12,412 research outputs found
Proton-Antiproton Annihilation in Baryonium
A possible interpretation of the near-threshold enhancement in the
-mass spectrum in is the of existence
of a narrow baryonium resonance X(1860). Mesonic decays of the
-bound state X(1860) due to the nucleon-antinucleon annihilation
are investigated in this paper. Mesonic coherent states with fixed -parity
and -parity have been constructed . The Amado-Cannata-Dedoder-Locher-Shao
formulation(Phys Rev Lett. {\bf 72}, 970 (1994)) is extended to the decays of
the X(1860). By this method, the branch-fraction ratios of , and are calculated. It is shown
that if the X(1860) is a bound state of , the decay channel ( is favored over . In this way, we develop
criteria for distinguishing the baryonium interpretation for the near-threshold
enhancement effects in -mass spectrum in from other possibilities. Experimental checks are expected. An intuitive
picture for our results is discussed.Comment: 19 pages, 3 figure
Pressure Effect on the superconducting properties of LaO_{1-x}F_{x}FeAs(x=0.11) superconductor
Diamagnetic susceptibility measurements under high hydrostatic pressure (up
to 1.03 GPa) were carried out on the newly discovered Fe-based superconductor
LaO_{1-x}F_{x}FeAs(x=0.11). The transition temperature T_c, defined as the
point at the maximum slope of superconducting transition, was enhanced almost
linearly by hydrostatic pressure, yielding a dT_c/dP of about 1.2 K/GPa.
Differential diamagnetic susceptibility curves indicate that the underlying
superconducting state is complicated. It is suggested that pressure plays an
important role on pushing low T_c superconducting phase toward the main
(optimal) superconducting phase.Comment: 7 pages, 4 figure
Universal cloning of continuous quantum variables
The cloning of quantum variables with continuous spectra is analyzed. A
universal - or Gaussian - quantum cloning machine is exhibited that copies
equally well the states of two conjugate variables such as position and
momentum. It also duplicates all coherent states with a fidelity of 2/3. More
generally, the copies are shown to obey a no-cloning Heisenberg-like
uncertainty relation.Comment: 4 pages, RevTex. Minor revisions, added explicit cloning
transformation, added reference
Improving Policy Learning via Language Dynamics Distillation
Recent work has shown that augmenting environments with language descriptions improves policy learning. However, for environments with complex language abstractions, learning how to ground language to observations is difficult due to sparse, delayed rewards. We propose Language Dynamics Distillation (LDD), which pretrains a model to predict environment dynamics given demonstrations with language descriptions, and then fine-tunes these language-aware pretrained representations via reinforcement learning (RL). In this way, the model is trained to both maximize expected reward and retain knowledge about how language relates to environment dynamics. On SILG, a benchmark of five tasks with language descriptions that evaluate distinct generalization challenges on unseen environments (NetHack, ALFWorld, RTFM, Messenger, and Touchdown), LDD outperforms tabula-rasa RL, VAE pretraining, and methods that learn from unlabeled demonstrations in inverse RL and reward shaping with pretrained experts. In our analyses, we show that language descriptions in demonstrations improve sample-efficiency and generalization across environments, and that dynamics modeling with expert demonstrations is more effective than with non-experts
Tissue-specific Accumulation of Flavonoids in Grape Berries is Related to Transcriptional Expression of VvF3â˛H and VvF3â˛5â˛H
The products and the related gene expression of flavonoid metabolism were examined in the skin and pulpof Yan73 (Vitis vinifera L. cv.) grapes, a teinturier variety cultivated in China, and the data were comparedwith those in the skin and pulp of Cabernet Sauvignon (Vitis vinifera L. cv.) grapes, a well-known redvariety. The results showed that, in comparison with the skins of Cabernet Sauvignon, the skins of Yan73berries were characterised by fewer types of flavonols and anthocyanins, a higher level of flavonoids,and a much lower percentage of 3â˛-hydroxylated flavonols. Flavonoid metabolism was also present in thepulp of Yan73, and the percentages of 3â˛-hydroxylated flavonols and 3â˛-hydroxylated flavan-3-ols weresignificantly higher than the percentages of their corresponding 3â˛,5â˛-hydroxylated forms. Only flavan-3-ols were found in the pulp of Cabernet Sauvignon. The expression of VvmybA1 exhibited a co-ordinationwith the accumulation of anthocyanins in the pulp of the teinturier cultivar, which showed great similarityto that in the skin. A good correlation was found between the expression of VvF3â˛H and 3â˛-hydroxylatedflavonoids, as well as between the expression of VvF3â˛5â˛H and 3â˛,5â˛-hydroxylated flavonoids in the skin andpulp of the grape berries. It is suggested that tissue-specific accumulation of flavonoids in grape berries isrelated to the transcriptional expression of VvF3â˛H and VvF3â˛5â˛H
