An Intelligent Advisor for City Traffic Policies

Nowadays, city streets are populated not only by private vehicles but also by public transport, fleets of workers, and deliveries. Since each vehicle class has a maximum cargo capacity, we study in this article how authorities could improve the road traffic by endorsing long term policies to change the different vehicle proportions: sedans, minivans, full size vans, trucks, and motorbikes, without losing the ability of moving cargo throughout the city. We have performed our study in a realistic scenario (map, road traffic characteristics, and number of vehicles) of the city of Malaga and captured the many details into the SUMO microsimulator. After analyzing the relationship between travel times, emissions, and fuel consumption, we have defined a multiobjective optimization problem to be solved, so as to minimize these city metrics. Our results provide a scientific evidence that we can improve the delivery of goods in the city by reducing the number of heavy duty vehicles and fostering the use of vans instead.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. This research has been partially funded by the Spanish MINECO and FEDER projects TIN2014-57341-R, TIN2016-81766-REDT, and TIN2017-88213-R. University of Malaga, Andalucia TECH. Daniel H. Stolfi is supported by a FPU grant (FPU13/00954) from the Spanish MECD. Christian Cintrano is supported by a FPI grant (BES-2015-074805) from Spanish MINECO

Quantum enhanced positioning and clock synchronization

A wide variety of positioning and ranging procedures are based on repeatedly sending electromagnetic pulses through space and measuring their time of arrival. This paper shows that quantum entanglement and squeezing can be employed to overcome the classical power/bandwidth limits on these procedures, enhancing their accuracy. Frequency entangled pulses could be used to construct quantum positioning systems (QPS), to perform clock synchronization, or to do ranging (quantum radar): all of these techniques exhibit a similar enhancement compared with analogous protocols that use classical light. Quantum entanglement and squeezing have been exploited in the context of interferometry, frequency measurements, lithography, and algorithms. Here, the problem of positioning a party (say Alice) with respect to a fixed array of reference points will be analyzed.Comment: 4 pages, 2 figures. Accepted for publication by Natur

Establishing comprehensive oral assessments for children with safeguarding concerns.

The dental profession is well placed to contribute important information in child protection cases but no previous research has been reported that assesses the volume or impact of this information. Comprehensive oral assessment clinics were introduced and established as an integral part of comprehensive medical assessments for children with welfare concerns in Greater Glasgow and Clyde. An assessment protocol and standardised paperwork for comprehensive oral assessments were developed to enhance information sharing and patient access to appropriate care. Two cases are presented and discussed to demonstrate the value of dental input

Parasites and allergy: observations from Brazil.

Brazil is a middle-income country undergoing the epidemiological transition. Effects of changes in daily life habits, and access to clean water, sanitation and urban services on a growing urban population have contributed to a double burden of both infectious and non-communicable chronic diseases. Studies have indicated that parasite infections may modulate the human immune system and influence the development of allergic conditions such as asthma. However, there is no consensus in the published literature on the effects of parasitic infections on allergy, perhaps as a consequence of factors determining the epidemiology of these infections that vary between populations such as age of first infection, duration and chronicity of infections, parasite burden and species, and host genetic susceptibility. In this review, we discuss the observations from Brazil concerning the relationship between parasite infections and allergy. This article is protected by copyright. All rights reserved

State based model of long-term potentiation and synaptic tagging and capture

Recent data indicate that plasticity protocols have not only synapse-specific but also more widespread effects. In particular, in synaptic tagging and capture (STC), tagged synapses can capture plasticity-related proteins, synthesized in response to strong stimulation of other synapses. This leads to long-lasting modification of only weakly stimulated synapses. Here we present a biophysical model of synaptic plasticity in the hippocampus that incorporates several key results from experiments on STC. The model specifies a set of physical states in which a synapse can exist, together with transition rates that are affected by high- and low-frequency stimulation protocols. In contrast to most standard plasticity models, the model exhibits both early- and late-phase LTP/D, de-potentiation, and STC. As such, it provides a useful starting point for further theoretical work on the role of STC in learning and memory

COVID-19: Is There Evidence for the Use of Herbal Medicines as Adjuvant Symptomatic Therapy?

