Sugar concentration influences decision making in <i>Apis mellifera</i> L. workers during early-stage honey storage behaviour

Decision making in honeybees is based on in- formation which is acquired and processed in order to make choices between two or more al- ternatives. These choices lead to the expression of optimal behaviour strategies such as floral constancy. Optimal foraging strategies such as floral constancy improve a colony’s chances of survival, however to our knowledge, there has been no research on decision making based on optimal storage strategies. Here we show, using diagnostic radioentomology, that decision mak- ing in storer bees is influenced by nectar sugar concentrations and that, within 48 hours of col- lection, honeybees workers store carbohydrates in groups of cells with similar sugar concentra- tions in a nonrandom way. This behaviour, as evidenced by patchy spatial cell distributions, would help to hasten the ripening process by reducing the distance between cells of similar sugar concentrations. Thus, colonies which ex- hibit optimal storage strategies such as these would have an evolutionary advantage and im- prove colony survival expectations over less efficient colonies and it should be plausible to select colonies that exhibit these preferred traits.

Mobile Cloud Networking: Mobile Network, Compute, and Storage as One Service On-Demand

The Future Communication Architecture for Mobile Cloud Services: Mobile Cloud Networking (MCN) is a EU FP7 Large-scale Integrating Project (IP) funded by the European Commission. MCN project was launched in November 2012 for the period of 36 month. In total top-tier 19 partners from industry and academia commit to jointly establish the vision of Mobile Cloud Networking, to develop a fully cloud-based mobile communication and application platform.

Matching Recall and Storage in Sequence Learning with Spiking Neural Networks

Storing and recalling spiking sequences is a general problem the brain needs to solve. It is, however, unclear what type of biologically plausible learning rule is suited to learn a wide class of spatiotemporal activity patterns in a robust way. Here we consider a recurrent network of stochastic spiking neurons composed of both visible and hidden neurons. We derive a generic learning rule that is matched to the neural dynamics by minimizing an upper bound on the Kullback–Leibler divergence from the target distribution to the model distribution. The derived learning rule is consistent with spike-timing dependent plasticity in that a presynaptic spike preceding a postsynaptic spike elicits potentiation while otherwise depression emerges. Furthermore, the learning rule for synapses that target visible neurons can be matched to the recently proposed voltage-triplet rule. The learning rule for synapses that target hidden neurons is modulated by a global factor, which shares properties with astrocytes and gives rise to testable predictions.

Vascular turbine powering a cardiac pacemaker: an in-vivo case study

Background: Today’s medical devices are powered by batteries with a limited energy storage capacity. Depleted batteries have to be replaced, exposing the patients to the risk of adverse events. Thus, a method for harvesting energy inside the body is desirable since it would allow building devices without batteries. Methods: A miniaturized intravascular Tesla turbine was implanted as an arteriovenous shunt between the common carotid artery and external jugular vein of a pig. The harvested energy was used to power a custom-built temporary cardiac pacemaker. Results: At a flow rate of ~150 ml/min, an output power of 0.4 mW was measured. Successful ventricular pacing was performed. Conclusion: Harvesting energy from the circulation using an intravascular turbine is technically feasible and provides enough energy to power a cardiac pacemaker.

Scheduling of continuous and discontinuous material flows with intermediate storage restrictions

This paper deals with scheduling batch (i.e., discontinuous), continuous, and semicontinuous production in process industries (e.g., chemical, pharmaceutical, or metal casting industries) where intermediate storage facilities and renewable resources (processing units and manpower) of limited capacity have to be observed. First, different storage configurations typical of process industries are discussed. Second, a basic scheduling problem covering the three above production modes is presented. Third, (exact and truncated) branch-and-bound methods for the basic scheduling problem and the special case of batch scheduling are proposed and subjected to an experimental performance analysis. The solution approach presented is flexible and in principle simple, and it can (approximately) solve relatively large problem instances with sufficient accuracy.

Storage problems in batch scheduling

This paper is concerned with the modelling of storage configurations for intermediate products in process industries. Those models form the basis of algorithms for scheduling chemical production plants. Different storage capacity settings (unlimited, finite, and no intermediate storage), storage homogeneity settings (dedicated and shared storage), and storage time settings (unlimited, finite, and no wait) are considered. We discuss a classification of storage constraints in batch scheduling and show how those constraints can be integrated into a general production scheduling model that is based on the concept of cumulative resources.

