Ferroelectricity in layered bismuth oxide down to 1 nanometer

Atomic-scale ferroelectrics are of great interest for high-density electronics, particularly field-effect transistors, low-power logic, and nonvolatile memories. We devised a film with a layered structure of bismuth oxide that can stabilize the ferroelectric state down to 1 nanometer through samarium bondage. This film can be grown on a variety of substrates with a cost-effective chemical solution deposition. We observed a standard ferroelectric hysteresis loop down to a thickness of ~1 nanometer. The thin films with thicknesses that range from 1 to 4.56 nanometers possess a relatively large remanent polarization from 17 to 50 microcoulombs per square centimeter. We verified the structure with first-principles calculations, which also pointed to the material being a lone pair-driven ferroelectric material. The structure design of the ultrathin ferroelectric films has great potential for the manufacturing of atomic-scale electronic devices.This work was supported by the National Key Research and Development Program of China (2018YFA0703700, 2017YFE0119700, and 2020YFA0406202), the National Natural Science Foundation of China (21801013, 51774034, 51961135107, 62104140, 12175235, 22090042, 12074016, 11704041, and 12274009), the Fundamental Research Funds for the Central Universities (FRF-IDRY-19-007 and FRF-TP-19-055A2Z), the National Program for Support of Top-notch Young Professionals, the Young Elite Scientists Sponsorship Program by CAST (2019-2021QNRC), and Lingang Laboratory Open Research Fund (grant LG-QS-202202-11). Use of the Beijing Synchrotron Radiation Facility (1W1A beamlines, China) of the Chinese Academy of Sciences is acknowledged. Y.-W.F. acknowledges the support of Masaki Azuma’s group during his stay at the Tokyo Institute of Technology. Y.L. acknowledges the support of the Beijing Innovation Team Building Program (grant no. IDHT20190503), the Beijing Natural Science Foundation (Z210016), the Research and Development Project from the Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering (2022SX-TD001), and the General Program of Science and Technology Development Project of Beijing Municipal Education Commission (KM202110005003).Peer reviewe

Unifying Model Explainability and Robustness for Joint Text Classification and Rationale Extraction

Recent works have shown explainability and robustness are two crucial ingredients of trustworthy and reliable text classification. However, previous works usually address one of two aspects: i) how to extract accurate rationales for explainability while being beneficial to prediction; ii) how to make the predictive model robust to different types of adversarial attacks. Intuitively, a model that produces helpful explanations should be more robust against adversarial attacks, because we cannot trust the model that outputs explanations but changes its prediction under small perturbations. To this end, we propose a joint classification and rationale extraction model named AT-BMC. It includes two key mechanisms: mixed Adversarial Training (AT) is designed to use various perturbations in discrete and embedding space to improve the model’s robustness, and Boundary Match Constraint (BMC) helps to locate rationales more precisely with the guidance of boundary information. Performances on benchmark datasets demonstrate that the proposed AT-BMC outperforms baselines on both classification and rationale extraction by a large margin. Robustness analysis shows that the proposed AT-BMC decreases the attack success rate effectively by up to 69%. The results indicate that there are connections between robust models and better explanations

Protocol for efficient and self-healing near-infrared perovskite light-emitting diodes.

Preparation of highly efficient and stable perovskite light-emitting diodes (PeLEDs) with reproducible device performance is challenging. This protocol describes steps for fabrication of high-performance and self-healing PeLEDs. These include instructions for synthesis of charge-transporting zinc oxide (ZnO) nanocrystals, step-by-step device fabrication, and control over self-healing of the degraded devices. For complete details on the use and execution of this protocol, please refer to Teng et al. (2021).Funding agencies: RC Starting Grant (no. 717026), the Swedish Energy AgencyEnergimyndigheten (no. 48758-1), and the Swedish Government Strategic Research Area in Mate-rials Science on Functional Materials Linko ̈ ping University (Faculty Grant SFO-Mat-LiU no. 2009-00971). Y.Z. and B.S. also thank the support from Macau SAR (file no. 0044/2021/A)</p

PlGF/FLT-1 deficiency leads to reduced STAT3-C/EBPβ signaling and aberrant polarization in decidual macrophages during early spontaneous abortion

IntroductionDysregulated macrophage polarization (excessive M1-like or limited M2-like macrophages) in the early decidua contributes to allogeneic fetal rejection and thus early spontaneous abortion. However, the modulators of M1/M2 balance at the early maternal-fetal interface remain mostly unknown.MethodsFirst-trimester decidual tissues were collected from normal pregnant women undergoing elective pregnancy terminations and patients with spontaneous abortion. We measured the expression of placental growth factor (PlGF) and Fms-like-tyrosine-kinase receptor 1 (FLT-1), and characterized the profiles of macrophages in decidua. Notably, we investigated the effect of recombinant human PlGF (rhPlGF) on decidual macrophages (dMös) from normal pregnancy and revealed the underlying mechanisms both in vitro and in vivo.ResultsThe downregulated expression of PlGF/ FLT-1 may result in spontaneous abortion by inducing the M1-like deviation of macrophages in human early decidua. Moreover, the CBA/J×DBA/2 abortion-prone mice displayed a lower FLT-1 expression in uterine macrophages than did CBA/J×BALB/c control pregnant mice. In in vitro models, rhPlGF treatment was found to drive the M2-like polarization of dMös via the STAT3/CEBPB signaling pathway. These findings were further supported by a higher embryo resorption rate and uterine macrophage dysfunction in Pgf knockout mice, in addition to the reduced STAT3 transcription and C/EBPâ expression in uterine macrophages.DiscussionPlGF plays a key role in early pregnancy maintenance by skewing dMös toward an M2-like phenotype via the FLT-1-STAT3-C/EBP â signaling pathway. Excitingly, our results highlight a rationale that PlGF is a promising target to prevent early spontaneous abortion

