Copper-based photocatalysts with natural organic ligands for efficient removal of tetracycline under visible light.

The excessive use of broad-spectrum antibiotics, such as tetracycline, presents a significant challenge to human survival and development. Oxygen vacancies (OVs) metal-organic framework (MOF) materials were synthesized using natural organic acids (L-malic acid, L-aspartic acid, and L-asparagine) with similar structures but different charge densities, along with copper as the metal linking agent. The presence of oxygen vacancies in the catalyst provides abundant active sites for photocatalytic reactions.

Prediction and validation of enzymatic degradation of aflatoxin M: Genomics and proteomics analysis of Bacillus pumilus E-1-1-1 enzymes.

Aflatoxins are a class of highly toxic mycotoxins. Aflatoxin M (AFM) is hydroxylated metabolite of aflatoxin B, having comparable toxicity, which is more commonly found in milk. In this study, the whole genome sequencing of Bacillus pumilus E-1-1-1 isolated from feces of 38 kinds of animals, having aflatoxin M degradation ability was conducted.

Flight Delay Regression Prediction Model Based on Att-Conv-LSTM.

Accurate prediction results can provide an excellent reference value for the prevention of large-scale flight delays. Most of the currently available regression prediction algorithms use a single time series network to extract features, with less consideration of the spatial dimensional information contained in the data. Aiming at the above problem, a flight delay prediction method based on Att-Conv-LSTM is proposed.

Evaporable Glass-State Molecule-Assisted Transfer of Clean and Intact Graphene onto Arbitrary Substrates.

Graphene and its clean transfer methods have gathered growing interest and concern in recent decades. Here, we develop a novel large-scale intact transferring technology of paraffin wax onto arbitrary substrates. The wax will then be removed by thermal evaporation, avoiding uncontrollable reactions and leaving no residues.

Erratum: 3D Printing Fiber Electrodes for an All-Fiber Integrated Electronic Device via Hybridization of an Asymmetric Supercapacitor and a Temperature Sensor.

[This corrects the article DOI: 10.1002/advs.201801114.

3D Printing Fiber Electrodes for an All-Fiber Integrated Electronic Device via Hybridization of an Asymmetric Supercapacitor and a Temperature Sensor.

Wearable fiber-shaped electronic devices have drawn abundant attention in scientific research fields, and tremendous efforts are dedicated to the development of various fiber-shaped devices that possess sufficient flexibility. However, most studies suffer from persistent limitations in fabrication cost, efficiency, the preparation procedure, and scalability that impede their practical application in flexible and wearable fields. In this study, a simple, low-cost 3D printing method capable of high manufacturing efficiency, scalability, and complexity capability to fabricate a fiber-shaped integrated device that combines printed fiber-shaped temperature sensors (FTSs) with printed fiber-shaped asymmetric supercapacitors (FASCs) is developed.

Different graphene layers to enhance or prevent corrosion of polycrystalline copper.

Graphene was used as an anticorrosive coating for metals as it can effectively isolate the corrosion factors such as oxygen. However, we found that the anticorrosive and corrosive effects on metal surface were related to graphene layers and metal crystal faces. In this paper, we found that different layers of graphene had significantly different effects on the corrosion of polycrystalline copper during long-term storage under atmospheric conditions.

Collective behavior of large-scale neural networks with GPU acceleration.

In this paper, the collective behaviors of a small-world neuronal network motivated by the anatomy of a mammalian cortex based on both Izhikevich model and Rulkov model are studied. The Izhikevich model can not only reproduce the rich behaviors of biological neurons but also has only two equations and one nonlinear term. Rulkov model is in the form of difference equations that generate a sequence of membrane potential samples in discrete moments of time to improve computational efficiency.

Effect of different glucose supply conditions on neuronal energy metabolism.

The glucose-excited neurons in brain can sense blood glucose levels and reflect different firing states, which are mainly associated with regulation of blood glucose and energy demand in the brain. In this paper, a new model of glucose-excited neuron in hypothalamus is proposed. The firing properties and energy consumption of this type of neuron under conditions of different glucose levels are simulated and analyzed.

Locating and navigation mechanism based on place-cell and grid-cell models.

Extensive experiments on rats have shown that environmental cues play an important role in goal locating and navigation. Major studies about locating and navigation are carried out based only on place cells. Nevertheless, it is known that navigation may also rely on grid cells.

Oscillations and synchrony in a cortical neural network.

In this paper, the oscillations and synchronization status of two different network connectivity patterns based on Izhikevich model are studied. One of the connectivity patterns is a randomly connected neuronal network, the other one is a small-world neuronal network. This Izhikevich model is a simple model which can not only reproduce the rich behaviors of biological neurons but also has only two equations and one nonlinear term.

Firing pattern and synchronization property analysis in a network model of the olfactory bulb.

In the olfactory system, both the temporal spike structure and spatial distribution of neuronal activity are important for processing odor information. In this paper, a biophysically-detailed, spiking neuronal model is used to simulate the activity of olfactory bulb. It is shown that by varying some key parameters such as maximal conductances of Ks and Nap the spike train of single neuron can exhibit various firing patterns.

Synchronization study in ring-like and grid-like neuronal networks.

In this paper, we study the synchronization status of both two gap-junction coupled neurons and neuronal network with two different network connectivity patterns. One of the network connectivity patterns is a ring-like neuronal network, which only considers nearest-neighbor neurons. The other is a grid-like neuronal network, with all nearest neighbor couplings.

Phase synchronization motion and neural coding in dynamic transmission of neural information.

In order to explore the dynamic characteristics of neural coding in the transmission of neural information in the brain, a model of neural network consisting of three neuronal populations is proposed in this paper using the theory of stochastic phase dynamics. Based on the model established, the neural phase synchronization motion and neural coding under spontaneous activity and stimulation are examined, for the case of varying network structure. Our analysis shows that, under the condition of spontaneous activity, the characteristics of phase neural coding are unrelated to the number of neurons participated in neural firing within the neuronal populations.