Empirical Equation for Limit of Hygroscopicity

ABSTRACT

In this paper we are promoting the properties related to wood anatomy and chemical composition as the factor of influence to limit of hygroscopicity of wood (LH).

The wood samples of the most important domestic Hood species: oak Ouercus robur, beech Fogus sylvatica, fir Abies alba and spruce Picea abies were selected for this investigation.

For determining LH in our investigations we have applied the method of compression strength parallel to grain.

The results of experimental measurements were statistically analyzed and the empirical equation for LH dependance upon the significant (influential) factors: temperature. cellullse content and wood density in oven dry state is defined.     

Reliability of masonry walls subjected to in‐plane loading: A slip failure along head joints / Zuverlässigkeit von Mauerwerkswänden bei Belastung in der Ebene: Versagen entlang der Stoßfugenflucht

Masonry structures are a sustainable, economical and traditionally widely used type of construction. However, current masonry design codes are rather conservative, so there is a growing need for revision i.e. calibration of safety factors to improve the allocation of material resources. In this paper, we investigate the probability of occurrence of slip failure along head joints (perpends) in masonry subjected to in‐plane loading. An appropriate limit state function is established and the masonry material properties and loads are defined as random variables in order to simulate likelihood of occurrence of a slip failure regime along the head joints. Furthermore, an example of masonry wall with probabilistic analysis outcomes using Monte Carlo simulation is presented and recommendations for further work are provided.     

Fuzzy relation equations and reduction of fuzzy automata

We show that the state reduction problem for fuzzy automata is related to the problem of finding a solution to a particular system of fuzzy relation equations in the set of all fuzzy equivalences on its set of states. This system may consist of infinitely many equations, and finding its non-trivial solutions may be a very difficult task. For that reason we aim our attention to some instances of this system which consist of finitely many equations and are easier to solve. First, we study right invariant fuzzy equivalences, and their duals, the left invariant ones. We prove that each fuzzy automaton possesses the greatest right (resp. left) invariant fuzzy equivalence, which provides the best reduction by means of fuzzy equivalences of this type, and we give an effective procedure for computing this fuzzy equivalence, which works if the underlying structure of truth values is a locally finite residuated lattice. Moreover, we show that even better reductions can be achieved alternating reductions by means of right and left invariant fuzzy equivalences. We also study strongly right and left invariant fuzzy equivalences, which give worse reductions than right and left invariant ones, but whose computing is much easier. We give an effective procedure for computing the greatest strongly right (resp. left) invariant fuzzy equivalence, which is applicable to fuzzy automata over an arbitrary complete residuated lattice.     

Comparison of Fenton's oxidation and ozonation for removal of estrogens

This study compares efficiency of Fenton's oxidation and ozonation of 17beta-estradiol (E2) and 17alpha-ethinylestradiol (EE2) as two possible processes for removal of estrogens from aqueous solutions. The effectiveness of Fenton's oxidative removal was studied at different ratios of reagents Fe2+:H2O2 (1:0.5; 1:10; 1:20; 1:33), where with some molar ratios up to 100% removal of E2 and EE2 was achieved in the first few minutes of reaction. The best molar ratio for E2 (17beta-estradiol) removal was 1:33, while in the case of EE2 the most efficient one was 1:20 ratio. Ozonation was much faster, because complete removal of estrogens was achieved in 30 seconds (pH approximately eaqual 6), but the time of ozonation was extended up to 60 minutes trying to decompose formed by-products, expressing estrogenic activity, detected by YES (Yeast Estrogen Screening) assay. The obtained results showed that the removal efficiency of estrogens from waters should be assessed by a combination of chemical analyses and bioassay.     

Sparse implicitization by interpolation: Characterizing non-exactness and an application to computing discriminants

We revisit implicitization by interpolation in order to examine its properties in the context of sparse elimination theory. Based on the computation of a superset of the implicit support, implicitization is reduced to computing the nullspace of a numeric matrix. The approach is applicable to polynomial and rational parameterizations of curves and (hyper)surfaces of any dimension, including the case of parameterizations with base points. Our support prediction is based on sparse (or toric) resultant theory, in order to exploit the sparsity of the input and the output. Our method may yield a multiple of the implicit equation: we characterize and quantify this situation by relating the nullspace dimension to the predicted support and its geometry. In this case, we obtain more than one multiple of the implicit equation; the latter can be obtained via multivariate polynomial GCD (or factoring). All of the above techniques extend to the case of approximate computation, thus yielding a method of sparse approximate implicitization, which is important in tackling larger problems. We discuss our publicly available Maple implementation through several examples, including the benchmark of a bicubic surface. For a novel application, we focus on computing the discriminant of a multivariate polynomial, which characterizes the existence of multiple roots and generalizes the resultant of a polynomial system. This yields an efficient, output-sensitive algorithm for computing the discriminant polynomial.     

