Long Residence Times Revealed by Aurora A Kinase‐Targeting Fluorescent Probes Derived from Inhibitors MLN8237 and VX‐689

We report the development of three fluorescent probes for protein kinase Aurora A that are derived from the well‐known inhibitors MLN8237 and VX‐689 (MK‐5108). Two of these probes target the ATP site of Aurora A, and one targets simultaneously the ATP and substrate sites of the kinase. The probes were tested in an assay with fluorescence polarisation/anisotropy readout, and we demonstrated slow association kinetics and long residence time of the probes (k_on 10⁵–10⁷ M ^?1 s^?1, k_off 10^?3–10^?4 s^?1; residence time 500–3000 s). The presence of the Aurora A activator TPX2 caused a significant reduction in the on‐rate and increase in the off‐rate of fluorescent probes targeting ATP site. These observations were supported by Aurora A inhibition assays with MLN8237 and VX‐689. Overall, our results emphasise the importance of rational design of experiments with these compounds and correct interpretation of the obtained data.     

Dispersion of PCB in the environment following an atmospheric release caused by a fire

During a fire at a power plant located in the coastal plain of Israel, PCBs were released to the atmosphere from a ruptured transformer. Since PCBs are probably carcinogenic to humans, this study was performed in order to assess the environmental contamination by PCBs via the atmospheric pathway and the need for remediation measures. The release conditions and the meteorological conditions which prevailed during the fire were analyzed. This provided the input to a Gaussian dispersion model used to estimate the downwind-contaminated sector as well as the location of the maximal concentration within this sector. A sampling plan was then devised and vegetation collected within this sector was analyzed for PCBs. A methodology was developed to convert PCB concentrations in vegetation to concentrations in the atmosphere. It allowed a reconstitution of the PCB source term to the atmosphere from the vegetation measurements. The PCB concentrations were found to be lower than the USEPA decontamination standards. Remediation measures were not needed beyond the plant fence.     

Book reviews

The Annals of Regional Science -     

Using Exploratory Scenarios in Planning Practice

Abstract

Problem, research strategy, and findings: Despite growing interest by practitioners in using exploratory scenarios within urban planning practice, there are few detailed guidelines for how to do this. Through the discussion of five case examples, we illustrate different approaches to linking exploratory scenarios to different planning contexts. We conclude by observing that to directly inform a plan, regardless of the specific approach taken, exploratory scenarios in urban planning must incorporate stakeholder values and not only rely on expert judgment and analysis.

Takeaway for practice: Exploratory scenarios are effective for analyzing uncertainty within a planning process. However, exploratory scenarios can be incorporated into planning practice in different ways, ranging from workshops among experts that aim to cultivate general learning to complex projects that result in highly detailed scenarios and recommendations for plans. Practitioners can draw on the cases we present to inspire planning methods for particular projects, taking into account specific contexts and goals.     

LRA: Local Rigid Averaging of Stretchable Non-rigid Shapes

We present a novel algorithm for generating the mean structure of non-rigid stretchable shapes. Following an alignment process, which supports local affine deformations, we translate the search of the mean shape into a diagonalization problem where the structure is hidden within the kernel of a matrix. This is the first step required in many practical applications, where one needs to model bendable and stretchable shapes from multiple observations.     

An efficient algorithm for maximizing the expected profit from a serial production line with inspection stations and rework

In this paper, an unreliable serial production line in which nonconforming items are sent back for rework is studied. The line consists of existing machines and optional quality control stations (QCSs). The designer of such a production line needs to decide where to install the QCSs along the line and to determine the production rate, so as to maximize the expected operational profit rate obtained at a steady state. An efficient algorithm for solving this problem is presented; several extensions of the problem are discussed. An extensive simulation study proves the applicability of the model in realistic settings and is used to derive some insights about the nature of optimal solutions.     

Perpendicular Orientation of Anisotropic Au‐Tipped CdS Nanorods at the Air/Water Interface

Anisotropic CdS nanorods tipped by Au nanoparticles on one edge (Au‐CdS‐NRs) are perpendicularly oriented at the air/water interface, whereby all the Au tips are located in the subphase, using the Langmuir–Blodgett technique. Since these nano‐objects reveal light‐induced charge separation at the semiconductor/metal interface, it is of high interest to control their organization. The orientation of these assemblies is studied in situ while compressing the Langmuir–Blodgett trough using the π‐A isotherm, Brewster angle microscopy, and horizontal touch voltammetry. All these analyses clearly confirm the induced organization of the amphiphilic Au‐CdS‐NRs by compression of the Langmuir layer. The compressed layers are successfully transferred by the Langmuir–Schaefer method onto transmission electron microscopy grids while maintaining the preferential orientation as analyzed by transmission, scanning and scanning trasmission electron microscopy, and X‐ray photoelectron spectroscopy. As far as can be determined, the Langmuir–Blodgett technique has not been used so far for perpendicularly orienting anisotropic nano‐objects. Moreover, these findings clearly demonstrate that anisotropic amphiphilic nano‐objects can be treated with some similarity to the traditional amphiphilic molecular building blocks.     

A Human-Robot Collaborative Reinforcement Learning Algorithm

This paper presents a new reinforcement learning algorithm that enables collaborative learning between a robot and a human. The algorithm which is based on the Q(λ) approach expedites the learning process by taking advantage of human intelligence and expertise. The algorithm denoted as CQ(λ) provides the robot with self awareness to adaptively switch its collaboration level from autonomous (self performing, the robot decides which actions to take, according to its learning function) to semi-autonomous (a human advisor guides the robot and the robot combines this knowledge into its learning function). This awareness is represented by a self test of its learning performance. The approach of variable autonomy is demonstrated and evaluated using a fixed-arm robot for finding the optimal shaking policy to empty the contents of a plastic bag. A comparison between the CQ(λ) and the traditional Q(λ)-reinforcement learning algorithm, resulted in faster convergence for the CQ(λ) collaborative reinforcement learning algorithm.