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The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.

In order to accelerate the construction of a resource-saving and environmentally-friendly industrial ecosystem, this paper uses the Tapio decoupling analysis model to calculate the decoupling index of Tianjin’s industrial economic growth and the major environmental pollutants of the industry from 2005 to 2015 and analyze the decoupling status. The results show that the decoupling state of Tianjin’s economic growth and environmental pollution from 2005 to 2015 is generally in a strong positive decoupling and a weak growth decoupling, but the decoupling state of some environmental pollution factors has temporarily deteriorated. The relationship between industrial economic growth and industrial pollutant emissions has eased in the 12th Five-Year Plan.

Biological supramolecular assemblies, such as phospholipid bilayer membranes, have been used to demonstrate signal processing via short-term synaptic plasticity (STP) in the form of paired pulse facilitation and depression, emulating the brain’s efficiency and flexible cognitive capabilities. However, STP memory in lipid bilayers is volatile and cannot be stored or accessed over relevant periods of time, a key requirement for learning. Using droplet interface bilayers (DIBs) composed of lipids, water and hexadecane, and an electrical stimulation training protocol featuring repetitive sinusoidal voltage cycling, we show that DIBs displaying memcapacitive properties can also exhibit persistent synaptic plasticity in the form of long-term potentiation (LTP) associated with capacitive energy storage in the phospholipid bilayer. The time scales for the physical changes associated with the LTP range between minutes and hours, and are substantially longer than previous STP studies, where stored energy dissipated after only a few seconds. STP behavior is the result of reversible changes in bilayer area and thickness. On the other hand, LTP is the result of additional molecular and structural changes to the zwitterionic lipid headgroups and the dielectric properties of the lipid bilayer that result from the buildup of an increasingly asymmetric charge distribution at the bilayer interfaces.

Herein, a first example of energetic-energetic cocrystal polymorphs with a 1:1 M ratio was discovered by cocrystallizing CL-20 (2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane) with 1,3-DNP (1,3-dinitropyrazole). These two energetic cocrystal polymorphs (cocrystal 1 and cocrystal 2) exhibit distinct crystal packing styles, which lead to significant variations in their physicochemical properties. Notably, cocrystal 2 has a high density of 1.963 g⋅cm−3 at 170 K, exhibiting high detonation performances (9187 m⋅s−1; 38.68 GPa) comparable to HMX (1,3,5,7-tetranitro-1,3,5,7-tetrazocane) meanwhile displaying an improved safety (10 J) relative to RDX (1,3,5-trinitro-1,3,5-triazinane), making it a potential high-energy, low-sensitivity energetic material. This work opens up a new strategy to deeply tune properties of energetic materials by constructing energetic-energetic cocrystal polymorphs. These energetic cocrystal polymorphs represent a new field of energetic materials that has not yet been studied. The first example of energetic-energetic cocrystal polymorphs was discovered by cocrystallizing CL-20 (2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane) with 1,3-DNP (1,3-dinitropyrazole). These energetic-energetic cocrystal polymorphs represent a new field of energetic materials that has not yet been studied. [Display omitted]

Local and customized services are realized with new type computing architecture by utilizing the spare resources distributed on the helper nodes (HNs) throughout the network. The heterogeneity of mobile edge and fog computing networks makes them natural to support multitarget tasks, and efficient task scheduling is always a fundamental and hot issue in multitask multihelper (MTMH) computing networks. Unlike most of the researches concentrating on the optimization of a single or limited service metrics, this article proposes a service framework for multitarget tasks, which is more universal for future 6G networks supporting customized services. The comprehensive quality of service (CQoS) is constructed to indicate the comprehensive objectives of the task nodes (TNs) with multiple targets. By formulating and transforming the CQoS maximal problem into two one-variable form subproblems, an algorithm named scheduling of comprehensive objectives for tasks with multitargets (SCOTT) is proposed. The SCOTT algorithm achieves the optimal offloading service solutions considering service metrics including delay, energy consumption, and economic cost. Extensive numerical simulations are carried out, which indicate that the proposed SCOTT algorithm can effectively achieve the optimal offloading solutions including node selection, task division, and transmission power for TNs with various service targets. Moreover, the universal applicability of the SCOTT algorithm is verified with case studies and numerical results.

Presented in this Dissertation are a series of studies on Janus liposomes, their formation, self-assembly and motion behaviors. Liposomes are closed, spherical lipid bilayer assemblies dispersed in water. Since their discovery in the 1960s, liposomes have become indispensable tools and ingredients not only in basic research but also in industry. Janus liposomes, on the other hand, are liposomes containing broken symmetry and surface heterogeneity in their structures. These less studied lipid structures are the focus of this Dissertation, specifically.In Chapter 1, a literature survey is given on research topics mostly related to this work. Through the survey, the feasibility of preparing Janus liposomes is determined. In Chapter 2, I describe a high-yield procedure for preparing micro-sized (giant) Janus liposomes via gel-assisted lipid swelling. An optimized formation procedure is presented, which reproducibly yields large liposome populations dominated by a single domain configuration. In Chapter 3, by combining gel-assisted lipid hydration with membrane-based lipid extrusion, I demonstrate a general procedure for size-controlled preparation for giant unilamellar liposomes, including homogeneous and Janus liposomes. In Chapter 4, I describe a straightforward strategy to incorporate biotin-conjugated lipids into Janus liposomes’ formation and clustering behavior of these liposomes directed by biotin-avidin affinity binding. In Chapter 5, I present the first report on dipolar Janus liposomes – liposomes that contain opposite surface charged decorating the two hemispheres of the same colloidal body. Using confocal fluorescence microscopy, the electrokinetic motion as well as electrostatic self-assembly of these new dipolar Janus particles are followed. Finally, in Chapter 6, I draw the main conclusion of my studies and offer an outlook of what might be accomplished in the near future along this direction.

