Recovering quantum entanglement after its certification.

Entanglement is a crucial quantum resource with broad applications in quantum information science. For harnessing entanglement in practice, it is a prerequisite to certify the entanglement of a given quantum state. However, the certification process itself destroys the entanglement, thereby precluding further exploitation of the entanglement. Resolving this conflict, here, we present a protocol that certifies the entanglement of a quantum state without complete destruction and then probabilistically recovers the original entanglement to provide useful entanglement for further quantum applications. We experimentally demonstrate this protocol in a photonic quantum system and highlight its usefulness for selecting high-quality entanglement from a realistic entanglement source. Moreover, our study reveals various trade-off relations among the physical quantities involved in the protocol. Our results show how entanglement certification can be made compatible with subsequent quantum applications and be beneficial to sort entanglement for better performance in quantum technologies.

miR-429 Suppresses Endometrial Cancer Progression and Drug Resistance via DDX53.

(1) Background: To examine miR-429-meditated DEAD (Asp-Glu-Ala-Asp) box polypeptide 53 (DDX53) function in endometrial cancer (EC). (2) Methods: DDX53 and miR-429 levels were measured using quantitative real-time polymerase chain reaction and western blotting assays, cell invasion and migration using Transwell invasion and wound healing assays, and cell proliferation using colony-forming/proliferation assays. A murine xenograft model was also generated to examine miR-429 and DDX53 functions in vivo. (3) Results: DDX53 overexpression (OE) promoted key cancer phenotypes (proliferation, migration, and invasion) in EC, while in vivo, DDX53 OE hindered tumor growth in the murine xenograft model. Moreover, miR-429 was identified as a novel miRNA-targeting DDX53, which suppressed EC proliferation and invasion. (4) Conclusions: DDX53 and miR-429 regulatory mechanisms could provide novel molecular therapies for EC.

Oral Squamous Cell Carcinoma and Concomitant Primary Tumors, What Do We Know? A Review of the Literature.

Head and neck cancer is among the top ten cancers worldwide, with most lesions in the oral cavity. Oral squamous cell carcinoma (OSCC) accounts for more than 90% of all oral malignancies and is a significant public health concern. Patients with OSCC are at increased risk for developing concomitant tumors, especially in the oral cavity, due to widely genetically susceptible mucosa to carcinogenic factors. Based on fulfilling specific criteria, these concomitant tumors can be called second primary tumors (SPTs), which can be further categorized into metachronous and synchronous tumors. This research reviews the literature that investigated the concurrent OSCC with second or multiple primaries to improve understanding of the definition, classification guidelines, and its effect on cancer survival. It also highlights the current investigation methods, the variation of standard treatment approaches due to such a phenomenon, and preventive measures discussed in the literature.

The Role of ROR1 in Chemoresistance and EMT in Endometrial Cancer Cells.

Background and Objectives: Receptor tyrosine kinase-like orphan receptor type 1 (ROR1) plays a critical role in embryogenesis and is overexpressed in many malignant cells. These characteristics allow ROR1 to be a potential new target for cancer treatment. The aim of this study was to investigate the role of ROR1 through in vitro experiments in endometrial cancer cell lines. Materials and Methods: ROR1 expression was identified in endometrial cancer cell lines using Western blot and RT-qPCR. The effects of ROR1 on cell proliferation, invasion, migration, and epithelial-mesenchymal transition (EMT) markers were analyzed in two endometrial cancer cell lines (HEC-1 and SNU-539) using either ROR1 silencing or overexpression. Additionally, chemoresistance was examined by identifying MDR1 expression and IC50 level of paclitaxel. Results: The ROR1 protein and mRNA were highly expressed in SNU-539 and HEC-1 cells. High ROR1 expression resulted in a significant increase in cell proliferation, migration, and invasion. It also resulted in a change of EMT markers expression, a decrease in E-cadherin expression, and an increase in Snail expression. Moreover, cells with ROR1 overexpression had a higher IC50 of paclitaxel and significantly increased MDR1 expression. Conclusions: These in vitro experiments showed that ROR1 is responsible for EMT and chemoresistance in endometrial cancer cell lines. Targeting ROR1 can inhibit cancer metastasis and may be a potential treatment method for patients with endometrial cancer who exhibit chemoresistance.