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Modern healthcare has a sharp focus on data aggregation and processing technologies. Consequently, from a data perspective, a patient may be regarded as a timestamped list of medical conditions and their corresponding corrective interventions. Technologies to securely aggregate and access data for individual patients in the quest for precision medicine have led to the adoption of Digital Twins in healthcare. Digital Twins are used in manufacturing and engineering to produce digital models of physical objects that capture the essence of device operation to enable and drive optimization. Thus, a patient’s Digital Twin can significantly improve health data sharing. However, creating the Digital Twin from multiple data sources, such as the patient’s electronic medical records (EMR) and personal health records (PHR) from wearable devices, presents some risks to the security of the model and the patient. The constituent data for the Digital Twin should be accessible only with permission from relevant entities and thus requires authentication, privacy, and provable provenance. This paper proposes a blockchain-secure patient Digital Twin that relies on smart contracts to automate the updating and communication processes that maintain the Digital Twin. The smart contracts govern the response the Digital Twin provides when queried, based on policies created for each patient. We highlight four research points: access control, interaction, privacy, and security of the Digital Twin and we evaluate the Digital Twin in terms of latency in the network, smart contract execution times, and data storage costs.</div

Digital Twin instances from multi-data sources.

Modern healthcare has a sharp focus on data aggregation and processing technologies. Consequently, from a data perspective, a patient may be regarded as a timestamped list of medical conditions and their corresponding corrective interventions. Technologies to securely aggregate and access data for individual patients in the quest for precision medicine have led to the adoption of Digital Twins in healthcare. Digital Twins are used in manufacturing and engineering to produce digital models of physical objects that capture the essence of device operation to enable and drive optimization. Thus, a patient’s Digital Twin can significantly improve health data sharing. However, creating the Digital Twin from multiple data sources, such as the patient’s electronic medical records (EMR) and personal health records (PHR) from wearable devices, presents some risks to the security of the model and the patient. The constituent data for the Digital Twin should be accessible only with permission from relevant entities and thus requires authentication, privacy, and provable provenance. This paper proposes a blockchain-secure patient Digital Twin that relies on smart contracts to automate the updating and communication processes that maintain the Digital Twin. The smart contracts govern the response the Digital Twin provides when queried, based on policies created for each patient. We highlight four research points: access control, interaction, privacy, and security of the Digital Twin and we evaluate the Digital Twin in terms of latency in the network, smart contract execution times, and data storage costs.</div

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Modern healthcare has a sharp focus on data aggregation and processing technologies. Consequently, from a data perspective, a patient may be regarded as a timestamped list of medical conditions and their corresponding corrective interventions. Technologies to securely aggregate and access data for individual patients in the quest for precision medicine have led to the adoption of Digital Twins in healthcare. Digital Twins are used in manufacturing and engineering to produce digital models of physical objects that capture the essence of device operation to enable and drive optimization. Thus, a patient’s Digital Twin can significantly improve health data sharing. However, creating the Digital Twin from multiple data sources, such as the patient’s electronic medical records (EMR) and personal health records (PHR) from wearable devices, presents some risks to the security of the model and the patient. The constituent data for the Digital Twin should be accessible only with permission from relevant entities and thus requires authentication, privacy, and provable provenance. This paper proposes a blockchain-secure patient Digital Twin that relies on smart contracts to automate the updating and communication processes that maintain the Digital Twin. The smart contracts govern the response the Digital Twin provides when queried, based on policies created for each patient. We highlight four research points: access control, interaction, privacy, and security of the Digital Twin and we evaluate the Digital Twin in terms of latency in the network, smart contract execution times, and data storage costs.</div

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Modern healthcare has a sharp focus on data aggregation and processing technologies. Consequently, from a data perspective, a patient may be regarded as a timestamped list of medical conditions and their corresponding corrective interventions. Technologies to securely aggregate and access data for individual patients in the quest for precision medicine have led to the adoption of Digital Twins in healthcare. Digital Twins are used in manufacturing and engineering to produce digital models of physical objects that capture the essence of device operation to enable and drive optimization. Thus, a patient’s Digital Twin can significantly improve health data sharing. However, creating the Digital Twin from multiple data sources, such as the patient’s electronic medical records (EMR) and personal health records (PHR) from wearable devices, presents some risks to the security of the model and the patient. The constituent data for the Digital Twin should be accessible only with permission from relevant entities and thus requires authentication, privacy, and provable provenance. This paper proposes a blockchain-secure patient Digital Twin that relies on smart contracts to automate the updating and communication processes that maintain the Digital Twin. The smart contracts govern the response the Digital Twin provides when queried, based on policies created for each patient. We highlight four research points: access control, interaction, privacy, and security of the Digital Twin and we evaluate the Digital Twin in terms of latency in the network, smart contract execution times, and data storage costs.</div

A visual representation of transactions on the blockchain.

A visual representation of transactions on the blockchain.</p