Review of Anisotropic 2D Materials: Controlled Growth, Optical Anisotropy Modulation, and Photonic Applications

Majorana zero mode, the bound state of Majorana fermion in a condensed matter system, plays a critical role in fault-tolerant topological quantum computation. It can be realized in the vortex of a two-dimensional topological superconductor as a zero-energy excitation. A topological superconductor can be constructed by coupling superconductivity to the topological surface states by the proximity effect. In this review article, we discuss the fabrication of such artificially engineered topological superconductors by molecular beam epitaxy. The topological phase and superconductivity are exhibited in Bi2Se3/NbSe2 and Bi2Te3/NbSe2 heterostructures simultaneously. Several characteristic features of Majorana zero mode have been revealed in the vortex by a low-temperature scanning tunneling microscope and corroborated by theoretical results. The discovery of Majorana zero mode may pave the way for further applications in topological quantum computing.

Majorana zero mode in the vortex of artificial topological superconductor

BACKGROUND
Limited evidence is available regarding the superior clinical properties of bioceramic sealers comparted with traditional standard sealers.


OBJECTIVES
This review aimed to answer the following research questions: 'In healthy patients requiring a root canal treatment (P), what is the efficacy of premixed bioceramic sealers (I) compared with traditional root canal epoxy resin-based sealers (C) in terms of survival, success rates (PICO1) sealer extrusion and resorption (PICO2) post-obturation pain (PICO3) (O)?'


METHODS
Authors independently searched three electronic databases: PubMed (including MEDLINE), Web of Science, Embase and Scopus up to 31 October 2023. This was accompanied by both grey literature and manual search. Detailed selection criteria were applied, namely mature permanent teeth requiring root canal treatment, premixed bioceramic sealer with gutta-percha as an intervention group, a standard filling technique as control group and full-text available in English. A random-effect meta-analysis was used to synthesize the body of evidence regarding the use of bioceramic sealers in root canal treatment and their impact on post-obturation pain. Effect sizes were represented as relative risks on a logarithmic scale for binary outcomes and as mean differences for continuous outcomes.


RESULTS
A total of 941 articles were identified. Fifteen Comparative clinical studies were finally included. Eleven were randomized clinical trials, and four were prospective clinical trials with control group. The follow-up of these studies was not greater than 2 years. No publication bias was observed in any study. No significant differences were observed between the two groups in terms of survival and success rates. A small non-significant lower risk of extrusion was observed for bioceramics. A small, non-significantly lower post-operative-pain within 24-h was observed when bioceramics were used.


DISCUSSION
The majority of current evidence shows inconsistencies in reporting and is of short-term duration. Robust prospective long-term trials are needed in this area to better support future recommendations.


CONCLUSION
This systematic review is the first to analyse several clinical outcomes using premixed sealers. Included studies differed in terms of clinical protocol and operator expertise, but reported a similar outcome when comparing bioceramic versus standard sealers. Tooth survival, treatment outcome, post-operative pain and periapical extrusion were similar and presented no significant differences between the two sealer types.


REGISTRATION
PROSPERO database (CRD42023449151).

The efficacy of premixed bioceramic sealers versus standard sealers on root canal treatment outcome, extrusion rate and post-obturation pain: A systematic review and meta-analysis.

/pdf/special-topic-on-topological-semimetals-new-directions-4oq8if4a67.pdf

Special topic on topological semimetals—New directions

We present a study of angle-resolved quantum oscillations of electric and thermoelectric transport coefficients in semimetallic WTe2, which has the particularity of displaying a large B(2) magnetoresistance. The Fermi surface consists of two pairs of electronlike and holelike pockets of equal volumes in a "Russian doll" structure. The carrier density, Fermi energy, mobility, and the mean-free path of the system are quantified. An additional frequency is observed above a threshold field and attributed to the magnetic breakdown across two orbits. In contrast to all other dilute metals, the Nernst signal remains linear in the magnetic field even in the high-field (ωcτ≫1) regime. Surprisingly, none of the pockets extend across the c axis of the first Brillouin zone, making the system a three-dimensional metal with moderate anisotropy in Fermi velocity, yet a large anisotropy in the mean-free path.

Quantum Oscillations, Termoelectric Coefficents, and the Fermi Surface of Semimetallic WTe2

This study aimed to compare the effect of a bioceramic sealer (iRoot SP) and a resin-based sealer (AH Plus) on the outcome of root canal treatment in a 2-year follow-up. Seventy-six teeth with irreversibly or necrotic pulp were recruited. After instrumentation and disinfection, the root canals were obturated using warm vertical compaction with iRoot SP (n = 43) or AH Plus (n = 33). Patients were followed up by clinical and radiographic examination at 6 12 and 24 months with recall rates of 84.2%, 65.8% and 48.7%, respectively. During each recall session, the success rates were 80%, 85.2% and 85% in the iRoot SP group and 82.8%, 91.3% and 88.2% in the AH Plus group. The success rates of the two groups did not differ significantly (p > 0.05). The bioceramic sealer resulted in a similar clinical performance and success rate to the resin-based sealer in endodontic treatment during a 2-year follow-up.

Outcome of root canal treatment using warm vertical compaction with bioceramic and resin-based sealers: A randomised clinical trial.

