An investigation of methods for the on-line estimation of tool wear

The paper examines the use of the measurements of spindle motor power for the estimation of wear and the detection of the end of effective tool life for a vertical milling machine. The measurements are analysed using spectral analysis and the effectiveness of using moving averages, running-means and cumulative sum of the power spectrum values to estimate wear is evaluated. For a specific machine tool (Beaver NC5), workpiece material (stainless steel) and under a particular set of cutting conditions it is shown that (a) there is a strong correlation between the cumulative sum of the power spectral energies and the total flank wear, and (b) the residuals obtained from computing a least squares linear fit to the plot of cumulative sums of the power spectral energies against cutting time clearly indicates when the tool is entering the region of high wear.     

The efficiency of a drinking fountain

In this experiment the efficiency of a water drinking fountain was studied. Efficiency was defined in terms of the percentage of water actually consumed in relation to the water that flows from the drinking fountain, the drinking time, the water consumed per user and the electricity required to cool the water. For this purpose four different spout diameters were used and the water pressure was regulated to give two different water trajectory heights for each spout diameter setting. This resulted in eight different flow rates. The results of the study indicated that the water fountain is a highly inefficient water transfer mechanism and that extreme flow rates worsened the efficiency of the system. The intermediate spout nozzle diameters proved to be superior with regard to all the efficiency statistics.     

Assay of aflatoxin in peanuts and peanut products using acetone-hexane-water for extraction

A quantitative method is described for the assay of aflatoxin in peanut products. The procedure involves extraction of aflatoxin from the sample with a homogeneous acetone-hexane-water solvent mixture followed by purification of the extract by phasic extraction of the aflatoxin with aqueous sodium chloride and then with chloroform. The purified chloroform extract is analyzed by thin-layer chromatography by comparison of the intensity of fluorescence of any aflatoxin with the intensity of a known standard. The aflatoxin analyses of peanuts were found to be very variable due to sampling, and this variability has been greatly reduced by finely grinding and thoroughly mixing 2 kg of the sample before removal of an aliquot for assay. The method is sensitive to approximately 2 parts per billion. Honorable mention, Bond Award competition. Presented at AOCS Meeting, Chicago, Illinois, October, 1964. So. Reg. Res. Lab., New Orleans, Louisiana, one of the laboratories of the So. Utiliz. Res. and Dev. Div., ARS, USDA.     

Model checking agent programming languages

In this paper we describe a verification system for multi-agent programs. This is the first comprehensive approach to the verification of programs developed using programming languages based on the BDI (belief-desire-intention) model of agency. In particular, we have developed a specific layer of abstraction, sitting between the underlying verification system and the agent programming language, that maps the semantics of agent programs into the relevant model-checking framework. Crucially, this abstraction layer is both flexible and extensible; not only can a variety of different agent programming languages be implemented and verified, but even heterogeneous multi-agent programs can be captured semantically. In addition to describing this layer, and the semantic mapping inherent within it, we describe how the underlying model-checker is driven and how agent properties are checked. We also present several examples showing how the system can be used. As this is the first system of its kind, it is relatively slow, so we also indicate further work that needs to be tackled to improve performance.     

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.     

NaCl doping and the conductivity of agar phantoms

A recipe for manipulating the conductivity of agar impedance-imaging phantoms through their NaCl (salt) content is reexamined. The conductivities at frequencies 100 kHz and below are characterized for phantoms created with the recipe. The data are compared against the recipe's predictive formula for conductivity as a function of salt content. Based on analysis of the data a modified version of the conductivity formula is generated. The modified predictive formula better approximates the observed NaCl dependence of conductivity in phantoms with salt concentrations under 0.1 M. The experimental data also provide verification for the asymptotic dependence of contact impedance on frequency and phantom conductivity. The results of these experiments will be helpful in better constructing agar phantoms to electrical specifications for future impedance-imaging experiments.