Anomalous metallic state underdoped infinite-layer nickelate superconducting thin films.

To date, the nature of the anomalous metallic state in two-dimensional systems remains unclear. In this study, we present the observation of a quantum superconductor-to-metal transition in underdoped NdSrNiO infinite-layer superconducting thin films, induced by a magnetic field. When a magnetic field perpendicular to the film is applied, we observed a robust intervening anomalous metallic state, characterized by a saturating resistance at low temperatures.

Changes in Retinal Vasculature Phenotype and Choroidal Blood Flow at High Altitude in Healthy Lowlanders.

Purpose: The aim of this study was to characterize changes in retinal vessel diameters and choroidal blood flow in healthy lowlanders during a high-altitude expedition.

Methods: Ocular examination, fundus images acquired using a handheld camera, and laser Doppler flowmetry (LDF) measurements within the subfoveal choroid (blood flow = ChBF, blood velocity = ChVel, and blood volume = ChVol) were carried out at 200 m and after 9 days at 5100 m in 11 healthy participants. Fundus images were analyzed with the semi-automatic software Vessel Assessment and Measurement Platform for Images of the Retina (VAMPIRE) version 3.

An attention-based approach for Koopman modeling and predictive control of nonlinear systems.

We develop an innovative attention-based deep learning method for constructing Koopman eigenfunctions, addressing the challenge of accurately modeling nonlinear systems for predictive control. This method is motivated by the need to identify a diffeomorphism that precisely delineates the topological conjugacy between nonlinear dynamics and their linearized counterparts. Leveraging the capabilities and suitability of invertible neural networks, we deploy an architecture equipped with conditional affine coupling layers to approximate this diffeomorphism.

Multicolor Fluorescent Hydrogels Based on CaZnOS Phosphors for Anticounterfeiting Applications.

As an inorganic phosphor, CaZnOS with highly efficient and stable emission exhibits strong potential in the fields of lighting display and information encryption. Although it has only a single luminescent region after sintering, it is anticipated that the unique differences in excitation and emission wavelengths of luminescent ions can be exploited to achieve information encryption by doping various luminescent ions. The hydrophilicity and water resistance of CaZnOS make it a suitable candidate for incorporation into hydrogel systems.

Elevating Detection Performance in Optical Remote Sensing Image Object Detection: A Dual Strategy with Spatially Adaptive Angle-Aware Networks and Edge-Aware Skewed Bounding Box Loss Function.

In optical remote sensing image object detection, discontinuous boundaries often limit detection accuracy, particularly at high Intersection over Union (IoU) thresholds. This paper addresses this issue by proposing the Spatial Adaptive Angle-Aware (SA3) Network. The SA3 Network employs a hierarchical refinement approach, consisting of coarse regression, fine regression, and precise tuning, to optimize the angle parameters of rotated bounding boxes.

Percolation Transitions in Edge-Coupled Interdependent Networks with Reinforced Inter-Layer Links.

Prior research on cascading failures within interdependent networks has predominantly emphasized the coupling of nodes. Nevertheless, in practical networks, interactions often exist not just through the nodes themselves but also via the connections (edges) linking them, a configuration referred to as edge-coupled interdependent networks. Past research has shown that introducing a certain percentage of reinforced nodes or connecting edges can prevent catastrophic network collapses.

Robustness of higher-order interdependent networks with reinforced nodes.

In reality, pairwise interactions are no longer sufficient to describe the higher-order interactions between nodes, such as brain networks, social networks, etc., which often contain groups of three or more nodes. Since the failure of one node in a high-order network can lead to the failure of all simplices in which it is located and quickly propagates to the whole system through the interdependencies between networks, multilayered high-order interdependent networks are challenged with high vulnerability risks.

Isotropic Quantum Griffiths Singularity in Nd_{0.8}Sr_{0.2}NiO_{2} Infinite-Layer Superconducting Thin Films.

This work reports on the emergence of quantum Griffiths singularity (QGS) associated with the magnetic field induced superconductor-metal transition (SMT) in unconventional Nd_{0.8}Sr_{0.2}NiO_{2} infinite layer superconducting thin films.

A Tunable Graphene Superlattice with Deformable Periodical Nano-Gating.

Graphene superlattices have simple and controllable electronic band structures, which can also be electrostatically tuned. They have been widely studied for band engineering and strong correlated physics, and have led to the discovery of a variety of exciting phenomena. To experimentally study the physics of graphene superlattices in a systematic way, it is desirable to control the structure parameters, which barely exist at the moment, onsite.

Threatening language detection from Urdu data with deep sequential model.

The Urdu language is spoken and written on different social media platforms like Twitter, WhatsApp, Facebook, and YouTube. However, due to the lack of Urdu Language Processing (ULP) libraries, it is quite challenging to identify threats from textual and sequential data on the social media provided in Urdu. Therefore, it is required to preprocess the Urdu data as efficiently as English by creating different stemming and data cleaning libraries for Urdu data.

Image fusion using Y-net-based extractor and global-local discriminator.

Although some deep learning-based image fusion approaches have realized promising results, how to extract information-rich features from different source images while preserving them in the fused image with less distortions remains challenging issue that needs to be addressed. Here, we propose a well worked-out GAN-based scheme with multi-scale feature extractor and global-local discriminator for infrared and visible image fusion. We use Y-Net as the backbone architecture to design the generator network, and introduce the residual dense block (RDblock) to yield more realistic fused images for infrared and visible images by learning discriminative multi-scale representations that are closer to the essence of different modal images.

In Situ Polymerization of Antibacterial Modification Polyamide 66 with Au@CuO-ZnO Ternary Heterojunction.

