A Framework for Detecting False Data Injection Attacks in Large-Scale Wireless Sensor Networks.

False data injection attacks (FDIAs) on sensor networks involve injecting deceptive or malicious data into the sensor readings that cause decision-makers to make incorrect decisions, leading to serious consequences. With the ever-increasing volume of data in large-scale sensor networks, detecting FDIAs in large-scale sensor networks becomes more challenging. In this paper, we propose a framework for the distributed detection of FDIAs in large-scale sensor networks.

Enhancing Occupant Comfort and Building Sustainability: Lessons from an Internet of Things-Based Study on Centrally Controlled Indoor Shared Spaces in Hot Climatic Conditions.

It is well known that buildings have a sizeable energy and environmental footprint. In particular, in environments like university campuses, the occupants as well as occupancy in shared spaces varies over time. Systems for cooling in such environments that are centrally controlled are typically threshold driven and do not account for occupant feedback and thus are often relying on a reactive approach (fix after identifying problems).

Injectable and Multifunctional Hydrogels Based on Poly(-acryloyl glycinamide) and Alginate Derivatives for Antitumor Drug Delivery.

Chemotherapy is a conventional treatment that uses drugs to kill cancer cells; however, it may induce side effects and may be incompletely effective, leading to the risk of tumor recurrence. To address this issue, we developed novel injectable thermal/near-infrared (NIR)-responsive hydrogels to control drug release. The injectable hydrogel formulation was composed of biocompatible alginates, poly(-acryloyl glycinamide) (PNAGA) copolymers with an upper critical solution temperature, and NIR-responsive cross-linkers containing coumarin groups, which were gelated through bioorthogonal inverse electron demand Diels-Alder reactions.

Real-time and lightweight detection of grape diseases based on Fusion Transformer YOLO.

Introduction: Grapes are prone to various diseases throughout their growth cycle, and the failure to promptly control these diseases can result in reduced production and even complete crop failure. Therefore, effective disease control is essential for maximizing grape yield. Accurate disease identification plays a crucial role in this process.

A novel parallel ant colony optimization algorithm for mobile robot path planning.

With the continuous development of mobile robot technology, its application fields are becoming increasingly widespread, and path planning is one of the most important topics in the field of mobile robot research. This paper focused on the study of the path planning problem for mobile robots in a complex environment based on the ant colony optimization (ACO) algorithm. In order to solve the problems of local optimum, susceptibility to deadlocks, and low search efficiency in the traditional ACO algorithm, a novel parallel ACO (PACO) algorithm was proposed.

Transfer-Free Analog and Digital Flexible Memristors Based on Boron Nitride Films.

The traditional von Neumann architecture of computers, constrained by the inherent separation of processing and memory units, faces challenges, for instance, memory wall issue. Neuromorphic computing and in-memory computing offer promising paradigms to overcome the limitations of additional data movement and to enhance computational efficiency. In this work, transfer-free flexible memristors based on hexagonal boron nitride films were proposed for analog neuromorphic and digital memcomputing.

High efficiency of drinking water treatment residual-based sintered ceramsite in biofilter for domestic wastewater treatment.

Aluminum (Al)-based drinking water treatment residue (DWTR) has often been attempted to be recycled as dominant ingredient to produce sintered ceramsite for water treatment. This study aimed to determine the long-term performance of DWTR-based ceramsite in treating domestic wastewater based on a 385-d biofilter test and by using physicochemical, metagenomic, and metatranscriptomic analyses. The results showed that the ceramsite-packed biofilter exhibited high and stable capability in removing phosphorus (P) and chemical oxygen demand (COD), with removal efficiencies of 92.

A Robust TabNet-Based Multi-Classification Algorithm for Infrared Spectral Data of Chinese Herbal Medicine with High-Dimensional Small Samples.

Robust classification algorithms for high-dimensional, small-sample datasets are valuable in practical applications. Faced with the infrared spectroscopic dataset with 568 samples and 3448 wavelengths (features) to identify the origins of Chinese medicinal materials, this paper proposed a novel embedded multiclassification algorithm, ITabNet, derived from the framework of TabNet. Firstly, a refined data pre-processing (DP) mechanism was designed to efficiently find the best adaptive one among 50 DP methods with the help of Support Vector Machine (SVM).

Biocompatibility and sub-chronic toxicity studies of phlorotannin/polycaprolactone coated trachea tube for advancing medical device applications.

The phlorotannin-polycaprolactone-coated endotracheal tube (PP tube) has been developed with the aim of preventing tracheal stenosis that can result from endotracheal intubation, a factor that can lead to a serious airway obstruction. Its preventive efficacy has been assessed through both in vitro and in vivo investigations. However, there is a lack of studies concerning its biocompatibility and sub-chronic toxicity in animal models, a crucial factor to ensure the safety of its usage as a functional endotracheal tube.

Large-scale smart bioreactor with fully integrated wireless multivariate sensors and electronics for long-term in situ monitoring of stem cell culture.

Achieving large-scale, cost-effective, and reproducible manufacturing of stem cells with the existing devices is challenging. Traditional single-use cell-bag bioreactors, limited by their rigid and single-point sensors, struggle with accuracy and scalability for high-quality cell manufacturing. Here, we introduce a smart bioreactor system that enables multi-spatial sensing for real-time, wireless culture monitoring.

Smartphone usage and overdependence risk among middle-aged and older adults: a cross-sectional study.

