Seawater evaporation and purification powered by solar energy are considered as a promising approach to alleviate the global freshwater crisis, and the development of photothermal materials with high efficiency is imminent. In this study, cellulose nanofiber (CNF)/MXene/Ni chain (CMN) aerogels were successfully synthesized by electrostatic force and hydrogen bond interaction force. CMN10 achieved a favorable evaporation rate as high as 1.85 kg m− 2 h− 1 in pure water, and the corresponding evaporation efficiency could be up to 96.04%. Even if it is applied to seawater with multiple interference factors, its evaporation rate can still be 1.81 kg m− 2 h− 1. The superior seawater evaporation activity origins from the promoted separation of photoexcited charges and photothermal conversion by the synergy of Ni chain and MXene, as well as the water transport channel supported by the 3D structure frame of CNF. Most importantly, CMN aerogel can maintain water vapor evaporation rates above 1.73 kg m− 2 h− 1 under extreme conditions such as acidic (pH 2) and alkaline (pH 12) conditions. In addition, various major ions, heavy metals and organic pollutants in seawater can be rejected by CMN10 during desalination, and the rejection rates can reach more than 99.69%, ensuring the purity of water resources after treatment. This work shows the great potential of CMN aerogel as a high-efficiency solar evaporator and low-cost photothermal conversion material. Cellulose nanofiber (CNF)/MXene/Ni chain (CMN) aerogels demonstrated high evaporation of water from sea water.

Aurantii Fructus Immature (AFI) and Aurantii Fructus (AF) are two important traditional Chinese herbs. As the harvesting time varies, the medicinal value of the plants is not uniform. Consequently, it has been difficult to quickly recognize them within the realm of traditional Chinese medicine. Separation and detection technologies are employed in combination to create fingerprints for identification. We proposed the utilization of graphene-assisted electrochemical fingerprint technology to acquire fingerprints of two varieties of medicinal materials. Simultaneously, we also obtained their fingerprints through HPLC. Two fingerprint recognition technologies were compared for their effectiveness. The findings demonstrate that the signals obtained through electrochemical fingerprinting have a higher recognition rate.

In this paper, we propose a new neural network architecture for item recommendation with structural information. Our model, structural neural recommender (SNR) is based on neural networks and operates on a hierarchy paradigm, aiming to explore the effectiveness of incorporating different structural information for recommendation. Many recent state-of-the-art neural network based recommendation models exploit the nonlinear transformations for modeling the complex user-item interaction patterns and user historical behaviors, ignoring the item-item structural relationship. This structural information, however, is uncomplicated to derive and useful for inferring item characteristics. To utilize this information, SNR simultaneously learns representation from user-item interactions and item-item relationships. Empirical studies on eight real-world datasets demonstrate the effectiveness of incorporating such structural information, by outperforming classic and recent baselines. We also conduct detail ablation studies and hyper-parameter analysis to provide further understanding towards the behaviors of our model. Following the model development, we conduct a field experiment to demonstrate that the effectiveness of algorithmic recommender systems can further increase by using different types of message framing when communicating recommendations to consumers. Our results suggest that recommendations framed with a relevance appeal (e.g. “Top 5 brands for you”) are more effective in general, yet recommendations that are framed with a popularity appeal (“Top 5 most popular brands”) are more effective for customers who were acquired via social media (versus non-social media) advertising or for those who have stronger (versus weaker) social orientation.

This study interprets Siberian shaman costumes from the perspective of Siberian shamanism’s spiritual culture by combining theoretical and empirical studies. According to the natural environment and language families, the Siberian people are classified into the Altai, Tungus, Ural, and Paleo-Siberian groups. Se Yin’s research classifies the spiritual culture of Siberian shamanism as cosmic, spiritual, and nature view. Eliade’s research has divided Siberian shaman costumes into form, headdress, and ornament. According to the present study, shaman costume form and decoration reflect the Siberian three-tiered cosmic view, such that the shaman’s head, body and feet correspond to the upperworld, middleworld and underworld. In addition, animism, totemism and ancestral worship appear in the shamanism’s spiritual view. For example, the costume’s form shows the totem of each tribe, while the costume accessories reflect animal worship, plant worship and ancestral worship. Finally, shamanism’s nature view mainly manifests through three processes: personification, deification, and ethics. As an intermediary between man and the spirits, shaman use their clothing to reproduce the image of half man and half spirit. The shaman’s costumes are deified and considered to have divine power. For example, the animals represented on the costume help the shaman travel through space. Generally, good animals help a shaman enter the upperworld, while animals that help a shaman enter the underworld are considered evil. Also, the number of hanging accessories represents the shaman’s ability.

This study attempts to analyze the social and cultural meanings of the ethnic groups to which different types of shamans belong in Siberia from the appearance characteristics in terms of clothing through Roland Barthes’s semiotic theory. The research method here is to analyze three types of shaman costume classified by Holmberg, which are bird-type, deer-type, and bear-type, through theoretical research and to investigate the analysis process of Roland Barthes’s semiotics theory. Roland Barthes’s approach to semiotics presents an analysis model that can explore the sociocultural meaning of the Siberian shaman costume. The research results are as follows. In the first type, to be closer to the god of the upperworld, shamans transform themselves into birds by decorating their costumes with the characteristic elements of birds such as feathers and wings. In the second type, the shamans’ costumes are made of deerskin, and the headdress is shown in the shape of antlers to make it easier to receive messages from the upperworld and run fast in the underworld. In the third type, the shaman’s costume is made of bearskin, the head is covered with bearskin, and the body is decorated with bear pendants. Through the power of the bear, the shaman is sent to the underworld to defeat evil gods and remove diseases. Shamans can show their particularity of being a demigod and non-binary gender through clothing. They use this to reflect their authority as a medium of communication between man and god.

Metal–organic frameworks (MOFs) are network-like frameworks composed of transition metals and organic ligands containing oxygen or nitrogen. Because of its highly controllable composition and ordered porous structure, it has broad application prospects in the field of material synthesis. In this work, Zn4( PYDC)4(DMF)2∙3DMF (ZPD) was synthesized via a hydrothermal method. Self-doped nitrogen porous carbon ZPDC-T was then prepared by one-step carbonization. The results show that the self-doped nitrogen porous carbon ZPDC-850 has a micro/mesoporous structure with a specific surface area of 1520 m2 g− 1 and a nitrogen content of 6.47%. When a current density is 1.0 A g− 1, its specific capacitance is 265.1 F g− 1. After 5000 times of constant current charging and discharging, the capacitance retention rate was 79.2%. Thus, self-doped nitrogen porous carbon ZPDC-850 exhibits excellent electrochemical properties and good cyclic stability. Therefore, the self-doped nitrogen porous carbon derived from MOFs can be a promising electrode material for supercapacitors.