Quantization in Graph Convolutional Neural Networks

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Efecto de la época de siembra sobre el crecimiento y el rendimiento de okra (Abelmoschus esculentus (L.) Moench) en el valle de Lerma, Salta

El objetivo del estudio fue determinar la época de siembra más apropiada para lograr un alto rendimiento de okra (cultivar Blue Sky) para el valle de Lerma (Salta) evaluando su efecto sobre los componentes del rendimiento. Los tratamientos consistieron en cinco fechas de siembra (24/09, 6/10, 15/10, 25/10 y 3/11 de 2010) bajo un diseño en bloques completos al azar con seis repeticiones. Las semillas emergieron en promedio a los trece días (rango de 11 a 19 días). Los frutos inmaduros con una longitud de 5 a 7 cm, fueron cosechados desde el 29/11/10 hasta el 20/04/11. Se analizaron las variables altura de la planta (cada 15 días), peso y número total de frutos cosechados en todo el ciclo de producción y por fecha de cosecha. La altura de las plantas durante el ciclo de cultivo presentó cambios significativos por efecto de tratamientos, encontrándose una tendencia a que las plantas tengan mayor altura a medida que la época de siembra se retrasa. No se observaron cambios significativos para el número y peso fresco de frutos debido a la fecha de siembra.The purpose of this paper was to determine the more appropriate sowing date to achieve a high yield of okra (cultivar Blue Sky) in Lerma valley (Salta), evaluating its effect on the components of the yield. The treatments consisted in five sowing dates (24/09, 6/10, 15/10, 25/10 and 3/11 of 2010) under a randomized complete block design with six repetitions. The seeds emerged on average to the thirteen days (range from 11 to 19 days). The immature fruits with a longitude from 5 to 7 cm, were harvested from 29/ 11/10 to 20/04/11. The variable height of the plant, weight and total number of fruits harvested were analyzed in the whole production cycle and for crop date. The height of the plants during the cultivation cycle varied significantly with the treatments being a tendency of the plants to have bigger height in late growing season. Significant changes were not observed as regard of the number of the fruits and their fresh weight, due to the sowing date.Fil: Lozano, Leila Beatriz. Universidad Nacional de Salta. Facultad de Ciencias Naturales; ArgentinaFil: Tálamo, Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - Conicet - Salta. Instituto de Bio y Geociencias del Noa; Argentina. Universidad Nacional de Salta. Facultad de Ciencias Naturales; ArgentinaFil: Artinián, Ana Laura. Universidad Nacional de Salta. Facultad de Ciencias Naturales; ArgentinaFil: Núñez, M. E.. Universidad Nacional de Salta. Facultad de Ciencias Naturales; Argentin

Topology Design to Increase Network Lifetime in WSN for Graph Filtering in Consensus Processes

Graph filters, which are considered as the workhorses of graph signal analysis in the emerging field of signal processing on graphs, are useful for many applications such as distributed estimation in wireless sensor networks. Many of these tasks are based on basic distributed operators such as consensus, which are carried out by sensor devices under limited energy supply. To cope with the energy constraints, this paper focuses on designing the network topology in order to maximize the network lifetime and reduce the energy consumption when applying graph filters. The problem is a complex combinatorial problem and in this work, we propose two efficient heuristic algorithms for solving it. We show by simulations that they provide good performance in terms of the network lifetime and the total energy consumption of the filtering process.acceptedVersionnivå

Topology design to reduce energy consumption of distributed graph filtering in WSN

The large number of nodes forming current sensor networks has made essential to introduce distributed mechanisms in many traditional applications. In the emerging field of graph signal processing, the distributed mechanism of information potentials constitutes a distributed graph filtering process that can be used to solve many different problems. An important limitation of this algorithm is that it is inherently iterative, which implies that the nodes incur in a repeated communication cost along the exchange periods of the filtering process. Since sensor nodes are battery powered and radio communications are one of the most energy demanding operations, in this work, we propose to redesign the network topology in order to reduce the total energy consumption of the filtering process. An accurate energy model is proposed and extensive numerical results are presented to show the efficiency of our methodology according to this energy model.acceptedVersionnivå

Monitoring the Bioactive Compounds Status in Olea europaea According to Collecting Period and Drying Conditions

Polyphenols and triterpenoids in olive have relevant importance both in the physiology of the plant and the nutritional and biological value of its products. Olive leaf extracts are of special interest for their numerous health-promoting properties. The present research is investigating the occurrence of phytochemicals in supercritical fluid extracts from leaves with regard to collection time and drying temperature. The phytochemical profiles of the olive leaf extracts were determined by reversed-phase high-performance liquid chromatography (HPLC) coupled to electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS) detection. The main extracted phytochemicals were phenols and terpenoids. A significant variation in the amounts of the different components was observed as a function of the different drying temperature and collecting time (p < 0.05). Among samples, the maximal contents of polyphenols and secoiridoid derivatives were found in the extracts from olive leaves collected in November and dried at 120 ºC, whereas triterpenoids showed the highest content in fresh leaves collected in August.This work was supported by the Tunisian Ministry of Higher Education under the Tunisian-Korean project “Development of Anti-arthritic remedy with Olive by-products”

