Cholesterol content of human parotid saliva

Free and esterifed cholesterol were determined in parotid fluid collected from 19 individuals by encapsulation of Stenson's duct in the oral 16.7±7.1 (SD) μg/100 ml and cholesterol esters averaged 13.2±8.0 (SD) μg/100 ml. Two assays are described for the measurement of cholesterol in parotid saliva. Lipophilic material was extracted with ether-ethanol (3∶1). In assay 1, the solid residue of the extract was separated into its components by thin layer chromatography. Substances on the chromatogram were made to fluoresce and the spots were photographed. Cholesterol was determined by densitometry of its black image on film. In assay 2, the ether-ethanol residue was subjected to quantitative gas chromatography. Both methods yield similar data.     

Theoretical assessment of the catalytic (Pt/TiO2) oxidation of formaldehyde at ambient temperature

A recent article [C. Zhang, H. He, K. Tanaka, Catal. Commun. 6 (2005) 211] investigates the use of a Pt/TiO₂ catalyst for the oxidation of formaldehyde. The findings demonstrate nearly complete oxidation at ambient temperature (25 °C) for values of the surface velocity in the range 5–10 × 10⁴ h⁻¹ and a 45% destruction when using a surface velocity of 20 × 10⁴ h⁻¹.In the present communication, this oxidation was assessed by theoretical considerations of the reaction kinetics. The destruction efficiency was predicted using a first-order reaction rate expression, combined with different theoretical or semi-empirical equations for the intrinsic reaction rate constant. Predicted and experimental data are in fair agreement, thus validating the theoretical approach and confirming the experimental results.     

Itemset mining: A constraint programming perspective

The field of data mining has become accustomed to specifying constraints on patterns of interest. A large number of systems and techniques has been developed for solving such constraint-based mining problems, especially for mining itemsets. The approach taken in the field of data mining contrasts with the constraint programming principles developed within the artificial intelligence community. While most data mining research focuses on algorithmic issues and aims at developing highly optimized and scalable implementations that are tailored towards specific tasks, constraint programming employs a more declarative approach. The emphasis lies on developing high-level modeling languages and general solvers that specify what the problem is, rather than outlining how a solution should be computed, yet are powerful enough to be used across a wide variety of applications and application domains.This paper contributes a declarative constraint programming approach to data mining. More specifically, we show that it is possible to employ off-the-shelf constraint programming techniques for modeling and solving a wide variety of constraint-based itemset mining tasks, such as frequent, closed, discriminative, and cost-based itemset mining. In particular, we develop a basic constraint programming model for specifying frequent itemsets and show that this model can easily be extended to realize the other settings. This contrasts with typical procedural data mining systems where the underlying procedures need to be modified in order to accommodate new types of constraint, or novel combinations thereof. Even though the performance of state-of-the-art data mining systems outperforms that of the constraint programming approach on some standard tasks, we also show that there exist problems where the constraint programming approach leads to significant performance improvements over state-of-the-art methods in data mining and as well as to new insights into the underlying data mining problems. Many such insights can be obtained by relating the underlying search algorithms of data mining and constraint programming systems to one another. We discuss a number of interesting new research questions and challenges raised by the declarative constraint programming approach to data mining.     

The Protective Effects of the Autophagic and Lysosomal Machinery in Vascular and Valvular Calcification: A Systematic Review

Background: Autophagy is a highly conserved catabolic homeostatic process, crucial for cell survival. It has been shown that autophagy can modulate different cardiovascular pathologies, including vascular calcification (VCN). Objective: To assess how modulation of autophagy, either through induction or inhibition, affects vascular and valvular calcification and to determine the therapeutic applicability of inducing autophagy. Data sources: A systematic review of English language articles using MEDLINE/PubMed, Web of Science (WoS) and the Cochrane library. The search terms included autophagy, autolysosome, mitophagy, endoplasmic reticulum (ER)-phagy, lysosomal, calcification and calcinosis. Study characteristics: Thirty-seven articles were selected based on pre-defined eligibility criteria. Thirty-three studies (89%) studied vascular smooth muscle cell (VSMC) calcification of which 27 (82%) studies investigated autophagy and six (18%) studies lysosomal function in VCN. Four studies (11%) studied aortic valve calcification (AVCN). Thirty-four studies were published in the time period 2015–2020 (92%). Conclusion: There is compelling evidence that both autophagy and lysosomal function are critical regulators of VCN, which opens new perspectives for treatment strategies. However, there are still challenges to overcome, such as the development of more selective pharmacological agents and standardization of methods to measure autophagic flux.     

Improved process control of an industrial sludge centrifuge-dryer installation through binary logistic regression modeling of the fouling issues

Biological wastewater treatment generates huge amounts of waste sludge which need to be dewatered and eventually dried to minimize transportation and incineration costs. A characteristic feature of sludge in this context is that it turns into a sticky substance during its drying process inducing fouling problems in the drying installation. At the wastewater treatment plant of Monsanto in Antwerp, Belgium, one enclosed centrifuge-dryer system is used to dry the sludge. In the past, this installation had to be shut down regularly due to dryer fouling problems. To avoid these operational problems, a binary logistic regression analysis is presented in this research based on a 5-year database, resulting in an empirical model for the evaluation of the dryer fouling risk as a function of the sludge feed characteristics. The model inputs are the sludge volume index (SVI) and the dosing of clay additive and tertiary (flotation) sludge, the latter containing polyaluminumchloride (PACl), to the sludge feed of this particular system.By exploiting the knowledge captured by this model, the derived control strategy is based on the value of the SVI. Whenever the SVI is high the original high clay dosing to the feed needs to be maintained. At moderate SVI values, implying an intrinsically better sludge dewaterability, the strategy dictates a reduction in the clay dosing to the sludge feed to have a reduced sludge solids dryness after dewatering, thereby avoiding that the sludge exhibits its most sticky phase when passing the most fouling sensitive part of the dryer. When the SVI is lower than 50 mL/g the control strategy states that conditioning of the sludge with PACl is required to mask the stickiness instead of postponing it, avoiding that the stickiness of the sludge already hampers the dewatering stage of the process.     