Background: Current recommendations for the self-management of SARS-Cov-2 disease (COVID-19) include self-isolation, rest, hydration, and the use of NSAID in case of high fever only. It is expected that many patients will add other symptomatic/adjuvant treatments, such as herbal medicines. Aims: To provide a benefits/risks assessment of selected herbal medicines traditionally indicated for “respiratory diseases” within the current frame of the COVID-19 pandemic as an adjuvant treatment. Method: The plant selection was primarily based on species listed by the WHO and EMA, but some other herbal remedies were considered due to their widespread use in respiratory conditions. Preclinical and clinical data on their efficacy and safety were collected from authoritative sources. The target population were adults with early and mild flu symptoms without underlying conditions. These were evaluated according to a modified PrOACT-URL method with paracetamol, ibuprofen, and codeine as reference drugs. The benefits/risks balance of the treatments was classified as positive, promising, negative, and unknown. Results: A total of 39 herbal medicines were identified as very likely to appeal to the COVID-19 patient. According to our method, the benefits/risks assessment of the herbal medicines was found to be positive in 5 cases (Althaea officinalis, Commiphora molmol, Glycyrrhiza glabra, Hedera helix, and Sambucus nigra), promising in 12 cases (Allium sativum, Andrographis paniculata, Echinacea angustifolia, Echinacea purpurea, Eucalyptus globulus essential oil, Justicia pectoralis, Magnolia officinalis, Mikania glomerata, Pelargonium sidoides, Pimpinella anisum, Salix sp, Zingiber officinale), and unknown for the rest. On the same grounds, only ibuprofen resulted promising, but we could not find compelling evidence to endorse the use of paracetamol and/or codeine. Conclusions: Our work suggests that several herbal medicines have safety margins superior to those of reference drugs and enough levels of evidence to start a clinical discussion about their potential use as adjuvants in the treatment of early/mild common flu in otherwise healthy adults within the context of COVID-19. While these herbal medicines will not cure or prevent the flu, they may both improve general patient well-being and offer them an opportunity to personalize the therapeutic approaches

Assessing the performance of multiobjective genetic algorithms for optimization of a batch process scheduling problem

Scheduling optimization problems provide much potential for innovative solutions by genetic algorithms. The complexities, constraints and practicalities of the scheduling process motivate the development of genetic algorithm (GA) techniques to allow innovative and flexible scheduling solutions. Multiobjective genetic algorithms (MOGAs) extend the standard evolutionary-based genetic algorithm optimization technique to allow individual treatment of several objectives simultaneously. This allows the user to attempt to optimize several conflicting objectives, and to explore the trade-offs, conflicts and constraints inherent in this process. The area of MOGA performance assessment and comparison is a relatively new field, as much research concentrates on applications rather than the theory. However, the theoretical exploration of MOGA performance can have tangible effects on the development of highly practical applications, such as the process plant scheduling system under development in this work. By assessing and comparing the strengths, variations and limitations of the developing MOGA using a quantitative method, a highly efficient MOGA can develop to suit the application. The user can also gain insight into behaviour the application itself. In this work, four MOGAs are implemented to solve a process scheduling optimization problem; using two and five objectives, and two schedule building rules

Entanglement-free Heisenberg-limited phase estimation

Measurement underpins all quantitative science. A key example is the measurement of optical phase, used in length metrology and many other applications. Advances in precision measurement have consistently led to important scientific discoveries. At the fundamental level, measurement precision is limited by the number N of quantum resources (such as photons) that are used. Standard measurement schemes, using each resource independently, lead to a phase uncertainty that scales as 1/sqrt(N) - known as the standard quantum limit. However, it has long been conjectured that it should be possible to achieve a precision limited only by the Heisenberg uncertainty principle, dramatically improving the scaling to 1/N. It is commonly thought that achieving this improvement requires the use of exotic quantum entangled states, such as the NOON state. These states are extremely difficult to generate. Measurement schemes with counted photons or ions have been performed with N <= 6, but few have surpassed the standard quantum limit and none have shown Heisenberg-limited scaling. Here we demonstrate experimentally a Heisenberg-limited phase estimation procedure. We replace entangled input states with multiple applications of the phase shift on unentangled single-photon states. We generalize Kitaev's phase estimation algorithm using adaptive measurement theory to achieve a standard deviation scaling at the Heisenberg limit. For the largest number of resources used (N = 378), we estimate an unknown phase with a variance more than 10 dB below the standard quantum limit; achieving this variance would require more than 4,000 resources using standard interferometry. Our results represent a drastic reduction in the complexity of achieving quantum-enhanced measurement precision.Comment: Published in Nature. This is the final versio

Synchrotron radiography studies of shear-induced dilation in semi-solid Al alloys and steels

An improved understanding of the response of solidifying microstructures to load is required to further minimize casting defects and optimize casting processes. This article overviews synchrotron radiography studies that directly measure the micromechanics of semisolid alloy deformation in a thin sample direct-shear cell. It is shown that shear-induced dilation (also known as Reynolds’ dilatancy) occurs in semisolid alloys with morphologies ranging from equiaxed-dendritic to globular, at solid fractions from the dendrite coherency point to ~90% solid, and it occurs in both Al alloys and carbon steels. Discrete-element method simulations that treat solidifying microstructures as granular materials are then used to explore the origins of dilatancy in semisolid alloys