Thermal transport at the quantum scale

The aim of this thesis is to add new experimental insights to the knowledge of thermal transport physics at the scale of single atoms and molecules, where quantum effects become apparent. In particular a new instrument and measurement protocol to study heat transport at the nanoscale will be introduced, and the key experimental results on single molecules will be presented and compared to the outcomes of the latest theoretical predictions. Finally, possible technological perspectives and future directions of the fields will be reviewed and commented

Androgenetic alopecia: a review

Purpose Androgenetic alopecia, commonly known as male pattern baldness, is the most common type of progressive hair loss disorder in men. The aim of this paper is to review recent advances in understanding the pathophysiology and molecular mechanism of androgenetic alopecia. Methods Using the PubMed database, we conducted a systematic review of the literature, selecting studies pub- lished from 1916 to 2016. Results The occurrence and development of androgenetic alopecia depends on the interaction of endocrine factors and genetic predisposition. Androgenetic alopecia is character- ized by progressive hair follicular miniaturization, caused by the actions of androgens on the epithelial cells of genetically susceptible hair follicles in androgen-dependent areas. Although the exact pathogenesis of androgenetic alopecia remains to be clari fi ed, research has shown that it is a polygenetic condition. Numerous studies have unequi- vocally identi fi ed two major genetic risk loci for androge- netic alopecia, on the X-chromosome AR ⁄ EDA2R locus and the chromosome 20p11 locus. Conclusions Candidate gene and genome-wide association studies have reported that single-nucleotide polymorphisms at different genomic loci are associated with androgenetic alopecia development. A number of genes determine the predisposition for androgenetic alopecia in a polygenic fashion. However, further studies are needed before the specific genetic factors of this polygenic condition can be fully explaine

Measuring impact: preliminary insights from interviews with impact investors

This research paper – the second of LSE Cities’ Measuring impact beyond financial return research project, draws out points of convergence and divergence in approaches to impact measurement. Testing out hypotheses set out in the first research paper, it is based on information derived from a series of interviews with established impact investors in the fields of the environment; social enterprise; microfinance; and social impact bonds. We see emerging signs of three types of impact investors – those that are focused on system building, those that assess each investment on a case by case basis, and those that follow the evidence of what works. Other key themes emerging are that there seems to be a relatively low level of engagement between impact investors and the ultimate beneficiaries of their social impact; and that the connections, actual or perceived, between non-financial and financial returns are a key factor in determining what impact gets measured, and the effort put into measurement

Comparing pre- and post-pandemic greenhouse gas and noise emissions from road traffic in Rome (Italy): a multi-step approach

This study presents the results of a traffic simulation analysis and emissions (greenhouse gas and noise) assessment comparing pre-pandemic (2019) and post-pandemic (2022) periods. The estimation of road traffic demand is based on conventional data sources and floating car data; next, the traffic simulation procedure was performed providing road network traffic volumes, which are the input for the emission models. The diffusion of teleworking, e-commerce, as well as the digitization of many processes, services and activities, lead to a significant change in urban mobility. Results show a significant though still not complete resumption of commuters travel activity (−10% compared to pre-pandemic period) in the morning peak-hour. This translates into an 11% reduction of greenhouse gas emissions and a 0.1% increase in noise emissions

Pairs of Fish Resolve Conflicts over Coordinated Movement by Taking Turns

SummaryWhen individuals stand to gain by interacting with one another, but disagree over their preferred course of collective action, coordination can be hard to achieve [1–4]. In previous work, we found that pairs of stickleback fish prefer to synchronize their trips out of cover to look for food [5], possibly because this reduces perceived predation risk [6]. To create a degree of conflict over group coordination, we trained individual fish to expect food at one of two alternative, exposed locations and paired individuals with different expectations. Compared with isolated individuals, members of a pair showed a significantly increased tendency to alternate between foraging sites, together taking turns to visit first one individual's favored site and then the other individual's. Using a Markov-chain model to infer the individual rules underlying their joint behavior, we found that fish respond to a partner that breaks the pattern of alternation by themselves reverting to less regular behavior. Our results confirm theoretical predictions that conflict over group coordination can be resolved by taking turns [7–10] and show that, in this system, the pattern of alternation is actively monitored and maintained

a robust algorithm to solve the signal setting problem considering different traffic assignment approaches

AbstractIn this paper we extend a stochastic discrete optimization algorithm so as to tackle the signal setting problem. Signalized junctions represent critical points of an urban transportation network, and the efficiency of their traffic signal setting influences the overall network performance. Since road congestion usually takes place at or close to junction areas, an improvement in signal settings contributes to improving travel times, drivers' comfort, fuel consumption efficiency, pollution and safety. In a traffic network, the signal control strategy affects the travel time on the roads and influences drivers' route choice behavior. The paper presents an algorithm for signal setting optimization of signalized junctions in a congested road network. The objective function used in this work is a weighted sum of delays caused by the signalized intersections. We propose an iterative procedure to solve the problem by alternately updating signal settings based on fixed flows and traffic assignment based on fixed signal settings. To show the robustness of our method, we consider two different assignment methods: one based on user equilibrium assignment, well established in the literature as well as in practice, and the other based on a platoon simulation model with vehicular flow propagation and spill-back. Our optimization algorithm is also compared with others well known in the literature for this problem. The surrogate method (SM), particle swarm optimization (PSO) and the genetic algorithm (GA) are compared for a combined problem of global optimization of signal settings and traffic assignment (GOSSTA). Numerical experiments on a real test network are reported

Multi-vehicle Stochastic Fundamental Diagram Consistent with Transportations Systems Theory

This paper describes a general approach to the specification the stable regime speed-flow function, for motorways, as a part of the stable regime Stochastic Fundamental Diagram consistent with main assumptions of Transportation Systems Theory. Main original elements are: • Specification of speed-flow functions consistent with travel time function, such as BPR-like functions; • Calibration from disaggregate data, say data from single vehicle trajectories; • Specification of the speed r. v. distribution consistent with those used in RUT for route choice behavior modelling, such as Gamma, Inv-Gamma

Non-contact video-based assessment of the respiratory function using a RGB-D camera

A fully automatic, non-contact method for the assessment of the respiratory function is proposed using an RGB-D camera-based technology. The proposed algorithm relies on the depth channel of the camera to estimate the movements of the body’s trunk during breathing. It solves in fixed-time complexity, O(1), as the acquisition relies on the mean depth value of the target regions only using the color channels to automatically locate them. This simplicity allows the extraction of real-time values of the respiration, as well as the synchronous assessment on multiple body parts. Two different experiments have been performed: a first one conducted on 10 users in a single region and with a fixed breathing frequency, and a second one conducted on 20 users considering a simultaneous acquisition in two regions. The breath rate has then been computed and compared with a reference measurement. The results show a non-statistically significant bias of 0.11 breaths/min and 96% limits of agreement of -2.21/2.34 breaths/min regarding the breath-by-breath assessment. The overall real-time assessment shows a RMSE of 0.21 breaths/min. We have shown that this method is suitable for applications where respiration needs to be monitored in non-ambulatory and static environments.This research was funded by Ministerio de Ciencia e Innovación with grant number PID2020-116011.Postprint (published version