Global ocean storage of anthropogenic carbon

The global ocean is a significant sink for anthropogenic carbon (Cant), absorbing roughly a third of human CO2 emitted over the industrial period. Robust estimates of the magnitude and variability of the storage and distribution of Cant in the ocean are therefore important for understanding the human impact on climate. In this synthesis we review observational and model-based estimates of the storage and transport of Cant in the ocean. We pay particular attention to the uncertainties and potential biases inherent in different inference schemes. On a global scale, three data-based estimates of the distribution and inventory of Cant are now available. While the inventories are found to agree within their uncertainty, there are considerable differences in the spatial distribution. We also present a review of the progress made in the application of inverse and data assimilation techniques which combine ocean interior estimates of Cant with numerical ocean circulation models. Such methods are especially useful for estimating the air–sea flux and interior transport of Cant, quantities that are otherwise difficult to observe directly. However, the results are found to be highly dependent on modeled circulation, with the spread due to different ocean models at least as large as that from the different observational methods used to estimate Cant. Our review also highlights the importance of repeat measurements of hydrographic and biogeochemical parameters to estimate the storage of Cant on decadal timescales in the presence of the variability in circulation that is neglected by other approaches. Data-based Cant estimates provide important constraints on forward ocean models, which exhibit both broad similarities and regional errors relative to the observational fields. A compilation of inventories of Cant gives us a "best" estimate of the global ocean inventory of anthropogenic carbon in 2010 of 155 ± 31 PgC (±20% uncertainty). This estimate includes a broad range of values, suggesting that a combination of approaches is necessary in order to achieve a robust quantification of the ocean sink of anthropogenic CO2.

Surface Roughness and Microhardness of Two Recent CAD/CAM-Materials After Storage

Objectives: To investigate surface roughness and microhardness of two recent resin-ceramic materials for computer-aided design/computer-aided manufacturing (CAD/CAM) after polishing with three polishing systems. Surface roughness and microhardness were measured immediately after polishing and after six months storage including monthly artificial toothbrushing. Methods: Sixty specimens of Lava Ultimate (3M ESPE) and 60 specimens of VITA ENAMIC (VITA Zahnfabrik) were roughened in a standardized manner and polished with one of three polishing systems (n=20/group): Sof-Lex XT discs (SOFLEX; three-step (medium-superfine); 3M ESPE), VITA Polishing Set Clinical (VITA; two-step; VITA Zahnfabrik), or KENDA Unicus (KENDA; one-step; KENDA Dental). Surface roughness (Ra; μm) was measured with a profilometer and microhardness (Vickers; VHN) with a surface hardness indentation device. Ra and VHN were measured immediately after polishing and after six months storage (tap water, 37°C) including monthly artificial toothbrushing (500 cycles/month, toothpaste RDA ~70). Ra- and VHN-values were analysed with nonparametric ANOVA followed by Wilcoxon rank sum tests (α=0.05). Results: For Lava Ultimate, Ra (mean [standard deviation] before/after storage) remained the same when polished with SOFLEX (0.18 [0.09]/0.19 [0.10]; p=0.18), increased significantly with VITA (1.10 [0.44]/1.27 [0.39]; p=0.0001), and decreased significantly with KENDA (0.35 [0.07]/0.33 [0.08]; p=0.03). VHN (mean [standard deviation] before/after storage) decreased significantly regardless of polishing system (SOFLEX: 134.1 [5.6]/116.4 [3.6], VITA: 138.2 [10.5]/115.4 [5.9], KENDA: 135.1 [6.2]/116.7 [6.3]; all p<0.0001). For VITA ENAMIC, Ra (mean [standard deviation] before/after storage) increased significantly when polished with SOFLEX (0.37 [0.18]/0.41 [0.14]; p=0.01) and remained the same with VITA (1.32 [0.37]/1.31 [0.40]; p=0.58) and with KENDA (0.81 [0.35]/0.78 [0.32]; p=0.21). VHN (mean [standard deviation] before/after storage) remained the same regardless of polishing system (SOFLEX: 284.9 [24.6]/282.4 [31.8], VITA: 284.6 [28.5]/276.4 [25.8], KENDA: 292.6 [26.9]/282.9 [24.3]; p=0.42-1.00). Conclusion: Surface roughness and microhardness of Lava Ultimate was more affected by storage and artificial toothbrushing than was VITA ENAMIC.

