Conceptual model to explain turning points in travel behavior: Application to bicycle use

Existing knowledge on cycling behavior, as with travel behavior in general, is based mainly on cross-sectional studies. It is questionable how much can be learned about the reasons for behavioral change from such studies. A major investment program to promote cycling in 12 English cities and towns between 2008 and 2011 provided the opportunity to study the bicycle use of residents and how that use was affected by the investment. Face-to-face interviews collected biographical information on travel behavior and life-change events during the investment period for 144 research participants and probed the reasons for changes in bicycle use. Theory (from the life course perspective) and preliminary analysis of the interview data were used to develop a conceptual model that hypothesized that turning points in travel behavior were triggered by contextual change (a life-change event or change in the external environment) and mediated by intrinsic motivations, facilitating conditions, and personal history. The model provided an effective means of explaining turning points in bicycle use. The analysis of the interview data showed how the nature of behavioral influences (in particular, life-change events and intrinsic motivations) varied over the life course. The research highlights the advantages of viewing travel behavior change in the context of people’s evolving lives and how that approach can help in developing transport policies and practices

Protecting a quantum state from environmental noise by an incompatible finite-time measurement

We show that measurements of finite duration performed on an open two-state system can protect the initial state from a phase-noisy environment, provided the measured observable does not commute with the perturbing interaction. When the measured observable commutes with the environmental interaction, the finite-duration measurement accelerates the rate of decoherence induced by the phase noise. For the description of the measurement of an observable that is incompatible with the interaction between system and environment, we have found an approximate analytical expression, valid at zero temperature and weak coupling with the measuring device. We have tested the validity of the analytical predictions against an exact numerical approach, based on the superoperator-splitting method, that confirms the protection of the initial state of the system. When the coupling between the system and the measuring apparatus increases beyond the range of validity of the analytical approximation, the initial state is still protected by the finite-time measurement, according with the exact numerical calculations.Comment: REVISED VERSION: 37 pages, 3 figure

Automatically generating streamlined constraint models with ESSENCE and CONJURE

Streamlined constraint reasoning is the addition of uninferred constraints to a constraint model to reduce the search space, while retaining at least one solution. Previously, effective streamlined models have been constructed by hand, requiring an expert to examine closely solutions to small instances of a problem class and identify regularities. We present a system that automatically generates many conjectured regularities for a given Essence specification of a problem class by examining the domains of decision variables present in the problem specification. These conjectures are evaluated independently and in conjunction with one another on a set of instances from the specified class via an automated modelling tool-chain comprising of Conjure, Savile Row and Minion. Once the system has identified effective conjectures they are used to generate streamlined models that allow instances of much larger scale to be solved. Our results demonstrate good models can be identified for problems in combinatorial design, Ramsey theory, graph theory and group theory - often resulting in order of magnitude speed-ups.Postprin

How large are the level sets of the Takagi function?

Let T be Takagi's continuous but nowhere-differentiable function. This paper considers the size of the level sets of T both from a probabilistic point of view and from the perspective of Baire category. We first give more elementary proofs of three recently published results. The first, due to Z. Buczolich, states that almost all level sets (with respect to Lebesgue measure on the range of T) are finite. The second, due to J. Lagarias and Z. Maddock, states that the average number of points in a level set is infinite. The third result, also due to Lagarias and Maddock, states that the average number of local level sets contained in a level set is 3/2. In the second part of the paper it is shown that, in contrast to the above results, the set of ordinates y with uncountably infinite level sets is residual, and a fairly explicit description of this set is given. The paper also gives a negative answer to a question of Lagarias and Maddock by showing that most level sets (in the sense of Baire category) contain infinitely many local level sets, and that a continuum of level sets even contain uncountably many local level sets. Finally, several of the main results are extended to a version of T with arbitrary signs in the summands.Comment: Added a new Section 5 with generalization of the main results; some new and corrected proofs of the old material; 29 pages, 3 figure

Remote mental health care interventions during the COVID-19 pandemic: an umbrella review

Mitigating the COVID-19 related disruptions in mental health care services is crucial in a time of increased mental health disorders. Numerous reviews have been conducted on the process of implementing technology- based mental health care during the pandemic. The research question of this umbrella review was to examine what the impact of COVID-19 was on access and delivery of mental health services and how mental health services have changed during the pandemic. A systematic search for systematic reviews and meta-analyses was conducted up to August 12, 2022, and 38 systematic reviews were identified. Main disruptions during COVID-19 were reduced access to outpatient mental health care and reduced admissions and earlier discharge from inpatient care. In response, synchronous telemental health tools such as videoconferencing were used to provide remote care similar to pre-COVID care, and to a lesser extent asynchronous virtual mental health tools such as apps. Implementation of synchronous tools were facilitated by time-efficiency and flexibility during the pandemic but there was a lack of accessibility for specific vulnerable populations. Main barriers among prac- titioners and patients to use digital mental health tools were poor technological literacy, particularly when preexisting inequalities existed, and beliefs about reduced therapeutic alliance particularly in case of severe mental disorders. Absence of organizational support for technological implementation of digital mental health interventions due to inadequate IT infrastructure, lack of funding, as well as lack of privacy and safety, chal- lenged implementation during COVID-19. Reviews were of low to moderate quality, covered heterogeneously designed primary studies and lacked findings of implementation in low- and middle-income countries. These gaps in the evidence were particularly prevalent in studies conducted early in the pandemic. This umbrella review shows that during the COVID-19 pandemic, practitioners and mental health care institutions mainly used synchronous telemental health tools, and to a lesser degree asynchronous tools to enable continued access to mental health care for patients. Numerous barriers to these tools were identified, and call for further improve- ments. In addition, more high quality research into comparative effectiveness and working mechanisms may improve scalability of mental health care in general and in future infectious disease outbreaks