Mass Spectrometric Study of Acoustically Levitated Droplet Illuminates Molecular-Level Mechanism of Photodynamic Therapy for Cancer involving Lipid Oxidation
Even though the general mechanism of photodynamic cancer therapy is known, the details and consequences of the reactions between the photosensitizerâgenerated singlet oxygen and substrate molecules remain elusive at the molecular level. Using temoporfin as the photosensitizer, here we combine fieldâinduced droplet ionization mass spectrometry and acoustic levitation techniques to study the âwallâlessâ oxidation reactions of 18:1 cardiolipin and 1âpalmitoylâ2âoleoylâsnâglyceroâ3âphosphoâ(1â˛âracâglycerol) (POPG) mediated by singlet oxygen at the airâwater interface of levitated water droplets. For both cardiolipin and POPG, every unsaturated oleyl chain is oxidized to an allyl hydroperoxide, which surprisingly is immune to further oxidation. This is attributed to the increased hydrophilicity of the oxidized chain, which attracts it toward the water phase, thereby increasing membrane permeability and eventually triggering cell death
Possible high temperature superconductivity in Ti-doped A-Sc-Fe-As-O (A= Ca, Sr) system
We report a systematic study on the effect of partial substitution of
Sc by Ti in SrScFeAsO, CaScFeAsO and
SrScFeAsO on their electrical properties. High
level of doping results in an increased carrier concentration and leads to the
appearance of superconductivity with the onset of T up to 45 K.Comment: 8 pages, 4 figures, 2 new figure
Applicative Bidirectional Programming with Lenses
A bidirectional transformation is a pair of mappings between source and view data objects, one in each direction. When the view is modified, the source is updated accordingly with respect to some laws. One way to reduce the development and maintenance effort of bidirectional transformations is to have specialized languages in which the resulting programs are bidirectional by construction---giving rise to the paradigm of bidirectional programming.
In this paper, we develop a framework for applicative-style and higher-order bidirectional programming, in which we can write bidirectional transformations as unidirectional programs in standard functional languages, opening up access to the bundle of language features previously only available to conventional unidirectional languages. Our framework essentially bridges two very different approaches of bidirectional programming, namely the lens framework and Voigtlanderâs semantic bidirectionalization, creating a new programming style that is able to bag benefits from both
Synthetic IR image refinement using adversarial learning with bidirectional mappings
Š 2019 IEEE. Collecting a large dataset of real infrared (IR) images is expensive, time-consuming, and even unavailable in some specific scenarios. With recent progress in machine learning, it has become more feasible to replace real IR images with qualified synthetic IR images in learning-based IR systems. However, this alternative may fail to achieve the desired performance, due to the gap between real and synthetic IR images. Inspired by adversarial learning for image-to-image translation, we propose the Synthetic IR Refinement Generative Adversarial Network (SIR-GAN) to narrow this gap. By learning the bidirectional mappings between two unpaired domains, the realism of the simulated IR images generated from the IR Simulator are significantly improved, where the source domain contains a large number of simulated IR images, where the target domain contains a limited quantity of real IR images. Specifically, driven by the idea of transferring infrared characteristic and protect target semantic information simultaneously, we propose a SIR refinement loss to consider an infrared loss and a structure loss further to the adversarial loss and the consistency loss. To further reduce the gap, stabilize training, and avoid artefacts, we modify the proposed algorithm by developing a training strategy, adding the U-net in the generators, using the dilated convolution in the discriminators and invoking the N-Adam acts as the optimizer. Qualitative, quantitative, and ablation study experiments demonstrate the superiority of the proposed approach compared with the state-of-the-art techniques in terms of realism and fidelity. In addition, our refined IR images are evaluated in the context of a feasibility study, where the accuracy of the trained classifier is significantly improved by adding our refined data into a small real-data training set
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