Abstract Polyzwitterions (PZs) are considered as model synthetic analogs of intrinsically disordered proteins. Based on this analogy, PZs in dilute aqueous solutions are expected to attain either globular (i.e. molten, compact) or random coil conformations. Addition of salt is expected to open these conformations. To the best of our knowledge, these hypotheses about conformations of PZs have never been verified. In this study, we test these hypotheses by studying effects of added salt [potassium bromide (KBr)] on gyration and hydrodynamic radii of poly(sulfobetaine methacrylate) in dilute aqueous solutions using dynamic light scattering and small-angle X-ray scattering, respectively. Effects of zwitteration are revealed by direct comparisons of the PZs with the polymers of the same backbone but containing (1) no explicit charges on side groups such as poly(2-dimethylaminoethyl methacrylate)s and (2) explicit cationic side groups with tertiary amino bromide pendants. Zeta-potential measurements, transmission electron microscopy, and ab initio molecular dynamics simulations reveal that the PZs acquire net positive charge in near salt-free conditions due to protonation but retain coiled conformations. Added KBr leads to nonmonotonic changes exhibiting an increase followed by a decrease in radius of gyration (and hydrodynamic radius), which are called antipolyelectrolyte and polyelectrolyte effects, respectively. Charge regulation and screening of charge–charge interactions are discussed in relation to the antipolyelectrolyte and polyelectrolyte effects, respectively, which highlight the importance of salt in affecting net charge and conformations of PZs.

Background: Wernicke’s concept of ‘sejunction’ or aberrant associations among specialized brain regions is one of the earliest hypotheses attempting to explain the myriad of symptoms in psychotic disorders. Unbiased data mining of all possible brain-wide connections in large data sets is an essential first step in localizing these aberrant circuits. Methods: We analyzed functional connectivity using the largest resting-state neuroimaging data set reported to date in the schizophrenia literature (415 patients vs. 405 controls from UK, USA, Taiwan, and China). An exhaustive brain-wide association study at both regional and voxel-based levels enabled a continuous data-driven discovery of the key aberrant circuits in schizophrenia. Results: Results identify the thalamus as the key hub for altered functional networks in patients. Increased thalamus–primary somatosensory cortex connectivity was the most significant aberration in schizophrenia ( P =10 −18 ). Overall, a number of thalamic links with motor and sensory cortical regions showed increased connectivity in schizophrenia, whereas thalamo–frontal connectivity was weakened. Network changes were correlated with symptom severity and illness duration, and support vector machine analysis revealed discrimination accuracies of 73.53–80.92%. Conclusions: Widespread alterations in resting-state thalamocortical functional connectivity is likely to be a core feature of schizophrenia that contributes to the extensive sensory, motor, cognitive, and emotional impairments in this disorder. Changes in this schizophrenia-associated network could be a reliable mechanistic index to discriminate patients from healthy controls. Locating the key altered brain connections in schizophrenia Altered communication between functional networks connecting parts of the forebrain likely contribute to the complex and diverse symptoms in psychotic disorders such as schizophrenia. These symptoms may be due to 'dysconnectivity' - the fragmentation of functional connections in the brain. However, findings from small-scale brain imaging investigations to pinpoint affected regions are often contradictory. In the largest brain-wide imaging study of its kind to date, Jianfeng Feng at Fudan University, China/Warwick University, UK, together with an international team, used data collected from resting-state functional MRI brain scans of 415 schizophrenia patients and 405 healthy controls from hospitals in four different countries to find which regions and connections were most affected. The team identified the thalamus, an area in the center of the forebrain with widespread connections throughout the brain, as the main region of impaired functionality in patients. Crucially, they also showed that altered connections between the thalamus and parietal sensorimotor and frontal cortical regions were associated with the severity of specific symptoms.

In this paper, a two-stage intelligent scheduler is proposed to minimize the packet-level delay jitter while guaranteeing delay bound. Firstly, Lyapunov technology is employed to transform the delay-violation constraint into a sequential slot-level queue stability problem. Secondly, a hierarchical scheme is proposed to solve the resource allocation between multiple base stations and users, where the multi-agent reinforcement learning (MARL) gives the user priority and the number of scheduled packets, while the underlying scheduler allocates the resource. Our proposed scheme achieves lower delay jitter and delay violation rate than the Round-Robin Earliest Deadline First algorithm and MARL with delay violation penalty.

Multi-source unsupervised domain adaptation (MUDA) aims to transfer knowledge from related source domains to an unlabeled target domain. While recent MUDA methods have shown promising results, most focus on aligning the overall feature distributions across source domains, which can lead to negative effects due to redundant features within each domain. Moreover, there is a significant performance gap between MUDA and supervised methods. To address these challenges, we propose a novel approach called Dynamic Domain Discrepancy Adjustment for Active Multi-Domain Adaptation (D3AAMDA). Firstly, we establish a multi-source dynamic modulation mechanism during the training process based on the degree of distribution differences between source and target domains. This mechanism controls the alignment level of features between each source domain and the target domain, effectively leveraging the local advantageous feature information within the source domains. Additionally, we propose a Multi-source Active Boundary Sample Selection (MABS) strategy, which utilizes a guided dynamic boundary loss to design an efficient query function for selecting important samples. This strategy achieves improved generalization to the target domain with minimal sampling costs. We extensively evaluate our proposed method on commonly used domain adaptation datasets, comparing it against existing UDA and ADA methods. The experimental results unequivocally demonstrate the superiority of our approach.