A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is
We investigate the quantum phase transition (QPT) in the XXZ central spin model, which can be described as a spin-1/2 particle coupled to N bath spins. In general, the QPT is supposed to occur only in the thermodynamical limit. In contrast, we present that the central spin model exhibits a normal-to-superradiant phase transition in the limit where the ratio of the transition frequency of the central spin to that of the bath spins and the number of the bath spins tend to infinity. We give thearXiv:2207.04191v1 fatcat:7tvbnp2ghvgb3mkug4egfhwp3q
more »... -energy effective Hamiltonian analytically in the normal phase and the superradiant phase, and we find that the longitudinal interaction can significantly influence the excitation number and the coherence of the ground state. These two quantities are remarkably enhanced for the negative longitudinal interaction while suppressed for the positive longitudinal interaction. We also use the quantum Fisher information (QFI) to characterize the QPT and illustrate a measurement scheme that can be applied in practice. This work builds a novel connection between the qubit-spin systems and the qubit-field systems, which provides a possibility for the realization of criticality-enhanced quantum sensing in central spin systems.
One of the key problems in multi-label text classification is how to take advantage of the correlation among labels. However, it is very challenging to directly model the correlations among labels in a complex and unknown label space. In this paper, we propose a Label Mask multi-label text classification model (LM-MTC), which is inspired by the idea of cloze questions of language model. LM-MTC is able to capture implicit relationships among labels through the powerful ability of pre-trainarXiv:2106.10076v1 fatcat:h74da3gp5raetbmyesy2u46zne
more »... ge models. On the basis, we assign a different token to each potential label, and randomly mask the token with a certain probability to build a label based Masked Language Model (MLM). We train the MTC and MLM together, further improving the generalization ability of the model. A large number of experiments on multiple datasets demonstrate the effectiveness of our method.
The cost of LTL model checking is highly sensitive to the length of the formula under verification. We observe that, under some specific conditions, the input LTL formula can be reduced to an easier-to-handle one before model checking. In our reduction, these two formulae need not to be logically equivalent, but they share the same counterexample set w.r.t the model. In the case that the model is symbolically represented, the condition enabling such reduction can be detected with a lightweightarXiv:1301.3299v1 fatcat:l67axysabfavpfh67lxrfqrxyy
more »... ffort (e.g., with SAT-solving). In this paper, we tentatively name such technique "Counterexample-Preserving Reduction" (CePRe for short), and finally the proposed technquie is experimentally evaluated by adapting NuSMV.
Distance metric learning is successful in discovering intrinsic relations in data. However, most algorithms are computationally demanding when the problem size becomes large. In this paper, we propose a discriminative metric learning algorithm, and develop a distributed scheme learning metrics on moderate-sized subsets of data, and aggregating the results into a global solution. The technique leverages the power of parallel computation. The algorithm of the aggregated distance metric learningdoi:10.1109/tnnls.2014.2377211 pmid:25532194 fatcat:5vj2u6fy75chnnyghjfoan7bwe
more »... DML) scales well with the data size and can be controlled by the partition. We theoretically analyse and provide bounds for the error induced by the distributed treatment. We have conducted experimental evaluation of ADML, both on specially designed tests and on practical image annotation tasks. Those tests have shown that ADML achieves the state-of-the-art performance at only a fraction of the cost incurred by most existing methods.
This paper presents an analysis of the level of blood hemoglobin and the rates of anemia in Chinese rural residents in the 2010-2012 National Nutrition and Health Survey, and the change in its prevalence in rural residents during the last ten years. Our methodology included data from the Chinese Nutrition and Health Surveillance in 2010-2012, where samples were selected through the method of probability proportion to size. The study objects were from 150 sites in provinces, autonomous regions,doi:10.3390/nu9030192 pmid:28245576 pmcid:PMC5372855 fatcat:vcabbfx4xjbsropwbq74ijrnwu
more »... r municipalities in China. The concentration of blood hemoglobin was determined using the cyanmethemoglobin method. Anemia was judged by the anemia standard recommended by the World Health Organization (WHO), combined with elevation correction standard. The level of blood hemoglobin, the prevalence of anemia, and the 95% CI (Confidence interval) value were analyzed using complex sampling weighted processing, combined with the population figures released by the National Bureau of Statistics in 2009. Our results indicate that the level of blood hemoglobin of the Chinese rural area population was 145.92 ± 0.83 g/L, with the prevalence of anemia in the Chinese rural population at 9.7% (95% CI: 9.4%-10.0%). The prevalence of anemia in children 6-11 years old was 5.5% (95% CI: 5.0%-6.0%), 8.1% (95% CI: 7.5%-8.7%) for 12-17-year-old teenagers, 10.0% (95% CI: 9.4%-10.6%) for 18-44-year-old adults, 9.6% (95% CI: 9.0%-10.1%) for 45-59-year-old adults, and 12.6% (95% CI: 11.9%-13.3%) for the elderly above 60 years old. Our conclusion shows that the prevalence of anemia in the Chinese rural population in 2010-2012 had obviously decreased compared to the last decade; however, women of reproductive age and the elderly still had a high prevalence of anemia.