In situ polymerization has proven to be an effective route through which to introduce function materials into polyamide materials. In this work, a nano-heterojunction material was evenly dispersed in PA66 via in situ polymerization methods to yield the antimicrobial PA66. The composites showed excellent antibacterial activity against and with strong mechanical properties.

Enhancing heart disease prediction using a self-attention-based transformer model.

Cardiovascular diseases (CVDs) continue to be the leading cause of more than 17 million mortalities worldwide. The early detection of heart failure with high accuracy is crucial for clinical trials and therapy. Patients will be categorized into various types of heart disease based on characteristics like blood pressure, cholesterol levels, heart rate, and other characteristics.

Fuzzy-based optimization of AODV routing for efficient route in wireless mesh networks.

The performance of any communication system heavily relies on the efficient routing of interventions. This article addresses the significant issue of routing protocol selection for optimal path determination in networks. Particularly, when wireless communication occurs among mobile nodes with limited resources, such as batteries, the routing problem becomes even more challenging.

A Systematic Literature Review on Trustworthiness for Applications Used in eHealth Environments.

Context: The technological advancement of the Internet of Things (IoT) creates opportunities in various social sectors. Patients in clinics or home care have their comfort and safety enhanced with remote monitoring, sensors and applications that control and transfer patient data. These applications must be trustworthy, since they deal with sensitive data.

BRT: An Efficient and Scalable Blockchain-Based Revocation Transparency System for TLS Connections.

Log-based public key infrastructure(PKI) refers to a robust class of CA-attack-resilient PKI that enhance transparency and accountability in the certificate revocation and issuance process by compelling certificate authorities (CAs) to submit revocations to publicly and verifiably accessible logs. However, log-based PKIs suffer from a reliance on centralized and consistent sources of information, rendering them susceptible to split-world attacks, and they regrettably fail to provide adequate incentives for recording or monitoring CA behavior. Blockchain-based PKIs address these limitations by enabling decentralized log audits through automated financial incentives.

MJ-GAN: Generative Adversarial Network with Multi-Grained Feature Extraction and Joint Attention Fusion for Infrared and Visible Image Fusion.

The challenging issues in infrared and visible image fusion (IVIF) are extracting and fusing as much useful information as possible contained in the source images, namely, the rich textures in visible images and the significant contrast in infrared images. Existing fusion methods cannot address this problem well due to the handcrafted fusion operations and the extraction of features only from a single scale. In this work, we solve the problems of insufficient information extraction and fusion from another perspective to overcome the difficulties in lacking textures and unhighlighted targets in fused images.

Learning Representative Features by Deep Attention Network for 3D Point Cloud Registration.

Three-dimensional point cloud registration, which aims to find the transformation that best aligns two point clouds, is a widely studied problem in computer vision with a wide spectrum of applications, such as underground mining. Many learning-based approaches have been developed and have demonstrated their effectiveness for point cloud registration. Particularly, attention-based models have achieved outstanding performance due to the extra contextual information captured by attention mechanisms.

Requirements, Deployments, and Challenges of LoRa Technology: A Survey.

LoRa is an ISM-band based LPWAN communication protocol. Despite their wide network penetration of approximately 20 kilometers or higher using lower than 14 decibels transmitting power, it has been extensively documented and used in academia and industry. Although LoRa connectivity defines a public platform and enables users to create independent low-power wireless connections while relying on external architecture, it has gained considerable interest from scholars and the market.

Mechanically Strong and Thermally Stable Chemical Cross-Linked Polyimide Aerogels for Thermal Insulator.

High-performance thermal insulating materials are highly desirable in several fields, especially for thermal insulation of buildings to reduce energy consumption. Owing to the remarkable thermal stability, high porosity, low density, and outstanding mechanical features, polyimide (PI) aerogels have attracted great attention. In this work, chemical cross-linked PI (CCPI) aerogels were fabricated via freeze-drying and thermal imidization, which possess outstanding mechanical properties, good thermal stability, and excellent thermal insulation characteristics.

Analysis of Risk Factors in Global Software Development: A Cross-Continental Study Using Modified Firefly Algorithm.

In today's competitive world, software organizations are moving towards global software development (GSD). This became even more significant in times such as COVID-19 pandemic, where team members residing in different geographical locations and from different cultures had to work from home to carry on their tasks and responsibilities as travelling was restricted. These teams are distributed in nature and work on the same set of goals and objectives.

Risk Prediction by Using Artificial Neural Network in Global Software Development.

The demand for global software development is growing. The nonavailability of software experts at one place or a country is the reason for the increase in the scope of global software development. Software developers who are located in different parts of the world with diversified skills necessary for a successful completion of a project play a critical role in the field of software development.

Hip-Knee Coupling Exoskeleton With Offset Theory for Walking Assistance.

To alleviate the influence of aging on the elderly, a hip-knee coupling exoskeleton with offset theory is designed in this article to improve people's athletic ability. With the novel design, the unique application strategy of the offset principle for hip and knee joints is developed, and a hip-knee coupling mechanism is proposed to solve the discrete power assistance problem for the knee joint. To acquire the success of the design, the mathematical model of the coupling mechanism is established to optimize the load environment of the exoskeleton system, and furthermore, an algorithm adapted to human movement is proposed to determine the monotonicity of the cam profiles.

Resource Allocation Schemes for 5G Network: A Systematic Review.

Fifth-generation (5G) communication technology is intended to offer higher data rates, outstanding user exposure, lower power consumption, and extremely short latency. Such cellular networks will implement a diverse multi-layer model comprising device-to-device networks, macro-cells, and different categories of small cells to assist customers with desired quality-of-service (QoS). This multi-layer model affects several studies that confront utilizing interference management and resource allocation in 5G networks.