Extensive Interest In Recent Years Research Articles

First-principles study of GeC/Ga2SO heterostructure as a potential direct Z-scheme photocatalyst for water splitting

The rational design of van der Waals heterostructure offers an effective avenue for improving the photocatalytic efficiency of individual two-dimensional materials, garnering extensive interest in recent years. Herein, the feasibility of GeC/Ga2SO heterostructure as a photocatalyst for overall water splitting has been explored based on the first-principles calculations. Our findings reveal that the electronic bandstructure of GeC/Ga2SO heterostructure can be engineered in staggered or straddling band alignment depending on stacking patterns. Particularly, in the GeC/Ga2SO heterostructure with staggered band alignment, an intrinsic built-in electric field is established at the interface with the direction from GeC to Ga2SO, facilitating the formation of a direct Z-scheme heterostructure. Also importantly, the band-edge positions of Z-scheme GeC/Ga2SO heterostructure cross the water redox potentials, providing adequate driving force for both the reduction and oxidation reactions of water. Gibbs free energy calculations demonstrated that the photocatalytic overall water splitting can proceed spontaneously in the neutral environment (pH = 7) under light irradiation. Moreover, GeC/Ga2SO heterostructure exhibits good thermal stability and a strong (magnitude in 105 cm−1) and broad (from visible to ultraviolet light) optical absorption. Finally, through applying the tensile strain, further enhancements in the optical absorption and carrier redox ability are achieved due to the favorable modulation in the bandgap. Therefore, all these features make GeC/Ga2SO heterostructure show great potential in the application of photocatalytic water splitting.

Biomimetic Design of 3D Fe3O4/V-EVOH Fiber-Based Self-Floating Composite Aerogel to Enhance Solar Steam Generation Performance.

An interfacial solar steam generation evaporator for seawater desalination has attracted extensive interest in recent years. Nevertheless, challenges still remain in relatively low evaporation rate, unsatisfactory energy conversion efficiency, and salt accumulation. Herein, we have demonstrated a biomimetic bilayer composite aerogel consisting of bottom hydrophilic and vertically aligned EVOH channels and an upper hydrophobic conical Fe3O4 array. Thanks to the design merits, the 3D Fe3O4/V-EVOH evaporator exhibits a high evaporation rate of ∼2.446 kg m-2 h-1 and an impressive solar energy conversion efficiency of ∼165.5% under 1 sun illumination, which is superior to those of state-of-the-art evaporators reported so far. Moreover, the asymmetrical wettability not only allows the evaporator to self-float on the water but also facilitates the salt ion diffusion in the channels; thus, the evaporator shows no salt crystals on its surface and only a 6% decrease in evaporation performance even after the salt concentration increases from 0 to 10.0 wt %.

Dendritic cell-targeted delivery of antigens using extracellular vesicles for anti-cancer immunotherapy.

Neoantigen delivery using extracellular vesicles (EVs) has gained extensive interest in recent years. EVs derived from tumour cells or immune cells have been used to deliver tumour antigens or antitumor stimulation signals. However, potential DNA contamination from the host cell and the cost of large-scale EV production hinder their therapeutic applications in clinical settings. Here, we develop an antigen delivery platform for cancer vaccines from red blood cell-derived EVs (RBCEVs) targeting splenic DEC-205+ dendritic cells (DCs) to boost the antitumor effect. By loading ovalbumin (OVA) protein onto RBCEVs and delivering the protein to DCs, we were able to stimulate and present antigenic OVA peptide onto major histocompatibility complex (MHC) class I, subsequently priming activated antigen-reactive T cells. Importantly, targeted delivery of OVA using RBCEVs engineered with anti-DEC-205 antibody robustly enhanced antigen presentation of DCs and T cell activation. This platform is potentially useful for producing personalised cancer vaccines in clinical settings.

The Social Inequality of Music: University Students from a Higher Social Class Are More Likely to Build Relationships and Feel Happiness Through Music.

The relationship between young people's music use and well-being has gained extensive interest in recent years. The relationship-building function of music is one of its most important functions. While many studies have documented the positive effects of this function, there is a lack of research discussing this topic from the perspective of social stratification. This study sampled 691(63.8% male, M age = 19.43, SD = 1.42) Chinese university students to examine the social class differences among university students in acquiring well-being through the relationship-building function of music. The results revealed that university students from a higher social class are more likely to acquire well-being through the relationship-building function of music. In addition, interdependent self-construal plays a moderating role in the mediating model. The mediating effect was only significant when university students have a higher level of interdependent self-construal. These results indicated social class differences among university students in the building of relationships with music, underscoring the need for future research and interventions to address social inequality in the context of music's functions.