We report the crystal and electronic structures of a non-centrosymmetric quasi-two-dimensional (2D), candidate of topological semimetal AuTe2Br. The Fermi surface of this layered compound consists of 2D-like, topological trivial electron and non-trivial hole pockets which host a Dirac cone along the kz direction. Our transport measurements on the single crystals show highly anisotropic, compensated low-density electrons and holes, both of which exhibit ultrahigh mobility at a level of 10^5cm^2V^-1s^-1 at low temperature. The highly mobile, compensated carriers lead a non-saturated, parabolic magnetoresistance as large as 3*10^5 in single-crystalline AuTe2Br in a magnetic field up to 58 T.

Highly Mobile Carriers in a Candidate of Quasi-Two-Dimensional Topological Semimetal AuTe$_2$Br

Abstract The study on quantum spin Hall effect and topological insulators formed the prologue to the surge of research activities in topological materials in the past decade. Compared to intricately engineered quantum wells, three-dimensional weak topological insulators provide a natural route to the quantum spin Hall effect, due to the adiabatic connection between them and a stack of quantum spin Hall insulators, and the convenience in exfoliation of samples associated with their van der Waals-type structure. Despite these advantages, both theoretical prediction and experimental identification of weak topological insulators remain scarce. Here, based on first-principles calculations, we show that AuTe 2 Br locates at the boundary between a strong and a weak topological semimetal state. We identify the key structural parameter that dictates the traversal of the topological transition, which can be easily realized in experiments. More interestingly, the critical topology of AuTe 2 Br persists up to an applied pressure of ~15.4 GPa before a structural phase transition accompanied by a change of electronic topology and the onset of superconductivity. Our results establish AuTe 2 Br as a new candidate for an effective tuning between weak and strong topological phases in a single material, with the potential to realize various other topological phases of matter. 

/pdf/critical-topology-and-pressure-induced-superconductivity-in-b8jfser7.pdf

Critical topology and pressure-induced superconductivity in the van der Waals compound AuTe2Br

Features play a critical role in computer vision tasks. Deep learning methods have resulted in significant breakthroughs in the field of object detection, but it is still an extremely challenging obstacle when an object is very small. In this work, we propose a feature-enhancement- and channel-attention-guided single-shot detector called the FCSSD with four modules to improve object detection performance. Specifically, inspired by the structure of atrous convolution, we built an efficient feature-extraction module (EFM) in order to explore contextual information along the spatial dimension, and then pyramidal aggregation module (PAM) is presented to explore the semantic features of deep layers, thus reducing the semantic gap between multi-scale features. Furthermore, we construct an effective feature pyramid refinement fusion (FPRF) to refine the multi-scale features and create benefits for richer object knowledge. Finally, an attention-guided module (AGM) is developed to balance the channel weights and optimize the final integrated features on each level; this alleviates the aliasing effects of the FPN with negligible computational costs. The FCSSD exploits richer information of shallow layers and higher layers by using our designed modules, thus accomplishing excellent detection performance for multi-scale object detection and reaching a better tradeoff between accuracy and inference time. Experiments on PASCAL VOC and MS COCO datasets were conducted to evaluate the performance, showing that our FCSSD achieves competitive detection performance compared with existing mainstream object detection methods.

https://www.mdpi.com/1424-8220/22/18/6857/pdf?version=1663073232

Single-Shot Object Detection via Feature Enhancement and Channel Attention

Visual Transformers (ViTs) have shown impressive performance due to their powerful coding ability to catch spatial and channel information. MetaFormer gives us a general architecture of transformers consisting of a token mixer and a channel mixer through which we can generally understand how transformers work. It is proved that the general architecture of the ViTs is more essential to the models’ performance than self-attention mechanism. Then, Depth-wise Convolution layer (DwConv) is widely accepted to replace local self-attention in transformers. In this work, a pure convolutional "transformer" is designed. We rethink the difference between the operation of self-attention and DwConv. It is found that the self-attention layer, with an embedding layer, unavoidably affects channel information, while DwConv only mixes the token information per channel. To address the differences between DwConv and self-attention, we implement DwConv with an embedding layer before as the token mixer to instantiate a MetaFormer block and a model named EmbedFormer is introduced. Meanwhile, SEBlock is applied in the channel mixer part to improve performance. On the ImageNet-1K classification task, EmbedFormer achieves top-1 accuracy of 81.7% without additional training images, surpassing the Swin transformer by +0.4% in similar complexity. In addition, EmbedFormer is evaluated in downstream tasks and the results are entirely above those of PoolFormer, ResNet and DeiT. Compared with PoolFormer-S24, another instance of MetaFormer, our EmbedFormer improves the score by +3.0% box AP/+2.3% mask AP on the COCO dataset and +1.3% mIoU on the ADE20K.

https://www.mdpi.com/1424-8220/22/24/9854/pdf?version=1671085357

EmbedFormer: Embedded Depth-Wise Convolution Layer for Token Mixing

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Papers

Outcome of root canal treatment using warm vertical compaction with bioceramic and resin-based sealers: A randomised clinical trial.

Highly Mobile Carriers in a Candidate of Quasi-Two-Dimensional Topological Semimetal AuTe$_2$Br

Critical topology and pressure-induced superconductivity in the van der Waals compound AuTe2Br

Single-Shot Object Detection via Feature Enhancement and Channel Attention

EmbedFormer: Embedded Depth-Wise Convolution Layer for Token Mixing