Non-separated states from squeezed dark-state polaritons in electromagnetically-induced-transparency media

Within the frame of quantized dark-state polaritons in electromagnetically-induced-transparency media, noise fluctuations in the quadrature components are studied. Squeezed state transfer, quantum correlation, and noise entanglement between probe field and atomic polarization are demonstrated in single- and double-$\Lambda$ configurations, respectively. Even though a larger degree of squeezing parameter in the continuous variable helps to establish stronger quantum correlations, inseparability criterion is satisfied only within a finite range of squeezing parameter. The results obtained in the present study may be useful for guiding experimental realization of quantum memory devices for possible applications in quantum information and computation.Comment: 12 pages, 7 figure

Linkage and association analyses of microsatellites and single-nucleotide polymorphisms in nuclear families

Several simulation studies have suggested that a high-density single-nucleotide polymorphisms (SNPs) marker set may be as useful as a traditional microsatellites (MS) marker set in performing whole-genome linkage analysis. However, very few studies have directly tested the SNPs-based genome-wide scan. In the present study, we compared the linkage results from the SNPs-based scan with a map density of 3-cM spacing with those from the MS scan using a 10-cM marker set among 300 nuclear families each from the Aipotu (AI), Danacaa (DA), and Karangar (KA) populations from the simulated Genetic Analysis Workshop 14 Problem 2 data. We found that information contents obtained from the SNPs scan were somewhat lower than those from the MS scan. However, the linkage results obtained from the two scans showed a high degree of similarity. Both scans identified a similar number of chromosomal regions attaining nominal significance (p < 0.05). Specifically, both scans detected confirmed evidence for linkage (NPL ≥ 4.07, p = 2 × 10(-5)) to chromosome 1 in the AI families, chromosomes 1 and 3 in the DA families, and chromosomes 3, 5, and 9 in the KA families. An additional confirmed linkage to chromosome 5 in the AI families was detected only by the MS scan. We also observed slightly wider 1-LOD intervals for more of the SNP peaks than for the MS peaks, which is likely due to lower information contents for the SNPs. Subsequent fine-mapping association analysis further identified 2 to 3 markers significantly associated with disease status in each population; B03T3056, B03T3058, and B05T4139 in the AI population, B03T3056 and B03T3058 in the KA population, and B03T3056, B03T3057, and B03T3058 in the DA population. Among the four markers, three were chosen based on results obtained from the two scans, but one was solely from the SNP scan. In summary, our finding suggests that the SNP-based genome scan has the potential to be as powerful as the traditional MS-based scan and offers good identification of peak location for further fine-mapped association analysis

Synthesis and crystal structure of the first 6a-thiathiophthen metal complex [Mo(CO)_5PPh_(2]2)(µ-C_5H_2S_3)

The first 6a-thiathiophthen metal complex was prepared by treating M(CO_)5[PPh_2CS_2CH_2C≡CH] with a catalytic amount of secondary amine or tertiary amine; the structure of the 6a-thiathiophthen molybdenum complex is confirmed by an X-ray diffraction analysis

Multimodality Helps Unimodality: Cross-Modal Few-Shot Learning with Multimodal Models

The ability to quickly learn a new task with minimal instruction - known as few-shot learning - is a central aspect of intelligent agents. Classical few-shot benchmarks make use of few-shot samples from a single modality, but such samples may not be sufficient to characterize an entire concept class. In contrast, humans use cross-modal information to learn new concepts efficiently. In this work, we demonstrate that one can indeed build a better ${\bf visual}$ dog classifier by ${\bf read}$ing about dogs and ${\bf listen}$ing to them bark. To do so, we exploit the fact that recent multimodal foundation models such as CLIP are inherently cross-modal, mapping different modalities to the same representation space. Specifically, we propose a simple cross-modal adaptation approach that learns from few-shot examples spanning different modalities. By repurposing class names as additional one-shot training samples, we achieve SOTA results with an embarrassingly simple linear classifier for vision-language adaptation. Furthermore, we show that our approach can benefit existing methods such as prefix tuning, adapters, and classifier ensembling. Finally, to explore other modalities beyond vision and language, we construct the first (to our knowledge) audiovisual few-shot benchmark and use cross-modal training to improve the performance of both image and audio classification.Comment: CVPR 2023. Project website: https://linzhiqiu.github.io/papers/cross_modal

