Figure 8. The number of children aged 0-5 years on the child protection register 2009-2013
Figure 8. The sequence diagram of communication between QKDNetSim entities based on ETSI 014 standard
Figure 8. Current in the secondary winding versus time.
Examples of Figure 8 in a sentence
Figure 8 Left: pedestal RMS in fC of all channels measured in the Lab (blue) and at the test beam (red); right: hit map of self-triggered events taken in the Lab with a 90Sr source where lit-up region indicates the source area.
The following tests were performed and showed good results: • Calibration and pedestal measurements: most strips show good ADC-to-charge response, with a reasonable noise level of ~0.5 fC, as shown by the blue histogram in Figure 8 (left); Strip Sensor KPiX1 KPiX2 Assembled module DAQ board • Self-trigger runs with or without a 90Sr electron source: the sensor is able to locate the signal position well as shown in the lit-up region in Figure 8 (right), and response well to the threshold changing.
Depending on the input of the user, the GUI then generates either a “pass” output (Figure 8) that features a green “thumbs-up” image recommending MDA distribution of ivermectin; or a “fail” output (Figure 9), which features a red “thumbs-down” image that recommends test and treat prior to ivermectin dispersal.
The calibration was repeated in the test beam area due to environmental and shielding changes, which shows an expected lower noise level at ~0.28 fC, see red histogram in Figure 8 (left).
More Definitions of Figure 8
Figure 8. The blue lines indicate the ground tracks of the Xxxxx missions within 400 km from the coast. The blue patches at the coast correspond to the part of the coastlines that have a ground track within 30 km of the coast. This product consists of along-track high-resolution (20 Hz, i.e., ~350 m) sea level anomalies and coastal sea level trends derived from a complete reprocessing of the Xxxxx altimetry data in several coastal regions worldwide. This product is only available for some regions of the world. In Figure 8 is shown the tracks of the Xxxxx series of missions less than 400 km from the coast. When fully validated this type of dataset can produce estimation of the coastal sea level trend at few km from the coast (between 4 and 10 km) for the period 2002-onward. It is worthwhile mentioning that in the future, the higher spatial resolution of the ESA Sentinel altimetry missions (Sentinel-3 and -6) should also provide valuable estimates of sea level trends at the coast. Nevertheless, the in situ data from tide gauges will always be required to validate this satellite altimetry products.
Figure 8. Concept Map: ”Robot Relations” RULE { IF NOT Predicate.Can_Move(THIS) THEN { DO {Action.Check_Battery(THIS..battery);} } } RULE { IF NOT Predicate.Can_Move(THIS) AND Action.Get_Battery(THIS..battery) > 0.5 THEN { DO {Action.Get_Dist(THIS, Action.Get_Closest(THIS, ENV.Thing..Obstacle)); } } } Rules, also can be used to imply predicates, e.g.: RULE { IF Action.Get_Battery(THIS..battery) > 0.9 THEN { Predicate.Charged(THIS..battery) } ELSE { NOT Predicate.Charged(THIS..battery) } } In additon, constraints may be used to constraint the behavior of the system or impose predicates, e.g.: CONSTRAINT { IF Action.Get_Battery(THIS..battery) < 0.1 THEN { NOT Action.Move(THIS) } CONSTRAINT { IF Xxxxxxxxx.Xx_Operational(THIS.locomotion_system) THEN { Action.Get_Battery(THIS..battery) > 0.5 AND Xxxxxxxxx.Xx_Operational (THIS..wheel[1]) AND Xxxxxxxxx.Xx_Operational (THIS..wheel[2]) AND Xxxxxxxxx.Xx_Operational (THIS..wheel[3]) AND Xxxxxxxxx.Xx_Operational (THIS..wheel[4]) AND Xxxxxxxxx.Xx_Operational (THIS..wheel[5]) AND Xxxxxxxxx.Xx_Operational (THIS..engine) AND Xxxxxxxxx.Xx_Operational (THIS..locomotion_soft) AND Xxxxxxxxx.Xx_Running (THIS..locomotion_soft) } } Constraints can also be used to impose data restrictions, e.g., let’s presume we want two robots to have different first goals: CONSTRAINT { robot[1].goal[1] <> robot[2].goal[1]; } Finally, we need to specify important situations and policies driving the system in those situations. The following examples represent the LoadedAndOperational situation and the policy ReturnAndUnload Figure 9: Gripper Concept and its Realization specified to eventually handle that situation. Recall that we need also to specify a relation that connects these two structures if we want the policy to handle the situation (see Section 2.4.2). CONCEPT_SITUATION LoadedAndOperational { CHILDREN {} PARENTS {SC.Thing..Situation} SPEC { SITUATION_STATES { SC.Thing..Robot.operational , SC.Thing..Gripper.locked_stable } SITUATION_ACTIONS { SC.Action.Move , SC.Action.Lay_dwn } } } CONCEPT_POLICY ReturnAndUnload { SPEC { POLICY_GOAL { UnloadGripper } POLICY_SITUATIONS { LoadedAndOperational } POLICY_RELATIONS {. } POLICY_ACTIONS {. } POLICY_MAPPINGS { MAPPING { CONDITIONS {SC.Action.Get_position = B } DO_ACTIONS {SC.Action.Lay_dwn } } MAPPING { CONDITIONS {SC.Action.Get_position <> B } DO_ACTIONS {SC.Action.Plan_trip, SC.Action.Move } } } } } 4 The Pyramid of Awareness The ultimate goal of our KR approach is to allow for awareness and self-awaren...
