Two-Dimensional Supramolecular Electron Spin Arrays

A bottom-up approach is introduced to fabricate two-dimensional self-assembled layers of molecular spin-systems containing Mn and Fe ions arranged in a chessboard lattice. We demonstrate that the Mn and Fe spin states can be reversibly operated by their selective response to coordination/decoordination of volatile ligands like ammonia (NH3).

Coronary artery stents: influence of adaptive statistical iterative reconstruction on image quality using 64-HDCT

OBJECTIVE: The assessment of coronary stents with present-generation 64-detector row computed tomography (HDCT) scanners is limited by image noise and blooming artefacts. We evaluated the performance of adaptive statistical iterative reconstruction (ASIR) for noise reduction in coronary stent imaging with HDCT. METHODS AND RESULTS: In 50 stents of 28 patients (mean age 64 ± 10 years) undergoing coronary CT angiography (CCTA) on an HDCT scanner the mean in-stent luminal diameter, stent length, image quality, in-stent contrast attenuation, and image noise were assessed. Studies were reconstructed using filtered back projection (FBP) and ASIR-FBP composites. ASIR resulted in reduced image noise vs. FBP (P < 0.0001). Two readers graded the CCTA stent image quality on a 4-point Likert scale and determined the proportion of interpretable stent segments. The best image quality for all clinical images was obtained with 40 and 60% ASIR with significantly larger luminal area visualization compared with FBP (+42.1 ± 5.4% with 100% ASIR vs. FBP alone; P < 0.0001) while the stent length was decreased (-4.7 ± 0.9%,

Nanometer-size anisotropy of injection-molded polymer micro-cantilever arrays

Understanding and controlling the structural anisotropies of injection-molded polymers is vital for designing products such as cantilever-based sensors. Such micro-cantilevers are considered as cost-effective alternatives to single-crystalline silicon-based sensors. In order to achieve similar sensing characteristics,structure and morphology have to be controlled by means of processing parameters including mold temperature and injection speed. Synchrotron radiation-based scanning small- (SAXS) and wide-angle x-ray scattering techniques were used to quantify crystallinity and anisotropy in polymer micro-cantilevers with micrometer resolution in real space. SAXS measurements confirmed the lamellar nature of the injection-molded semi-crystalline micro-cantilevers. The homogenous cantilever material exhibits a lamellar periodicity increasing with mold temperature but not with injection speed. We demonstrate that micro-cantilevers made of semi-crystalline polymers such as polyvinylidenefluoride, polyoxymethylene, and polypropylene show the expected strong degree of anisotropy along the injection direction.

Surface patterned polymer micro-cantilever arrays for sensing

Microinjection molding was employed to fabricate low-cost polymer cantilever arrays for sensor applications. Cantilevers with micrometer dimensions and aspect ratios as large as 10 were successfully manufactured from polymers, including polypropylene and polyvinylidenfluoride. The cantilevers perform similar to the established silicon cantilevers, with Q-factors in the range of 10–20. Static deflection of gold coated polymer cantilevers was characterized with heat cycling and self-assembled monolayer formation of mercaptohexanols. A hybrid mold concept allows easy modification of the surface topography, enabling customized mechanical properties of individual cantilevers. Combined with functionalization and surface patterning, the cantilever arrays are qualified for biomedical applications

Adaptive Molecular Evolution in the Opsin Genes of Rapidly Speciating Cichlid Species

Cichlid fish inhabit a diverse range of environments that vary in the spectral content of light available for vision. These differences should result in adaptive selective pressure on the genes involved in visual sensitivity, the opsin genes. This study examines the evidence for differential adaptive molecular evolution in East African cichlid opsin genes due to gross differences in environmental light conditions. First, we characterize the selective regime experienced by cichlid opsin genes using a likelihood ratio test format, comparing likelihood models with different constraints on the relative rates of amino acid substitution, across sites. Second, we compare turbid and clear lineages to determine if there is evidence of differences in relative rates of substitution. Third, we present evidence of functional diversification and its relationship to the photic environment among cichlid opsin genes. We report statistical evidence of positive selection in all cichlid opsin genes, except short wavelength–sensitive 1 and short wavelength–sensitive 2b. In all genes predicted to be under positive selection, except short wavelength–sensitive 2a, we find differences in selective pressure between turbid and clear lineages. Potential spectral tuning sites are variable among all cichlid opsin genes; however, patterns of substitution consistent with photic environment–driven evolution of opsin genes are observed only for short wavelength–sensitive 1 opsin genes. This study identifies a number of promising candidate-tuning sites for future study by site-directed mutagenesis. This work also begins to demonstrate the molecular evolutionary dynamics of cichlid visual sensitivity and its relationship to the photic environment.