Optimal bispectral index exists in healthy patients undergoing general anesthesia: A validation study.

Continuous cerebrovascular reactivity monitoring in both neurocritical and intra-operative care has gained extensive interest in recent years, as it has documented associations with long-term outcomes (in neurocritical care populations) and cognitive outcomes (in operative cohorts). This has sparked further interest into the exploration and evaluation of methods to achieve an optimal cerebrovascular reactivity measure, where the individual patient is exposed to the lowest insult burden of impaired cerebrovascular reactivity. Recent literature has documented, in neural injury populations, the presence of a potential optimal sedation level in neurocritical care, based on the relationship between cerebrovascular reactivity and quantitative depth of sedation (using bispectral index (BIS)) - termed BISopt. The presence of this measure outside of neural injury patients has yet to be proven. We explore the relationship between BIS and continuous cerebrovascular reactivity in two cohorts: (A) healthy population undergoing elective spinal surgery under general anesthesia, and (B) healthy volunteer cohort of awake controls. We demonstrate the presence of BISopt in the general anesthesia population (96% of patients), and its absence in awake controls, providing preliminary validation of its existence outside of neural injury populations. Furthermore, we found BIS to be sufficiently separate from overall systemic blood pressure, this indicates that they impact different pathophysiological phenomena to mediate cerebrovascular reactivity. Findings here carry implications for the adaptation of the individualized physiologic BISopt concept to non-neural injury populations, both within critical care and the operative theater. However, this work is currently exploratory, and future work is required.

Recent advances in micro/nanomotors for antibacterial applications.

Currently, the rapid spread of multidrug-resistant bacteria derived from the indiscriminate use of traditional antibiotics poses a significant threat to public health worldwide. Moreover, established bacterial biofilms are extremely difficult to eradicate because of their high tolerance to traditional antimicrobial agents and extraordinary resistance to phagocytosis. Hence, it is of universal significance to develop novel robust and efficient antibacterial strategies to combat bacterial infections. Micro/nanomotors exhibit many intriguing properties, including enhanced mass transfer and micro-mixing resulting from their locomotion, intrinsic antimicrobial capabilities, active cargo delivery, and targeted treatment with precise micromanipulation, which facilitate the targeted delivery of antimicrobials to infected sites and their deep permeation into sites of bacterial biofilms for fast inactivation. Thus, the ideal antimicrobial activity of antibacterial micro/nanorobots makes them desirable alternatives to traditional antimicrobial treatments and has aroused extensive interest in recent years. In this review, recent advancements in antibacterial micro/nanomotors are briefly summarized, focusing on their synthetic methods, propulsion mechanism, and versatile antibacterial applications. Finally, some personal insights into the current challenges and possible future directions to translate proof-of-concept research to clinic application are proposed.

A butterfly-shaped AIEgen with excited-state intramolecular proton transfer effect for colorimetric and fluorescent detection of copper and zinc ions

Multipurpose aggregation-induced emission (AIE) fluorescence probes for metal ion detection have drawn extensive interest in recent years. Here, a butterfly-shaped AIE luminogen (TOPD) was synthesized from 2-hydroxy-5-(1,2,2-triphenylethenyl)-benzaldehyde and o-phenylenediamine via a one-step Schiff-base condensation for flexibly detecting copper and zinc ions. The aggregated state of TOPD revealed a large Stokes shift of 263 nm due to the excited-state intramolecular proton transfer (ESIPT) effect benefiting from the planar cis-configuration and enol-keto tautomerization of TOPD molecules confirmed by the modeling investigation. TOPD showed remarkable colorimetric and high selective fluorescence turn-off response to Cu2+ in phosphate buffer saline/tetrahydrofuran (PBS/THF, 9:1, v/v) with a low detection limit (0.14 μM) and quick response time (<30 s). TOPD realized the Zn2+ sensing via turn-on and blue-shifted fluorescence in PBS/THF (8:2, v/v) with a detection limit of 0.93 μM. The significant color changes can be directly discriminated by the “naked eye”. Experiments and DFT theoretical calculations strongly suggested that sensing mechanisms were via 1:1 TOPD-metal complexes. The strategy of tunable AIE fluorescence could provide new ideas for potential applications in the detection of multiple ions in environmental fields.

Spin-selectivity effect of G-quadruplex DNA molecules.

