Linearisation via input–output injection of time delay systems

This paper deals with the problem of linearisation of systems with constant commensurable delays by input–output injection using algebraic control tools based on the theory of non-commutative rings. Solutions for the problem of linearisation free of delays, and with delays of an observable nonlinear time-delay systems are presented based on the analysis of the input–output equation. These results are achieved by means of constructive algorithms that use the nth derivative of the output expressed in terms of the state-space variables instead of the explicit computation of the input–output representation of the system. Necessary and sufficient conditions are established in both cases by means of an invertible change of coordinates.     

MicroRNAs as Biomarkers for Diagnosis,Prognosis and Theranostics in Prostate Cancer

Prostate cancer (PC) includes several phenotypes, from indolent to highly aggressive cancer. Actual diagnostic and prognostic tools have several limitations, and there is a need for new biomarkers to stratify patients and assign them optimal therapies by taking into account potential genetic and epigenetic differences. MicroRNAs (miRNAs) are small sequences of non-coding RNA regulating specific genes involved in the onset and development of PC. Stable miRNAs have been found in biofluids, such as serum and plasma; thus, the measurement of PC-associated miRNAs is emerging as a non-invasive tool for PC detection and monitoring. In this study, we conduct an in-depth literature review focusing on miRNAs that may contribute to the diagnosis and prognosis of PC. The role of miRNAs as a potential theranostic tool in PC is discussed. Using a meta-analysis approach, we found a group of 29 miRNAs with diagnostic properties and a group of seven miRNAs with prognostic properties, which were found already expressed in both biofluids and PC tissues. We tested the two miRNA groups on The Cancer Genome Atlas dataset of PC tissue samples with a machine-learning approach. Our results suggest that these 29 miRNAs should be considered as potential panel of biomarkers for the diagnosis of PC, both as in vivo non-invasive test and ex vivo confirmation test.     

Improving Performance on Data-Intensive Applications Using a Load Balancing Methodology Based on Divisible Load Theory

Data-intensive applications are those that explore, query, analyze, and, in general, process very large data sets. Generally, these applications can be naturally implemented in parallel but, in many cases, these implementations show severe performance problems mainly due to load imbalances, inefficient use of available resources, and improper data partition policies. It is worth noticing that the problem becomes more complex when the conditions causing these problems change at run time. This paper proposes a methodology for dynamically improving the performance of certain data-intensive applications based on: adapting the size and number of data partitions, and the number of processing nodes, to the current application conditions in homogeneous clusters. To this end, the processing of each exploration is monitored and gathered data is used to dynamically tune the performance of the application. The tuning parameters included in the methodology are: (i) the partition factor of the data set, (ii) the distribution of the data chunks, and (iii) the number of processing nodes to be used. The methodology assumes that a single execution includes multiple related explorations on the same partitioned data set, and that data chunks are ordered according to their processing times during the application execution to assign first the most time consuming partitions. The methodology has been validated using the well-known bioinformatics tool—BLAST—and through extensive experimentation using simulation. Reported results are encouraging in terms of reducing total execution time of the application (up to a 40 % in some cases).     

Solid dispersions enhance solubility,dissolution, and permeability of thalidomide

Thalidomide (THD) is a BCS class II drug with renewed and growing therapeutic applicability. Along with the low aqueous solubility, additional poor biopharmaceutical properties of the drug, i.e. chemical instability, high crystallinity, and polymorphism, lead to a slow and variable oral absorption. In this view, we developed solid dispersions (SDs) containing THD dispersed in different self-emulsifying carriers aiming at an enhanced absorption profile for the drug. THD was dispersed in lauroyl macrogol-32 glycerides (Gelucire^® 44/14) and α-tocopherol polyethylene glycol succinate (Kolliphor^® TPGS), in the presence or absence of the precipitation inhibitor polyvinylpyrrolidone K30 (PVP K30), by means of the solvent method. Physicochemical analysis revealed the formation of semicrystalline SDs. X-ray diffraction and infrared spectroscopy analyses suggest that the remaining crystalline fraction of the drug in the SDs did not undergo polymorphic transition. The impact of the solubility-enhancing formulations on the THD biopharmaceutical properties was evaluated by several in vitro techniques. The developed SDs were able to increase the apparent solubility of the drug (up to 2–3x the equilibrium solubility) for a least 4?h. Dissolution experiments (paddle method, 75?rpm) in different pHs showed that around 80% of drug dissolved after 120?min (versus 40% of pure crystalline drug). Additionally, we demonstrated the enhanced solubility obtained via SDs could be translated into increased flux in a parallel artificial membrane permeability assay (PAMPA). In summary, the results demonstrate that SDs could be considered an interesting and unexplored strategy to improve the biopharmaceutical properties of THD, since SDs of this important drug have yet to be reported.     