The cost of LTL model checking is highly sensitive to the length of the formula under verification. We observe that, under some specific conditions, the input LTL formula can be reduced to an easier-to-handle one before model checking. In such reduction, these two formulae need not to be logically equivalent, but they share the same counterexample set w.r.t the model. In the case that the model is symbolically represented, the condition enabling such reduction can be detected with a lightweightdoi:10.1155/2014/702165 fatcat:litn3aokbvhf5jcm5zxf2ee7hy
more »... effort (e.g., with SAT-solving). In this paper, we tentatively name such technique "counterexample-preserving reduction" (CePRe, for short), and the proposed technique is evaluated by conducting comparative experiments of BDD-based model checking, bounded model checking, and property directed reachability-(IC3) based model checking.
This paper shows our work on CLEF 2008. Our group joined the Visual Concept Detection Task of ImageCLEF 2008 this year. We submitted one run (run id: HJ_FA) for the evaluation. In the run, we applied a method called "Feature Annotation" to detect visual concept for the predefined concepts and we want to know how this information help in solving the photographic retrieval task. The applied method selected high level features for each concept from both local and global features, based on whichdblp:conf/clef/JiangRY08 fatcat:qqtbhv6z5fc37oepejo2wgirqa
more »... visual concepts are detected. The applied method consists of three procedures. First, feature extraction in which both local and global features are extracted from images. Then, a clustering algorithm is applied to "annotate the features". In this procedure, the features are affiliated with their corresponding concepts. Finally, we applied KNN algorithm to classify tests images according to the training images with the annotated features. The experiments were performed on the given training and test data on the 17 concepts. The paper concludes with an analysis of our results. Finally we identify the weaknesses in our approach and ways in which the algorithm could be optimized and improved.
Nowadays, a large amount of information is stored as text, and numerous text mining techniques have been developed for various applications, such as event detection, news topic classification, public opinion detection, and sentiment analysis. Although significant progress has been achieved for short text classification, document-level text classification requires further exploration. Long documents always contain irrelevant noisy information that shelters the prominence of indicative features,doi:10.3390/app12052544 fatcat:ezwyetiz7jdpbesupatcss3cxy
more »... imiting the interpretability of classification results. To alleviate this problem, a model called MIPELD (mining the frequent pattern of a named entity for long document classification) for long document classification is demonstrated, which mines the frequent patterns of named entities as features. Discovered patterns allow semantic generalization among documents and provide clues for verifying the results. Experiments on several datasets resulted in good accuracy and marco-F1 values, meeting the requirements for practical application. Further analysis validated the effectiveness of MIPELD in mining interpretable information in text classification.
In quantum systems, the measurement of operators and the measurement of the quantum states of the system are very challenging tasks. In this Letter, we propose a method to obtain the average value of one operator in a certain state by measuring the instantaneous change of the average value of another operator with the assistance of a known reference state. We refer to this measurement method as the instantaneous indirect measurement method. By studying the application of this method to somearXiv:2207.04761v2 fatcat:j5mtpqin5rdx3fgywyj7gnbo6q
more »... cal models, we find that this measurement can be applied to the measurement of an arbitrary state of a quantum system. Furthermore, for the system to be measured, we find that such measurement neither significantly affects the wave function of the system nor causes wave function collapse of the system. Also, our study shows that when two independent systems are coupled, the information mapping between them is done instantaneously. Finally, we discuss applying this measurement method to the measurement of quantum Fisher information, which quantizes the limited accuracy of estimating a parameter from a quantum state.
The placenta has numerous functions, such as transporting oxygen and nutrients and building the immune tolerance of the fetus. Cell fusion is an essential process for placental development and maturation. In human placental development, mononucleated cytotrophoblast (CTB) cells can fuse to form a multinucleated syncytiotrophoblast (STB), which is the outermost layer of the placenta. Nephrin is a transmembrane protein that belongs to the Ig superfamily. Previous studies have shown that nephrindoi:10.1530/rep-14-0424 pmid:25614620 fatcat:fwjnzixkknguxf6blja3ekwkma
more »... ntributes to the fusion of myoblasts into myotubes in zebrafish and mice, presenting a functional conservation with its Drosophila ortholog sticks and stones. However, whether nephrin is involved in trophoblast syncytialization remains unclear. In this study, we report that nephrin was localized predominantly in the CTB cells and STB of human placenta villi from first trimester to term pregnancy. Using a spontaneous fusion model of primary CTB cells, the expression of nephrin was found to be increased during trophoblast cell fusion. Moreover, the spontaneous syncytialization and the expression of syncytin 2, connexin 43, and human chorionic gonadotropin beta were significantly inhibited by nephrin-specific siRNAs. The above results demonstrate that nephrin plays an important role in trophoblast syncytialization.
