Межличностные отношения — связывающая структура в системе управления

Hybrid-electric vehicles (HEVs) and battery-electric vehicles (BEVs) are currently more expensive than conventional passenger cars but may become cheaper due to technological learning. Here, we obtain insight into the prospects of future price decline by establishing ex-post learning rates for HEVs and ex-ante price forecasts for HEVs and BEVs. Since 1997, HEVs have shown a robust decline in their price and price differential at learning rates of 7 ± 2% and 23 ± 5%, respectively. By 2010, HEVs were only 31 ± 22 €2010 kW-1 more expensive than conventional cars. Mass-produced BEVs are currently introduced into the market at prices of 479 ± 171 €2010 kW-1, which is 285 ± 213 €2010 kW-1 and 316 ± 209 €2010 kW-1 more expensive than HEVs and conventional cars. Our forecast suggests that price breakeven with these vehicles may only be achieved by 2026 and 2032, when 50 and 80 million BEVs, respectively, would have been produced worldwide. We estimate that BEVs may require until then global learning investments of 100–150 billion € which is less than the global subsidies for fossil fuel consumption paid in 2009. These findings suggest that HEVs, including plug-in HEVs, could become the dominant vehicle technology in the next two decades, while BEVs may require long-term policy support

Allopurinol and oxypurinol are hydroxyl radical scavengers

AbstractAllopurinol is a scavenger of the highly reactive hydroxyl radical (k2 approx. 109 M−1s−1). One product of attack of hydroxyl radical upon allopurinol is oxypurinol, which is a major metabolite of allopurinol. Oxypurinol is a better hydroxyl radical scavenger than is allopurinol (k2 approx. 4 × 109 M−1s−1) and it also reacts with the myeloperoxidase-derived oxidant hypochlorous acid. Hence the protective actions of allopurinol against reperfusion damage after hypoxia need not be entirely due to xanthine oxidase inhibition

Application of data augmentation techniques towards metabolomics

Niemann–Pick Class 1 (NPC1) disease is a rare and debilitating neurodegenerative lysosomal storage disease (LSD). Metabolomics datasets of NPC1 patients available to perform this type of analysis are often limited in the number of samples and severely unbalanced. In order to improve the predictive capability and identify new biomarkers in an NPC1 disease urinary dataset, data augmentation (DA) techniques based on computational intelligence have been employed to create synthetic samples, i.e. the addition of noise, oversampling techniques and conditional generative adversarial networks. These techniques have been used to evaluate their predictive capacities on a set of urine samples donated by 13 untreated NPC1 disease and 47 heterozygous (parental) carrier control participants. Results on the prediction have also been obtained using different machine learning classification models and the partial least squares techniques. These results provide strong evidence for the ability of DA techniques to generate good quality synthetic data. Results acquired show increases in sensitivity of 20%–50%, an F1 score of 6%–30%, and a predictive capacity of 0.3 (out of 1). Additionally, more conventional forms of multivariate data analysis have been employed. These have allowed the detection of unusual urinary metabolite profiles, and the identification of biomarkers through the use of synthetically augmented datasets. Results indicate that urinary branched-chain amino acids such as valine, 3-aminoisobutyrate and quinolinate, may be employable as valuable biomarkers for the diagnosis and prognostic monitoring of NPC1 diseaseThe authors acknowledge the support from MINECO (Spain) through grants TIN2017-88728-C2-1-R and PID2020-116898RB-I00 (MICINN), from Universidad de Málaga y Junta de Andalucía through grant UMA20-FEDERJA-045, and from Instituto de Investigación Biomédica de Málaga – IBIMA (all including FEDER funds). Funding for open access charge: Universidad de Málaga / CBUA

Assessment of antimicrobial activity of textiles for wound dressing: methodology optimization

