Computing the homology of groups: The geometric way

In this paper, we present several algorithms related with the computation of the homology of groups, from a geometric perspective (that is to say, carrying out the calculations by means of simplicial sets and using techniques of Algebraic Topology). More concretely, we have developed some algorithms which, making use of the effective homology   method, construct the homology groups of Eilenberg–MacLane spaces K(G,1)$K(G,1)$ for different groups G$G$, allowing one in particular to determine the homology groups of G$G$.     

Acoustic evaluation and adjustment of an open-plan office through architectural design and noise control

Arranging office space into a single open room offers advantages in terms of easy exchange of information and interaction among coworkers, but reduces privacy and acoustic comfort. Thus, the purpose of this work was to evaluate the acoustic quality of a real open-plan office and to propose changes in the room to improve the acoustic conditioning of this office. The computational model of the office under study was calibrated based on RT and STI measurements. Predictions were made of the RT and STI, which generated the radius of distraction r(D), and the rate of spatial decay of sound pressure levels per distance doubling DL(2) in the real conditions of the office and after modifications of the room. The insertion of dividers between work stations and an increase in the ceiling's sound absorption improved the acoustic conditions in the office under study.     

SNR gap approximation for M-PSK-Based bit loading

Adaptive OFDM has the potential of providing bandwidth-efficient communications in hostile propagation environments. Currently, bit loading algorithms use M-ary quadrature amplitude modulation of the OFDM sub-carriers, where the number of bits per symbol modulating each of them is obtained in order to maximize the performance. SNR gap approximation for M-QAM signaling makes the algorithms simpler to implement. However, in some circumstances it may be preferable to use. M-ary phase shift keying. In this letter an approximation is derived for M-PSK similar to the SNR gap of M-QAM so that bit loading algorithms can be extended to this type of modulation. In addition, the performance obtained when using M-PSK is compared to that of M-QAM in a practical situation.     

Pollution Buildup on Road Surfaces

Samples of sediment found on an urban road in Aberdeen (Scotland) were collected by washing designated surfaces. This method, called the “wet” method, was capable of collecting sediment of the smallest particle size range that is normally left behind by traditional sampling techniques using dry vacuuming. Over 17 months (mainly on a weekly basis), 66 samples were collected and analyzed for sediment loading, particle size distribution, concentration of heavy metals (Zn, Cu, Pb, Cd) in four sediment size fractions, and several dissolved pollutants in the effluent collected from washing (NO3?,?SO42?,?PO43?,?Cl?,?F?,?NH4+, total organic carbon, total carbon). Standard statistical methods, including multiple regressions, were used to determine relationships amongst different sediment characteristics. It was found that sediment loading, as well as concentrations of Cl? and SO42?, were highest in the winter months, especially when snow was present on the road surface. It was observed that 66% of total road sediment loading was found within a 0.5 m strip next to the curb. The average sediment particle sizes found were smaller than those previously recorded in the literature. As expected, the concentrations of heavy metals were highest in the smallest particle size fraction analyzed (<63?μm), and this occurred during the summer months when less sediment was available on the street surface. The antecedent dry weather period had a very weak and negative influence on the loading rate of the smallest particle size fraction next to the curb.     

Influence diagnostics in regression with complex designs through conditional bias

One of the areas of Statistics in which the influence analysis has been widely studied is the multiple linear regression model. Nevertheless, the influence diagnostics proposed in this context cannot be applied to regression in complex survey, under randomized inference, since the i.i.d. case does not incorporate any probability weighting or population structure, such as clustering, stratification or measures of size into the analysis. In this paper we introduce some influence diagnostics in regression in complex survey. They are built on the conditional bias concept (Moreno-Rebollo et al., 1999). We emphasize the similarities and differences of the proposed measures with respect to the existing ones for the i.i.d. case. Research partly supported by the Spanish MCYT grant BFM2001-3844 and Spanish MEC grant MTM2004-0111433.     