Leveraging Hand-Object Interactions in Assistive Egocentric Vision.

Egocentric vision holds great promise for increasing access to visual information and improving the quality of life for blind people. While we strive to improve recognition performance, it remains difficult to identify which object is of interest to the user; the object may not even be included in the frame due to challenges in camera aiming without visual feedback. Also, gaze information, commonly used to infer the area of interest in egocentric vision, is often not dependable. However, blind users tend to include their hand either interacting with the object they wish to recognize or simply placing it in proximity for better camera aiming. We propose a method that leverages the hand as the contextual information for recognizing an object of interest. In our method, the output of a pre-trained hand segmentation model is infused to later convolutional layers of our object recognition network with separate output layers for localization and classification. Using egocentric datasets from sighted and blind individuals, we show that the hand-priming achieves more accurate localization than other approaches that encode hand information. Given only object centers along with labels, our method achieves comparable classification performance to the state-of-the-art method that uses bounding boxes with labels.

Contributing to Accessibility Datasets: Reflections on Sharing Study Data by Blind People.

To ensure that AI-infused systems work for disabled people, we need to bring accessibility datasets sourced from this community in the development lifecycle. However, there are many ethical and privacy concerns limiting greater data inclusion, making such datasets not readily available. We present a pair of studies where 13 blind participants engage in data capturing activities and reflect with and without probing on various factors that influence their decision to share their data via an AI dataset. We see how different factors influence blind participants' willingness to share study data as they assess risk-benefit tradeoffs. The majority support sharing of their data to improve technology but also express concerns over commercial use, associated metadata, and the lack of transparency about the impact of their data. These insights have implications for the development of responsible practices for stewarding accessibility datasets, and can contribute to broader discussions in this area.

Meta-Analysis of Survival Effects of Receptor Tyrosine Kinase-like Orphan Receptor 1 (ROR1).

Background and Objectives: Identification and targeting of membrane proteins in tumor cells is one of the key steps in the development of cancer drugs. The receptor tyrosine kinase-like orphan receptor (ROR) type 1 is a type-I transmembrane protein expressed in various cancer tissues, which is in contrast to its limited expression in normal tissues. These characteristics make ROR1 a candidate target for cancer treatment. This study aimed to identify the prognostic value of ROR1 expression in cancers. Materials and Methods: We conducted a comprehensive systematic search of electronic databases (PubMed) from their inception to September 2021. The included studies assessed the effect of ROR1 on overall survival (OS) and progression-free survival (PFS). Hazard ratios (HR) from collected data were pooled in a meta-analysis using Revman version 5.4 with generic inverse-variance and random effects modeling. Results: A total of fourteen studies were included in the final analysis. ROR1 was associated with worse OS (HR 1.95, 95% confidence interval (CI) 1.50−2.54; p < 0.001) with heterogeneity. The association between poor OS and ROR1 expression was high in endometrial cancer, followed by ovarian cancer, and diffuse large B cell lymphoma. In addition, ROR1 was associated with poor PFS (HR 1.84, 95% CI 1.60−2.10; p < 0.001), but heterogeneity was not statistically significant. In subgroup analysis, high ROR1 expression showed a significantly higher rate of advanced stage or lymph node metastasis. Conclusions: This meta-analysis provides evidence that ROR1 expression is associated with adverse outcome in cancer survival. This result highlights ROR1 as a target for developmental therapeutics in cancers.

Multi-Color Space Network for Salient Object Detection.

The salient object detection (SOD) technology predicts which object will attract the attention of an observer surveying a particular scene. Most state-of-the-art SOD methods are top-down mechanisms that apply fully convolutional networks (FCNs) of various structures to RGB images, extract features from them, and train a network. However, owing to the variety of factors that affect visual saliency, securing sufficient features from a single color space is difficult. Therefore, in this paper, we propose a multi-color space network (MCSNet) to detect salient objects using various saliency cues. First, the images were converted to HSV and grayscale color spaces to obtain saliency cues other than those provided by RGB color information. Each saliency cue was fed into two parallel VGG backbone networks to extract features. Contextual information was obtained from the extracted features using atrous spatial pyramid pooling (ASPP). The features obtained from both paths were passed through the attention module, and channel and spatial features were highlighted. Finally, the final saliency map was generated using a step-by-step residual refinement module (RRM). Furthermore, the network was trained with a bidirectional loss to supervise saliency detection results. Experiments on five public benchmark datasets showed that our proposed network achieved superior performance in terms of both subjective results and objective metrics.

