RNAGCN: RNA tertiary structure assessment with a graph convolutional network

RNAs play crucial and versatile roles in cellular biochemical reactions. Since experimental approaches of determining their three-dimensional (3D) structures are costly and less efficient, it is greatly advantageous to develop computational methods to predict RNA 3D structures. For these methods, designing a model or scoring function for structure quality assessment is an essential step but this step poses challenges. In this study, we designed and trained a deep learning model to tackle this problem. The model was based on a graph convolutional network (GCN) and named RNAGCN. The model provided a natural way of representing RNA structures, avoided complex algorithms to preserve atomic rotational equivalence, and was capable of extracting features automatically out of structural patterns. Testing results on two datasets convincingly demonstrated that RNAGCN performs similarly to or better than four leading scoring functions. Our approach provides an alternative way of RNA tertiary structure assessment and may facilitate RNA structure predictions. RNAGCN can be downloaded from https://gitee.com/dcw-RNAGCN/rnagcn.     

Highly sensitive perylene tetra-(alkoxycarbonyl) based colorimetric and ratiometric probes for fluorine detection

Fluoride anion (F^?) affects environmental, biological, and chemical processes significantly. Therefore, its detection has received increasing attention, and sensitive, effective, and convenient probes for F^? detection need to be developed urgently. In this work, two perylene tetra-(alkoxycarbonyl) (PTAC) based colorimetric and ratiometric probes, P1 and P2, were developed for the detection of F^?. The interactions between F^? and these two probes were investigated by absorption, electrochemistry, ¹H NMR, and density functional methods. Both the two probes were complexed with F^? with a ratio of 1:1. The detection limits of P1 and P2 were 0.22 μM and 0.87 μM, respectively. It was worth noting that the absorption peak of P1 showed a 190 nm red shift when sensing F^?, and P1 is the largest red shift value reported in F^? probes based on PTAC derivatives. This phenomenon was resulted from the unique configuration and deprotonation of P1 that can promote the intramolecular charge transfer (ICT). This strategy provides an example for the development of other ion probes based on D-A type ICT mechanism.     

A facile approach to fabricate and embed multifunctional nano ZnO into soap matrix and liquid cleansing products for enhanced antibacterial and photostability for health and hygiene applications

This research demonstrates, a facile approach to fabricate the nano ZnO system in an unique combination of surfactant-polyol-assembly (SPA) acting as a caging agent restricting the ZnO crystallite size in nano-regime. This SPA is suitable for health and hygiene products and such optimized technique is among the very few researches exploring the impact of embedding low concentrations of nano ZnO system into the matrix of sodium salt of long chain fatty acids (soap bar) and liquid cleansing personal care products. The fabricated nano ZnO in SPA and infused products were systematically characterized using various advanced and appropriate techniques. The hexagonal wurtzite structure of nano ZnO-SPA is evaluated based on XRD pattern which also exhibit an average crystallite size as 20.18 nm and high specific surface area as 52.99 m²/g. The SEM-supported morphological assessment confirms the formation of agglomerates of ultrafine ZnO rods and spherical particles. Novel nano ZnO having wideband gap energy (3.66 eV) embedded in soap bar act as a UV-blocker preventing the oxidation of unsaturated long chain fatty acids. Soap bar without ZnO experienced degradation and reduction in whiteness to 17.85% whereas 2.5 mg/g nano ZnO infused soap shows the reduction to 7.9% which clearly reflects the increased photostability of soap bar. The antibacterial efficacy of nano ZnO-SPA and infused products are investigated against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) by Zone of Inhibition (ZOI) and European standard EN:1276. Infused products exhibited high antibacterial efficacy up to 4.43 log reduction equivalent to >99.99% germ kill.     

Hyperparameter on-line learning of stochastic resonance based threshold networks

Aiming at training the feed-forward threshold neural network consisting of nondifferentiable activation functions, the approach of noise injection forms a stochastic resonance based threshold network that can be optimized by various gradient-based optimizers. The introduction of injected noise extends the noise level into the parameter space of the designed threshold network, but leads to a highly non-convex optimization landscape of the loss function. Thus, the hyperparameter on-line learning procedure with respective to network weights and noise levels becomes of challenge. It is shown that the Adam optimizer, as an adaptive variant of stochastic gradient descent, manifests its superior learning ability in training the stochastic resonance based threshold network effectively. Experimental results demonstrate the significant improvement of performance of the designed threshold network trained by the Adam optimizer for function approximation and image classification.     