Figure 8. A mobile application provides the interface to experience the story. Virtual characters enact the narrative and guide the user to participate.
Figure 8. Anatomy of nigrostriatal pathway in DRD mice. Representative sections immunostained for TH (A) or DAT (B) from striatum or midbrain of normal and DRD mice (scale bars = 1.5 mm, striatum; 200 µm, midbrain). (C) Stereological cell counts of TH-positive neurons in the SN (p>0.1, Student’s t test) and VTA (p>0.1, Student’s t test). (D) Stereological assessment of striatal volume (p>0.1, Student’s t test). Values represent mean ± SEM. Microstructural changes to corticostriatal and thalamostriatal connectivity We further examined the anatomical consequences of the p.382Q>K mutation to basal ganglia circuitry by examining glutamatergic cortical and thalamic inputs to striatum. These inputs act in concert with DA in the striatum to coordinate normal movement (Bamford et al., 2004, Costa et al., 2006). Further, glutamatergic synapses in the striatum undergo complex changes in other animal models with striatal DA depletion (Xxxxxx et al., 1998, Xxxxxxxx et al., 2009, Xxxxxxxx and Xxxxx, 2013). Thus, despite normal DAT-positive innervation and striatal volume (Fig. 8), other changes to striatal circuitry could result from the p.382Q>K mutation. We first assessed the gross distribution of glutamatergic input to striatum by staining brain sections for vGluT1, a selective marker of corticostriatal terminals, and vGluT2 a selective marker of thalamostriatal terminals. Using densitometry to quantify vGluT1 and vGluT2 staining intensity, no significant differences between genotypes were observed in any of the subregions of striatum examined (Fig. 9; p>0.1 for all subregions). Next, we examined the density of corticostriatal and thalamostriatal terminals at the synaptic level in the dorsolateral striatum, counting the number of labeled synaptic boutons in images collected by electron microscopy (Fig. 10A and 10B). In agreement with the light microscopy densitometry data, no significant differences were observed in the density of either population of terminals between normal and DRD mice (Fig. 10C; p>0.1). Further, the number of perforated vGluT1-positive (p>0.1) or vGluT2-positive (p>0.1) synapses did not significantly differ between genotypes (not shown). However, the ratio of axo-spinous to axo-dendritic synaptic contacts was significantly smaller for vGluT1-positive terminals in DRD mice compared to normal mice (Fig. 10D; p<0.05), and there was a similar trend for vGluT2-positive terminals (p=0.052). The functional significance of this shift toward more dendritic contact...
Figure 8. Assembly window (1: treeview; 2: viewer; 3: timeline; 4: operation) The assembly window is divided into several sub-windows:
Figure 8. The iron loss power density in the magnetic core of the transformer. Use the Magnetic Fields interface to model the magnetic fields of the transformer. Model the primary and secondary windings with Coil features. Connect the primary and secondary windings to an external circuit with the AC voltage source and resistors using an Electrical Circuit interface. Add a Coil Geometry Analysis study step to calculate the current in the coils. Perform a Time Dependent study to determine the voltage and currents in both the primary and secondary windings. Add the Loss Calculation subfeatures in the Windings and Core and perform a Time to Frequency Losses study to compute the corresponding losses. Application Library path: ACDC_Module/Other_Industrial_Applications/ ecore_transformer Modeling Instructions From the File menu, choose New. NEW In the New window, click Model Wizard. MODE L WIZARD 1 In the Model Wizard window, click 3D.