Chirality-induced spin selectivity has been attracting extensive interest in recent years and is demonstrated in a variety of chiral molecules, all of which arise from inherent molecular chirality. Here, we first propose a theoretical model to study the spin-dependent electron transport along guanine-quadruplex (G4) DNA molecules, connected to two nonmagnetic electrodes, by considering the molecule-electrode contact and weak spin-orbit coupling. Our results indicate that the G4-DNA molecular junctions exhibit pronounced spin-selectivity effect, and the asymmetric contact-induced external chirality, instead of the inherent molecular chirality, dominates their spin filtration efficiency. Furthermore, the spin-selectivity effect is robust against the disorder and hold in a wide range of model parameters. These results could be checked by charge transport measurements and provide an alternative way to improve the spin-selectivity effect of chiral nanodevices.

A novel adjusted learning algorithm for online portfolio selection using peak price tracking approach

Online Portfolio Selection (OLPS) has attracted extensive interest in recent years. Accurate prediction of future prices and determining the optimal portfolio selection strategy based on the estimated return is a challenging topic in machine learning. We propose a novel adjusted learning algorithm based on peak price tracking for OLPS to tackle this challenge. The algorithm is based on an aggressive strategy with residual information and transaction costs. We first propose an adjusted online portfolio selection algorithm using Peak Price Tracking Approach (PPTA) to improve the accuracy of return prediction by introducing λ to adjust the impact of peak price and residual term on the predicted price. We then build the Net Profit Maximization (NPM) model with transaction costs. Finally, we integrate the PPTA and the NPM algorithms into a new algorithm called the PPTA-NPM to maximize the cumulative return. Extensive benchmark data experiment results and statistical analysis show that the PPTA algorithm significantly improves the accuracy in predicting the future price, and the integrated PPTA-NPM algorithm is superior to multiple classic OLPS algorithms.

Observation of the "invisible" pulsation of soliton molecules in a bidirectional ultrafast fiber laser.

A novel optical soliton dynamics phenomenon, called "invisible" pulsation, has gradually attracted extensive interest in recent years, which can only be identified effectively with the help of real-time spectroscopy technique, i.e., dispersive Fourier transformation (DFT). In this paper, based on a new bidirectional passively mode-locked fiber laser (MLFL), the "invisible" pulsation dynamics of soliton molecules (SMs) is systematically studied. It is indicated that the spectral center intensity, pulse peak power and relative phase of SMs are periodically changed during the "invisible" pulsation, while the temporal separation inside the SMs is constant. The degree of spectral distortion is positively correlated with the pulse peak power, which verifies that self-phase modulation (SPM) is the inducement of spectral distortion. Finally, the universality of the SMs "invisible" pulsation is further experimentally verified. We believe our work is not only conducive to the development of compact and reliable bidirectional ultrafast light sources, but also of great significance to enrich the study of nonlinear dynamics.

Role of CYP6MS subfamily enzymes in detoxification of Sitophilus zeamais after exposure to terpinen-4-ol and limonene

Food security is an important basis and guarantee to national safety, the loss caused by storage pests was a serious problem which affects the food security widely. Frequent application of chemical pesticides caused several critical crises including the development of resistance, pesticide residues, environmental pollution, and exposure risk to human or non-target organisms. The utilization of volatile components acts as a natural alternative for controlling storage pests has aroused extensive interest in recent years. It has been reported that terpinene-4-ol and limonene showed significant insecticidal activity against Sitophilus zeamais in our previous studies, which was evaluated to have strong influences to CYP450 genes. To determine the links and roles of related genes, we identified the SzCYP6MS subfamily genes which encoded a putative protein of 493 or 494 amino acids. Then, the expression of four CYP6MS subfamily genes were increased significantly under the fumigation stress by terpinen-4-ol and limonene, which was determined by the RT-qPCR analysis compared with non-fumigated colonies. In addition, we determined that RNAi-mediated CYP6MS genes knockdown significantly increased the sensitivity of S. zeamais to terpinen-4-ol and limonene, the mortality rates of insects with knocked down CYP6MS1, CYP6MS5, CYP6MS6, CYP6MS8, and CYP6MS9 genes increased by 25%, 25%, 16%, 17%, and 4% in terpinen-4-ol treatment groups and by 29%, 25%, 15%, 22%, and 3% in limonene treatment groups compared with that in the control groups, respectively. Finally, it was validated that CYP6MS5 exhibited the most stable binding with terpinen-4-ol that was similar to the result between CYP6MS8 and limonene which were verified by molecular docking analysis. In together, this study demonstrates the potential of terpinen-4-ol and limonene used as novel botanical pesticides to control storage pests, thereby reducing application of chemical pesticides and postponing resistance development.

