490 research outputs found
Assessment of the Nexus between Groundwater Extraction and Greenhouse Gas Emissions Employing Aquifer Modelling
AbstractOne of the main sources of Greenhouse Gas Emissions (GHG) is electricity consumption which is getting used for different purposes.Water pumping, especially, pumping from deep groundwater resources consumes a lot of energy. In arid and semi-arid areas, in which groundwater is the only source of water, water pumping is done for different purposes such as agricultural, industrial and urban uses. Kerman plain is one of these arid and semi-arid areas which is located in South East of Iran. Groundwater reliance and aquifer decline are the most prominent challenges that this area is faced with in recent years. This challenges increase the demand for more electricity consumption to pump water from the aquifer so that CO2 emissions will be increased. A large percentage of water extraction from the aquifer is used for agricultural purposes. In this paper, by modelling Kerman plain aquifer with MODFLOW software by using Geographical Information System (GIS) database and also studying height of groundwater table from 1999 to 2012, electricity energy consumption of groundwater extraction for agricultural, industrial and urban water supply is calculated and the CO2 emissions trends resulted from electricity energy consumption is evaluated. Then model results are examined for a business as usual (BAU) scenario of changes in water resources. As a result the amount of CO2 emitted from groundwater abstraction by three mentioned sectors is calculated for specified time horizon. Finally, some suggestions are presented for reducing greenhouse gas emissions for the time horizon
Implications of surface noise for the motional coherence of trapped ions
Electric noise from metallic surfaces is a major obstacle towards quantum
applications with trapped ions due to motional heating of the ions. Here, we
discuss how the same noise source can also lead to pure dephasing of motional
quantum states. The mechanism is particularly relevant at small ion-surface
distances, thus imposing a new constraint on trap miniaturization. By means of
a free induction decay experiment, we measure the dephasing time of the motion
of a single ion trapped 50~m above a Cu-Al surface. From the dephasing
times we extract the integrated noise below the secular frequency of the ion.
We find that none of the most commonly discussed surface noise models for ion
traps describes both, the observed heating as well as the measured dephasing,
satisfactorily. Thus, our measurements provide a benchmark for future models
for the electric noise emitted by metallic surfaces.Comment: (5 pages, 4 figures
Long-Lived Ultracold Molecules with Electric and Magnetic Dipole Moments
We create fermionic dipolar NaLi molecules in their triplet ground
state from an ultracold mixture of Na and Li. Using
magneto-association across a narrow Feshbach resonance followed by a two-photon
STIRAP transfer to the triplet ground state, we produce
ground state molecules in a spin-polarized state. We observe a lifetime of
in an isolated molecular sample, approaching the -wave
universal rate limit. Electron spin resonance spectroscopy of the triplet state
was used to determine the hyperfine structure of this previously unobserved
molecular state.Comment: 5 pages, 5 figure
Leaves of more cold hardy grapes have a higher density of small, sunken stomata
Leaf stomatal density, index and size are known to be affected by the growing conditions, presumably to provide a better function for plant development. The question was whether there is a difference in stomatal parameters between grape species with different cold hardiness: V. riparia and V. vinifera; and the V. vinifera cultivars 'Riesling', 'Chardonnay', 'Sauvignon Blanc' and 'Merlot'. Analysis by scanning electron microscopy allowed the observation of 3 types of stomata in developing and mature leaves of all examined grape leaves. Stomatal parameters were found to be significantly affected by species or cultivar and growing conditions but not rootstock. A higher stomatal density and index were determined for the more cold hardy V. riparia and V. vinifera 'Riesling', whereby the higher number of stomata in 'Riesling' was found to be due to a higher number of small, sunken stomata. These findings might indicate a strategy of grape plants to optimize growth under low temperatures by using fast-acting stomata whose gas and water exchange are less affected than for larger stomata
Seed germination and seedling establishment of some wild almond species
