Discovering Robust Knowledge from Databases that Change

Many applications of knowledge discovery and data mining such as rule discovery for semantic query optimization, database integration and decision support, require the knowledge to be consistent with the data. However, databases usually change over time and make machine-discovered knowledge inconsistent. Useful knowledge should be robust against database changes so that it is unlikely to become inconsistent after database updates. This paper defines this notion of robustness in the context of relational databases and describes how robustness of first-order Horn-clause rules can be estimated. Experimental results show that our estimation approach can accurately identify robust rules. We also present a rule antecedent pruning algorithm that improves the robustness and applicability of machine discovered rules to demonstrate the usefulness of robustness estimation.     

Confounding Effect of Flow on Estuarine Response to Nitrogen Loading

The total maximum daily load (TMDL) concept provides the basis for regulating pollution load from riverine sources to impaired water bodies. However, load is comprised of two components: flow and concentration. These two components may have confounding, or even conflicting, effects on waterbody attributes of concern. This is particularly the case for dynamic, advective systems, such as estuaries. Resolving these components is critical for properly predicting the response of impaired systems to watershed management actions. The Neuse River Estuary in North Carolina is an example of such an impaired system. Nitrogen has been identified as the pollutant of concern, and the process of developing a TMDL for nitrogen is underway. We, therefore, analyze the extensive data that have been collected for the Neuse River and estuary to investigate spatiotemporal relationships between river flow, riverine total nitrogen (TN) inputs, water temperature, dissolved inorganic nitrogen concentration, algal density, and primary productivity. Results support the belief that phytoplankton in the estuary are under substantial riverine control. However, the riverine TN concentration alone has only a minor role in determining estuarine chlorophyll concentration. River flow has a stronger influence, likely through its effects on down-estuary nitrogen delivery, residence time, salinity, and turbidity. These results imply that using riverine nitrogen load as the metric to evaluate watershed nutrient management may not be appropriate. While nitrogen controls should reduce loads in the long term, in the short term, river flow is the dominant component of load and has the opposite effect of nitrogen on algae at the up-estuary locations.     

Reliability-Based Design for Internal Stability of Mechanically Stabilized Earth Walls

A parametric study was conducted using Monte Carlo simulation to assess how uncertainty in design parameters affects the probability of internal failure of mechanically stabilized earth (MSE) walls. Bishop’s simplified method was used to conduct the internal stability analyses. The results of the analyses indicate that the mean and coefficient of variation of the backfill friction angle, mean and coefficient of variation of the tensile strength of reinforcement, mean unit weight of the backfill, mean surcharge, mean reinforcement vertical spacing, and mean reinforcement length have a significant effect on the probability of internal failure of MSE walls. Based on the results of the parametric study, a series of additional simulations were conducted where the significant parameters were varied over a broad range. The results of these simulations were used to develop a set of reliability-based design (RBD) charts for internal stability of MSE walls. A method to adapt these charts to address model bias and model uncertainty is also presented. A MSE wall was designed using the RBD method and two other deterministic design methods. The required tensile strength of the reinforcement obtained from the RBD method fell between the strengths determined from the deterministic methods.     

Confirmatory Factor Analysis of the Psychopathy Checklist: Screening Version in Offenders With Axis I Disorders.

One hundred forty-nine inpatients within a maximum security psychiatric facility were assessed with the Psychopathy Checklist: Screening Version (PCL:SV; S. D. Hart, D. N. Cox, & R. D. Hare, 1995). Within the total sample, 68% had a psychotic disorder and 30% met criteria for psychopathy. Using confirmatory factor analysis, the authors tested the 2-factor PCL:SV model of psychopathy and recent 3- and 4-factor models. Results indicated good fit for each model, with the 4-factor model showing best overall fit. Structural equation modeling was used to determine which psychopathy factors predicted 6-month follow-up of inpatient aggression. The 2-, 3-, and 4-factor models, respectively, accounted for 16%.27%. and 3l% of the variance in aggression. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Wear of filled and unfilled dental restorative resins

The influence of double-pass sliding on the surface failure of filled and unfilled dental restorative resins was evaluated. Damage was more severe for double-pass than for single-pass sliding. Wear of restorative resins and composites was influenced by the resistance to penetration and by the mode of deformation during sliding.     

Effects of institutional room acoustics on speech discrimination of developmentally disabled residents and of staff.

