Topological phase transition based on the attractive Hubbard model

We theoretically investigate the effect of an attractive on-site interaction on the two-band magnetic Dirac fermion model based on a square lattice system. When the attractive fermion interaction is taken into account by the mean-field approximation, a phase diagram is obtained. It is found that a quantum phase transition from a band insulator state to quantum anomalous Hall state occurs with increased attractive interaction. For an existing quantum anomalous Hall state, the attractive interaction enlarges its nontrivial band gap and makes the topological edge states more localized, which protects the transport of linear-dispersive edge states against finite-size and further disorder effects.Comment: 5 pages, 4 figure

ALUMINUMDODECATUNGSTOPHOSPHATE (Al0.9H0.3PW12O40) NANOTUBE AS A SOLID ACID CATALYST ONE-POT PRODUCTION OF BIODIESEL FROM WASTE COOKING OIL

Solid nanocatalyst aluminum dodecatungstophosphate (Al0.9H0.3PW12O40, abbreviated as AlPW) with nanotube structure was synthesized through a natural cellulose fiber template. The AlPW nanotubes, which are highly water-tolerant and acid-tolerant, can be described as green double acids, as they combine both Brønsted and Lewis acid sites. They have been applied as an efficient nanoheterogeneous catalyst for the preparation of biodiesel from waste cooking oil containing 26.89 wt% high free fatty acids (FFAs) and 1% moisture via esterification of FFAs and transesterification of triglycerides in one pot under mild conditions

Unraveling Trends in Schistosomiasis: Deep Learning insights into National Control Programs in China

OBJECTIVES: to achieve the ambitious goal of eliminating schistosome infections, the Chinese government has implemented diverse control strategies. This study explored the progress of the 2 most recent national schistosomiasis control programs in an endemic area along the Yangtze River in China. METHODS: We obtained village-level parasitological data from cross-sectional surveys combined with environmental data in Anhui Province, China from 1997 to 2015. A convolutional neural network (CNN) based on a hierarchical integro-difference equation (IDE) framework (i.e., CNN-IDE) was used to model spatio-temporal variations in schistosomiasis. Two traditional models were also constructed for comparison with 2 evaluation indicators: the mean-squared prediction error (MSPE) and continuous ranked probability score (CRPS). RESULTS: The CNN-IDE model was the optimal model, with the lowest overall average MSPE of 0.04 and the CRPS of 0.19. From 1997 to 2011, the prevalence exhibited a notable trend: it increased steadily until peaking at 1.6 per 1000 in 2005, then gradually declined, stabilizing at a lower rate of approximately 0.6 per 1000 in 2006, and approaching zero by 2011. During this period, noticeable geographic disparities in schistosomiasis prevalence were observed; high-risk areas were initially dispersed, followed by contraction. Predictions for the period 2012 to 2015 demonstrated a consistent and uniform decrease. CONCLUSION: The proposed CNN-IDE model captured the intricate and evolving dynamics of schistosomiasis prevalence, offering a promising alternative for future risk modeling of the disease. The comprehensive strategy is expected to help diminish schistosomiasis infection, emphasizing the necessity to continue implementing this strategy

Hybrid Biodegradable Nanomotors through Compartmentalized Synthesis

Designer particles that are embued with nanomachinery for autonomous motion have great potential for biomedical applications; however, their development is highly demanding with respect to biodegradability/compatibility. Previously, biodegradable propulsive machinery based on enzymes has been presented. However, enzymes are highly susceptible to proteolysis and deactivation in biological milieu. Biodegradable hybrid nanomotors powered by catalytic inorganic nanoparticles provide a proteolytically stable alternative to those based upon enzymes. Herein we describe the assembly of hybrid biodegradable nanomotors capable of transducing chemical energy into motion. Such nanomotors are constructed through a process of compartmentalized synthesis of inorganic MnO2 nanoparticles (MnPs) within the cavity of organic stomatocytes. We show that the nanomotors remain active in cellular environments and do not compromise cell viability. Effective tumor penetration of hybrid nanomotors is also demonstrated in proof-of-principle experiments. Overall, this work represents a new prospect for engineering of nanomotors that can retain their functionality within biological contexts

Molecular Programming of Biodegradable Nanoworms via Ionically Induced Morphology Switch toward Asymmetric Therapeutic Carriers

Engineering biodegradable nanostructures with precise morphological characteristics is a key objective in nanomedicine. In particular, asymmetric (i.e., nonspherical) nanoparticles are desirable due to the advantageous effects of shape in a biomedical context. Using molecular engineering, it is possible to program unique morphological features into the self-assembly of block copolymers (BCPs). However, the criteria of biocompatibility and scalability limit progress due to the prevalence of nondegradable components and the use of toxic solvents during fabrication. To address this shortfall, a robust strategy for the fabrication of morphologically asymmetric nanoworms, comprising biodegradable BCPs, has been developed. Modular BCPs comprising poly (ethylene glycol)-block-poly(caprolactone-gradient-trimethylene carbonate) (PEG−PCLgTMC), with a terminal chain of quaternary ammonium-TMC (PTMC-Q), undergo self-assembly via direct hydration into well-defined nanostructures. By controlling the solution ionic strength during hydration, particle morphology switches from spherical micelles to nanoworms (of varying aspect ratio). This ionically-induced switch is driven by modulation of chain packing with salts screening interchain repulsions, leading to micelle elongation. Nanoworms can be loaded with cytotoxic cargo (e.g., doxorubicin) at high efficiency, preferentially interact with cancer cells, and increase tumor penetration. This work showcases the ability to program assembly of BCPs and the potential of asymmetric nanosystems in anticancer drug delivery

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

A Ship Driving Teaching System Based on Multi-level Virtual Reality Technology

The present ship driving teaching system cannot ensure that all seafarers or students have enough time to go into training for basic skills, and it is not practical or feasible in all cases. We construct a consistent VR marine training environment to enhance maritime education and training at all levels. The basic equation of key algorithm involving the multilevel virtual reality ship driving teaching system is presented in this paper. The system is equipped with V.Dragon 2000. The application results show that the system can project visual system with wide field of view, and instructor control station etc. The training environment provides a strong visual reinforcement and a strong sense of immersion

Floquet Weyl nodes in Weyl semimetal via a one-photon resonance

Topological phase transition under the influence of periodic driving is regarded as one of the major topics in materials science. For most materials, we usually expect a full dynamical gap opened at the resonance energy $(\varepsilon_c - \varepsilon_v = \hbar\omega)$ , which can convert a topologically trivial state into a Floquet topological insulator state. However, according to both analytical and numerical calculations, we find that new Weyl nodes emerge on the resonance sphere when a Weyl semimetal is irradiated by any kind of continuous driving. These nodes are called Floquet Weyl nodes due to linear dispersion around them. In general cases, we can find four Floquet Weyl nodes, which have the same chiralities with the equilibrium Weyl node