Probabilistic Approach to Predict Cracking in Lightly Reinforced Microconcrete Panels

The ultimate strength of structures made of brittle materials—such as microconcrete—strongly depends on microstructural defects, the structure size, and the loading pattern. Probabilistic approaches allow one to take account of such dependencies. By using a Weibull model, cracking of ferrocement panels is analyzed. Provided the behavior of the reinforcement remains elastic, it is shown that the Weibull parameters identified on unreinforced microconcrete samples tested in flexure may be used to predict multiple cracking in ferrocement panels tested in tension. A key aspect of the analysis is related to the understanding and modeling of the stress heterogeneity effect on the local failure probability of unreinforced as well as reinforced microconcrete by the use of a so-called Weibull stress.     

ZRC – A Refinement Calculus for Z

The fact that Z is a specification language only, with no associated program development method, is a widely recognised problem. As an answer to that, we present ZRC, a refinement calculus based on Morgan's work that incorporates the Z notation and follows its style and conventions. This work builds upon existing refinement techniques for Z, but distinguishes itself mainly in that ZRC is completely formalised. In this paper, we explain how programs can be derived from Z specifications using ZRC. We present ZRC-L, the language of our calculus, and its conversion laws, which are concerned with the transformation of Z schemas into programs of this language. Moreover, we present the weakest precondition semantics of ZRC-L, which is the basis for the derivation of the laws of ZRC. More than a refinement calculus, ZRC is a theory of refinement for Z. Received July 1997 / Accepted in revised form October 1998     

Identification of a Maturation Plasma Cell Index through a Highly Sensitive Droplet Digital PCR Assay Gene Expression Signature Validation in Newly Diagnosed Multiple Myeloma Patients

DNA microarrays and RNA-based sequencing approaches are considered important discovery tools in clinical medicine. However, cross-platform reproducibility studies undertaken so far have highlighted that microarrays are not able to accurately measure gene expression, particularly when they are expressed at low levels. Here, we consider the employment of a digital PCR assay (ddPCR) to validate a gene signature previously identified by gene expression profile. This signature included ten Hedgehog (HH) pathways’ genes able to stratify multiple myeloma (MM) patients according to their self-renewal status. Results show that the designed assay is able to validate gene expression data, both in a retrospective as well as in a prospective cohort. In addition, the plasma cells’ differentiation status determined by ddPCR was further confirmed by other techniques, such as flow cytometry, allowing the identification of patients with immature plasma cells’ phenotype (i.e., expressing CD19+/CD81+ markers) upregulating HH genes, as compared to others, whose plasma cells lose the expression of these markers and were more differentiated. To our knowledge, this is the first technical report of gene expression data validation by ddPCR instead of classical qPCR. This approach permitted the identification of a Maturation Index through the integration of molecular and phenotypic data, able to possibly define upfront the differentiation status of MM patients that would be clinically relevant in the future.     

New Perspectives on the Sustainable Employment of Chestnut Shells as Active Ingredient against Oral Mucositis: A First Screening

Oral mucositis (OM), a common side effect of oncological treatment, is an oral mucosal disorder characterized by painful ulcerations and increased risk of infection. The use of natural antioxidants to suppress the redox imbalance responsible for the OM condition has emerged as an interesting approach to prevent/treat OM. This study aims to explore the chestnut (Castana sativa) shells as potential active ingredient against OM. Therefore, chestnut shells were extracted at different temperatures (110–180 °C) by Subcritical Water Extraction (SWE), aiming to recover antioxidants. The extracts were also evaluated against microorganisms present in the oral cavity as well as on human oral cell lines (TR146 and HSC3). The highest phenolic content was obtained with the extraction temperature of 110 °C, exhibiting the best antioxidant/antiradical activities and scavenging efficiencies against HOCl (IC₅₀ = 4.47 μg/mL) and ROO^• (0.73 μmol TE/mg DW). High concentrations of phenolic acids (e.g., gallic and protocatechuic acids) and flavanoids (catechin, epicatechin and rutin) characterized the phenolic profile. The antimicrobial activity against several oral microorganisms present in the oral cavity during OM, such as Streptococcus, Staphylococcus, Enterococcus, and Escherichia, was demonstrated. Finally, the effects on HSC3 and TR146 cell lines revealed that the extract prepared at 110 °C had the lowest IC₅₀ (1325.03 and 468.15 µg/mL, respectively). This study highlights the potential effects of chestnut shells on OM.