Boosting alternating decision trees modeling of disease trait information

We applied the alternating decision trees (ADTrees) method to the last 3 replicates from the Aipotu, Danacca, Karangar, and NYC populations in the Problem 2 simulated Genetic Analysis Workshop dataset. Using information from the 12 binary phenotypes and sex as input and Kofendrerd Personality Disorder disease status as the outcome of ADTrees-based classifiers, we obtained a new quantitative trait based on average prediction scores, which was then used for genome-wide quantitative trait linkage (QTL) analysis. ADTrees are machine learning methods that combine boosting and decision trees algorithms to generate smaller and easier-to-interpret classification rules. In this application, we compared four modeling strategies from the combinations of two boosting iterations (log or exponential loss functions) coupled with two choices of tree generation types (a full alternating decision tree or a classic boosting decision tree). These four different strategies were applied to the founders in each population to construct four classifiers, which were then applied to each study participant. To compute average prediction score for each subject with a specific trait profile, such a process was repeated with 10 runs of 10-fold cross validation, and standardized prediction scores obtained from the 10 runs were averaged and used in subsequent expectation-maximization Haseman-Elston QTL analyses (implemented in GENEHUNTER) with the approximate 900 SNPs in Hardy-Weinberg equilibrium provided for each population. Our QTL analyses on the basis of four models (a full alternating decision tree and a classic boosting decision tree paired with either log or exponential loss function) detected evidence for linkage (Z ≥ 1.96, p < 0.01) on chromosomes 1, 3, 5, and 9. Moreover, using average iteration and abundance scores for the 12 phenotypes and sex as their relevancy measurements, we found all relevant phenotypes for all four populations except phenotype b for the Karangar population, with suggested subgroup structure consistent with latent traits used in the model. In conclusion, our findings suggest that the ADTrees method may offer a more accurate representation of the disease status that allows for better detection of linkage evidence

What do they eat? A survey of eat-out habit of university students in Taiwan

[EN] Main purpose of this research is trying to understand food likeliness of Taiwan college students, and probe whether these food are healthy. Three survey steps are taken as: step 1, market survey for what kind of foods are selling around the campuses; step 2, questionnaire investigation for students food preference; step 3, analyzing whether these favorite foods are healthy or not. The result shows: major consideration for students food selection are “taste” and “price”; 63% of students are taking food or snacks late at night at least once a week. Top three most favorite foods are: Taiwanese fries (yan su ji), carbon grilled chicken and fried fish steaks. Quantities of these foods are small, prices are low, and easy access from roadside food stands. Problems of them are high calories, easy to accumulate free radical in human body, plus insanitary food processing environment. They are harmful to student health. We suggest Taiwan government take it seriouslyShih, K.; Wang, M.; Shih, H.; Lee, S.; Lin, T. (2020). What do they eat? A survey of eat-out habit of university students in Taiwan. Editorial Universitat Politècnica de València. 421-430. https://doi.org/10.4995/INN2019.2019.10562OCS42143

Decoration of graphene nanoribbons by 5d5d transition-metal elements

Graphene is a famous truly two-dimensional (2D) material, possessing a cone-like energy structure near the Fermi level and treated as a gapless semiconductor. Its unique properties trigger researchers to find applications of it. The gapless feature shrinks the development of graphene nanoelectronics. Making one-dimensional (1D) strips of graphene nanoribbons (GNRs) could be one of the promising routes to modulating the electronic and optical properties of graphene. The electronic and optical properties of GNRs are highly sensitive to the edge and width. The tunability in electronic and optical properties further implies the possibilities of GNR application. However, the dangling bonds at ribbon edges remain an open question in GNR systems. Various passivation at the ribbon edge might change the essential physical properties. In this work, $5d$ transition-metal elements are considered as the guest atoms at the edges. The geometric structure, energy bands, density of states, charge distribution, and optical transitions are discussed

Maintaining CD4/CD8 ratio and Th1-CTL subsets of chimeric antigen receptor (CAR)-T cells in serum-free culture conditions

Chimeric antigen receptor (CAR) T cells therapy is a promising strategy that significantly controlled the progress of cancer diseases. CAR-T cells could kill cancer cells through cellular immune response; therefore, CD8+ cytotoxic T cells are critical for CAR-T cell therapy. However, recent papers reported that CD4+ T helper cells were important for the response and maintenance of CAR-T cells in vivo. Here, we developed a serum-free CAR-T cell preparation process that maintained the T cell population and controlled the T cell subsets. The CD4+ and CD8+ T cell population in CAR-T cells were maintained at averagely 59.4 % and 34.6%, and the major T cell subsets were Th1 cells and cytotoxic T lymphocytes (CTLs), implying the potentially high cellular immune response. To verifying whether the prepared CAR-T cells were exhausted, the expression of several immune checkpoint markers was determined. Of interest, only less than 20% of CAR-T cells at endpoint were PD-1+ or CTLA4+, but more than 40% of CAR-T cells at the endpoint were TIM-3+, implying most CAR-T cells were not exhausted. These CAR-T cells produced more than 1 ng/mL of IFN-γ in the response to the antigen. Altogether, CAR-T cells could be prepared in our serum-free process in the controlling of T cell subsets, leading to potential high therapeutic potency. Please click Additional Files below to see the full abstract