The quartet theory of human emotions: An integrative and neurofunctional model

Despite an explosion of research in the affective sciences during the last few decades, interdisciplinary theories of human emotions are lacking. Here we present a neurobiological theory of emotions that includes emotions which are uniquely human (such as complex moral emotions), considers the role of language for emotions, advances the understanding of neural correlates of attachment-related emotions, and integrates emotion theories from different disciplines. We propose that four classes of emotions originate from four neuroanatomically distinct cerebral systems. These emotional core systems constitute a quartet of affect systems: the brainstem-, diencephalon-, hippocampus-, and orbitofrontal-centred affect systems. The affect systems were increasingly differentiated during the course of evolution, and each of these systems generates a specific class of affects (e.g., ascending activation, pain/pleasure, attachment-related affects, and moral affects). The affect systems interact with each other, and activity of the affect systems has effects on – and interacts with – biological systems denoted here as emotional effector systems. These effector systems include motor systems (which produce actions, action tendencies, and motoric expression of emotion), peripheral physiological arousal, as well as attentional and memory systems. Activity of affect systems and effector systems is synthesized into an emotion percept (pre-verbal subjective feeling), which can be transformed (or reconfigured) into a symbolic code such as language. Moreover, conscious cognitive appraisal (involving rational thought, logic, and usually language) can regulate, modulate, and partly initiate, activity of affect systems and effector systems. Our emotion theory integrates psychological, neurobiological, sociological, anthropological, and psycholinguistic perspectives on emotions in an interdisciplinary manner, aiming to advance the understanding of human emotions and their neural correlates.     

SE-MCNN-CTC的中文语音识别声学模型

针对国内外缺少对振动轮噪声预估的问题,以某型振动轮为研究对象,首先基于动力学有限元理论对振动轮进行频率响应分析,其次采用声学边界元技术对振动轮辐射噪声进行了数值模拟,并通过实验验证了仿真结果的准确性,然后比较了垂直振动与圆周振动两种不同激振形式对辐射噪声的影响,得出垂直振动辐射噪声低的结论,最后对驾驶室声腔模态进行了仿真,与振动轮激振频率相近发生共振。通过调整激振频率,降低了司机耳旁噪声。所得研究成果可为振动轮辐射噪声的预估与改进提供一种切实可行的参考依据。     

Two-dimensional Supramolecular Polymers Based on Selectively Recognized Aromatic Cation-π and Donor-Acceptor Motifs for Photocatalytic Hydrogen Evolution

Two-dimensional (2D) organic polymers have recently received considerable interest, especially those whose architectures are held together via supramolecular engineering. However, current approaches toward supramolecular 2D structures usually suffer from mutual interference of noncovalent interactions and lack of intrinsic functions. Herein, we report well-regulated 2D supramolecular polymers (2DSPs) through an aromatics-selective recognition strategy of cation-π and donor-acceptor (D-A) motifs, which are derived from C₄-symmetric cationic monomers and electron-withdrawing molecules. By subtly designing the strength and direction of noncovalent driving forces, the mutual interference between cation-π and D-A interactions is effectively avoided, enabling the construction of 2DSPs in aqueous solution. On this basis, the resultant 2DSPs possess boosted photocatalytic hydrogen evolution activity at a rate of 600 μmol g⁻¹ h⁻¹, which is mainly ascribed to the specific stacking mode of cation-π/D-A motifs and the ordered 2D structures.     

Achieving Molecular Recognition of Structural Analogues in Surface-Enhanced Raman Spectroscopy: Inducing Charge and Geometry Complementarity to Mimic Molecular Docking

Molecular recognition of complex isomeric biomolecules remains challenging in surface-enhanced Raman scattering (SERS) spectroscopy due to their small Raman cross-sections and/or poor surface affinities. To date, the use of molecular probes has achieved excellent molecular sensitivities but still suffers from poor spectral specificity. Here, we induce “charge and geometry complementarity” between probe and analyte as a key strategy to achieve high spectral specificity for effective SERS molecular recognition of structural analogues. We employ 4-mercaptopyridine (MPY) as the probe, and chondroitin sulfate (CS) disaccharides with isomeric sulfation patterns as our proof-of-concept study. Our experimental and in silico studies reveal that “charge and geometry complementarity” between MPY's binding pocket and the CS sulfation patterns drives the formation of site-specific, multidentate interactions at the respective CS isomerism sites, which “locks” each CS in its analogue-specific complex geometry, akin to molecular docking events. Leveraging the resultant spectral fingerprints, we achieve > 97 % classification accuracy for 4 CSs and 5 potential structural interferences, as well as attain multiplex CS quantification with < 3 % prediction error. These insights could enable practical SERS differentiation of biologically important isomers to meet the burgeoning demand for fast-responding applications across various fields such as biodiagnostics, food and environmental surveillance.     

Engineering Hierarchical Recognition-Mediated Senolytics for Reliable Regulation of Cellular Senescence and Anti-Atherosclerosis Therapy

Precise regulation of vascular senescence represents a far-reaching strategy to combat age-related diseases. However, the high heterogeneity of senescence, alongside the lack of targeting and potent senolytics, makes it very challenging. Here we report a molecular design to tackle this challenge through multidimensional, hierarchical recognition of three hallmarks commonly shared among senescence, namely, aptamer-mediated recognition of a membrane marker for active cell targeting, a self-immolative linker responsive to lysosomal enzymes for switchable drug release, and a compound against antiapoptotic signaling for clearance. Such senolytic can target and trigger severe cell apoptosis in broad-spectrum senescent endothelial cells, and importantly, distinguish them from the quiescent state. Its potential for in vivo treatment of vascular diseases is successfully illustrated in a model of atherosclerosis, with effective suppression of the plaque progression yet negligible side effects.     

The Story of the Little Blue Box: A Tribute to Siegfried Hünig

The tetracationic cyclophane, cyclobis(paraquat-p-phenylene), also known as the little blue box, constitutes a modular receptor that has facilitated the discovery of many host–guest complexes and mechanically interlocked molecules during the past 35 years. Its versatility in binding small π-donors in its tetracationic state, as well as forming trisradical tricationic complexes with viologen radical cations in its doubly reduced bisradical dicationic state, renders it valuable for the construction of various stimuli-responsive materials. Since the first reports in 1988, the little blue box has been featured in over 500 publications in the literature. All this research activity would not have been possible without the seminal contributions carried out by Siegfried Hünig, who not only pioneered the syntheses of viologen-containing cyclophanes, but also revealed their rich redox chemistry in addition to their ability to undergo intramolecular π-dimerization. This Review describes how his pioneering research led to the design and synthesis of the little blue box, and how this redox-active host evolved into the key component of molecular shuttles, switches, and machines.     

High-yield synthesis of a novel water-soluble macrocycle for selective recognition of naphthalene

A novel good water-soluble macrocycle containing two pyridinium moieties was synthesized in high yield.It could form 1:1 complexes with neutral guests containing naphthalene or phenyl units in water.The water-soluble macrocycle can selectively encapsulate naphthalene to form a 1:1 complex over a variety of polycyclic aromatic hydrocarbons.     

模糊识别模式在粉土液化判别中的应用

基于模糊数学的基本原理和方法,分析了粉土液化的影响因素,选取粉土的平均粒径,相对密度,标准贯入击数和上覆有效压力作为评价指标,构造粉土液化的模糊识别模式。验证和应用结果表明,模糊识别模式具有很好的映射能力,是粉土液化势预测的有效手段。