Background: Previous studies have predominantly focused on smartphone overdependence among adolescents and young adults. However, as smartphone usage has recently surged among South Korean middle-aged and older adults, the risk of smartphone overdependence cannot be overlooked among this population. Therefore, this study was conducted to examine the smartphone usage pattern and the associated risk of overdependence in this specific age group.

A pilot study of measuring emotional response and perception of LLM-generated questionnaire and human-generated questionnaires.

The advent of ChatGPT has sparked a heated debate surrounding natural language processing technology and AI-powered chatbots, leading to extensive research and applications across various disciplines. This pilot study aims to investigate the impact of ChatGPT on users' experiences by administering two distinct questionnaires, one generated by humans and the other by ChatGPT, along with an Emotion Detecting Model. A total of 14 participants (7 female and 7 male) aged between 18 and 35 years were recruited, resulting in the collection of 8672 ChatGPT-associated data points and 8797 human-associated data points.

NCSP-PLM: An ensemble learning framework for predicting non-classical secreted proteins based on protein language models and deep learning.

Non-classical secreted proteins (NCSPs) refer to a group of proteins that are located in the extracellular environment despite the absence of signal peptides and motifs. They usually play different roles in intercellular communication. Therefore, the accurate prediction of NCSPs is a critical step to understanding in depth their associated secretion mechanisms.

A literature review of bioactive substances for the treatment of periodontitis: , and clinical studies.

Periodontitis is a common chronic inflammatory disease of the supporting tissues of the tooth that involves a complex interaction of microorganisms and various cell lines around the infected site. To prevent and treat this disease, several options are available, such as scaling, root planning, antibiotic treatment, and dental surgeries, depending on the stage of the disease. However, these treatments can have various side effects, including additional inflammatory responses, chronic wounds, and the need for secondary surgery.

Research on improved black widow algorithm for medical image denoising.

Improving the quality of medical images is crucial for accurate clinical diagnosis; however, medical images are often disrupted by various types of noise, posing challenges to the reliability and diagnostic accuracy of the images. This study aims to enhance the Black Widow optimization algorithm and apply it to the task of denoising medical images to improve both the quality of medical images and the accuracy of diagnostic results. By introducing Tent mapping, we refined the Black Widow optimization algorithm to better adapt to the complex features of medical images.

Antimicrobial, antibiofilm, and antivirulence properties of Eisenia bicyclis-extracts and Eisenia bicyclis-gold nanoparticles towards microbial pathogens.

Nanomaterials derived from seaweed have developed as an alternative option for fighting infections caused by biofilm-forming microbial pathogens. This research aimed to discover potential seaweed-derived nanomaterials with antimicrobial and antibiofilm action against bacterial and fungal pathogens. Among seven algal species, the extract from Eisenia bicyclis inhibited biofilms of Klebsiella pneumoniae, Staphylococcus aureus, and Listeria monocytogenes most effectively at sub-MIC levels.

FPIRST: Fatigue Driving Recognition Method Based on Feature Parameter Images and a Residual Swin Transformer.

Fatigue driving is a serious threat to road safety, which is why accurately identifying fatigue driving behavior and warning drivers in time are of great significance in improving traffic safety. However, accurately recognizing fatigue driving is still challenging due to large intra-class variations in facial expression, continuity of behaviors, and illumination conditions. A fatigue driving recognition method based on feature parameter images and a residual Swin Transformer is proposed in this paper.

Estimating the frost damage index in lettuce using UAV-based RGB and multispectral images.

Introduction: The cold stress is one of the most important factors for affecting production throughout year, so effectively evaluating frost damage is great significant to the determination of the frost tolerance in lettuce.

Methods: We proposed a high-throughput method to estimate lettuce FDI based on remote sensing. Red-Green-Blue (RGB) and multispectral images of open-field lettuce suffered from frost damage were captured by Unmanned Aerial Vehicle platform.

Antioxidant Effects and Probiotic Properties of MS103 Isolated from Sweet Pickled Garlic.

Fermented vegetable-based foods, renowned for their unique flavors and human health benefits, contain probiotic organisms with reported in vitro antioxidative effects. This study investigates the probiotic properties of MS103 ( MS103) and its antioxidant activities using an in vitro oxidative stress model based on the hydrogen peroxide (HO)-induced oxidative damage of RAW 264.7 cells.

Unlocking Mutual Gains-An Experimental Study on Collaborative Autonomous Driving in Urban Environment.

Convoy driving, a specialized form of collaborative autonomous driving, offers a promising solution to the multifaceted challenges that transportation systems face, including traffic congestion, pollutant emissions, and the coexistence of connected autonomous vehicles (CAVs) and human-driven vehicles on the road, resulting in mixed traffic flow. While extensive research has focused on the collective societal benefits of convoy driving, such as safety and comfort, one critical aspect that has been overlooked is the willingness of individual vehicles to participate in convoy formations. While the collective benefits are evident, individual vehicles may not readily embrace this paradigm shift without explicit tangible benefits and incentives to motivate them.

An end-to-end seed vigor prediction model for imbalanced samples using hyperspectral image.

Hyperspectral imaging is a key technology for non-destructive detection of seed vigor presently due to its capability to capture variations of optical properties in seeds. As the seed vigor data depends on the actual germination rate, it inevitably results in an imbalance between positive and negative samples. Additionally, hyperspectral image (HSI) suffers from feature redundancy and collinearity due to its inclusion of hundreds of wavelengths.