Quantized squeezing and even-odd asymmetry of trapped bosons

We investigate the exact nature of the superfluid-to-Mott-insulator crossover for interacting bosons on an optical lattice in a one-dimensional, harmonic trap by high-precision density-matrix renormalization-group calculations. The results reveal an intermediate regime characterized by a cascade of microscopic steps. These arise as a consequence of individual boson "squeezing" events and display an even-odd alternation dependent on the trap symmetry. We discuss the experimental observation of this behavior, which is generic in an external trapping potential.Comment: 4.05 pages, 4 figures. Presents significantly more, and more systematic, calculations and explanations than cond-mat/070169

The impact of implicit theories on resilience among Chinese nurses: The chain mediating effect of grit and meaning in life

Implicit theories refer to assumptions people hold about different domains, also known as mindsets. There are two implicit theories on the malleability of one’s ability: entity theory and incremental theory. They constrain and regulate people’s understanding and responses to an individual’s behavior, leading to different social cognitive patterns and behavioral responses. Resilience is a positive adaptation in highly stressful situations that represents mechanisms for coping with and transcending difficult experiences, i.e., a person’s ability to successfully adapt to change, resist the adverse effects of stressors, avoid significant dysfunction, and be chronically affected by considered a protective factor for mental health. Although previous studies showed that individuals’ implicit theories are associated with resilience, this relationship has received little attention in the nursing population. It is unclear which variables may contribute to explaining the relationship between implicit theories and resilience. Therefore, the current study aims to deeply explore the relationship between implicit theories and the resilience of Chinese nurses. In addition, we also seek to demonstrate the chain mediating effects of grit and meaning in life on this relationship. We surveyed 709 Chinese nurses through online questionnaires using the self-made demographic questionnaire, the Implicit Theories Scale, the Short Grit Scale, the Meaning in Life Questionnaire, and the 10-item Connor-Davidson Resilience Scale. After controlling for demographic variables such as age, gender, educational background, marital status, professional title, and working years, the results reveal positive associations between Chinese nurses’ implicit theories and their resilience, and grit and meaning in life play a partial mediating role in this relationship, respectively. Furthermore, grit and meaning in life play a chain mediating role between implicit theories and resilience. These findings contribute to understanding the psychological impact mechanism of implicit theories on nurses’ resilience and provide a theoretical basis for nursing managers to formulate strategies to improve nurses’ psychological resilience

Location Design of Electrification Road in Transportation Networks for On-Way Charging

Electric vehicles tend to be a great mobility option for the potential benefits in energy consumption and emission reduction. On-way charging (OWC) has been recognized to be a promising solution to extend driving range for electric vehicles. Location of the electrification road (ER) is a critical issue for future urban traffic management to accommodate the new mobility option. This paper proposes a mathematical program with equilibrium constraint (MPEC) approach to solve this problem, which minimizes the total travel time with a limited construction budget. To describe the drivers’ routing choice, a path-constrained network equilibrium model is proposed to minimize their travel time and prevent running out of charge. We develop a modified active set algorithm to solve the MPEC model. Numerical experiments are presented to demonstrate the performance of the model and the solution algorithm and analyze the impact of charging efficiency, battery size, and comfortable range

GPR Data Augmentation Methods by Incorporating Domain Knowledge

Deep learning has significantly improved the recognition efficiency and accuracy of ground-penetrating radar (GPR) images. A significant number of weight parameters need to be specified, which requires lots of labeled GPR images. However, obtaining the ground-truth subsurface distress labels is challenging as they are invisible. Data augmentation is a predominant method to expand the dataset. The traditional data augmentation methods, such as rotating, scaling, cropping, and flipping, would change the GPR signals’ real features and cause the model’s poor generalization ability. We proposed three GPR data augmentation methods (gain compensation, station spacing, and radar signal mapping) to overcome these challenges by incorporating domain knowledge. Then, the most state-of-the-art model YOLOv7 was applied to verify the effectiveness of these data augmentation methods. The results showed that the proposed data augmentation methods decrease loss function values when the training epochs grow. The performance of the deep learning model gradually became stable when the original datasets were augmented two times, four times, and eight times, proving that the augmented datasets can increase the robustness of the training model. The proposed data augmentation methods can be used to expand the datasets when the labeled training GPR images are insufficient

