Beyond Fermi pseudopotential: a modified GP equation

We present an effective potential and the corresponding modified Gross-Pitaevskii equation that account for the energy dependence of the two-body scattering amplitude through an effective-range expansion. For the ground state energy of a trapped condensate, the theory leads to what we call a shape-dependent confinement correction that improves agreements with diffusion Monte Carlo calculations. The theory illustrates, for relatively strong confinement and/or high density, how the shape dependence on atom-atom interaction can come into play in a many-atom quantum system.Comment: 8 pages, 5 figure

In vitro isolation of class-specific oligonucleotide-based small-molecule receptors

Class-specific bioreceptors are highly desirable for recognizing structurally similar small molecules, but the generation of such affinity elements has proven challenging. We here develop a novel ‘parallel-and-serial’ selection strategy for isolating class-specific oligonucleotide-based receptors (aptamers) in vitro. This strategy first entails parallel selection to selectively enrich cross-reactive binding sequences, followed by serial selection that enriches aptamers binding to a designated target family. As a demonstration, we isolate a class-specific DNA aptamer against a family of designer drugs known as synthetic cathinones. The aptamer binds to 12 diverse synthetic cathinones with nanomolar affinity and does not respond to 11 structurally similar non-target compounds, some of which differ from the cathinone targets by a single atom. This is the first account of an aptamer exhibiting a combination of broad target cross-reactivity, high affinity and remarkable specificity. Leveraging the qualities of this aptamer, instantaneous colorimetric detection of synthetic cathinones at nanomolar concentrations in biological samples is achieved. Our findings significantly expand the binding capabilities of aptamers as class-specific bioreceptors and further demonstrate the power of rationally designed selection strategies for isolating customized aptamers with desired binding profiles. We believe that our aptamer isolation approach can be broadly applied to isolate class-specific aptamers for various small molecule families

Scenario Analysis of Natural Gas Consumption in China Based on Wavelet Neural Network Optimized by Particle Swarm Optimization Algorithm

Natural gas consumption has increased with an average annual growth rate of about 10% between 2012 and 2017. Total natural gas consumption accounted for 6.4% of consumed primary energy resources in 2016, up from 5.4% in 2012, making China the world’s third-largest gas user. Therefore, accurately predicting natural gas consumption has become very important for market participants to organize indigenous production, foreign supply contracts and infrastructures in a better way. This paper first presents the main factors affecting China’s natural gas consumption, and then proposes a hybrid forecasting model by combining the particle swarm optimization algorithm and wavelet neural network (PSO-WNN). In PSO-WNN model, the initial weights and wavelet parameters are optimized using PSO algorithm and updated through a dynamic learning rate to improve the training speed, forecasting precision and reduce fluctuation of WNN. The experimental results show the superiority of the proposed model compared with ANN and WNN based models. Then, this study conducts the scenario analysis of the natural gas consumption from 2017 to 2025 in China based on three scenarios, namely low scenario, reference scenario and high scenario, and the results illustrate that the China’s natural gas consumption is going to be 342.70, 358.27, 366.42 million tce (“standard” tons coal equivalent) in 2020, and 407.01, 437.95, 461.38 million tce in 2025 under the low, reference and high scenarios, respectively. Finally, this paper provides some policy suggestions on natural gas exploration and development, infrastructure construction and technical innovations to promote a sustainable development of China’s natural gas industry

Bi-Level Planning Model of Charging Stations Considering the Coupling Relationship between Charging Stations and Travel Route

The major factors affecting the popularization of electric vehicles (EV) are the limited travel range and the lack of charging infrastructure. Therefore, to further promote the penetration of EVs, it is of great importance to plan and construct more fast charging stations rationally. In this study, first we establish a travel pattern model based on the Monte Carlo simulation (MCS). Then, with the traveling data of EVs, we build a bi-level planning model of charging stations. For the upper model, with an aim to maximize the travel success ratio, we consider the influence of the placement of charging stations on the user’s travel route. We adopt a hybrid method based on queuing theory and the greedy algorithm to determine the capacity of charging stations, and we utilize the total social cost and satisfaction index as two indicators to evaluate the optimal solutions obtained from the upper model. Additionally, the impact of the increase of EV ownership and slow charger coverage in the public parking lot on the fast charging demands and travel pattern of EV users are also studied. The example verifies the feasibility of the proposed method

No Structure-Switching Required: A Generalizable Exonuclease-Mediated Aptamer-Based Assay for Small-Molecule Detection

The binding of small molecules to double-stranded DNA can modulate its susceptibility to digestion by exonucleases. Here, we show that the digestion of aptamers by exonuclease III can likewise be inhibited upon binding of small-molecule targets and exploit this finding for the first time to achieve sensitive, label-free small-molecule detection. This approach does not require any sequence engineering and employs prefolded aptamers which have higher target-binding affinities than structure-switching aptamers widely used in current small-molecule detecting assays. We first use a dehydroisoandrosterone-3-sulfate-binding aptamer to show that target binding halts exonuclease III digestion four bases prior to the binding site. This leaves behind a double-stranded product that retains strong target affinity, whereas digestion of nontarget-bound aptamer produces a single-stranded product incapable of target binding. Exonuclease I efficiently eliminates these single-stranded products but is unable to digest the target-bound double-stranded product. The remaining products can be fluorescently quantified with SYBR Gold to determine target concentrations. We demonstrate that this dual-exonuclease-mediated approach can be broadly applied to other aptamers with differing secondary structures to achieve sensitive detection of various targets, even in biological matrices. Importantly, each aptamer digestion product has a unique sequence, enabling the creation of multiplex assays, and we successfully demonstrate simultaneous detection of cocaine and ATP in a single microliter volume sample in 25 min via sequence-specific molecular beacons. Due to the generality and simplicity of this assay, we believe that different DNA signal-reporting or amplification strategies can be adopted into our assay for target detection in diverse analytical contexts