An improved quantum network communication model based on compressed tensor network states

An improved quantum network communication model based on compressed tensor network state

An engineering route to synthesize stable bulk nanocrystalline magnesium with an average grain size of 20 nm

A simple and effective route to preparing bulk nanocrystalline (NC) pure Mg with an average grain size of 20 nm is first proposed by hydrogenation-disproportionation-desorption-recombination (HDDR) followed by spark plasma sintering (SPS) and hot extrusion (HE) techniques. NC Mg is thermodynamically super-stable against annealing at 550 °C and straining under compression and tension. Moreover, the as-extruded NC Mg samples show high tensile yield stress (TYS) of 259 MPa and compressive yield strength (CYS) of 157 MPa, which are about 2 times and about 7–10 times higher than those of their coarse-grain counterparts and the as-cast samples, respectively

Branched polyethylenes attainable using thermally enhanced bis(imino)acenaphthene-nickel catalysts: Exploring the effects of temperature and pressure

The 4,4′-difluorobenzhydryl-containing nickel(II) bromide and chloride chelates, [1-[2,6-{(4-F-C6H4)2CH}2-4-{C(CH3)3}-C6H2N]-2-(ArN)C2C10H6]NiX2 (X = Br: Ar = 2,6-Me2C6H3 Ni1, 2,6-Et2C6H3 Ni2, 2,6-i-Pr2C6H3 Ni3, 2,4,6-Me3C6H2 Ni4, 2,6-Et2-4-MeC6H2 Ni5 and X = Cl: Ar = 2,6-Me2C6H3 Ni6, 2,6-Et2C6H3 Ni7, 2,6-i-Pr2C6H3 Ni8, 2,4,6-Me3C6H2 Ni9, 2,6-Et2-4-MeC6H2 Ni10), have been prepared and fully characterized. The solid-state structures of representative Ni3 and Ni7 display distorted tetrahedral geometries which are maintained in solution with broad paramagnetically shifted resonances a feature of all the 1H and 19F NMR spectra; the effect the halide (Br/Cl) ligand has on the proton and fluorine chemical shifts presents a further point of interest. All ten nickel complexes displayed, on activation with either MAO (methylaluminoxane) or EASC (ethyl aluminum sesquichloride), very high activities (up to 1.36 × 107 g PE mol−1 (Ni) h−1) for ethylene polymerization at either 1 or 10 atm C2H4 with the structural features of the N,N’-ligand influential. Significantly, with EASC as co-catalyst, Ni5 was capable of operating effectively at 90 °C without comprising too much catalytic activity [ca. 4.34 × 106 g PE mol−1 (Ni) h−1]. All the polyethylenes are highly branched with the branching content and type of branch strongly affected by a combination of temperature, pressure and the class of co-catalyst employed. Moreover, good tensile strength (εb up to 2839.5%) and elastic recovery (up to 74%) have been displayed, properties that are characteristic of thermoplastic elastomers (TPEs)

Building High-fidelity Human Body Models from User-generated Data

We propose a key point-based approach, refers to as KPhub-PC, to estimate high-fidelity human body models from low quality point clouds acquired with an affordable 3D scanner and a variation KPhub-I that can achieve the same purpose based on low-resolution single images taken by smartphones. In KPhub-PC, a sparse set of key points is annotated to guide the deformation of a parametric 3D human body model SMPL and then a high-fidelity human body model that can explain the target point cloud is built. Besides building 3D human body models from point clouds, KPhub-I is designed to estimate accurate 3D human body models from single 2D images. The SMPL model is fitted to 2D joints and the boundary of the human body which are detected using CNN based methods automatically. Considering that people are in stable poses at most of the time, a stable pose prior is defined from CMU motion capture dataset for further improving accuracy. Intensive experiments demonstrate that in both types of user-generated data, the proposed approaches can build believable and animatable human body models robustly. Our approach outperforms the state-of-the-arts in the accuracy of both human body shape and pose estimation.</p

Co-catalyst effects on the thermal stability/activity of N,N,N-Co ethylene polymerization Catalysts Bearing Fluoro-Substituted N-2,6-dibenzhydrylphenyl groups