A continuous-time delta-sigma modulator for 802.11a/b/g WLAN implemented with a hierarchical bottom-up optimization methodology

This paper presents a 3rd-order continuous-time Delta-Sigma modulator with a resolution of 10 bits for a 10 MHz signal bandwidth. It is designed in a standard 0.18 μm CMOS technology and consumes only 6 mW. After the design/selection of the topologies for the integrators, comparator and D/A converters, optimal sizing of the complete modulator was ensured by using a hierarchical bottom-up, multi-objective evolutionary design methodology. With this methodology, a set of Pareto-optimal modulator designs is generated by using Pareto-optimal performance solutions of the hierarchically decomposed lower-level subblocks. From the generated Pareto-optimal design set, a final optimal design is chosen that complies with the specifications for the 802.11a/b/g WLAN standard and has minimal power consumption.     

A Serpent without Teeth. The Conservative Transformism of Jean‐Baptiste d’Omalius d’Halloy (1783–1875)

Abstract Historians dealing with evolutionary theory in the period between the death of Jean‐Baptiste Lamarck (in 1829) and the publication of Charles Darwin’s The Origin of Species (in 1859) have mainly focussed on evolutionist radicals who were, for the most part, working at the margins of mainstream science. This essay, however, wants to indicate that in the same time period, a more moderate (even conservative) transformism was developed in the well‐respected centres of scientific debate. It does so by concentrating on the intellectual trajectory of the Belgian Jean‐Baptiste d’Omalius d’Halloy, not only a geologist of European reputation but also a noted conservative and catholic aristocrat. On the basis of previously unused archival material, this essay researches how d’Omalius developed his evolutionist ideas, starting from the lessons he took with Lamarck in the beginning of the 19th century and ending with the last transformist publications he published as a 90‐year‐old in the 1870s. Furthermore, the essay analyses how d’Omalius adapted Lamarck’s transformist ideas to his personal worldview and looks at the tactics he used to open a space for the evolution debate. In this way, it shows a largely unknown aspect of the transforming of transformism in mid‐19th‐century science.     

Q-measures and betweenness centrality in a collaboration network: a case study of the field of informetrics

We study global and local Q-measures, as well as betweenness centrality, as indicators of international collaboration in research. After a brief review of their definitions, we introduce the concepts of external and internal inter-group geodesics. These concepts are applied to a collaboration network of 1129 researchers from different countries, which is based on publications in bibliometrics, informetrics, webometrics, and scientometrics (BIWS in short) from the period 1990–2009. It is thus illustrated how international collaboration (among authors from different countries) in BIWS is carried out. Our results suggest that average scores for local Q-measures are typically higher, indicating a relatively low degree of international collaboration in BIWS. The dominating form of international collaboration is bilateral, whereas multilateral collaboration is relatively rare in the field of BIWS. We also identify and visualize the most important global and local actors. Dividing the entire period in four 5-year periods, it is found that most international collaboration in the field has happened in the last time slice (2005–2009). A comparison of the different time slices reveals the non-linear growth of the indicators studied and the international expansion of the field.     

Second-order statistical regression and conditioning of replicate transient kinetic data

A new method has been developed to estimate physico-chemical parameters from transient kinetic data: second-order statistical regression (SOSR). It allows to account for heteroskedasticity and nonwhiteness of the noise in the time series measured. SOSR makes use of replicates to estimate the second-order statistics, i.e. the autocovariance pattern of the noise. A sample principal noise component analysis of the experimental time series allows nonlinear least-squares (NLSQ) regression of the latter. The method has been validated by regression of artificially generated experimental data and the results have been compared with those obtained with direct NLSQ regression. The SOSR has also been applied to the irreversible adsorption of oxygen on a reduced vanadia/silica catalyst and the interaction of propane with a copper/ceria catalyst, as studied with a temporal analysis of products (TAP) setup. In general, compared with those obtained with direct NLSQ regression, the parameter estimates and their confidence intervals are more accurate.     

Parameter identification and modeling of the biochemical methane potential of waste activated sludge

Anaerobic digestion is widely used in waste activated sludge treatment. In this paper, partial least-squares (PLS) is employed to identify the parameters that are determining the biochemical methane potential (BMP) of waste activated sludge. Moreover, a model is developed for the prediction of the BMP. A strong positive correlation is observed between the BMP and volatile fatty acids and carbohydrate concentrations in the sludge. A somewhat weaker correlation with COD is also present. Soluble organics (sCOD, soluble carbohydrates and soluble proteins) were shown not to influence the BMP in the observed region. This finding could be most-valuable in the context of application of sludge pretreatment methods. The obtained model was able to satisfactory predict the BMP.