Pattern transition and regulation in a subthalamopallidal network under electromagnetic effect

Although the significant roles of magnetic induction and electromagnetic radiation in the neural system have been widely studied, their influence on Parkinson's disease (PD) has yet to be well explored. By virtue of the magnetic flux variable, this paper studies the transition of firing patterns induced by magnetic induction and the regulation effect of external magnetic radiation on the firing activities of the subthalamopallidal network in basal ganglia. We find: (i) The network reproduces five typical waveforms corresponding to the severity of symptoms: weak cluster, episodic, continuous cluster, episodic, and continuous wave. (ii) Magnetic induction is a double-edged sword for the treatment of PD. Although the increase of magnetic coefficient may lead the physiological firing activity to transfer to pathological firing activity, it also can regulate the pathological intensity firing activity with excessive β-band power transferring to the physiological firing pattern with weak β-band power. (iii) External magnetic radiation could inhibit continuous tremulous firing and β-band power of subthalamic nucleus (STN), which means the severity of symptoms weakened. Especially, the bi-parameter plane of the regulation region shows that a short pulse period of magnetic radiation and a medium level of pulse percentage can well regulate pathological oscillation. This work helps to understand the firing activity of the subthalamopallidal network under electromagnetic effect. It may also provide insights into the mechanisms behind the electromagnetic therapy of PD-related firing activity.     

Research progress of Pt and Pt-based cathode electrocatalysts for proton-exchange membrane fuel cells

Proton-exchange membrane fuel cells (PEMFCs) have been widely used commercially to solve the energy crisis and environmental pollution. The oxygen reduction reaction (ORR) at the cathode is the rate-determining step in PEMFCs. Platinum (Pt) catalysts are used to accelerate the ORR kinetics. Pt's scarcity, high cost, and instability in an acidic environment at high potentials seriously hinder the commercialization of PEMFCs. Therefore, studies should explore electrocatalysts with high catalytic activity, enhanced stability, and low-Pt loading. This review briefly introduces the research progress on Pt and Pt-based ORR electrocatalysts for PEMFCs, including anticorrosion catalyst supports, Pt, and Pt-based alloy electrocatalysts. Advanced preparation technology and material characterization of Pt-based ORR electrocatalysts are necessary to improve the performance and corresponding reaction mechanisms.     

Existence of multi-bump solutions for a system with critical exponent in RN

We consider the following system with critical exponent in ${\mathbb{R}}^N$:$\{\begin{array}{c}?\mathrm{\Delta }u=K_1(y)u^{2^{?}?1}+\frac{p}{2^{?}}V(y)u^{p?1}{v}^q\text{in}{\mathbb{R}}^N,\hfill \\ ?\mathrm{\Delta }v=K_2(y)v^{2^{?}?1}+\frac{q}{2^{?}}V(y)u^p{v}^{q?1}\text{in}{\mathbb{R}}^N,\hfill \\ u,v>0,y\in {\mathbb{R}}^N,\hfill \end{array}$ where $N\ge 5$, $p,q>1$ and $p+q=2^{?}=\frac{2N}{N?2}$. Using finite dimensional reduction method, we prove the existence of multi-bump solutions. Their bumps can be placed on arbitrarily many or even infinitely many lattice points in ${\mathbb{R}}^N$. Since $p<2$ or $q<2$, we introduce two new norms to avoid singularity.     

Electrochemical detection of nitrate,nitrite and ammonium for on-site water quality monitoring

This review examines the most recent electrochemical developments for nitrate, nitrite and ammonium detection for on-site water monitoring. There remains a high demand for effective field-based detection of the dissolved inorganic nitrogen (DIN) analytes to aid in mitigating nitrogen loading. Electrochemical approaches show increasing potential to fill this role as advancements in nanotechnology continually improve analytical performance and on-site applicability. However, translating these improvements into the field still faces the resonating challenges of reaching analytical proficiency (selectivity, sensitivity, robustness, stability), practical end-user functionality, minimal matrix interferences and cost effectiveness. Herein, we elaborate on these challenges via a critical evaluation of current studies and examine how realistic the prospects of on-site nitrate, nitrite and ammonium are. We also present recommendations in addressing these gaps to conclude the review.     

基于视觉辐条图案识别方法的蓝宝石引晶机制研究

工业生产蓝宝石晶体过程中,引晶步骤有着至关重要的地位。引晶必须在温度梯度较小,温度分布趋于稳定的条件下进行。目前,工业生产蓝宝石主要依靠人工经验操控籽晶杆实现引晶操作,但是人工引晶操作的准确性不高会导致成品品质不佳、资源浪费。为此,本文提出一种基于蓝宝石视觉辐条图案识别方法来检测蓝宝石熔体状态自由液面状态,从而实现一种高效率引晶的机制。此方法利用经典骨架化算法细化辐条图案,Harris算子实现特征信息的提取,提取的特征信息放入运动轨迹模型中判断熔体稳定性,分析液面温度分布稳定性从而实现引晶。结果表明,此算法具有有效性,蓝宝石晶体引晶效率大大提高,生产出的成品良率也有提升,可有效指导蓝宝石的工业生产。     

High-fidelity Recognition of Organotrifluoroborate Anions (R−BF3−) as Designer Guest Molecules

The recognition of boron compounds is well developed as boronic acids but untapped as organotrifluoroborate anions (R−BF₃⁻). We are exploring the development of these and other designer anions as anion-recognition motifs by considering them as substituted versions of the parent inorganic ion. To this end, we demonstrate strong and reliable binding of organic trifluoroborates, R−BF₃⁻, by cyanostar macrocycles that are size-complementary to the inorganic BF₄⁻ progenitors. We find that recognition is modulated by the substituent's sterics and that the affinities are retained using the common K⁺ salts of R−BF₃⁻ anions.