API protocols specify correct sequences of method invocations. Despite their usefulness, API protocols are often unavailable in practice because writing them is cumbersome and error prone. Multiple object API protocols are more expressive than single object API protocols. However, the huge number of objects of typical object-oriented programs poses a major challenge to the automatic mining of multiple object API protocols: besides maintaining scalability, it is important to capture variousdoi:10.1155/2013/171647 pmid:23844378 pmcid:PMC3690388 fatcat:7trhc7uxibas3b3up4y7fstldu
more »... t interactions. Current approaches utilize various heuristics to focus on small sets of methods. In this paper, we present a general, scalable, multiple object API protocols mining approach that can capture all object interactions. Our approach uses abstract field values to label object states during the mining process. We first mine single object typestates as finite state automata whose transitions are annotated with states of interacting objects before and after the execution of the corresponding method and then construct multiple object API protocols by composing these annotated single object typestates. We implement our approach for Java and evaluate it through a series of experiments.
Hypoxic-ischemic brain injury (HIBD) causes neonatal death and serious neurological disability; however, there are currently no promising therapies for it excepting cooling. Therefore, in this study, we used peptidome analysis to identify differentially expressed peptides in cerebrospinal fluid (CSF) of neonates with HIBD or controls, which may give a foundation for finding new promising drugs of neonatal HIBD. CSF samples were collected from neonates with HIBD (n = 4) or controls (n = 4).doi:10.1186/s13041-020-00671-9 pmid:33008433 fatcat:5gkpyrgjpjdvfpxtdlqigruakm
more »... LC–MS/MS was used to identify differentially expressed peptides between two groups. A total of 35 differentially expressed peptides from 25 precursor proteins were identified. The 2671.5 Da peptide (HSQFIGYPITLFVEKER), one of the down-regulated peptides in neonatal HIBD, is a fragment of heat shock protein 90-alpha (HSP90α/HSP90AA1). Results of bioinformatics analysis showed that HSP90α/HSP90AA1 was located in the protein–protein interaction (PPI) network hub and was involved in the NOD-LIKE receptor (NLR) signaling pathway. This peptide, we named it Hypoxic-Ischemic Brain Damage Associated Peptide (HIBDAP), is a hydrophilic peptide with high stability and has a long half-life of 3.5 h in mammalian reticulocytes. It was demonstrated that TAT-HIBDAP could successfully enter PC12 cells and further into the nucleus. After HIBDAP pretreatment and 6 h of OGD treatment, low concentrations of HIBDAP increased the survival rate of cells, except 40 μM had a toxic effect. Safe concentrations of HIBDAP reduced pyroptosis of PC12 cells under OGD, except 20 μM had no effect, by suppressing expressions of NLRP3, ASC and Caspase-1 except NLRP1. The results of our study identified the characterization and expression profiles of peptides in CSF of neonatal HIBD. Several meaningful peptides such as HIBDAP may play significant roles in neonatal HIBD and provide new therapeutic targets for neonatal HIBD.
As a complementary technique of the BDD-based approach, bounded model checking (BMC) has been successfully applied to LTL symbolic model checking. However, the expressiveness of LTL is rather limited, and some important properties cannot be captured by such logic. In this paper, we present a semantic BMC encoding approach to deal with the mixture ofETLfandETLl. Since such kind of temporal logic involves both finite and looping automata as connectives, all regular properties can be succinctlydoi:10.1155/2013/462532 fatcat:62o6ezqlgrfinprbrbumysf7zu
more »... cified with it. The presented algorithm is integrated into the model checker ENuSMV, and the approach is evaluated via conducting a series of imperial experiments.
Air pollution has raised people's intensive concerns especially in developing countries such as China and India. Different from using expensive or unreliable methods like sensor-based or social network based one, photo based air pollution estimation is a promising direction, while little work has been done up to now. Focusing on this immediate problem, this paper devises an effective convolutional neural network to estimate air's quality based on photos. Our method is comprised of twodoi:10.1145/2964284.2967230 dblp:conf/mm/ZhangYLRLB16 fatcat:lqwiz4t65babhi4cojww6th7oy
more »... s: first a negative log-log ordinal classifier is devised in the last layer of the network, which can improve the ordinal discriminative ability of the model. Second, as a variant of the Rectified Linear Units (ReLU), a modified activation function is developed for photo based air pollution estimation. This function has been shown it can alleviate the vanishing gradient issue effectively. We collect a set of outdoor photos and associate the pollution levels from official agency as the ground truth. Empirical experiments are conducted on this real-world dataset which shows the capability of our method.
« Previous Showing results 1 — 15 out of 395 results