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This review aims to systematically assess the current status and prospects of artificial intelligence (AI) in the rehabilitation management of patients with schizophrenia and their impact on the rehabilitation process. We selected 70 studies from 2012 to the present, focusing on application, technology categories, products, and data types of machine learning, deep learning, reinforcement learning, and other technologies in mental health interventions and management. The results indicate that AI can be widely used in symptom monitoring, relapse risk prediction, and rehabilitation treatment by analyzing ecological momentary assessment, behavioral, and speech data. This review further explores the potential challenges and future directions of emerging products, technologies, and analytical methods based on AI, such as social media analysis, serious games, and large language models in rehabilitation. In summary, this study systematically reviews the application status of AI in schizophrenia rehabilitation management and provides valuable insights and recommendations for future research paths.

Quantum steering in a global state allows an observer to remotely steer a subsystem into different ensembles by performing different local measurements on the other part. We show that, in general, this property cannot be perfectly cloned by any joint operation between a steered subsystem and a third system. Perfect cloning is viable if and only if the initial state is of zero discord. We also investigate the process of cloning the steered qubit of a Bell state using a universal cloning machine. Einstein-Podolsky-Rosen (EPR) steering, which is a type of quantum correlation existing in the states without a local-hidden-state model, is observed in the two copy subsystems. This contradicts the conclusion of no-cloning of quantum steering (EPR steering) [C. Y. Chiu et al., npj Quantum Inf. 2, 16020 (2016)] based on a mutual information criterion for EPR steering., Comment: Published by CPL as Editors' Suggestion; This work has been reported in Physics World (https://physicsworld.com/a/cloning-quantum-steering-is-a-no-go/)

The hierarchy of nonlocality and entanglement in multipartite systems is one of the fundamental problems in quantum physics. We study this topic in three-qubit systems considering the entanglement classification of stochastic local operations and classical communication (SLOCC). The equivalence under SLOCC divides threequbit states into separable, biseparable, W, and Greenberger-Horne-Zeilinger (GHZ) classes. The W and GHZ are two subclasses of genuine tripartite entanglement.We adopt the family of GHZ-symmetric states as a research subject, which share the symmetries of the GHZ state and have a complete characterization of SLOCC classes. In the biseparable region (with bipartite entanglement), there exist GHZ-symmetric states that are found to be fully local. In addition, there are bilocal states in both theW and GHZ classes. That is, neither of the subclasses of genuine tripartite entanglement can ensure genuinely tripartite nonlocality., Comment: 4 figures, 7 pages

STITCH is a computer program that processes raw nucleotide-sequence data to automatically remove unwanted vector information, perform reverse-complement comparison, stitch shorter sequences together to make longer ones to which the shorter ones presumably belong, and search against the user s choice of private and Internet-accessible public 16S rRNA databases. ["16S rRNA" denotes a ribosomal ribonucleic acid (rRNA) sequence that is common to all organisms.] In STITCH, a template 16S rRNA sequence is used to position forward and reverse reads. STITCH then automatically searches known 16S rRNA sequences in the user s chosen database(s) to find the sequence most similar to (the sequence that lies at the smallest edit distance from) each spliced sequence. The result of processing by STITCH is the identification of the most similar well-described bacterium. Whereas previously commercially available software for analyzing genetic sequences operates on one sequence at a time, STITCH can manipulate multiple sequences simultaneously to perform the aforementioned operations. A typical analysis of several dozen sequences (length of the order of 103 base pairs) by use of STITCH is completed in a few minutes, whereas such an analysis performed by use of prior software takes hours or days.