The unsymmetrical bis (arylimino)pyridines, 2-[CMeN{2,6-{(4-FC6H4)2CH}2–4-t-BuC6H2}]-6-(CMeNAr)C5H3N (Ar = 2,6-Me2C6H3 L1, 2,6-Et2C6H3 L2, 2,6-i-Pr2C6H3 L3, 2,4,6-Me3C6H2 L4, 2,6-Et2–4-MeC6H2 L5), each containing one N-aryl group bedecked with ortho-substituted fluorobenzhydryl groups, have been employed in the preparation of the corresponding five-coordinate cobalt (II) chelates, LCoCl2 (Co1 – Co5); the symmetrical comparator [2,6-{CMeN(2,6-(4-FC6H4)2CH)2–4-t-BuC6H2}2C5H3N]CoCl2 (Co6) is also reported. All cobaltous complexes are paramagnetic and have been characterized by 1H/19F NMR spectroscopy, FT-IR spectroscopy and elemental analysis. The molecular structures of Co3 and Co6 highlight the different degrees of steric protection given to the metal center by the particular N-aryl group combination. Depending on the aluminoxane co-catalyst employed to activate the cobalt precatalyst, distinct variations in thermal stability and activity of the catalyst towards ethylene polymerization were exhibited. In particular with MAO, the resultant catalysts reached their optimal performance at 70 °C delivering high activities of up to 10.1 × 106 g PE (mol of Co)−1 h−1 with Co1 > Co4 > Co2 > Co5 > Co3 >> Co6. On the other hand, using MMAO, the catalysts operate most effectively at 30 °C but are by comparison less productive. In general, the polyethylenes were highly linear, narrowly disperse and displayed a wide range of molecular weights [Mw range: 18.5–58.7 kg mol−1 (MAO); 206.1–352.5 kg mol−1 (MMAO)]

Responses of fecal bacterial communities to resistant starch intervention in diabetic rats

Recent studies have revealed that diabetes mellitus caused gut bacterial dysbiosis, and intervention studies aiming to selectively alter the composition and metabolism of the gut microbiota are crucial next steps for investigating the links between the microbiome and diabetes. The sequences encompassing V1–3 16S rDNA hypervariable regions were PCR amplified from rat fecal samples fed with resistant starch (RS). In total, 13 different phyla and 107 different genus were obtained with a 3% distance cut off. The microbiota profile of normal rats was significantly different from that of rats in diabetic control and RS intervention group. The most prominent phyla were Firmicutes and Bacteroidetes in the three groups. The proportion of Proteobacteria was significantly higher in the rats of diabetic control compared to normal group, and RS intervention could inhibit the proliferation of Proteobacteria phyla, including a wide variety of pathogenic species, such as Escherichia-Shige, Klebsiella, and Pseudomona. At genus level, Lactobacillus in the diabetic control was significantly lower than that in the normal group, whereas the feeding of RS increased the amount of Lactobacillus. More importantly, the consumption of RS reduced the composition of Ruminococcus and increased S24-7 norank comparing with the diabetic control. This study might indicate that RS is an effective food ingredient for manipulating the gut microbiota

Du-net based Unsupervised Contrastive Learning for Cancer Segmentation in Histology Images

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CTooth+: A Large-scale Dental Cone Beam Computed Tomography Dataset and Benchmark for Tooth Volume Segmentation

  CTooth+: A Large-scale Dental Cone Beam Computed Tomography Dataset and Benchmark for Tooth Volume Segmentation</p

Multi-factor based session secret key agreement for the Industrial Internet of Things

Industrial Internet of Things (IIoT) is the main field of application of the Internet of Things (IoT). The high degree of autonomy and resource constraints of the IIoT network poses challenges to the security of IIoT. Enabling the legitimate users to securely and remotely access resource-constrained intelligent terminal nodes in an open wireless channel has become a challenge in the IIoT environment. User authentication and key agreement schemes have been proposed for different IoT application scenarios to solve this problem. However, most existing three-party authentication and key agreement schemes for remote users have high computational costs and do not consider sufficient security attributes, such as unlinkability and anonymity. To address the aforementioned problems, the proposed scheme uses the IIoT as the application scenario and proposes a novel three-factor authentication and lightweight remote user identity authentication key agreement. This scheme is effective for devices with limited resources because it mainly uses a one-way hash function and a bitwise XOR operation. The security of the proposed scheme is demonstrated under the real-or-random model via a rigorous formal security analysis

Parallel Key-Insulated Multi-user Searchable Encryption for Industrial Internet of Things

With the rapid development of the industrial Internet of Things (IIoT) and cloud computing, an increasing number of companies outsource their data to cloud servers to save costs. To protect data privacy, sensitive industrial data must be encrypted before being outsourced to cloud servers. A multi-user searchable encryption (MUSE) scheme was introduced to ensure high efficiency of encrypted data retrieval. In an IIoT system with numerous users, the existing MUSE schemes suffer from certain key exposure problems owing to the limited key protection of smart devices and frequent queries by users. In this study, we propose a parallel key-insulated MUSE scheme for IIoT. This scheme utilizes broadcast encryption technology to implement MUSE. In addition, our scheme introduces a key-insulated primitive to improve the tolerance to key exposure. The security of our scheme is proved in the random oracle model. The experimental results show that our scheme achieves high computational efficiency