From the Lab to People's Home: Lessons from Accessing Blind Participants' Interactions via Smart Glasses in Remote Studies.

Researchers have adopted remote methods, such as online surveys and video conferencing, to overcome challenges in conducting in-person usability testing, such as participation, user representation, and safety. However, remote user evaluation on hardware testbeds is limited, especially for blind participants, as such methods restrict access to observations of user interactions. We employ smart glasses in usability testing with blind people and share our lessons from a case study conducted in blind participants' homes (N = 12), where the experimenter can access participants' activities via dual video conferencing: a third-person view via a laptop camera and a first-person view via smart glasses worn by the participant. We show that smart glasses hold potential for observing participants' interactions with smartphone testbeds remotely; on average 58.7% of the interactions were fully captured via the first-person view compared to 3.7% via the third-person. However, this gain is not uniform across participants as it is susceptible to head movements orienting the ear towards a sound source, which highlights the need for a more inclusive camera form factor. We also share our lessons learned when it comes to dealing with lack of screen reader support in smart glasses, a rapidly draining battery, and Internet connectivity in remote studies with blind participants.

Blind Users Accessing Their Training Images in Teachable Object Recognizers.

Teachable object recognizers provide a solution for a very practical need for blind people - instance level object recognition. They assume one can visually inspect the photos they provide for training, a critical and inaccessible step for those who are blind. In this work, we engineer data descriptors that address this challenge. They indicate in real time whether the object in the photo is cropped or too small, a hand is included, the photos is blurred, and how much photos vary from each other. Our descriptors are built into open source testbed iOS app, called MYCam. In a remote user study in (N = 12) blind participants' homes, we show how descriptors, even when error-prone, support experimentation and have a positive impact in the quality of training set that can translate to model performance though this gain is not uniform. Participants found the app simple to use indicating that they could effectively train it and that the descriptors were useful. However, many found the training being tedious, opening discussions around the need for balance between information, time, and cognitive load.

Recent Advances and Progress of Conducting Polymer-Based Hydrogels in Strain Sensor Applications.

Conducting polymer-based hydrogels (CPHs) are novel materials that take advantage of both conducting polymers and three-dimensional hydrogels, which endow them with great electrical properties and excellent mechanical features. Therefore, CPHs are considered as one of the most promising platforms for employing wearable and stretchable strain sensors in practical applications. Herein, we provide a critical review of distinct features and preparation technologies and the advancements in CPH-based strain sensors for human motion and health monitoring applications. The fundamentals, working mechanisms, and requirements for the design of CPH-based strain sensors with high performance are also summarized and discussed. Moreover, the recent progress and development strategies for the implementation of CPH-based strain sensors are pointed out and described. It has been surmised that electronic skin (e-skin) sensors are the upward tendency in the development of CPHs for wearable strain sensors and human health monitoring. This review will be important scientific evidence to formulate new approaches for the development of CPH-based strain sensors in the present and in the future.

High-Temperature Carbonized Ceria Thermophotovoltaic Emitter beyond Tungsten.

Thermophotovoltaics (TPVs) require emitters with a regulated radiation spectrum tailored to the spectral response of integrated photovoltaic cells. Such spectrally engineered emitters developed thus far are structurally too complicated to be scalable, are thermally unstable, or lack reliability in terms of temperature cycling. Herein, we report wafer-scale, thermal-stress-free, and wavelength-selective emitters that operate for high-temperature TPVs equipped with GaSb photovoltaic cells. One inch crystalline ceria wafers were prepared by sequentially pressing and annealing the pellets of ceria nanoparticles. The direct pyrolysis of citric acid mixed with ceria nanoparticles created agglomerated, pyrolytic carbon and ceria microscale dots, thus forming a carbonized film strongly adhering to a wafer surface. Depending on the thickness of the carbonized film that was readily tuned based on the amount of citric acid used in the reaction, the carbonized ceria emitter behaved as a tungsten-like emitter, a graphite-like emitter, or their hybrid in terms of the absorptivity spectrum. A properly synthesized carbonized ceria emitter produced a power density of 0.63 W/cm2 from the TPV system working at 900 °C, providing 13 and 9% enhancements compared to tungsten and graphite emitters, respectively. Furthermore, only the carbonized ceria emitter preserved its pristine absorptivity spectrum after a 48 h heating test at 1000 °C. The scalable and facile fabrication of thermostable emitters with a structured spectrum will prompt the emergence of thermal emission-harnessed energy devices.