Wild almond species are important genetic resources for resistance to unsuitable condition, especially drought stress. They have been used traditionally as rootstocks in some areas of Iran. So far, 21 wild almond species and 7 inter species hybrids have been identified in Iran. To study seed germination and seedling establishment of some of these species, three separate experiments were designed. In the first experiment, the application of gibberellic acid (GA3) (0, 250, 500 and 750 ppm) for 24 h was studied on germination characteristics of four wild almond accessions after stratification at 5 ± 0.5°C in Perlite media. Germination percentage, index vigor and root initiation factors were different in almond accessions, but were not affected by hormonal treatments. In the second experiment, seeds of another six wild almond accessions were stratified to compare their germination ability. Germination percentage, index vigor and root initiation were different among accessions significantly. In the last experiment, the establishment and vigor of 14 accessions from eight almond species have been evaluated in plastic bags in outdoor conditions. Two ecotypes of Prunus spp. had the highest stem diameter and length at all growing stages.Keywords: Amygdalus, germination percentage, index vigor, root initiation, stem length, stem diameter
The effect of resveratrol on the expression of MDR1 gene in leukemic lymphoblast's of acute lymphoblastic leukemia patients
Background: Chemotherapy plays a very important role in the treatment of leukemia but the resistance properties of the lymphoblasts limit the effect of chemotherapy. One of the main mechanisms of resistance to chemotherapy is the increased expression of MDR1 gene. The aim of this study was to explore the effect of resveratrol on the expression of MDR1 gene in leukemic lymphoblast of new cases of acute lymphoblastic leukemia (ALL) patients in vitro. Methods: Separation of lymphoblasts of 5 new case ALL patients from peripheral blood was performed by ficoll density gradient centrifugation. Lymphoblasts were cultured in RPMI 1640 medium. Lymphoblasts were treated with 50μmol/L resveratrol for 48 h. Total RNA was extracted with guanidine isothiocyanate. RNA was converted to cDNA. Real time PCR was used to detect mRNA expression of MDR1. Results: The results of gene detection showed that the expression of MDR1 did not change significantly in the patients however, in one patient expression of MDR1 increased upon treatment with resveratrol. Conclusion: The results of this study did not support resveratrol as a compound to reverse multidrug resistance in leukemic lymphoblasts
Machine learning discovery of new phases in programmable quantum simulator snapshots
Machine learning has recently emerged as a promising approach for studying
complex phenomena characterized by rich datasets. In particular, data-centric
approaches lend to the possibility of automatically discovering structures in
experimental datasets that manual inspection may miss. Here, we introduce an
interpretable unsupervised-supervised hybrid machine learning approach, the
hybrid-correlation convolutional neural network (Hybrid-CCNN), and apply it to
experimental data generated using a programmable quantum simulator based on
Rydberg atom arrays. Specifically, we apply Hybrid-CCNN to analyze new quantum
phases on square lattices with programmable interactions. The initial
unsupervised dimensionality reduction and clustering stage first reveals five
distinct quantum phase regions. In a second supervised stage, we refine these
phase boundaries and characterize each phase by training fully interpretable
CCNNs and extracting the relevant correlations for each phase. The
characteristic spatial weightings and snippets of correlations specifically
recognized in each phase capture quantum fluctuations in the striated phase and
identify two previously undetected phases, the rhombic and boundary-ordered
phases. These observations demonstrate that a combination of programmable
quantum simulators with machine learning can be used as a powerful tool for
detailed exploration of correlated quantum states of matter.Comment: 9 pages, 5 figures + 12 pages, 10 figures appendi
A quantum processor based on coherent transport of entangled atom arrays
The ability to engineer parallel, programmable operations between desired
qubits within a quantum processor is central for building scalable quantum
information systems. In most state-of-the-art approaches, qubits interact
locally, constrained by the connectivity associated with their fixed spatial
layout. Here, we demonstrate a quantum processor with dynamic, nonlocal
connectivity, in which entangled qubits are coherently transported in a highly
parallel manner across two spatial dimensions, in between layers of single- and
two-qubit operations. Our approach makes use of neutral atom arrays trapped and
transported by optical tweezers; hyperfine states are used for robust quantum
information storage, and excitation into Rydberg states is used for
entanglement generation. We use this architecture to realize programmable
generation of entangled graph states such as cluster states and a 7-qubit
Steane code state. Furthermore, we shuttle entangled ancilla arrays to realize
a surface code with 19 qubits and a toric code state on a torus with 24 qubits.
Finally, we use this architecture to realize a hybrid analog-digital evolution
and employ it for measuring entanglement entropy in quantum simulations,
experimentally observing non-monotonic entanglement dynamics associated with
quantum many-body scars. Realizing a long-standing goal, these results pave the
way toward scalable quantum processing and enable new applications ranging from
simulation to metrology.Comment: 23 pages, 14 figures; movie attached as ancillary fil
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