Revisiting Rubik's Cube: Self-supervised Learning with Volume-wise Transformation for 3D Medical Image Segmentation

Deep learning highly relies on the quantity of annotated data. However, the annotations for 3D volumetric medical data require experienced physicians to spend hours or even days for investigation. Self-supervised learning is a potential solution to get rid of the strong requirement of training data by deeply exploiting raw data information. In this paper, we propose a novel self-supervised learning framework for volumetric medical images. Specifically, we propose a context restoration task, i.e., Rubik's cube++, to pre-train 3D neural networks. Different from the existing context-restoration-based approaches, we adopt a volume-wise transformation for context permutation, which encourages network to better exploit the inherent 3D anatomical information of organs. Compared to the strategy of training from scratch, fine-tuning from the Rubik's cube++ pre-trained weight can achieve better performance in various tasks such as pancreas segmentation and brain tissue segmentation. The experimental results show that our self-supervised learning method can significantly improve the accuracy of 3D deep learning networks on volumetric medical datasets without the use of extra data.Comment: Accepted by MICCAI 202

A Model for the Prediction of Fiber Elasticity

A model is presented that enables the elastic properties of wood fibers to be estimated from the properties of its polymeric constituents, cellulose, hemicellulose, and lignin. The influence of the value of the axial stiffness of the cellulose crystal is demonstrated, its proper value being discussed in comparison with experimental data on fibers. The effects on fiber stiffness of the S2 fibril angle, the fibril angles of other layers, the crystallinity, and layer thicknesses are analyzed. The manner in which the effect of a variation in yield can be simulated by a change in shape factor of the reinforcing cellulose crystals is demonstrated, the cell wall thus being considered to be a discontinuous reinforced composite

Synthesis and characterisation of lamellar ZnS nanosheets containing intercalated diamines

A solvothermal method has been used to preparehybrid inorganic-organic composites with a lamellar structure in which layers of wurtzite ZnS are separated by intercalated diamine molecules. A hybrid composite prepared with diethylenetriamine has been isolated and characterisedand its structure and properties compared with those of the composite prepared using ethylenediamine. Comparative structural and morphological studies of the two lamellar hybrid composites are described on the basis of powder XRD, electron and scanning probe microscopies and thermal analysis of the materials

Improved Constraints on Sterile Neutrino Mixing from Disappearance Searches in the MINOS, MINOS+, Daya Bay, and Bugey-3 Experiments.

Searches for electron antineutrino, muon neutrino, and muon antineutrino disappearance driven by sterile neutrino mixing have been carried out by the Daya Bay and MINOS+ collaborations. This Letter presents the combined results of these searches, along with exclusion results from the Bugey-3 reactor experiment, framed in a minimally extended four-neutrino scenario. Significantly improved constraints on the θ_{μe} mixing angle are derived that constitute the most constraining limits to date over five orders of magnitude in the mass-squared splitting Δm_{41}^{2}, excluding the 90% C.L. sterile-neutrino parameter space allowed by the LSND and MiniBooNE observations at 90% CL_{s} for Δm_{41}^{2}<13  eV^{2}. Furthermore, the LSND and MiniBooNE 99% C.L. allowed regions are excluded at 99% CL_{s} for Δm_{41}^{2}<1.6 eV^{2}

Is spoken language all-or-nothing? Implications for future speech-based human-machine interaction

Recent years have seen significant market penetration for voice-based personal assistants such as Apple’s Siri. However, despite this success, user take-up is frustratingly low. This article argues that there is a habitability gap caused by the inevitablemismatch between the capabilities and expectations of human users and the features and benefits provided by contemporary technology. Suggestions aremade as to how such problems might be mitigated, but a more worrisome question emerges: “is spoken language all-or-nothing”? The answer, based on contemporary views on the special nature of (spoken) language, is that there may indeed be a fundamental limit to the interaction that can take place between mismatched interlocutors (such as humans and machines). However, it is concluded that interactions between native and non-native speakers, or between adults and children, or even between humans and dogs, might provide critical inspiration for the design of future speech-based human-machine interaction

Phase-plate electron microscopy: a novel imaging tool to reveal close-to-life nano-structures

After slow progress in the efforts to develop phase plates for electron microscopes, functional phase plate using thin carbon film has been reported recently. It permits collecting high-contrast images of close-to-life biological structures with cryo-fixation and without staining. This report reviews the state of the art for phase plates and what is innovated with them in biological electron microscopy. The extension of thin-film phase plates to the material-less type using electrostatic field or magnetic field is also addressed

The more the merrier? Increasing group size may be detrimental to decision-making performance in nominal groups

<div><p>Demonstrability—the extent to which group members can recognize a correct solution to a problem—has a significant effect on group performance. However, the interplay between group size, demonstrability and performance is not well understood. This paper addresses these gaps by studying the joint effect of two factors—the difficulty of solving a problem and the difficulty of verifying the correctness of a solution—on the ability of groups of varying sizes to converge to correct solutions. Our empirical investigations use problem instances from different computational complexity classes, NP-Complete (NPC) and PSPACE-complete (PSC), that exhibit similar solution difficulty but differ in verification difficulty. Our study focuses on nominal groups to isolate the effect of problem complexity on performance. We show that NPC problems have higher demonstrability than PSC problems: participants were significantly more likely to recognize correct and incorrect solutions for NPC problems than for PSC problems. We further show that increasing the group size can actually <i>decrease</i> group performance for some problems of low demonstrability. We analytically derive the boundary that distinguishes these problems from others for which group performance monotonically improves with group size. These findings increase our understanding of the mechanisms that underlie group problem-solving processes, and can inform the design of systems and processes that would better facilitate collective decision-making.</p></div

Monodisperse α-Fe2O3 Mesoporous Microspheres: One-Step NaCl-Assisted Microwave-Solvothermal Preparation, Size Control and Photocatalytic Property

A simple one-step NaCl-assisted microwave-solvothermal method has been developed for the preparation of monodisperse α-Fe2O3 mesoporous microspheres. In this approach, Fe(NO3)3 · 9H2O is used as the iron source, and polyvinylpyrrolidone (PVP) acts as a surfactant in the presence of NaCl in mixed solvents of H2O and ethanol. Under the present experimental conditions, monodisperse α-Fe2O3 mesoporous microspheres can form via oriented attachment of α-Fe2O3 nanocrystals. One of the advantages of this method is that the size of α-Fe2O3 mesoporous microspheres can be adjusted in the range from ca. 170 to ca. 260 nm by changing the experimental parameters. High photocatalytic activities in the degradation of salicylic acid are observed for α-Fe2O3 mesoporous microspheres with different specific surface areas