Heavy metal pollutant in urban street dust has become a growing concern in recent years. Street dust samples from urban and suburban areas were collected from the Sarajevo area, Bosnia and Herzegovina, during the spring season of 2013. Samples were collected from low and high density traffic roads, industrial zones, parks, parking places, hospitals and local health centres, school gardens. The levels of heavy metals of street dusts were determined by flame atomic absorption spectrometry (FAAS). Cadmium, chromium, copper, nickel, iron, manganese, lead and zinc levels in the dust samples were found in the range of 0.58–3.65, 3.42–60.82, 5.49– 388, 9.31–161, 647–2244, 6.10–13.32, 31.63-1760 and 40.29–378 μg/g, respectively. The highest metal concentrations were found in samples from industrial zone and in the streets with heavy traffic. The lowest levels of the metal concentrations were found in the samples from health centres and school gardens. The concentrations of the metals were, in most of cases, similar to the mean world-wide contents of the street dust samples. Correlations between heavy trace metal levels of the dust samples were also evaluated.

Significance Although scientists have identified surprising cognitive flexibility in animals and potentially unique features of human psychology, we know less about the selective forces that favor cognitive evolution, or the proximate biological mechanisms underlying this process. We tested 36 species in two problem-solving tasks measuring self-control and evaluated the leading hypotheses regarding how and why cognition evolves. Across species, differences in absolute (not relative) brain volume best predicted performance on these tasks. Within primates, dietary breadth also predicted cognitive performance, whereas social group size did not. These results suggest that increases in absolute brain size provided the biological foundation for evolutionary increases in self-control, and implicate species differences in feeding ecology as a potential selective pressure favoring these skills. Cognition presents evolutionary research with one of its greatest challenges. Cognitive evolution has been explained at the proximate level by shifts in absolute and relative brain volume and at the ultimate level by differences in social and dietary complexity. However, no study has integrated the experimental and phylogenetic approach at the scale required to rigorously test these explanations. Instead, previous research has largely relied on various measures of brain size as proxies for cognitive abilities. We experimentally evaluated these major evolutionary explanations by quantitatively comparing the cognitive performance of 567 individuals representing 36 species on two problem-solving tasks measuring self-control. Phylogenetic analysis revealed that absolute brain volume best predicted performance across species and accounted for considerably more variance than brain volume controlling for body mass. This result corroborates recent advances in evolutionary neurobiology and illustrates the cognitive consequences of cortical reorganization through increases in brain volume. Within primates, dietary breadth but not social group size was a strong predictor of species differences in self-control. Our results implicate robust evolutionary relationships between dietary breadth, absolute brain volume, and self-control. These findings provide a significant first step toward quantifying the primate cognitive phenome and explaining the process of cognitive evolution.

This paper deals with combination of two modern engineering methods in order to optimise the shape of a representative casting product. The product being analysed is a sling, which is used to attach pulling rope in timber transportation. The first step was 3D modelling and static stress/strain analysis using CAD/CAE software NX4. The slinger shape optimization was performed using Traction method, by means of software Optishape-TS. To define constraints for shape optimization, FEA software FEMAP was used. The mould pattern with optimized 3D shape was then prepared using Fused Deposition Modelling (FDM) Rapid prototyping method. The sling mass decreased by 20%, while signifficantly better stress distribution was achieved, with maximum stress 3.5 times less than initial value. The future researches should use 3D scanning technology in order to provide more accurate 3D model of initial part. Results of this research can be used by toolmakers in order to engage FEA/RP technology to design and manufacture lighter products with acceptable stress distribution.

We describe a ribonucleic acid (RNA) reporter system for live-cell imaging of gene expression to detect changes in polymerase II activity on individual promoters in individual cells. The reporters use strings of RNA aptamers that constitute IMAGEtags (Intracellular MultiAptamer GEnetic tags) that can be expressed from a promoter of choice. For imaging, the cells are incubated with their ligands that are separately conjugated with one of the FRET pair, Cy3 and Cy5. The IMAGEtags were expressed in yeast from the GAL1, ADH1 or ACT1 promoters. Transcription from all three promoters was imaged in live cells and transcriptional increases from the GAL1 promoter were observed with time after adding galactose. Expression of the IMAGEtags did not affect cell proliferation or endogenous gene expression. Advantages of this method are that no foreign proteins are produced in the cells that could be toxic or otherwise influence the cellular response as they accumulate, the IMAGEtags are short lived and oxygen is not required to generate their signals. The IMAGEtag RNA reporter system provides a means of tracking changes in transcriptional activity in live cells and in real time.