Dentin Bond Strength of Two Recent CAD/CAM-Materials after Storage

Purpose: To investigate the bond strength to dentin of two recent resin-ceramic materials for computer-aided design/computer-aided manufacturing (CAD/CAM) after 24 hours and after six months storage. Methods and Materials: Ninety cylinders were milled out of Lava Ultimate (3M ESPE) and 90 cylinders out of VITA ENAMIC (VITA Zahnfabrik) (dimension of cylinders: ∅=3.6 mm, h=2 mm). All Lava Ultimate cylinders were sandblasted (aluminium oxide, grain size: 27 μm) and cleaned with ethanol, whereas all VITA ENAMIC cylinders were acid-etched (5% hydrofluoric acid) and cleaned with water-spray. According to the three groups of cements used, the cylinders (n=30/resin-ceramic material) were further pretreated with 1) Scotchbond Universal for RelyX Ultimate (3M ESPE), 2) CLEARFIL Ceramic Primer for PANAVIA F2.0 (Kuraray), or 3) no further pretreatment for Ketac Cem Plus (3M ESPE). The cylinders were then bonded to ground human dentin specimens with 1) Scotchbond Universal and RelyX Ultimate (light-cured), 2) ED PRIMER II and PANAVIA F2.0 (light-cured), or 3) no adhesive system; Ketac Cem Plus (self-cured). Shear bond strength (SBS) was measured after 24 hours for 15 specimens/group and after six months (37°C, 100% humidity) for the other 15 specimens/group. SBS-values were statistically analysed with nonparametric ANOVA followed by exact Wilcoxon rank sum tests (α=0.05). Results: SBS of the two resin-ceramic materials and the three cements after 24 hours and after six months storage are shown in Figure 1. The statistical analysis showed that the duration of storage had a significant effect on SBS of Lava Ultimate for all three cements but had no significant effect on SBS of VITA ENAMIC. For Lava Ultimate SBS-values were (MPa; medians after 24 hours/six months): 13.5/22.5 (p=0.04) for RelyX Ultimate, 11.4/5.8 (p=0.0006) for PANAVIA F2.0, and 0.34/0.09 (p=0.04) for Ketac Cem Plus (Fig. 1). For VITA ENAMIC SBS-values were (MPa; medians after 24 hours/six months): 16.0/21.2 (p=0.10) for RelyX Ultimate, 11.4/14.4 (p=0.06) for PANAVIA F2.0, and 0.43/0.41 (p=0.32) for Ketac Cem Plus (Fig. 1). After 24 hours, there was no significant difference in SBS between Lava Ultimate and VITA ENAMIC for all three cements (p≥0.37). After six months, there was no significant difference in SBS between Lava Ultimate and VITA ENAMIC for RelyX Ultimate and Ketac Cem Plus (p≥0.07) whereas for PANAVIA F2.0, SBS was significantly lower for Lava Ultimate than for VITA ENAMIC (p<0.0001). Conclusion: SBS of Lava Ultimate was more affected by six months storage and by the cement used than was VITA ENAMIC.

Long-term storage affects adhesion between titanium and zirconia using resin cements.

PURPOSE To determine the impact of long-term storage on adhesion between titanium and zirconia using resin cements. MATERIALS AND METHODS Titanium grade 4 blocks were adhesively fixed onto zirconia disks with four resin cements: Panavia F 2.0 (Kuraray Europe), GC G-Cem (GC Europe), RelyX Unicem (3M ESPE), and SmartCem 2 (Dentsply DeguDent). Shear bond strength was determined after storage in a water bath for 24 h, 16, 90, and 150 days at 37°C, and after 6000 cycles between 5°C and 55°C. Fracture behavior was evaluated using scanning electron microscopy. RESULTS After storage for at least 90 days and after thermocycling, GC G-Cem (16.9 MPa and 15.1 MPa, respectively) and RelyX Unicem (10.8 MPa and 15.7 MPa, respectively) achieved higher shear bond strength compared to SmartCem 2 (7.1 MPa and 4.0 MPa, respectively) and Panavia F2 (4.1 MPa and 7.4 MPa, respectively). At day 150, GC G-Cem and RelyX Unicem caused exclusively mixed fractures. SmartCem 2 and Panavia F2 showed adhesive fractures in one-third of the cases; all other fractures were of mixed type. After 24 h (GC G-Cem: 26.0, RelyX Unicem: 20.5 MPa, SmartCem 2: 16.1 MPa, Panavia F2: 23.6 MPa) and 16 days (GC G-Cem: 12.8, RelyX Unicem: 14.2 MPa, SmartCem 2: 9.8 MPa, Panavia F2: 14.7 MPa) of storage, shear bond strength was similar among the four cements. CONCLUSION Long-term storage and thermocycling differentially affects the bonding of resin cement between titanium and zirconia.