Recent development in friction of 2D materials: from mechanisms to applications.

Two-dimensional (2D) materials with a layered structure are excellent candidates in the field of lubrication due to their unique physical and chemical properties, including weak interlayer interaction and large specific surface area. For the last few decades, graphene has received lots of attention due to its excellent properties. Besides graphene, various new 2D materials (including MoS2, WS2, WSe2, NbSe2, NbTe2, ReS2, TaS2and h-BN etc.) are found to exhibit a low coefficient of friction at the macro- and even micro-scales, which may lead to widespread application in the field of lubrication and anti-wear. This article focuses on the latest development trend in 2D materials in the field of tribology. The review begins with a summary of widely accepted nano-scale friction mechanisms contain surface friction mechanism and interlayer friction mechanism. The following sections report the applications of 2D materials in lubrication and anti-wear as lubricant additives, solid lubricants, and composite lubricating materials. Finally, the research prospects of 2D materials in tribology are presented.

Genetic Diversity and Population Structure of Potato Germplasm in RDA-Genebank: Utilization for Breeding and Conservation.

Potato (Solanum tuberosum L.) is an important staple food and economic crop in many countries. It is of critical importance to understand the genetic diversity and population structure for effective collection, conservation, and utilization of potato germplasm. Thus, the objective of the present study was to investigate the genetic diversity and population structure of potato germplasm conserved in the National Agrobiodiversity Center (NAC) of South Korea to provide basic data for future preservation and breeding of potato genetic resources. A total of 24 simple sequence repeat (SSR) markers were used to assess the genetic diversity and population structure of 482 potato accessions. A total of 257 alleles were detected, with an average of 10.71 alleles per locus. Analysis of molecular variance showed that 97% of allelic diversity was attributed to individual accessions within the population, while only 3% was distributed among populations. Results of genetic structure analysis based on STRUCTURE and discriminant analysis of principal components revealed that 482 potato accessions could be divided into two main subpopulations. Accessions of subpopulation 1 mainly belonged to cultivars and breeding lines. Accessions of subpopulations 2 basically corresponded to wild relatives of potatoes. Results of this study provide useful information for potato improvement and conservation programs, although further studies are needed for a more accurate evaluation of genetic diversity and phenotypic traits of potatoes.

Dental 3D-Printing: Transferring Art from the Laboratories to the Clinics.

The rise of three-dimensional (3D) printing technology has changed the face of dentistry over the past decade. 3D printing is a versatile technique that allows the fabrication of fully automated, tailor-made treatment plans, thereby delivering personalized dental devices and aids to the patients. It is highly efficient, reproducible, and provides fast and accurate results in an affordable manner. With persistent efforts among dentists for refining their practice, dental clinics are now acclimatizing from conventional treatment methods to a fully digital workflow to treat their patients. Apart from its clinical success, 3D printing techniques are now employed in developing haptic simulators, precise models for dental education, including patient awareness. In this narrative review, we discuss the evolution and current trends in 3D printing applications among various areas of dentistry. We aim to focus on the process of the digital workflow used in the clinical diagnosis of different dental conditions and how they are transferred from laboratories to clinics. A brief outlook on the most recent manufacturing methods of 3D printed objects and their current and future implications are also discussed.

Accessing Passersby Proxemic Signals through a Head-Worn Camera: Opportunities and Limitations for the Blind.

The spatial behavior of passersby can be critical to blind individuals to initiate interactions, preserve personal space, or practice social distancing during a pandemic. Among other use cases, wearable cameras employing computer vision can be used to extract proxemic signals of others and thus increase access to the spatial behavior of passersby for blind people. Analyzing data collected in a study with blind (N=10) and sighted (N=40) participants, we explore: (i) visual information on approaching passersby captured by a head-worn camera; (ii) pedestrian detection algorithms for extracting proxemic signals such as passerby presence, relative position, distance, and head pose; and (iii) opportunities and limitations of using wearable cameras for helping blind people access proxemics related to nearby people. Our observations and findings provide insights into dyadic behaviors for assistive pedestrian detection and lead to implications for the design of future head-worn cameras and interactions.