High ambient noise levels and long reverberation times can degrade speech discrimination. An experiment examined the effects on speech discrimination of 2 acoustic factors: (a) noise level (high, 72 db; low, 65 db); and (b) reverberation times (long, 1.77 sec; short, .79 sec). Ss were 12 developmentally disabled state school residents and 12 normal staff members. Their speech discrimination abilities were tested under conditions simulating the institutional environment prior to renovations (high noise/long reverberation time) and following renovations (low noise/short reverberation time). A 3-way mixed ANOVA showed main effects of noise, reverberation time, and group. There was a Noise?×?Group interaction and a significant difference between simulated prerenovation and postrenovation conditions. (21 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Transverse bulk solid behaviour during discharge from troughed belt conveyors

Guidelines for the calculation of bulk solid material cross sectional dimensions and the influence of the belt conveyor transition length on the inclination of the trajectory at discharge are well established. However, not a great deal of research has been conducted on the influence of bulk solid material properties and conveyor belt transition geometry on the bulk solid material cross section at discharge. As such, assessment of cross section break-up associated with cohesive materials and transverse spreading of free flowing materials is missing. Conversely, the majority of discharge trajectory analysis techniques focus on analysis in a single vertical plane along the length of the belt.This paper presents an analysis of high speed conveyor discharge trajectories in three dimensions, taking into account transverse spreading of free flowing materials and shearing, or cross section discontinuity, exhibited by cohesive materials. Transverse bulk solid material behaviour and trajectory discharge is evaluated using a combination of experimental laboratory tests, a continuum mechanics approach incorporating CAD and Discrete Element Modelling (DEM). The work presented shows that bulk solid material behaviour at discharge is directly influenced by material characteristics and interactions resulting from the geometry of the belt conveyor transition zone.     

Guest Editors' Introduction: The Evolution of RFIC Design and Test

There are several challenges facing RFIC design and test. The demand in the wireless market will drive RFIC products. For RFIC chipsets, improvements are needed for the elimination of passive components, better integrated passives, power reduction, modeling of devices and interconnects, packaging, and cost-effective testing. However, this innovation cannot come at the cost of time to market for new products. Also, development costs must be driven to a minimum, as average selling prices for RFICs remain flat or decline. Moreover, one of the biggest challenges in moving from low GHz to higher frequencies is the lack of integration between the production testing infrastructure, EDA tools, and device designs. Advancements in device and test equipment modeling and simulation technology are beginning to bridge this gap. Finally, RF measurement requires specialized capital equipment investments and highly skilled engineers with many years of experience. This special issue on design and test of RFIC chips describes some of these challenges and proposes some interesting solutions.     

Development of a Mortality Prediction Model in Hospitalised SARS-CoV-2 Positive Patients Based on Routine Kidney Biomarkers

Acute kidney injury (AKI) is a prevalent complication in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive inpatients, which is linked to an increased mortality rate compared to patients without AKI. Here we analysed the difference in kidney blood biomarkers in SARS-CoV-2 positive patients with non-fatal or fatal outcome, in order to develop a mortality prediction model for hospitalised SARS-CoV-2 positive patients. A retrospective cohort study including data from suspected SARS-CoV-2 positive patients admitted to a large National Health Service (NHS) Foundation Trust hospital in the Yorkshire and Humber regions, United Kingdom, between 1 March 2020 and 30 August 2020. Hospitalised adult patients (aged ≥ 18 years) with at least one confirmed positive RT-PCR test for SARS-CoV-2 and blood tests of kidney biomarkers within 36 h of the RT-PCR test were included. The main outcome measure was 90-day in-hospital mortality in SARS-CoV-2 infected patients. The logistic regression and random forest (RF) models incorporated six predictors including three routine kidney function tests (sodium, urea; creatinine only in RF), along with age, sex, and ethnicity. The mortality prediction performance of the logistic regression model achieved an area under receiver operating characteristic (AUROC) curve of 0.772 in the test dataset (95% CI: 0.694–0.823), while the RF model attained the AUROC of 0.820 in the same test cohort (95% CI: 0.740–0.870). The resulting validated prediction model is the first to focus on kidney biomarkers specifically on in-hospital mortality over a 90-day period.     

Oxygen Vacancies Evoked Blue TiO2(B) Nanobelts with Efficiency Enhancement in Sodium Storage Behaviors

Oxygen vacancies (OVs) dominate the physical and chemical properties of metal oxides, which play crucial roles in the various fields of applications. Density functional theory calculations show the introduction of OVs in TiO₂(B) gives rise to better electrical conductivity and lower energy barrier of sodiation. Here, OVs evoked blue TiO₂(B) (termed as B‐TiO₂(B)) nanobelts are successfully designed upon the basis of electronically coupled conductive polymers to TiO₂, which is confirmed by electron paramagnetic resonance and X‐ray photoelectron spectroscopy. The superiorities of OVs with the aid of carbon encapsulation lead to higher capacity (210.5 mAh g^?1 (B‐TiO₂(B)) vs 102.7 mAh g^?1 (W‐TiO₂(B)) at 0.5 C) and remarkable long‐term cyclability (the retention of 94.4% at a high rate of 10 C after 5000 times). In situ X‐ray diffractometer analysis spectra also confirm that an enlarged interlayer spacing stimulated by OVs is beneficial to accommodate insertion and removal of sodium ions to accelerate storage kinetics and preserve its original crystal structure. The work highlights that injecting OVs into metal oxides along with carbon coating is an effective strategy for improving capacity and cyclability performances in other metal oxide based electrochemical energy systems.