Quantum walks, Ihara zeta functions and cospectrality in regular graphs

In this paper we explore an interesting relationship between discrete-time quantum walks and the Ihara zeta function of a graph. The paper commences by reviewing the related literature on the discrete-time quantum walks and the Ihara zeta function. Mathematical definitions of the two concepts are then provided, followed by analyzing the relationship between them. Based on this analysis we are able to account for why the Ihara zeta function can not distinguish cospectral regular graphs. This analysis suggests a means by which to develop zeta functions that have potential in distinguishing such structures.     

Pharmaceutical residues in the Danube River Basin in Serbia - a two-year survey

Pharmaceuticals are emerging contaminants with damaging effects to the environment and human health. Their presence in surface and especially groundwaters is regarded as detrimental, as they can ultimately reach drinking water. The aim of this work was to monitor pharmaceutical contamination of the Danube River and its tributaries in Serbia, and to assess the potential of their passing through all natural filtrations and reaching the groundwater. A total of 70 surface and groundwater samples was collected at 38 sampling sites at the Danube in Serbia. They were taken in five sampling campaigns performed in summer and autumn of 2009 and winter, spring and autumn of 2010. Samples were analyzed using a previously developed method which includes solid-phase extraction followed by liquid chromatography-tandem mass spectrometry.     

GEOCHEMICAL CHARACTERISTICS OF CRUDE OILS FROM THE SHARARA-C OIL FIELD,MURZUQ BASIN,SOUTHWESTERN LIBYA

Crude oil samples from the Sharara-C oil field (Concession NC-115, Murzuq Basin, SW Libya) were analysed by organic geochemical methods in order to infer the geochemical characteristics of their respective source rocks. Aromatic hydrocarbons were analysed by gas chromatography – mass spectrometry (GC-MS), and gas chromatography – tandem mass spectrometry (GC-MS-MS) was used to analyse saturated biomarkers. The Sharara-C oils are interpreted to have been generated by marine shales containing mixed terrigenous and marine organic materials deposited in an intermediate (suboxic) environment. Age-specific biomarker ratios indicated that the oils are older than Cretaceous, and maturation-related parameters pointed to their high thermal maturity. Consistent with previous studies, source rocks are inferred to be “hot” shales in the Lower Silurian Tanezzuft Formation. Almost all the parameter ratios calculated varied over a very narrow range, indicating that the investigated oils were compositionally similar. The only significant difference that was noted concerned the sterane/hopane ratios whose variation suggested that there was some variability in the composition of the source organic material. The organic geochemical parameters determined for the Sharara-C crude oils were compared with published data on other crude oils from Concession NC-115. Almost all the parameters agreed well with previously published data on oils from this part of the Murzuq Basin. The greatest deviation concerned the values of some of the maturity parameters. This tended to confirm the conclusions of previous studies concerning the presence of a number of distinct oil families and sub-families in the Sharara oil field area which are genetically related but which have different maturities.     

Electronic Nose Technology in Quality Assessment: Predicting Volatile Composition of Danish Blue Cheese During Ripening

This work describes for the 1st time the use of an electronic nose (e‐nose) for the determination of changes of blue cheeses flavor during maturation. Headspace analysis of Danish blue cheeses was made for 2 dairy units of the same producer. An e‐nose registered changes in cheeses flavor 5, 8, 12, and 20 wk after brining. Volatiles were collected from the headspace and analyzed by gas chromatography‐mass spectrometry (GC‐MS). Features from the chemical sensors of the e‐nose were used to model the volatile changes by multivariate methods. Differences registered during ripening of the cheeses as well as between producing units are described and discussed for both methods. Cheeses from different units showed significant differences in their e‐nose flavor profiles at early ripening stages but with ripening became more and more alike. Prediction of the concentration of 25 identified aroma compounds by e‐nose features was possible by partial least square regression (PLS‐R). It was not possible to create a reliable predictive model for both units because cheeses from 1 unit were contaminated by Geotrichum candidum, leading to unstable ripening patterns. Correction of the e‐nose features by multiple scatter correction (MSC) and mean normalization (MN) of the integrated GC areas made correlation of the volatile concentration to the e‐nose signal features possible. Prediction models were created, evaluated, and used to reconstruct the headspace of unknown cheese samples by e‐nose measurements. Classification of predicted volatile compositions of unknown samples by their ripening stage was successful at a 78% and 54% overall correct classification for dairy units 1 and 2, respectively. Compared with GC‐MS, the application of the rapid and less demanding e‐nose seems an attractive alternative for this type of investigation.