A New Framework for DDoS Attack Detection and Defense in SDN Environment

While software defined network (SDN) brings more innovation to the development of future networks, it also faces a more severe threat from DDoS attacks. In order to deal with the single point of failure on SDN controller caused by DDoS attacks, we propose a framework for detection and defense of DDoS attacks in the SDN environment. Firstly, we deploy a trigger mechanism of DDoS attack detection on data plane to screen for abnormal flows in the network. Then, we use a combined machine learning algorithm based on K-Means and KNN to exploit the rate characteristics and asymmetry characteristics of the flows and to detect the suspicious flows determined by the detection trigger mechanism. Finally, the controller will take corresponding actions to defense against the attacks. In this paper, we propose a new framework of cooperative detection methods of control plane and data plane, which effectively improve the detection accuracy and efficiency, and prevent DDoS attacks on SDN

Novel TRAPPC11 Mutations in a Chinese Pedigree of Limb Girdle Muscular Dystrophy

Limb girdle muscular dystrophies (LGMDs) are a heterogeneous group of genetic myopathies leading primarily to proximal muscle weakness. It is caused by mutations at over 50 known genetic loci typically from mutations in genes encoding constituents of the sarcolemmal dystrophin complex or related functions. Herein we describe the case of two siblings with LGMD that were investigated using whole-exome sequencing followed by Sanger sequencing validation of a specific double-mutation in the TRAPPC11 gene. Further, from parental sequencing we determined the mode of transmission, a double heterozygous mutation at the maternal and paternal alleles. The two mutations detected have not been described in other patients

Relationship between Earthquake-Induced Hydrologic Changes and Faults

Hydraulic properties of fault zones are important to understanding the pore pressure development and fault stability. In this work, we examined the relationship between water level changes caused by the 2008 Wenchuan Mw 7.9 earthquake and faults using four wells with the same lithology around the Three Gorges Dam, China. Two of the wells penetrating the fault damage zones recorded sustained water level changes, while the other two wells that are not penetrating any fault damage zones recorded transient water level changes. The phase shift and tidal factor calculated from water level, a proxy of permeability and storage coefficient, revealed that both the permeability and storage coefficient changed in the two wells penetrating the fault damage zones, while the other two wells not penetrating the fault damage zone did not show any change in permeability and storage coefficient. Thus, we tentatively suggest that faults may play an important controlling role on earthquake-induced hydrologic changes because the detrital or clogging components in the fractures may be more easily removed by seismic waves

Stress-Induced Apparent Resistivity Variations at the Kalpin Observatory and the Correlation with the 2020 Mw 6.0 Jiashi Earthquake

Stress may induce apparent resistivity changes. Clarifying the deformation process of the source media is critical for determining the correlations between resistivity variations and earthquake occurrence. In this study, the stress state of a medium was analyzed by integrating GPS measurements, the spatiotemporal evolution of the load/unload response ratio (LURR), geochemical monitoring, and synchronous apparent resistivity changes preceding the 2020 Mw 6.0 Jiashi earthquake. The medium hosting the Kalpin Observatory underwent elastic deformation before 2019, and the synchronous decreases in the E–W and N–S apparent resistivities from 2015 can be attributed to N–S-dominated compressive stress. The microdamage stage occurred in 2019, with subsequent E–W apparent resistivity variation amplitudes that were ~0.4 Ωm higher than those in previous years. This difference is a result of microdamage to the medium owing to tensile stress during the seismogenic process. The spatiotemporal evolution of the LURR and gas seepage monitoring data also indicate that the medium was damaged prior to the earthquake. Variations in the apparent resistivity measured at the Kalpin Observatory indicate that the medium underwent elastic deformation, followed by microdamage, until stress triggered the earthquake