Biomimetic Aspects of Oral and Dentofacial Regeneration.

Biomimetic materials for hard and soft tissues have advanced in the fields of tissue engineering and regenerative medicine in dentistry. To examine these recent advances, we searched Medline (OVID) with the key terms "biomimetics", "biomaterials", and "biomimicry" combined with MeSH terms for "dentistry" and limited the date of publication between 2010-2020. Over 500 articles were obtained under clinical trials, randomized clinical trials, metanalysis, and systematic reviews developed in the past 10 years in three major areas of dentistry: restorative, orofacial surgery, and periodontics. Clinical studies and systematic reviews along with hand-searched preclinical studies as potential therapies have been included. They support the proof-of-concept that novel treatments are in the pipeline towards ground-breaking clinical therapies for orofacial bone regeneration, tooth regeneration, repair of the oral mucosa, periodontal tissue engineering, and dental implants. Biomimicry enhances the clinical outcomes and calls for an interdisciplinary approach integrating medicine, bioengineering, biotechnology, and computational sciences to advance the current research to clinics. We conclude that dentistry has come a long way apropos of regenerative medicine; still, there are vast avenues to endeavour, seeking inspiration from other facets in biomedical research.

Hand-Priming in Object Localization for Assistive Egocentric Vision.

Egocentric vision holds great promises for increasing access to visual information and improving the quality of life for people with visual impairments, with object recognition being one of the daily challenges for this population. While we strive to improve recognition performance, it remains difficult to identify which object is of interest to the user; the object may not even be included in the frame due to challenges in camera aiming without visual feedback. Also, gaze information, commonly used to infer the area of interest in egocentric vision, is often not dependable. However, blind users often tend to include their hand either interacting with the object that they wish to recognize or simply placing it in proximity for better camera aiming. We propose localization models that leverage the presence of the hand as the contextual information for priming the center area of the object of interest. In our approach, hand segmentation is fed to either the entire localization network or its last convolutional layers. Using egocentric datasets from sighted and blind individuals, we show that the hand-priming achieves higher precision than other approaches, such as fine-tuning, multi-class, and multi-task learning, which also encode hand-object interactions in localization.

Pedestrian Detection with Wearable Cameras for the Blind: A Two-way Perspective.

Blind people have limited access to information about their surroundings, which is important for ensuring one's safety, managing social interactions, and identifying approaching pedestrians. With advances in computer vision, wearable cameras can provide equitable access to such information. However, the always-on nature of these assistive technologies poses privacy concerns for parties that may get recorded. We explore this tension from both perspectives, those of sighted passersby and blind users, taking into account camera visibility, in-person versus remote experience, and extracted visual information. We conduct two studies: an online survey with MTurkers (N=206) and an in-person experience study between pairs of blind (N=10) and sighted (N=40) participants, where blind participants wear a working prototype for pedestrian detection and pass by sighted participants. Our results suggest that both of the perspectives of users and bystanders and the several factors mentioned above need to be carefully considered to mitigate potential social tensions.

Passive Anti-Flooding Superhydrophobic Surfaces.

Superhydrophobic (SHPo) surfaces can provide high condensation heat transfer due to facilitated droplet removal. However, such high performance has been limited to low supersaturation conditions due to surface flooding. Here, we quantify flooding resistance defined as the rate of increase in the fraction of water-filled cavities with respect to the supersaturation level. Based on the quantitative understanding of surface flooding, we suggest effective anti-flooding strategies through tailoring the nanoscale coating heterogeneity and structure length scale. Experimental verification is conducted using CuO nanostructures having different length scales combined with hydrophobic coatings with different nanoscale heterogeneities. The proposed anti-flooding SHPo can provide a ∼130% enhanced average heat transfer coefficient with ∼14% larger supersaturation range for droplet jumping compared to a previous CuO SHPo. The proposed anti-flooding parameter and the scalable SHPo will help develop high-performance condensers for real-world applications operating in a wide range of supersaturation levels.