Efficient Verifiable Protocol for Privacy-Preserving Aggregation in Federated Learning

Federated learning has gained extensive interest in recent years owing to its ability to update model parameters without obtaining raw data from users, which makes it a viable privacy-preserving machine learning model for collaborative distributed learning among various devices. However, due to the fact that adversaries can track and deduce private information about users from shared gradients, federated learning is vulnerable to numerous security and privacy threats. In this work, a communication-efficient protocol for secure aggregation of model parameters in a federated learning setting is proposed where training is done on user devices while the aggregated trained model could be constructed on the server side without revealing the raw data of users. The proposed protocol is robust against users’ dropouts, and it enables each user to independently validate the aggregated result supplied by the server. The suggested protocol is secure in an honest-but-curious environment, and privacy is maintained even if the majority of parties are in collusion. A practical scenario for the proposed setting is discussed. Additionally, a simulation of the protocol is evaluated, and results demonstrate that it outperforms one of the state-of-art protocols, especially when the number of dropouts increases.

Spin transport properties and nanodevice simulations of NiI2 monolayer

Two-dimensitional (2D) magnetic semiconducting materials attract extensive interest in recent years. A new type of magnetic semiconducting nickel-based transition metal diiodide-NiI2 monolayer (NiI2-ML) was successfully prepared in recent experiments. Some nanodevices based on the NiI2-ML are designed and their spin-resolved transport and photoelectric properties are studied. Strong rectification and spin filtering effects are observed in the NiI2-ML pn-junction. The NiI2-ML pin-junction shows a field-effect property. Moreover, it is found that NiI2-ML has a strong response to green light that promotes its phototransistor to generate exploitable photocurrent. The results of this paper show that NiI2-ML is a multifunctional magnetic semiconducting material with potential applications in the fields of spintronic and optoelectronic devices.

Graphene oxide-covered melamine foam utilizing as a hybrid foam toward organic dye removal and recyclability

Graphene-based adsorbents have been attracted extensive interest in recent years. Herein, graphene oxide-covered melamine foam (GO-covered MF) was designed and prepared by a mild submerge-covering method with the support of a super-hydrophilic melamine framework, showing its adsorption performances for various organic dyes. The structure morphology as well as chemical, thermal and mechanical properties of the as-obtained hybrid foam (HF) were further determined for the possible structure changes after covering the GO sheets on the MF framework. Moreover, the HF exhibited an excellent ability for organic dye adsorption application, and which was well fitted in the pseudo-second-order kinetic and Langmuir models corresponding to a chemical adsorption and a mono-layer approach during the adsorption process. The maximum adsorption capacity by using the as-obtained HF corresponded to 258.56 ​mg ​g−1 (methylene blue), 233.22 ​mg ​g−1 (Rhodamine B), 206.92 ​mg ​g−1 (methyl orange), and 184.93 ​mg ​g−1 (Congo red), which are competitive with that of other graphene-based absorbents. In particular, the HF could be reused without a noticeable degradation of organic dye removal performance. As such, the HF prepared in this study can become an encouraging candidate for practical application owing to the reliable recyclability and low-cost.

Multiple roles of m6A methylation in epithelial-mesenchymal transition.

Epithelial-mesenchymal transition (EMT) plays an important role in migration and invasion of cancer cell and the development of tissue fibrosis diseases. N6-methyladenosine (m6A) is the most extensive type of RNA methylation and has aroused extensive interest in recent years. However, m6A methylation seems to play different roles in different cancer cells and tissue fibrotic diseases. To determine the function of m6A methylation in EMT, we summarized the molecular mechanism of EMT and recent progress in the regulation of EMT by m6A methylation, suggesting that m6A methylation targets EMT program by affecting the expression of transcription factors, EMT markers, long noncoding RNA and EMT-associated signaling pathways, which provides more possibilities for early diagnosis and treatment.

Strain Sensor with Enhanced Sensitivity for Wearable Electronics Using an Over‐Balanced Planar Elastomer

AbstractFlexible sensor technologies have gained extensive interest in recent years owing to the increasing demands of wearable electronics. Here, the authors propose a flexible strain sensor with enhanced sensitivity by designing a new sensing approach for strain detection. The sensing approach uses an over‐balanced planar elastomer (OBPE) inspired by Kirigami‐like auxetic structure for stretchable sensing. The OBPE substrate is designed and fabricated with four polydimethylsiloxane (PDMS) supporting beam embedded into Ecoflex elastomer to realize auxetic characteristics. The auxetic characteristics induce the sensing region of the sensor to expand in directions both along and orthogonally to the stretch loading. Consequently, the local disconnections of the electrically linked paths composed of multi‐wall carbon nanotubes (MWCNTs) in the sensing region are enhanced. Gauge factor of the OBPE strain sensor is improved up to 6 times higher than the typical strain sensor without OBPE architecture. Therefore, the enhanced sensor outputs the stronger electrical signals than the typical sensor in perceiving human motions. Moreover, the two‐step casting fabrication is a low‐cost process and suitable for large volume manufacturing. In addition, as this sensing method is independent of the constituent conductive materials, it has the potential to be further employed for developing other stretchable strain sensors.

