Information scrambling and entanglement in quantum approximate optimization algorithm circuits

Variational quantum algorithms, which consist of optimal parameterized quantum circuits, are promising for demonstrating quantum advantages in the noisy intermediate-scale quantum (NISQ) era. Apart from classical computational resources, different kinds of quantum resources have their contributions in the process of computing, such as information scrambling and entanglement. Characterizing the relation between complexity of specific problems and quantum resources consumed by solving these problems is helpful for us to understand the structure of VQAs in the context of quantum information processing. In this work, we focus on the quantum approximate optimization algorithm (QAOA), which aims to solve combinatorial optimization problems. We study information scrambling and entanglement in QAOA circuits respectively, and discover that for a harder problem, more quantum resource is required for the QAOA circuit to obtain the solution. We note that in the future, our results can be used to benchmark complexity of quantum many-body problems by information scrambling or entanglement accumulation in the computing process.Comment: 11 pages, 9 figures, Some minor correction

Effects of Palatable Food Versus Thin Figure Conflicts on Responses of Young Dieting Women

Many young women use dieting to achieve a thinner figure yet most tend to fail as a result of heightened responsiveness to palatable food environments and increases in hedonic cravings. In this preliminary study, we developed a novel palatable food vs. thin figure conflict task to assess conflicting motives associated with eating among young women. Forty young dieting women [mean body mass index (BMI) = 22.98 kg/m2, SD = 3.81] completed a food vs. figure conflict task within a 2 (distractor image: food vs. figure) × 2 (word-image congruence: congruent vs. incongruent) within-subjects design. Results supported the view that this new task could effectively capture conflict costs. Dieting young women displayed stronger food conflicts than figure conflicts based on having longer response delays and higher error rates in the food conflict condition than the figure conflict condition. Although young women often proclaimed “dieting” to achieve or maintain a good figure, dieters appeared to exhibit stronger preferences for palatable food cues relative to thin figure cues. These results provide important information for understanding automatic processing biases toward palatable foods and underscore the need for research extensions in other cultural contexts to determine whether such biases are universal in nature

Effect of an in-situ thermal annealing on the structural properties of self-assembled GaSb/GaAs quantum dots

In this work, the effect of the application of a thermal annealing on the structural properties of GaSb/GaAs quantum dots (QDs)1 is analyzed by aberration corrected high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM)2 and electron energy loss spectroscopy (EELS)3 Our results show that the GaSb/GaAs QDs are more elongated after the annealing, and that the interfaces are less abrupt due to the Sb diffusion. We have also found a strong reduction in the misfit dislocation density with the annealing. The analysis by EELS of a threading dislocation has shown that the dislocation core is rich in Sb. In addition, the region of the GaAs substrate delimited by the threading dislocation is shown to be Sb-rich as well. An enhanced diffusion of Sb due to a mechanism assisted by the dislocation movement is discussed

Identification and validation of a novel cuproptosis-related gene signature in multiple myeloma

Background: Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown.Method: In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MM cell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR).Results: The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group (p < 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR in vitro.Conclusion: CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients

A novel glycolysis-related gene signature for predicting the prognosis of multiple myeloma

Background: Metabolic reprogramming is an important hallmark of cancer. Glycolysis provides the conditions on which multiple myeloma (MM) thrives. Due to MM’s great heterogeneity and incurability, risk assessment and treatment choices are still difficult.Method: We constructed a glycolysis-related prognostic model by Least absolute shrinkage and selection operator (LASSO) Cox regression analysis. It was validated in two independent external cohorts, cell lines, and our clinical specimens. The model was also explored for its biological properties, immune microenvironment, and therapeutic response including immunotherapy. Finally, multiple metrics were combined to construct a nomogram to assist in personalized prediction of survival outcomes.Results: A wide range of variants and heterogeneous expression profiles of glycolysis-related genes were observed in MM. The prognostic model behaved well in differentiating between populations with various prognoses and proved to be an independent prognostic factor. This prognostic signature closely coordinated with multiple malignant features such as high-risk clinical features, immune dysfunction, stem cell-like features, cancer-related pathways, which was associated with the survival outcomes of MM. In terms of treatment, the high-risk group showed resistance to conventional drugs such as bortezomib, doxorubicin and immunotherapy. The joint scores generated by the nomogram showed higher clinical benefit than other clinical indicators. The in vitro experiments with cell lines and clinical subjects further provided convincing evidence for our study.Conclusion: We developed and validated the utility of the MM glycolysis-related prognostic model, which provides a new direction for prognosis assessment, treatment options for MM patients

Applications of Nanomaterials in Electrogenerated Chemiluminescence Biosensors

Electrogenerated chemiluminescence (also called electrochemiluminescence and abbreviated ECL) involves the generation of species at electrode surfaces that then undergo electron-transfer reactions to form excited states that emit light. ECL biosensor, combining advantages offered by the selectivity of the biological recognition elements and the sensitivity of ECL technique, is a powerful device for ultrasensitive biomolecule detection and quantification. Nanomaterials are of considerable interest in the biosensor field owing to their unique physical and chemical properties, which have led to novel biosensors that have exhibited high sensitivity and stability. Nanomaterials including nanoparticles and nanotubes, prepared from metals, semiconductor, carbon or polymeric species, have been widely investigated for their ability to enhance the efficiencies of ECL biosensors, such as taking as modification electrode materials, or as carrier of ECL labels and ECL-emitting species. Particularly useful application of nanomaterials in ECL biosensors with emphasis on the years 2004-2008 is reviewed. Remarks on application of nanomaterials in ECL biosensors are also surveyed

Measurements of J/psi Decays into 2(pi+pi-)eta and 3(pi+pi-)eta

Based on a sample of 5.8X 10^7 J/psi events taken with the BESII detector, the branching fractions of J/psi--> 2(pi+pi-)eta and J/psi-->3(pi+pi-)eta are measured for the first time to be (2.26+-0.08+-0.27)X10^{-3} and (7.24+-0.96+-1.11)X10^{-4}, respectively.Comment: 11 pages, 6 figure