Normally, the skin is capable of restore the tissue integrity, after wound injury. However, the deposition of bacteria on the wound site results on infection causing pain and healing delay. To control bacteria proliferation, antimicrobial textiles have been developed, and the assessment of their activity is a required step. Although, several standard methods were published to assess textiles antimicrobial activity, they are time and material consuming and have some shortcomings with regard to the real conditions of use. Therefore, the aim of this work was to optimize the method described on JIS L 1902:2008-Testing for antibacterial activity and efficacy on textile products, the most commonly used standard. Two textile samples were used: A-cotton without treatment (control) and B-cotton with 10% of the recommend concentration of Ruco-bac AGP. The microorganism used was Staphylococcus aureus-ATCC 6538. The first improvement was sample size. On the qualitative method, square samples with 1x1cm2 were used instead 2.5x2.5cm2 (suggested by the standard). For sample A no antimicrobial activity was observed and for sample B the halo size was similar for both sizes used. For the quantitative method, the samples used had 0.4g (standard suggestion) and 0.1g. Sample A had the same bacterial growth before and after contact with the fabric and sample B had no bacterial growth. With this improvement, the amount of sample and solutions need for the test was reduced four times. To reduce the use of disposable material, instead of 50mL falcons, 6 well plates were used. In this case, no bacteria were recovered from the sample A after incubation period on 6 well plates. These means, that the centrifugation is a crucial step to detach all bacteria from the fabric. The effect of the bacterial inoculum volume was also assessed. Three inoculum volumes (250, 100 and 50µL) were added to 0,1g samples. No significant differences were observed for both samples. A healthy skin has 105bacteria/cm2 and up to this value it is considered that the skin is infected. Therefore, 3 inoculum concentrations were tested-3x105, 3x106, 3x107cell/mL. The results showed that the inoculum concentration had no significant changes for both samples after the incubation period. In conclusion, it is possible to use samples 4 times smaller than the standard suggestion, use higher inoculum volume to simulate wound exudate and higher concentration, to accurately predict the sample behaviour on an infected skin

Computational intelligence techniques in medicine

El advenimiento de la Era de la Información, también conocida como la Era Digital, ha realizado un profundo impacto en las ciencias de la salud. Vastas cantidades de conjuntos de datos fluyen ahora a través de los diferentes estratos de las organizaciones sanitarias, y existe un requisito importante para extraer el conocimiento y emplearlo en la mejora de estos centros en todos los aspectos. Los sistemas informáticos inteligentes proporcionan apoyo a los profesionales de la salud implicados tanto en los contextos médicos como administrativos. Entre estos sistemas, métodos de inteligencia computacional han adquirido una creciente popularidad, dada su capacidad para hacer frente a grandes cantidades de datos clínicos e información precisa.El fin de esta edición especial es ofrecer una amplia visión de este apasionante campo, cuya creciente importancia es impulsada por el aumento de la disponibilidad de datos y sus potenciales de cálculo. The advent of the information age, also commonly known as the digital age, has made a profound impact on health sciences. Vast amounts of datasets now flow through the different stages of healthcare organizations, and there is a major requirement to extract knowledge and employ it to improve these centres in all respects. Intelligent computer systems provide support to health professionals involved both in the medical and managerial contexts. Amongst these systems, computational intelligence approaches have gained increasing popularity given their ability to cope with large amounts of clinical data and uncertain information. Thegoal of this special issue is to offer a broad view of this exciting field, the ever-growing importance of which is driven by the increasing availability of data and computational power.peerReviewe

Characterisation of Actions of p-menthane-3,8 diol (PMD) Repellent Formulations against Aedes aegypti mosquitoes

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Background Characterisation of mosquito repellents using arm-in-cage tests are performed by assessing the ED95, half-life and complete protection times (CPT). This study fully characterises p-menthane-3,8 diol PMD which has not been widely studied, and a long-acting formulation containing a PMD-vanillin composite. Method A series of arm in cage tests against Aedes aegypti aegypti (Dipera-Culicidae) strain mosquitoes were devised using 6 volunteers to estimate CPT or 10 to estimate the effective dose (ED95) and half-life for three repellents: 20% DEET, 30% PMD and a novel 30% PMD-vanillin formulation. Non-linear Regression analysis was used to characterise the relationship between applied dose and CPT. were also estimated Results PMD and DEET showed a very similar log dose relationship to CPT; however, the PMD-vanillin formulation exhibited a sigmoidal ‘S-shape’ relationship. This resulted in a 1.5 times higher CPT for PMD-vanillin compared to that of 20% DEET when applied at a dose of 1.6mg/cm2, but little difference at lower doses of 0.8-1mg/cm2. The ED95 value for the 30% PMD and PMD-vanillin formulations were 0.25 and 0.24 mg/cm2 respectively, these being higher than that for 20% DEET (0.09 mg/cm2). The half-lives for 30% PMD and 20% DEET were similar (2.23 vs. 2.74 hrs.), but longer for the PMD-vanillin formulations (3.8 hrs.). Conclusion Such a full characterisation for other repellent formulations, particularly those claiming extended longevity, should be conducted in order to identify differences at various applied doses

