-arts approaches. This novel method can benefit expert systems in various applications by automatically acquiring knowledge from databases to improve the quality of knowledge base

Discussion: behaviour of jacked and driven piles in sandy soil

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Behaviour of jacked and driven piles in sandy soil

As an alternative to conventional dynamic pile installation methods, pile jacking is an environmentally friendly technique that could become more widely accepted. Great concern has arisen over the performance of jacked piles as compared with that of driven piles. This paper describes a comprehensive field study that was aimed at investigating the differences and similarities between the behaviour of jacked H-piles and that of driven H-piles. The instrumented piles, varying in length from 32 to 55 m and having a design capacity of up to 3540 kN, were installed in residual soils whose properties are close to silty sands. The load test results indicate that the shaft resistance of jacked piles is generally suffer and stronger than that of driven piles, but the base resistance of jacked piles is weaker than that of driven piles. At a load level of twice the design capacity, the percentage of pile head load carried by base varies from 2% to 10% for jacked piles, with a mean value of 6%; for driven piles the percentage varies from 6% to 61% with a mean value of 38%. The back-calculated values of the shaft friction coefficient, β, were found to be in a range of 0.25-0.6 for both jacked and driven piles. A correlation was also observed between the ultimate shaft friction and the mean standard penetration test N value (N̄), which suggests that the shaft friction can be taken as 1.5N̄ to 2N̄ (kPa) for both jacked and driven H-piles.published_or_final_versio

Discussion: behaviour of jacked and driven piles in sandy soil

published_or_final_versio

Neural stem cell transplantation in a rat model of intracerebral haemorrhage plus haematoma aspiration

INTRODUCTION: Cell replacement therapy holds great potential for brain tissue repair following intracerebral haemorrhage (ICH). Haematoma evacuation alleviates the mass effect and prevents the secondary pathological processes. This study was conducted to investigate the survival and differentiation of neural stem cells (NSCs) after transplantation into the brain cavity following haematoma aspiration in adult male Sprague-Dawley rats …published_or_final_versio

Improved survival with lymph node sampling in Wilms tumor

We sought to determine the impact of number of lymph nodes examined on survival for Wilms tumor (WT). Data from the Surveillance, Epidemiology, and End Results and Florida Cancer Data System were queried for patients < 20 years of age with WT. Of 1805 WT patients, 1340 had lymph node (LN) data available following surgery. The mean age for the cohort was 3.3 ± 2.8 y. Most patients were White (78%), and non-Hispanic (78%). A total of 297 patients (22%) had 0 LN sampled, while 697 (52%) had 1–5 LN, 210 (16%) had 6–10 LN, and 136 (10%) had >10 LN. Overall 5-y survival was 91%. By univariate analysis, 5-y survival was significantly lower for patients with 0 LN sampled (87% versus 91% 1–5 LN; 93% 6–10 LN; 95% >10 LN, P = 0.005). Multivariate analysis confirmed a survival advantage for patients having 1–5 LN (HR 0.600, P = 0.016), 6–10 LN (HR 0.521, P = 0.048), and >10 LN (HR 0.403, P = 0.039) compared with patients with 0 LN examined. Failure to biopsy lymph nodes for WT patients not only increases the risk of local recurrence due to understaging and inadequate adjuvant therapy, but is also an independent prognostic indicator of lower survival

On the modelling of valve point loadings for power electricity dispatch

Modelling the effect of valve point loadings on the performance and cost of power generators for electricity dispatch problems is necessary. For the past 20 years, the development of computer based methods for the identification of optimal designs have been based on a single model, introduced by Walters and Sheble (1993). This model approximates the non-monotonic incremental cost curve using a sine function. This note explores the properties of this model, highlighting one critical deficiency for use within an automated optimization based design system and proposes a new model

Intestinal stem cells lacking the Math1 tumour suppressor are refractory to Notch inhibitors

Intestinal cells are constantly produced from a stem cell reservoir that gives rise to proliferating transient amplifying cells, which subsequently differentiate into one of the four principal cell types. Signalling pathways, including the Notch signalling pathway, coordinate these differentiation processes and their deregulation may cause cancer. Pharmacological inhibition through γ-secretase inhibitors or genetic inactivation of the Notch signalling pathway results in the complete loss of proliferating crypt progenitors due to their conversion into post-mitotic goblet cells. The basic helix–loop–helix transcription factor Math1 is essential for intestinal secretory cell differentiation. Because of the critical roles of both Math1 and Notch signalling in intestinal homeostasis and neoplastic transformation, we sought to determine the genetic hierarchy regulating the differentiation of intestinal stem cells into secretory cells. In this paper, we demonstrate that the conversion of intestinal stem cells into goblet cells upon inhibition of the Notch signalling pathway requires Math1

Application of a target array Comparative Genomic Hybridization to prenatal diagnosis

<p>Abstract</p> <p>Background</p> <p>While conventional G-banded karyotyping still remains a gold standard in prenatal genetic diagnoses, the widespread adoption of array Comparative Genomic Hybridization (array CGH) technology for postnatal genetic diagnoses has led to increasing interest in the use of this same technology for prenatal diagnosis. We have investigated the value of our own designed DNA chip as a prenatal diagnostic tool for detecting submicroscopic deletions/duplications and chromosome aneuploidies.</p> <p>Methods</p> <p>We designed a target bacterial artificial chromosome (BAC)-based aCGH platform (MacArray™ M-chip), which specifically targets submicroscopic deletions/duplications for 26 known genetic syndromes of medical significance observed prenatally. To validate the DNA chip, we obtained genomic DNA from 132 reference materials generated from patients with 22 genetic diseases and 94 clinical amniocentesis samples obtained for karyotyping.</p> <p>Results</p> <p>In the 132 reference materials, all known genomic alterations were successfully identified. In the 94 clinical samples that were also subjected to conventional karyotyping, three cases of balanced chromosomal aberrations were not detected by aCGH. However, we identified eight cases of microdeletions in the Yq11.23 chromosomal region that were not found by conventional karyotyping. This region harbors the DAZ gene, and deletions may lead to non-obstructive spermatogenesis.</p> <p>Conclusions</p> <p>We have successfully designed and applied a BAC-based aCGH platform for prenatal diagnosis. This platform can be used in conjunction with conventional karyotyping and will provide rapid and accurate diagnoses for the targeted genomic regions while eliminating the need to interpret clinically-uncertain genomic regions.</p