Alya is the BSC in-house HPC-based multi-physics simulation code. It is designed from scratch to run efficiently in parallel supercomputers, solving coupled problems. The target domain is engineering, with all its particular features: complex geome- tries and unstructured meshes, coupled multi-physics with exotic coupling schemes and Physical models, ill-posed problems, flexibility needs for rapidly including new models, etc. Since its conception in 2004, Alya has shown scaling behaviour in an increasing number of cores. In this paper, we present its performance up to 100.000 cores in Blue Waters, the NCSA supercomputer. The selected tests are representative of the engineering world, all the problematic features included: incompressible flow in a hu- man respiratory system, low Mach combustion problem in a kiln furnace and coupled electro-mechanical problem in a heart. We show scalability plots for all cases, discussing all the aspects of such kind of simulations, including solvers convergence.

Objectives1) To measure and compare the time required to perform (pTUG) and the time required to imagine (iTUG) the Timed Up & Go (TUG), and the time difference between these two tasks (i.e., TUG delta time) in older adults with cognitive decline (i.e., mild cognitive impairment (MCI) and mild-to-moderate Alzheimer disease and related disorders (ADRD)) and in cognitively healthy individuals (CHI); and 2) to examine any association between the TUG delta time and a cognitive status.MethodsSixty-six participants (24 CHI, 23 individuals with MCI, and 19 individuals with ADRD) were recruited in this cross-sectional study. The mean and standard deviation of the pTUG and iTUG completion times and the TUG delta time, as well as age, gender, and Mini-Mental State Examination (MMSE) scores were used as outcomes. Participants were separated into three groups based on the tertilization of TUG delta time: lowest (<13.6%; n = 22; best performance), intermediate (13.6-52.2%; n = 22), and highest tertile (>52.2%; n = 22, worst performance).ResultsFewer CHI were in the group exhibiting the highest tertile of TUG delta time compared to individuals with lowest and intermediate TUG delta times (p = 0.013). Being in the highest tertile of the TUG delta time was associated with cognitive decline in the unadjusted model (p = 0.012 for MCI, and p = 0.021 for mild-to-moderate ADRD). In the multivariate models, this association remained significant only for individuals with MCI (p = 0.019 while adjusting for age and gender; p = 0.047 while adjusting for age, gender, and MMSE score; p = 0.012 for the stepwise backward model).ConclusionsOur results provide the first evidence that motor imagery of gait may be used as a biomarker of MCI in older adults.

1) To measure and compare the time required to perform (pTUG) and the time required to imagine (iTUG) the Timed Up & Go (TUG), and the time difference between these two tasks (i.e., TUG delta time) in older adults with cognitive decline (i.e., mild cognitive impairment (MCI) and mild-to-moderate Alzheimer disease and related disorders (ADRD)) and in cognitively healthy individuals (CHI); and 2) to examine any association between the TUG delta time and a cognitive status. Sixty-six participants (24 CHI, 23 individuals with MCI, and 19 individuals with ADRD) were recruited in this cross-sectional study. The mean and standard deviation of the pTUG and iTUG completion times and the TUG delta time, as well as age, gender, and Mini-Mental State Examination (MMSE) scores were used as outcomes. Participants were separated into three groups based on the tertilization of TUG delta time: lowest (<13.6%; n = 22; best performance), intermediate (13.6-52.2%; n = 22), and highest tertile (>52.2%; n = 22, worst performance). Fewer CHI were in the group exhibiting the highest tertile of TUG delta time compared to individuals with lowest and intermediate TUG delta times (p = 0.013). Being in the highest tertile of the TUG delta time was associated with cognitive decline in the unadjusted model (p = 0.012 for MCI, and p = 0.021 for mild-to-moderate ADRD). In the multivariate models, this association remained significant only for individuals with MCI (p = 0.019 while adjusting for age and gender; p = 0.047 while adjusting for age, gender, and MMSE score; p = 0.012 for the stepwise backward model). Our results provide the first evidence that motor imagery of gait may be used as a biomarker of MCI in older adults.