The role of polydimethylsiloxane in suppressing the evolution of lipid oxidation products in thermo-oxidised sunflower oil : influence of stirring processes

Suppressing the evolution of lipid oxidation products (LOPs) in commercially available culinary oils is considered to represent a valuable health-promoting incentive since these agents have cytotoxic and genotoxic properties and have been implicated in the pathogenesis of several chronic disease states. One agent used to suppress LOPs formation is polydimethylsiloxane (PDMS). In this study, proton nuclear magnetic resonance (1H NMR) analysis was employed to evaluating the influence of increasing PDMS concentrations (6.25 × 10−7, 1.0 × 10−5, 0.025, 0.05, 0.1, 0.5, 1.0, 5.0, and 10.0 ppm) in either stirred or unstirred refined sunflower oil exposed to thermal stressing episodes continuously at 180°C for 300 min with no oil replenishment. Results acquired showed that the extent of blockage of LOPs generation was correlated with increasing concentrations of PDMS. The minimal level of added PDMS required to provide a statistically significant protective role for both stirred and unstirred culinary oils when exposed to high frying temperatures was only 6.25 × 10−7 ppm. Furthermore, stirring at 250 rpm was experimentally determined to reduce the functional role PDMS. This is vital in a real world setting since the boiling process of frying may ultimately reduce the LOPs suppression activity of PDMS

Nuclear magnetic resonance spectroscopic analysis of the evolution of peroxidation products arising from culinary oils exposed to thermal oxidation : an investigation employing ¹H and ¹H-¹H COSY and TOCSY techniques

Scientific warnings on the deleterious health effects exerted by dietary lipid oxidation products (LOPs) present in thermally stressed culinary oils have, to date, not received adequate attention given that there has been an increase in the use and consumption of such oil products in everyday life. In this study, high-resolution (1)H nuclear magnetic resonance (NMR) analysis was used to characterize and map chemical modifications to fatty acid (FA) acyl groups and the evolution of LOPs in saturated fatty acid (SFA)-rich ghee, monounsaturated fatty acid (MUFA)-rich groundnut, extra virgin olive, and macadamia oils, along with polyunsaturated fatty acid (PUFA)-rich sesame, corn and walnut oils, which were all thermally stressed at 180 °C, continuously and discontinuously for 300 and 480 min, respectively. Results acquired revealed that PUFA-rich culinary oils were more susceptible to thermo-oxidative stress than the others tested, as expected. However, ghee and macadamia oil both generated only low levels of toxic LOPs, and these results demonstrated a striking similarity. Furthermore, at the 120 min thermo-oxidation time-point, the discontinuous thermo-oxidation episodes produced higher concentrations of aldehydic LOPs than those produced during continuous thermo-oxidation sessions for the same duration. On completion of the thermo-oxidation period, a higher level of triacylglycerol chain degradation, and hence, higher concentrations of aldehydes, were registered in culinary oils thermally stressed continuously over those found in discontinuous thermo-oxidized oils. These findings may be crucial in setting targets and developing scientific methods for the suppression of LOPs in thermo-oxidized oils

Current Concepts of Laser–Oral Tissue Interaction.

open access articleFundamental to the adjunctive use of laser photonic energy for delivering therapy and tissue management, is the ability of the incident energy to be absorbed by target tissues. The aim of this review is to examine the differential performance of the separate components of oral hard and soft tissues when exposed to laser photonic irradiance of variable wavelengths and power values. Through an examination of peer-reviewed published data and materials, the interaction of laser photonic energy and target tissues are explored in detail. Varying laser wavelength emissions relative to anatomical structures explores the ability to optimise laser–tissue interactions, and also identifies possible risk scenarios as they apply to adjacent non-target structures. The concepts and practical aspects of laser photonic energy interactions with target oral tissues are clearly demonstrated. Emphasis was placed on optimising the minimum level of laser power delivery in order to achieve a desired tissue effect, whilst minimising the risk or outcome of collateral tissue damage