Hybridization and adaptive radiation

Whether interspecific hybridization is important as a mechanism that generates biological diversity is a matter of controversy. Whereas some authors focus on the potential of hybridization as a source of genetic variation, functional novelty and new species, others argue against any important role, because reduced fitness would typically render hybrids an evolutionary dead end. By drawing on recent developments in the genetics and ecology of hybridization and on principles of ecological speciation theory, I develop a concept that reconciles these views and adds a new twist to this debate. Because hybridization is common when populations invade new environments and potentially elevates rates of response to selection, it predisposes colonizing populations to rapid adaptive diversification under disruptive or divergent selection. I discuss predictions and suggest tests of this hybrid swarm theory of adaptive radiation and review published molecular phylogenies of adaptive radiations in light of the theory. Some of the confusion about the role of hybridization in evolutionary diversification stems from the contradiction between a perceived necessity for cessation of gene flow to enable adaptive population differentiation on the one hand [1], and the potential of hybridization for generating adaptive variation, functional novelty and new species 2, 3 and 4 on the other. Much progress in the genetics 5, 6, 7, 8 and 9 and ecology of hybridization 9, 10 and 11, and in our understanding of the role of ecology in speciation (see Glossary) 12, 13 and 14 make a re-evaluation timely. Whereas botanists traditionally stressed the diversity-generating potential of hybridization 2, 3 and 14, zoologists traditionally saw it as a process that limits diversification [1] and refer to it mainly in the contexts of hybrid zones (Box 1) and reinforcement of reproductive isolation [15]. Judging by the wide distribution of allopolyploidy among plants, many plant species might be of direct hybrid origin or descended from a hybrid species in the recent past [16]. The ability to reproduce asexually might explain why allopolyploid hybrid species are more common in plants than in animals. Allopolyploidy arises when meiotic mismatch of parental chromosomes or karyotypes causes hybrid sterility. Mitotic error, duplicating the karyotype, can restore an asexually maintained hybrid line to fertility. Although bisexual allopolyploid hybrid species are not uncommon in fish [17] and frogs [18], the difficulty with which allopolyploid animals reproduce, typically requiring gynogenesis[19], makes establishment and survival of allopolyploid animal species difficult.

CAOR: Context-aware Adaptive Opportunistic Routing in Mobile Ad-hoc Networks

Opportunistic routing (OR) employs a list of candidates to improve wireless transmission reliability. However, conventional list-based OR restricts the freedom of opportunism, since only the listed nodes are allowed to compete for packet forwarding. Additionally, the list is generated statically based on a single network metric prior to data transmission, which is not appropriate for mobile ad-hoc networks (MANETs). In this paper, we propose a novel OR protocol - Context-aware Adaptive Opportunistic Routing (CAOR) for MANETs. CAOR abandons the idea of candidate list and it allows all qualified nodes to participate in packet transmission. CAOR forwards packets by simultaneously exploiting multiple cross-layer context information, such as link quality, geographic progress, energy, and mobility.With the help of the Analytic Hierarchy Process theory, CAOR adjusts the weights of context information based on their instantaneous values to adapt the protocol behavior at run-time. Moreover, CAOR uses an active suppression mechanism to reduce packet duplication. Simulation results show that CAOR can provide efficient routing in highly mobile environments. The adaptivity feature of CAOR is also validated.

Locomotor velocity and striatal adaptive gene expression changes of the direct and indirect pathways in Parkinsonian rats

BACKGROUND In Parkinson's disease (PD), bradykinesia, or slowness of movement, only appears after a large striatal dopamine depletion. Compensatory mechanisms probably play a role in this delayed appearance of symptoms. OBJECTIVE Our hypothesis is that the striatal direct and indirect pathways participate in these compensatory mechanisms. METHODS We used the unilateral 6-hydroxydopamine (6-OHDA) rat model of PD and control animals. Four weeks after the lesion, the spontaneous locomotor activity of the rats was measured and then the animals were killed and their brain extracted. We quantified the mRNA expression of markers of the striatal direct and indirect pathways as well as the nigral expression of dopamine transporter (DAT) and tyrosine hydroxylase (TH) mRNA. We also carried out an immunohistochemistry for the striatal TH protein expression. RESULTS As expected, the unilateral 6-OHDA rats presented a tendency to an ipsilateral head turning and a low locomotor velocity. In 6-OHDA rats only, we observed a significant and positive correlation between locomotor velocity and both D1-class dopamine receptor (D1R) (direct pathway) and enkephalin (ENK) (indirect pathway) mRNA in the lesioned striatum, as well as between D1R and ENK mRNA. CONCLUSIONS Our results demonstrate a strong relationship between both direct and indirect pathways and spontaneous locomotor activity in the parkinsonian rat model. We suggest a synergy between both pathways which could play a role in compensatory mechanisms and may contribute to the delayed appearance of bradykinesia in PD.

