Anomalous temperature dependence of the band-gap in Black Phosphorus

Black Phosphorus (BP) has gained renewed attention due to its singular anisotropic electronic and optical properties that might be exploited for a wide range of technological applications. In this respect, the thermal properties are particularly important both to predict its room temperature operation and to determine its thermoelectric potential. From this point of view, one of the most spectacular and poorly understood phenomena is, indeed, the BP temperature-induced band-gap opening: when temperature is increased the fundamental band-gap increases instead of decreasing. This anomalous thermal dependence has also been observed, recently, in its monolayer counterpart. In this work, based on \textit{ab-initio} calculations, we present an explanation for this long known, and yet not fully explained, effect. We show that it arises from a combination of harmonic and lattice thermal expansion contributions, which are, in fact, highly interwined. We clearly narrow down the mechanisms that cause this gap opening by identifying the peculiar atomic vibrations that drive the anomaly. The final picture we give explains both the BP anomalous band-gap opening and the frequency increase with increasing volume (tension effect).Comment: Published in Nano Letter

El frijol en El Salvador: implicaciones para la investigacion agricola

Results of a study on bean cultivation in El Salvador are given. Aspects analyzed were as follows: consumption structure (apparent, per capita, and rural-urban; preferences, consumption and cooking ways, and nutritive value); area, production, and yields (at national and regional levels, by cropping system, and by planting time), production constraints (abiotic, biotic, and technological factors), and production perspectives. Recommendations are included on future research activities. (CIAT

Prevalence, risk factors, and treatment outcomes of isoniazid- and rifampicin-mono-resistant pulmonary tuberculosis in Lima, Peru

Background : Isoniazid and rifampicin are the two most efficacious first-line agents for tuberculosis (TB) treatment. We assessed the prevalence of isoniazid and rifampicin mono-resistance, associated risk factors, and the association of mono-resistance on treatment outcomes. Methods : A prospective, observational cohort study enrolled adults with a first episode of smear-positive pulmonary TB from 34 health facilities in a northern district of Lima, Peru, from March 2010 through December 2011. Participants were interviewed and a sputum sample was cultured on Lowenstein-Jensen (LJ) media. Drug susceptibility testing was performed using the proportion method. Medication regimens were documented for each patient. Our primary outcomes were treatment outcome at the end of treatment. The secondary outcome included recurrent episodes among cured patients within two years after completion of the treatment. Results : Of 1292 patients enrolled, 1039 (80%) were culture-positive. From this subpopulation, isoniazid mono-resistance was present in 85 (8%) patients and rifampicin mono-resistance was present in 24 (2%) patients. In the multivariate logistic regression model, isoniazid mono-resistance was associated with illicit drug use (adjusted odds ratio (aOR) = 2.10; 95% confidence interval (CI): 1.1-4.1), and rifampicin mono-resistance was associated with HIV infection (aOR = 9.43; 95% CI: 1.9-47.8). Isoniazid mono-resistant patients had a higherrisk of poor treatment outcomes including treatment failure (2/85, 2%, p-value<0.01) and death (4/85, 5%, p<0.02). Rifampicin mono-resistant patients had a higher risk of death (2/24,8%, p<0.01). Conclusion : A high prevalence of isoniazid and rifampicin mono-resistance was found among TB patients in our low HIV burden setting which were similar to regions with high HIV burden. Patients with isoniazid and rifampicin mono-resistance had an increased risk of poor treatment outcomes

First-principles calculation of hot carriers in black phosphorus

ABSTRACT Black Phosphorus (BP), a layered semiconductor, has atracted enormous attention due to its singular anisotropic electronic, optical and thickness-dependent direct bandgap properties. As a consequence, BP has been envisioned as a promising material for several technological applications including photonics electronics and optolectronics. Nonetheless, most of the materials that integrate these devices undergo scattering and decay processes that are governed by quantum mechanical effects. From this point of view, the correct understanding and prediction of hot carriers dynamics in prospective materials as BP is crucial for its succesfull integration in future technology. In this work, based on ab initio calculations, we study the carrier relaxation rates in BP. Thus, the electron-electron and electron-phonon scattering contributions are investigated. Our results suggest that for the near-infrared and visible light spectrum [1.5 to 3.5 eV], the carriers in BP follow an ultrafast dynamics with relaxation times of the order of few to tens of femtoseconds while for the far-infrared range the relaxation times is of the order of hundreds of femtoseconds. Our reults are consistent with previous studies of pump-probe measurements on carrier dynamics

Accounting for atmospheric carbon dioxide variations in pollen-based reconstructions of past hydroclimates.

Changes in atmospheric carbon dioxide (CO2) concentration directly influence the ratio of stomatal water loss to carbon uptake. This ratio (e) is a fundamental quantity for terrestrial ecosystems, as it defines the water requirement for plant growth. Statistical and analogue-based methods used to reconstruct past hydroclimate variables from fossil pollen assemblages do not take account of the effect of CO2 variations on e. Here we present a general, globally applicable method to correct for this effect. The method involves solving an equation that relates e to a climatic moisture index (MI, the ratio of mean annual precipitation to mean annual potential evapotranspiration), mean growing-season temperature, and ambient CO2. The equation is based on the least-cost optimality hypothesis, which predicts how the ratio (χ) of leaf-internal to ambient CO2 varies with vapour pressure deficit (vpd), growing-season temperature and atmospheric pressure, combined with experimental evidence on the response of χ to the CO2 level at which plants have been grown. An empirical relationship based on global climate data is used to relate vpd to MI and growing-season temperature. The solution to the equation allows past MI to be estimated from pollen-reconstructed MI, given past CO2 and temperature. This MI value can be used to estimate mean annual precipitation, accounting for the effects of orbital variations, temperature and cloud cover (inferred from MI) on potential evapotranspiration. A pollen record from semi-arid Spain that spans the last glacial interval is used to illustrate the method. Low CO2 leads to estimated MI being larger than reconstructed MI during glacial times. The CO2 effect on inferred precipitation was partly offset by increased cloud cover; nonetheless, inferred precipitation was greater than present almost throughout the glacial period. This method allows a more robust reconstruction of past hydroclimatic variations than currently available tools

A Cough-Based Algorithm for Automatic Diagnosis of Pertussis

Pertussis is a contagious respiratory disease which mainly affects young children and can be fatal if left untreated. The World Health Organization estimates 16 million pertussis cases annually worldwide resulting in over 200,000 deaths. It is prevalent mainly in developing countries where it is difficult to diagnose due to the lack of healthcare facilities and medical professionals. Hence, a low-cost, quick and easily accessible solution is needed to provide pertussis diagnosis in such areas to contain an outbreak. In this paper we present an algorithm for automated diagnosis of pertussis using audio signals by analyzing cough and whoop sounds. The algorithm consists of three main blocks to perform automatic cough detection, cough classification and whooping sound detection. Each of these extract relevant features from the audio signal and subsequently classify them using a logistic regression model. The output from these blocks is collated to provide a pertussis likelihood diagnosis. The performance of the proposed algorithm is evaluated using audio recordings from 38 patients. The algorithm is able to diagnose all pertussis successfully from all audio recordings without any false diagnosis. It can also automatically detect individual cough sounds with 92% accuracy and PPV of 97%. The low complexity of the proposed algorithm coupled with its high accuracy demonstrates that it can be readily deployed using smartphones and can be extremely useful for quick identification or early screening of pertussis and for infection outbreaks control