Understanding and addressing exhibitionism in Java empirical research about method accessibility

Empirical Software Engineering - Information hiding is a positive consequence of properly defining component interfaces. Unfortunately, determining what should constitute a public interface remains...     

Deep Cavitand Self‐Assembled on Au NPs‐MWCNT as Highly Sensitive Benzene Sensing Interface

The unprecedented sensitivity and partial selectivity of quinoxaline‐walled thioether‐legged deep cavitand functionalized multiwall carbon nanotubes toward traces of benzene vapors are presented. The cavitand is grafted onto gold nanoparticle (Au‐NP) decorated oxygen plasma treated multiwall carbon nanotubes (O‐MWCNT) by a self‐assembled monolayer process affording a product referred to as cav‐Au‐MWCNT. The reported technique is suitable for the mass production of hybrid nanomaterials at low cost. The cav‐Au‐MWCNT resistive gas sensor operates at room temperature and shows an outstanding performance toward traces of benzene vapors. The detection of 2.5 ppb of benzene in dry air is demonstrated with a limit of detection (LOD) near 600 ppt. For the first time, it is shown that a CNT nanomaterial can effectively sense the extremely harmful benzene molecule with higher sensitivity than toluene or o‐xylene at the trace levels. The cavitand is well suited for binding benzene, which, being in close proximity to the MWCNT, affects its density of states (DOS) shifting the Fermi level away from the valence band. The binding of benzene is transduced in a diminution of MWCNT conductance. Furthermore, the inclusion of benzene is fully reversible at room temperature, implying that the sensor can operate at very low power consumption.     

Fluorescence anisotropy analysis of protein–antibody interaction

The interaction between glutathione S-transferase and its antibody α-glutathione S-transferase (B-14) was studied using fluorescence anisotropy, subsequent to glutathione S-transferase bioconjugation with fluorescein-5-maleimide, leading to the determination of the dissociation and association binding constants, K_d and K_a; good binding specificity was observed between glutathione S-transferase and the antibody B-14. The use of spectroscopic techniques, fluorescence anisotropy in particular, is a useful and favourable tool to study biochemical problems.     

Batch and continuous precipitation of scorodite from dilute industrial solutions

Enriched arsenic precipitates were obtained from dilute industrial As(III) solutions (1.1–0.1 g As/L) at 95 °C in batch and continuous reactor operations. A complete and fast oxidation of As(III) was obtained at room temperature with 20% excess of hydrogen peroxide. Arsenic removal varied from 80.5 to 94.6% and increased with the total surface area (SSA) of the seed. SSA higher than 270 m²/g was required to promote an arsenic removal of approximately 85%. Recycling of solids was necessary to achieve high yields of arsenic removal in continuous operation. Approximately 75 to 85% As was removed in 1 h of residence time in the MSMPRR (Mixed Suspension Mixed Product Removal with Solids Recycle) reactor; the rate of crystal growth was calculated as 10^? 12 m/s. Arsenic removal was not favored by the excess of iron in the solution. TCLP (Toxicity Characterization Leaching Procedure) testing indicated that ageing plays an important role in the leachability of scorodite, which decreased from 13.6 mg As/L to 0.1 mg As/L after 8 h in a batch reactor. The decrease in As leachability was related to the decrease in the SSA (14 m²/g to 0.9 m²/g after 62 h in the MSMPRR) as a combination of crystal growth (1.6 μm to 5.3 μm) and densification. Scorodite was the only arsenic phase identified by X-ray diffraction and micro-Raman analyses of the precipitates.