Species distribution, antibiotic resistance and virulence traits in canine and feline enterococci in Tunisia

In order to investigate the possible role of dogs and cats in the carriage and potential dissemination of resistant enterococci, seventy faecal samples from dogs and cats were tested for enterococci. Fifty-eight enterococci were recovered. Isolates were identified as Enterococcus faecium (n = 31) and E. faecalis (n = 14) E. durans (n = 6), E. casseliflavus (n = 2), E. hirae and E. gallinarum (2 isolates each). Enterococcal isolates showed resistance to ciprofloxacin (n = 35), erythromycin (n = 31), tetracycline (n = 25), kanamycin (n = 15), streptomycin (n = 13), pristinamycin (n = 11), gentamicin (n = 10), chloramphenicol (n = 8), and linezolid (n = 6). The gene erm(B) was detected in 22 out of 31 erythromycin-resistant enterococci. All tetracycline-resistant enterococci carried tet(M) and/or tet(L) genes. The gene aac(6′)-Ie-aph(2″)-Ia was identified in five of high-level gentamicin-resistant isolates, the genes aph(3′)-IIIa and/or aac(6′)-Ie-aph(2″)-Ia in eleven high-level kanamycin-resistant isolates and the gene ant(6)-Ia in eleven high-level streptomycin-resistant isolates. Only one strain harboured cat(A) gene, and five strains contained vat(E) or vat(D) genes. Virulence genes gel(E) (21 strains), esp (11 strains) and cylA/cylB (5 strains) were detected. High genetic diversity was demonstrated among E. faecium isolates by pulsed-field gel electrophoresis (PFGE). Dogs and cats can be carriers of antibiotic-resistant enterococci in their faeces that could shed into the household environment

Measuring the availability of human resources for health and its relationship to universal health coverage for 204 countries and territories from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: Human resources for health (HRH) include a range of occupations that aim to promote or improve human health. The UN Sustainable Development Goals (SDGs) and the WHO Health Workforce 2030 strategy have drawn attention to the importance of HRH for achieving policy priorities such as universal health coverage (UHC). Although previous research has found substantial global disparities in HRH, the absence of comparable cross-national estimates of existing workforces has hindered efforts to quantify workforce requirements to meet health system goals. We aimed to use comparable and standardised data sources to estimate HRH densities globally, and to examine the relationship between a subset of HRH cadres and UHC effective coverage performance. Methods: Through the International Labour Organization and Global Health Data Exchange databases, we identified 1404 country-years of data from labour force surveys and 69 country-years of census data, with detailed microdata on health-related employment. From the WHO National Health Workforce Accounts, we identified 2950 country-years of data. We mapped data from all occupational coding systems to the International Standard Classification of Occupations 1988 (ISCO-88), allowing for standardised estimation of densities for 16 categories of health workers across the full time series. Using data from 1990 to 2019 for 196 of 204 countries and territories, covering seven Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) super-regions and 21 regions, we applied spatiotemporal Gaussian process regression (ST-GPR) to model HRH densities from 1990 to 2019 for all countries and territories. We used stochastic frontier meta-regression to model the relationship between the UHC effective coverage index and densities for the four categories of health workers enumerated in SDG indicator 3.c.1 pertaining to HRH: physicians, nurses and midwives, dentistry personnel, and pharmaceutical personnel. We identified minimum workforce density thresholds required to meet a specified target of 80 out of 100 on the UHC effective coverage index, and quantified national shortages with respect to those minimum thresholds. Findings: We estimated that, in 2019, the world had 104·0 million (95% uncertainty interval 83·5–128·0) health workers, including 12·8 million (9·7–16·6) physicians, 29·8 million (23·3–37·7) nurses and midwives, 4·6 million (3·6–6·0) dentistry personnel, and 5·2 million (4·0–6·7) pharmaceutical personnel. We calculated a global physician density of 16·7 (12·6–21·6) per 10 000 population, and a nurse and midwife density of 38·6 (30·1–48·8) per 10 000 population. We found the GBD super-regions of sub-Saharan Africa, south Asia, and north Africa and the Middle East had the lowest HRH densities. To reach 80 out of 100 on the UHC effective coverage index, we estimated that, per 10 000 population, at least 20·7 physicians, 70·6 nurses and midwives, 8·2 dentistry personnel, and 9·4 pharmaceutical personnel would be needed. In total, the 2019 national health workforces fell short of these minimum thresholds by 6·4 million physicians, 30·6 million nurses and midwives, 3·3 million dentistry personnel, and 2·9 million pharmaceutical personnel. Interpretation: Considerable expansion of the world's health workforce is needed to achieve high levels of UHC effective coverage. The largest shortages are in low-income settings, highlighting the need for increased financing and coordination to train, employ, and retain human resources in the health sector. Actual HRH shortages might be larger than estimated because minimum thresholds for each cadre of health workers are benchmarked on health systems that most efficiently translate human resources into UHC attainment