352 research outputs found
Interaction-induced corrections to conductance and thermopower in quantum wires
We study transport properties of weakly interacting spinless electrons in
one-dimensional single channel quantum wires. The effects of interaction
manifest as three-particle collisions due to the severe constraints imposed by
the conservation laws on the two-body processes. We focus on short wires where
the effects of equilibration on the distribution function can be neglected and
collision integral can be treated in perturbation theory. We find that
interaction-induced corrections to conductance and thermopower rely on the
scattering processes that change number of right- and left-moving electrons.
The latter requires transition at the bottom of the band which is exponentially
suppressed at low temperatures. Our theory is based on the scattering approach
that is beyond the Luttinger-liquid limit. We emphasize the crucial role of the
exchange terms in the three-particle scattering amplitude that was not
discussed in the previous studies.Comment: 4 pages, 2 figure
SKI: A New Agile Framework that supports DevOps, Continuous Delivery, and Lean Hypothesis Testing
This paper explores the need for a new process framework that can effectively support DevOps and Continuous Delivery teams. It then defines a new framework, which adheres to the lean Kanban philosophy but augments Kanban by providing a structured iteration process. This new Structured Kanban Iteration (SKI) framework defines capability-based iterations (as opposed to Kanban-like no iterations or Scrum-like time-based sprints) as well as roles, meetings and artifacts. This structure enables a team to adopt a well-defined process that can be consistently used across groups and organizations. While many of SKIâs concepts are similar to those in found in Scrum, SKIâs capability-based iterations can support the demands of product development as well as operational support efforts, and hence, is well suited for DevOps and Continuous Delivery. SKI also supports lean hypothesis testing as well as more traditional software development teams where capability-based iterations are deemed more appropriate than time-based sprints
Beyond Randomised Controlled Trials - expanding the horizon for experimental research techniques in the social sciences
Experimental research methods have become mainstream across many disciplines in the social and behavioural sciences. Highlighting, the application of new experimental methods that employ innovations in digital technology, machine learning and theory, Jonathan Breckon and Alex Sutherland argue that social scientists should be encouraged to add a wider variety of experimental techniques to their methodological repertoire
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The Trick Doesnât Work if Youâve Already Seen the Gorilla: How Anticipatory Effects Contaminate Pre-treatment Measures in Field Experiments
Objectives: When participants in experiments can anticipate the intervention, the study outcomes are said to be confounded. Ample evidence on intentional and unintentional interferences with the stimuli exists which suggests that participants tend to alter their response to the intervention prior to exposure to it; consequently, the measurement of post-treatment effects has been shown to be contaminated because there is a systematic interaction between measurement and treatment. However, an often-ignored consequence of such anticipatory effects is the impact on the baseline measure. If participants can anticipate the intervention early enough, the pretreatment scores will be conditional, therefore producing a biased estimate of the measure. We explore recent evidence on this bias and present a practical option for the mitigation of anticipatory effects.
Methods: A review of the literature across multiple disciplines which addresses concerns regarding anticipatory effects.
Results: Pretreatment measures, especially of the dependent variables at their baseline values, can be contaminated by anticipatory effects. We show that the major concerns experimenters should consider in this context are: (1) When can we say that the treatment effect âcommencedâ? (2) What forms the pretesting measure? (3) Are anticipatory effects case-specific or are there industry-wide, global anticipatory effects? (4) What can we conclude from studies whose pretest measures are affected by the anticipated treatment effect? and (5) What solutions are there for anticipatory effects?
Conclusions: We outline arguments against the fundamental hypothesis that pre-treatment measurements of baseline measures are unaffected by the study conditions. The implications of anticipatory effects for both research and policy are often ignored, which may lead to erroneous conclusions regarding the treatmentâs effectiveness, its benefits being underestimated, or both. The bias can be resolved by collecting âcleanâ baseline measures prior to the commencement of the anticipatory effects, but the first step is to be aware of their potential
Achieving Lean Data Science Agility Via Data Driven Scrum
This paper first explores the concept of a lean project and defines four principles team should follow to achieve lean data science. It then describes a new team process framework, which we call Data Driven Scrum (DDS), which enables lean data science project agility. DDS is similar to Scrum but key differences include that DDS defines capability-based iterations (as compared to Scrum time-based sprints), DDS increases the focus in observing and analyzing the output of each iteration (experiment), and that DDS defines process improvement meetings (e.g. retrospectives iteration reviews) to be held on a frequency the team deems appropriate (as compared to Scrum which defines these meetings to be at the end of each iteration). The paper also reports on a pilot study of an organization that adopted the DDS framework
'Lowering the threshold of effective deterrence'-Testing the effect of private security agents in public spaces on crime: A randomized controlled trial in a mass transit system.
Supplementing local police forces is a burgeoning multibillion-dollar private security industry. Millions of formal surveillance agents in public settings are tasked to act as preventative guardians, as their high visibility presence is hypothesized to create a deterrent threat to potential offenders. Yet, rigorous evidence is lacking. We randomly assigned all train stations in the South West of England that experienced crime into treatment and controls conditions over a six-month period. Treatment consisted of directed patrol by uniformed, unarmed security agents. Hand-held trackers on every agent yielded precise measurements of all patrol time in the stations. Count-based regression models, estimated marginal means and odds-ratios are used to assess the effect of these patrols on crimes reported to the police by victims, as well as new crimes detected by police officers. Outcomes are measured at both specified target locations to which security guards were instructed to attend, as well as at the entire station complexes. Analyses show that 41% more patrol visits and 29% more minutes spent by security agents at treatment compared to control stations led to a significant 16% reduction in victim-generated crimes at the entirety of the stations' complexes, with a 49% increase in police-generated detections at the target locations. The findings illustrate the efficacy of private policing for crime prevention theory
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