An Early-Warning System for Hypo-/Hyperglycemic Events Based on Fusion of Adaptive Prediction Models

Introduction: Early warning of future hypoglycemic and hyperglycemic events can improve the safety of type 1 diabetes mellitus (T1DM) patients. The aim of this study is to design and evaluate a hypoglycemia / hyperglycemia early warning system (EWS) for T1DM patients under sensor-augmented pump (SAP) therapy. Methods: The EWS is based on the combination of data-driven online adaptive prediction models and a warning algorithm. Three modeling approaches have been investigated: (i) autoregressive (ARX) models, (ii) auto-regressive with an output correction module (cARX) models, and (iii) recurrent neural network (RNN) models. The warning algorithm performs postprocessing of the models′ outputs and issues alerts if upcoming hypoglycemic/hyperglycemic events are detected. Fusion of the cARX and RNN models, due to their complementary prediction performances, resulted in the hybrid autoregressive with an output correction module/recurrent neural network (cARN)-based EWS. Results: The EWS was evaluated on 23 T1DM patients under SAP therapy. The ARX-based system achieved hypoglycemic (hyperglycemic) event prediction with median values of accuracy of 100.0% (100.0%), detection time of 10.0 (8.0) min, and daily false alarms of 0.7 (0.5). The respective values for the cARX-based system were 100.0% (100.0%), 17.5 (14.8) min, and 1.5 (1.3) and, for the RNN-based system, were 100.0% (92.0%), 8.4 (7.0) min, and 0.1 (0.2). The hybrid cARN-based EWS presented outperforming results with 100.0% (100.0%) prediction accuracy, detection 16.7 (14.7) min in advance, and 0.8 (0.8) daily false alarms. Conclusion: Combined use of cARX and RNN models for the development of an EWS outperformed the single use of each model, achieving accurate and prompt event prediction with few false alarms, thus providing increased safety and comfort.

Adaptive Algorithms for Personalized Diabetes Treatment

Dynamic systems, especially in real-life applications, are often determined by inter-/intra-variability, uncertainties and time-varying components. Physiological systems are probably the most representative example in which population variability, vital signal measurement noise and uncertain dynamics render their explicit representation and optimization a rather difficult task. Systems characterized by such challenges often require the use of adaptive algorithmic solutions able to perform an iterative structural and/or parametrical update process towards optimized behavior. Adaptive optimization presents the advantages of (i) individualization through learning of basic system characteristics, (ii) ability to follow time-varying dynamics and (iii) low computational cost. In this chapter, the use of online adaptive algorithms is investigated in two basic research areas related to diabetes management: (i) real-time glucose regulation and (ii) real-time prediction of hypo-/hyperglycemia. The applicability of these methods is illustrated through the design and development of an adaptive glucose control algorithm based on reinforcement learning and optimal control and an adaptive, personalized early-warning system for the recognition and alarm generation against hypo- and hyperglycemic events.

High-density large-scale field emitter arrays for x-ray free electron laser cathodes

High brightness electron sources are of great importance for the operation of the hard X-ray free electron lasers. Field emission cathodes based on the double-gate metallic field emitter arrays (FEAs) can potentially offer higher brightness than the currently used ones. We report on the successful application of electron beam lithography for fabrication of the large-scale single-gate as well as double-gate FEAs. We demonstrate operational high-density single-gate FEAs with sub-micron pitch and total number of tips up to 106 as well as large-scale double-gate FEAs with large collimation gate apertures. The details of design, fabrication procedure and successful measurements of the emission current from the single- and double-gate cathodes are presented.

Collimated Field Emission Beams from Metal Double-Gate Nanotip Arrays Optically Excited via Surface Plasmon Resonance

The generation of collimated electron beams from metal double-gate nanotip arrays excited by near infrared laser pulses is studied. Using electromagnetic and particle tracking simulations, we showed that electron pulses with small rms transverse velocities are efficiently produced from nanotip arrays by laser-induced field emission with the laser wavelength tuned to surface plasmon polariton resonance of the stacked double-gate structure. The result indicates the possibility of realizing a metal nanotip array cathode that outperforms state-of-the-art photocathodes.