Reliable representations for association rules

Association rule mining has contributed to many advances in the area of knowledge discovery. However, the quality of the discovered association rules is a big concern and has drawn more and more attention recently. One problem with the quality of the discovered association rules is the huge size of the extracted rule set. Often for a dataset, a huge number of rules can be extracted, but many of them can be redundant to other rules and thus useless in practice. Mining non-redundant rules is a promising approach to solve this problem. In this paper, we first propose a definition for redundancy, then propose a concise representation, called a Reliable basis, for representing non-redundant association rules. The Reliable basis contains a set of non-redundant rules which are derived using frequent closed itemsets and their generators instead of using frequent itemsets that are usually used by traditional association rule mining approaches. An important contribution of this paper is that we propose to use the certainty factor as the criterion to measure the strength of the discovered association rules. Using this criterion, we can ensure the elimination of as many redundant rules as possible without reducing the inference capacity of the remaining extracted non-redundant rules. We prove that the redundancy elimination, based on the proposed Reliable basis, does not reduce the strength of belief in the extracted rules. We also prove that all association rules, their supports and confidences, can be retrieved from the Reliable basis without accessing the dataset. Therefore the Reliable basis is a lossless representation of association rules. Experimental results show that the proposed Reliable basis can significantly reduce the number of extracted rules. We also conduct experiments on the application of association rules to the area of product recommendation. The experimental results show that the non-redundant association rules extracted using the proposed method retain the same inference capacity as the entire rule set. This result indicates that using non-redundant rules only is sufficient to solve real problems needless using the entire rule set.     

Modeling the glucose regulatory system in extreme preterm infants

Background

Premature infants represent a significant proportion of the neonatal intensive care population. Blood glucose homeostasis in this group is often disturbed by immaturity of endogenous regulatory systems and the stress of their condition. Hypo- and hyperglycemia are frequently reported in very low birth weight infants, and more mature infants often experience low levels of glycemia. A model capturing the unique fundamental dynamics of the neonatal glucose regulatory system could be used to develop better blood glucose control methods.

Methods

A metabolic system model is adapted from adult critical care to the unique physiological case of the neonate. Integral-based fitting methods were used to identify time-varying insulin sensitivity and non-insulin mediated glucose uptake profiles. The clinically important predictive ability of the model was assessed by assuming insulin sensitivity was constant over prediction intervals of 1, 2 and 4 h forward and comparing model-simulated versus actual clinical glucose values for all recorded interventions. The clinical data included 1091 glucose measurements over 3567 total patient hours, along with all associated insulin and nutritional infusion data, for N = 25 total cases. Ethics approval was obtained from the Upper South A Regional Ethics Committee for this study.

Results

The identified model had a median absolute percentage error of 2.4% [IQR: 0.9-4.8%] between model-fitted and clinical glucose values. Median absolute prediction errors at 1-, 2- and 4-h intervals were 5.2% [IQR: 2.5-10.3%], 9.4% [IQR: 4.5-18.4%] and 13.6% [IQR: 6.3-27.6%] respectively.

Conclusions

The model accurately captures and predicts the fundamental dynamic behaviors of the neonatal metabolism well enough for effective clinical decision support in glycemic control. The adaptation from adult to a neonatal case is based on the data from the literature. Low prediction errors and very low fitting errors indicate that the fundamental dynamics of glucose metabolism in both premature neonates and critical care adults can be described by similar mathematical models.     

Simulation of cardiovascular system diseases by including the autonomic nervous system into a minimal model

Diagnosing cardiovascular system (CVS) diseases from clinically measured data is difficult, due to the complexity of the hemodynamic and autonomic nervous system (ANS) interactions. Physiological models could describe these interactions to enable simulation of a variety of diseases, and could be combined with parameter estimation algorithms to help clinicians diagnose CVS dysfunctions. This paper presents modifications to an existing CVS model to include a minimal physiological model of ANS activation. A minimal model is used so as to minimise the number of parameters required to specify ANS activation, enabling the effects of each parameter on hemodynamics to be easily understood. The combined CVS and ANS model is verified by simulating a variety of CVS diseases, and comparing simulation results with common physiological understanding of ANS function and the characteristic hemodynamics seen in these diseases. The model of ANS activation is required to simulate hemodynamic effects such as increased cardiac output in septic shock, elevated pulmonary artery pressure in left ventricular infarction, and elevated filling pressures in pericardial tamponade. This is the first known example of a minimal CVS model that includes a generic model of ANS activation and is shown to simulate diseases from throughout the CVS.     

Integral-based filtering of continuous glucose sensor measurements for glycaemic control in critical care

