Splitting and Parallelizing of Quantum Convolutional Neural Networks for Learning Translationally Symmetric Data

A quantum convolutional neural network (QCNN) is a promising quantum machine learning (QML) model to achieve quantum advantages in classically intractable problems. However, QCNN requires a large number of measurements for data learning, limiting its practical applications for large-scale problems. To relieve this requirement, we propose a novel architecture called split-parallelizing QCNN (sp-QCNN), which exploits the prior knowledge of quantum data for designing efficient circuits. This architecture draws inspiration from geometric quantum machine learning and targets translationally symmetric quantum data commonly encountered in condensed matter physics. By splitting the quantum circuit based on translational symmetry, sp-QCNN substantially parallelizes conventional QCNN without increasing the number of qubits and further improves the measurement efficiency by an order of the number of qubits. To demonstrate its effectiveness, we apply sp-QCNN to a quantum phase recognition task and show that it can achieve similar performance to conventional QCNN while considerably reducing the measurement resources required. Due to its high measurement efficiency, sp-QCNN can mitigate statistical errors in estimating the gradient of the loss function, thereby accelerating the learning process. These results open up new possibilities for incorporating the prior knowledge of data into the efficient design of QML models, leading to practical quantum advantages.Comment: 15 pages, 10 figure

Robust and Hierarchical Stop Discovery in Sparse and Diverse Trajectories

The advance of GPS tracking technique brings a large amount of trajectory data. To better understand such mobility data, semantic models like “stop/move” (or inferring “activity”, “transportation mode”) recently become a hot topic for trajectory data analysis. Stops are important parts of tra- jectories, such as “working at office”, “shopping in a mall”, “waiting for the bus”. There are several methods such as velocity, clustering, density algorithms being designed to discover stops. However, existing works focus on well-defined trajectories like movement of vehicle and taxi, not working well for heterogeneous cases like diverse and sparse trajectories. On the contrary, our paper addresses three main challenges: (1) provide a robust clustering-based method to discover stops; (2) discover both shared stops and personalized stops, where shared stops are the common places where many trajectories pass and stay for a while (e.g. shopping mall), whilst personalized stops are individual places where user stays for his/her own purpose (e.g. home, office); (3) further build stop hierarchy (e.g. a big stop like EPFL campus and a small stop like an office building). We evaluate our approach with several diverse and spare real-life GPS data, compare it with other methods, and show its better data abstraction on trajectory

SOME RESULTS OF AIR MONITORING QUALITY IN HANOI AND ASSESSMENT OF AIR MONITORING METHODS USED IN VIETNAM

Joint Research on Environmental Science and Technology for the Eart

Urinary catecholamine excretion, cardiovascular variability, and outcomes in tetanus

Severe tetanus is characterized by muscle spasm and cardiovascular system disturbance. The pathophysiology of muscle spasm is relatively well understood and involves inhibition of central inhibitory synapses by tetanus toxin. That of cardiovascular disturbance is less clear, but is believed to relate to disinhibition of the autonomic nervous system. The clinical syndrome of autonomic nervous system dysfunction (ANSD) seen in severe tetanus is characterized principally by changes in heart rate and blood pressure which have been linked to increased circulating catecholamines. Previous studies have described varying relationships between catecholamines and signs of ANSD in tetanus, but are limited by confounders and assays used. In this study, we aimed to perform detailed characterization of the relationship between catecholamines (adrenaline and noradrenaline), cardiovascular parameters (heart rate and blood pressure) and clinical outcomes (ANSD, mechanical ventilation required, and length of intensive care unit stay) in adults with tetanus, as well as examine whether intrathecal antitoxin administration affected subsequent catecholamine excretion. Noradrenaline and adrenaline were measured by ELISA from 24-h urine collections taken on day 5 of hospitalization in 272 patients enrolled in a 2 × 2 factorial-blinded randomized controlled trial in a Vietnamese hospital. Catecholamine results measured from 263 patients were available for analysis. After adjustment for potential confounders (i.e., age, sex, intervention treatment, and medications), there were indications of non-linear relationships between urinary catecholamines and heart rate. Adrenaline and noradrenaline were associated with subsequent development of ANSD, and length of ICU stay

Concomitant Bacteremia in Adults With Severe Falciparum Malaria.

BackgroundApproximately 6% of children hospitalized with severe falciparum malaria in Africa are also bacteremic. It is therefore recommended that all children with severe malaria should receive broad-spectrum antibiotics in addition to parenteral artesunate. Empirical antibiotics are not recommended currently for adults with severe malaria.MethodsBlood cultures were performed on sequential prospectively studied adult patients with strictly defined severe falciparum malaria admitted to a single referral center in Vietnam between 1991 and 2003.ResultsIn 845 Vietnamese adults with severe falciparum malaria admission blood cultures were positive in 9 (1.07%: 95% confidence interval [CI], .37-1.76%); Staphylococcus aureus in 2, Streptococcus pyogenes in 1, Salmonella Typhi in 3, Non-typhoid Salmonella in 1, Klebsiella pneumoniae in 1, and Haemophilus influenzae type b in 1. Bacteremic patients presented usually with a combination of jaundice, acute renal failure, and high malaria parasitemia. Four bacteremic patients died compared with 108 (12.9%) of 836 nonbacteremic severe malaria patients (risk ratio, 3.44; 95% CI, 1.62-7.29). In patients with >20% parasitemia the prevalence of concomitant bacteremia was 5.2% (4/76; 95% CI, .2-10.3%) compared with 0.65% (5/769; 0.08-1.2%) in patients with ConclusionsIn contrast to children, the prevalence of concomitant bacteremia in adults with severe malaria is low. Administration of empirical antibiotics, in addition to artesunate, is warranted in the small subgroup of patients with very high parasitemias, emphasizing the importance of quantitative blood smear microscopy assessment, but it is not indicated in most adults with severe falciparum malaria

An open label randomized controlled trial of tamoxifen combined with amphotericin B and fluconazole for cryptococcal meningitis

Background: Cryptococcal meningitis has high mortality. Flucytosine is a key treatment but is expensive and rarely available. The anti-cancer agent tamoxifen has synergistic anti-cryptococcal activity with amphotericin in vitro. It is off-patent, cheap, and widely available. We performed a trial to determine its therapeutic potential. Methods:Open label randomized controlled trial. Participants received standard care - amphotericin combined with fluconazole for the first two weeks - or standard care plus tamoxifen 300mg/day. The primary end point was Early Fungicidal Activity (EFA) - the rate of yeast clearance from cerebrospinal fluid (CSF). Trial registration https://clinicaltrials.gov/ct2/show/NCT03112031 . Results: 50 patients were enrolled, (median age 34 years, 35 male). Tamoxifen had no effect on EFA (- 0.48log10 colony-forming units/mL/CSF control arm versus -0.49 tamoxifen arm, difference - 0.005log10CFU/ml/day, 95%CI: -0.16, 0.15, P=0.95). Tamoxifen caused QTc prolongation. Conclusion: High dose tamoxifen does not increase the clearance rate of Cryptococcus from CSF. Novel, affordable therapies are needed. Funding:The trial was funded through the Wellcome Trust Asia Programme Vietnam Core Grant 106680 and a Wellcome Trust Intermediate Fellowship to JND grant number WT097147MA