Discrete online cross-modal hashing

With the prevalence of multimedia content on the Web which usually continuously comes in a stream fashion, online cross-modal hashing methods have attracted extensive interest in recent years. However, most online hashing methods adopt a relaxation strategy or real-valued auxiliary variable strategy to avoid complex optimization of hash codes, leading to large quantization errors. In this paper, based on Discrete Latent Factor model-based cross-modal Hashing (DLFH), we propose a novel cross-modal online hashing method, i.e., Discrete Online Cross-modal Hashing (DOCH). To generate uniform high-quality hash codes of different modal, DOCH not only directly exploits the similarity between newly coming data and old existing data in the Hamming space, but also utilizes the fine-grained semantic information by label embedding. Moreover, DOCH can discretely learn hash codes by an efficient optimization algorithm. Extensive experiments conducted on two real-world datasets demonstrate the superiority of DOCH.

Antiferromagnetic skyrmion-based logic gates controlled by electric currents and fields

Antiferromagnets are promising materials for future spintronic applications due to their unique properties including zero stray fields, robustness vs external magnetic fields, and ultrafast dynamics, which have attracted extensive interest in recent years. In this work, we investigate the dynamics of isolated skyrmions in an antiferromagnetic nanotrack with a voltage-gated region. It is found that the skyrmion can be jointly controlled by the driving current and the voltage-controlled magnetic anisotropy gradient. We further propose a design of logic computing gates based on the manipulation of antiferromagnetic skyrmions, which is numerically realized combining several interactions and phenomena, including the spin Hall effect, voltage-controlled magnetic anisotropy effect, skyrmion–skyrmion interaction, and skyrmion–edge interaction. The proposed logic gates can perform the basic Boolean operations of the logic AND, OR, NOT, NAND, and NOR gates. Our results may have a great impact on fundamental physics and be useful for designing future nonvolatile logic computing devices with ultra-low energy consumption and ultra-high storage density.

Cluster‐assembled materials: Ordered structures with advanced properties

AbstractCluster‐assembled materials (CAMs) present delicate structures and tailored properties, which have gained extensive interest in recent years. Due to the noncovalent linkage and size of sub‐1 nm, clusters present polymer‐like solution behaviors distinct from conventional nanocrystals, whereby a variety of CAMs with different constructions have been fabricated. To our knowledge, the morphologies and properties of CAMs are closely connected, which are strongly dependent on the structure and coordination state of cluster building blocks. For the CAMs with superior performances, the specific arrangement and surroundings of clusters at subnanometer scale usually result in well‐organized structures. In this review, we will summarize the recent progress of CAMs with highly ordered structures and advanced properties, where polyoxometalate cluster assemblies as well as cluster–nuclei co‐assemblies are involved. The application potentials of CAMs are then discussed, especially on the cluster arrangements and interactions at subnanometer scale. However, current researches are far from reaching the point, and future efforts are needed before the nature of cluster‐based nanostructures can be sufficiently revealed. We hope this article can offer unique insights and instructive understanding to the CAMs.

Recent Advances of Near-Infrared (NIR) Emissive Metal Complexes Bridged by Ligands with N- and/or O-Donor Sites

Near-infrared (NIR) emissive metal complexes have shown potential applications in optical communication, chemosensors, bioimaging, and laser and organic light-emitting diodes (OLEDs) due to their structural tunability and luminescence stability. Among them, complexes with bridging ligands that exhibit unique emission behavior have attracted extensive interests in recent years. The target performance can be easily achieved by NIR light-emitting metal complexes with bridging ligands through molecular structure design. In this review, the luminescence mechanism and design strategies of NIR luminescent metal complexes with bridging ligands are described firstly, and then summarize the recent advance of NIR luminescent metal complexes with bridging ligands in the fields of electroluminescence and biosensing/bioimaging. Finally, the development trend of NIR luminescent metal complexes with bridging ligands are proposed, which shows an attractive prospect in the field of photophysical and photochemical materials.