Hyperglycaemia is prevalent in critical illness and increases the risk of further complications and mortality, while tight control can reduce mortality up to 43%. Adaptive control methods are capable of highly accurate, targeted blood glucose regulation using limited numbers of manual measurements due to patient discomfort and labour intensity. Therefore, the option to obtain greater data density using emerging continuous glucose sensing devices is attractive. However, the few such systems currently available can have errors in excess of 20-30%. In contrast, typical bedside testing kits have errors of approximately 7-10%. Despite greater measurement frequency larger errors significantly impact the resulting glucose and patient specific parameter estimates, and thus the control actions determined creating an important safety and performance issue. This paper models the impact of the continuous glucose monitoring system (CGMS, Medtronic, Northridge, CA) on model-based parameter identification and glucose prediction. An integral-based fitting and filtering method is developed to reduce the effect of these errors. A noise model is developed based on CGMS data reported in the literature, and is slightly conservative with a mean Clarke Error Grid (CEG) correlation of R=0.81 (range: 0.68-0.88) as compared to a reported value of R=0.82 in a critical care study. Using 17 virtual patient profiles developed from retrospective clinical data, this noise model was used to test the methods developed. Monte-Carlo simulation for each patient resulted in an average absolute 1-h glucose prediction error of 6.20% (range: 4.97-8.06%) with an average standard deviation per patient of 5.22% (range: 3.26-8.55%). Note that all the methods and results are generalizable to similar applications outside of critical care, such as less acute wards and eventually ambulatory individuals. Clinically, the results show one possible computational method for managing the larger errors encountered in emerging continuous blood glucose sensors, thus enabling their more effective use in clinical glucose regulation studies.     

On the pH dependence of protein stability

This paper treats the free energy contribution of ionizable groups to protein stability. A method is presented for the calculation of the pH dependence of the denaturation free energy of a protein, which yields results that can be compared directly to experiment. The first step in the treatment is the determination of the average charges of all the ionizable groups in both the folded and unfolded protein. An expression due to Tanford then relates the pH dependence of the unfolding free energy to the difference in net charge between the two states. In order to determine absolute rather than relative unfolding free energies, it is necessary to calculate the total contribution of ionizable groups to protein stability at some reference pH. This is accomplished through a statistical mechanical treatment similar to the one used previously in the calculation of pKas. The treatment itself is rigorous but it suffers from uncertainties in the pKa calculations. Nevertheless, the overall shape of experimentally observed plots of denaturation free energy as a function of pH are reasonably well reproduced by the calculations. A number of general conclusions that arise from the analysis are: (1) knowledge of titration curves and/or effective pKa values of ionizable groups in proteins is sufficient to calculate the pH dependence of the denaturation free energy with respect to some reference pH value. However, in order to calculate the absolute contribution of ionizable groups to protein stability, it is necessary to also know the intrinsic pKa of each group. This is defined as the pKa of a group in a hypothetical state of the protein where all other groups are neutral. (2) Due to desolvation effects, ionizable groups destabilize proteins, although the effect is strongly dependent on pH. There are however, strongly stabilizing pairwise Coulombic interactions on the surface of proteins. (3) Plots of stability versus pH should not be interpreted in terms of a group whose pKa corresponds to the titration midpoint, but rather to a group with different pKas (that correspond approximately to the titration end points) in each state. (4) Any residual structure in the GuHCl-denatured state of proteins appears to have little effect on the pH dependence of stability. (5) pH-dependent unfolding, for example to the "molten globule" state, appears due to individual groups with anomalous pKas whose locations on the protein surface may determine the nature of the unfolded state.     

Atmospheric winds from occultation spectra

By measuring the mean shifts of hundreds of lines in solar occultation spectra obtained at satellite altitudes, relative wind speeds along the lines of sight of the rays can be obtained with precisions of 5 m/sec or better at altitudes up to 100 km. It is necessary to obtain more accurate line positions or to introduce a gas sample for frequency calibration if absolute wind speeds are to be obtained.     

Mode matching for a passive resonant ring laser gyroscope

An analytical method of matching the mode of an input laser to the lowest-order mode of a passive resonant ring laser gyro is described, as are the steps in determining the location and focal length of cylindrical mode matching lenses. Results were obtained with no mode matching, with a compromise spherical lens, with horizontal mode matching only, and with the proper cylindrical mode matching lenses. Compared with no mode matching, the latter case shows that the amplitude of the lowest-order mode is increased approximately 2.5 times. In addition, the number and intensity of higher-order modes are reduced to near zero, and the relative intensity of the lowest-order mode to the higher-order mode increased from approximately 5 to approximately 60 times greater.     

Hot deboning beef with and without electrical stimulation

Two hot deboning procedures for producing vacuum packed primal beef joints were compared with conventional side chilling followed by cold deboning. Cold shortening toughness was avoided in the hot procedures either by a delay before chilling or by electrical stimulation of the carcass. Overall evaporative losses were 0·6% with hot deboning and 1·9% with cold deboning. Hot deboning reduced drip loss but the effect was smaller after electrical stimulation. The colour of large muscles which cool unevenly on the side was more uniform after hot deboning, but again the improvement was smaller after electrical stimulation. There was no difference in bacterial contamination or growth on hot and cold deboned meat, and instrumental and sensory assessments confirmed that eating quality was similar for all three treatments.     

Unconventional Field Dependence of Magnetoresistance of (TMTSF)2ClO4 Studied by 46-T Pulsed Magnetic Field System

A new TTP donor, Me-DH-TTP (2-methyl-5-(1,3-dithiolan-2-yliden)-1,3,4,6-tetrathiapentalene), was designed to realize a system with large on-site Coulomb repulsion as compared with the previously known bis-fused type TTP donors. Probably as a consequence, (Me-DH-TTP)₂AsF₆ exhibits semiconducting behavior from room temperature to liquid helium temperature. By increasing pressure, metallic behavior appears below 300 K, and with distinct metal-insulator (M-I) transition up to 2.2 GPa. This M-I transition suddenly disappears beyond 2.5 GPa, and metallic state is stabilized down to 2.6 K. We discuss the possibility of quantum critical point around 2.4 GPa.