Integrating accelerometry, GPS, GIS and molecular data to investigate mechanistic pathways of the urban environmental exposome and cognitive outcomes in older adults: a longitudinal study protocol.

Introduction: Maintaining cognitive health in later life is a global priority. Encouraging individuals to make health behaviour changes, such as regular physical activity, and providing supportive urban environments can help maintain cognitive health, thereby preventing or delaying the progress of dementia and cognitive decline. However, the mechanistic pathways by which the urban environmental exposome influences cognitive health outcomes are poorly understood.

Correlation between organic residuals of green synthesized nanoparticles and resistive switching behavior.

In this work, ZnO nanoparticles (NPs) are synthesized using avocado seed extract and annealed at different annealing temperatures from 400 to 800 °C. The morphology of the nanoparticles changes from poly shapes at 400 °C to spherical ones at 800 °C, and particle sizes increase from ∼42 nm to ∼128 nm. The Ag/ZnO@400/FTO memory device exhibits stable resistive switching over 100 cycles and a resistance window of approximately 150.

Enhancement of Visible Light Antibacterial Activities of Cellulose Fibers from Lotus Petiole Decorated ZnO Nanoparticles.

Cellulose/ZnO (CZ) nanocomposites are promising antimicrobial materials known for their antibiotic-free nature, biocompatibility, and environmental friendliness. In this study, cellulose fibers extracted from lotus petioles were utilized as a substrate and decorated with various shapes of ZnO nanoparticles (NPs), including small bean, hexagonal ingot-like, long cylindrical, and hexagonal cylinder-shaped NPs. Increasing zinc salt molar concentration resulted in highly crystalline ZnO NPs forming and enhanced interactions between ZnO NPs and -OH groups of cellulose.

TwinPort: 5G drone-assisted data collection with digital twin for smart seaports.

Numerous ports worldwide are adopting automation to boost productivity and modernize their operations. At this point, smart ports become a more important paradigm for handling increasing cargo volumes and increasing operational efficiency. In fact, as ports become more congested and cargo volumes increase, the need for accurate navigation through seaports is more pronounced to avoid collisions and the resulting consequences.

Joint Clustering and Resource Allocation Optimization in Ultra-Dense Networks with Multiple Drones as Small Cells Using Game Theory.

In this study, we consider the combination of clustering and resource allocation based on game theory in ultra-dense networks that consist of multiple macrocells using massive multiple-input multiple-output and a vast number of randomly distributed drones serving as small-cell base stations. In particular, to mitigate the intercell interference, we propose a coalition game for clustering small cells, with the utility function being the ratio of signal to interference. Then, the optimization problem of resource allocation is divided into two subproblems: subchannel allocation and power allocation.

Entanglement detection with artificial neural networks.

Quantum entanglement is one of the essential resources involved in quantum information processing tasks. However, its detection for usage remains a challenge. The Bell-type inequality for relative entropy of coherence serves as an entanglement witness for pure entangled states.

Enhancement of antibacterial activities of green synthesized-CuO/ZnO nanocomposites using Boehmeria nivea leaf extract.

This study investigated CuO and ZnO nanoparticles and CuO/ZnO nanocomposites in a friendly environment with a low-cost and renewable biosynthesis method. This approach involved using Boehmeria nivea leaf extract to facilitate the growth and formation of nanocomposites with performance-enhancing phytochemicals released during the co-precipitation process. All nanoparticles/nanocomposites explored the microstructure, morphology, and point defects using FTIR, XRD, SEM, and PL characterization techniques.

Multiclass Classification of Metrologically Resourceful Tripartite Quantum States with Deep Neural Networks.

Quantum entanglement is a unique phenomenon of quantum mechanics, which has no classical counterpart and gives quantum systems their advantage in computing, communication, sensing, and metrology. In quantum sensing and metrology, utilizing an entangled probe state enhances the achievable precision more than its classical counterpart. Noise in the probe state preparation step can cause the system to output unentangled states, which might not be resourceful.

A Wearable-based Preventive Model To Promote Oral Health Through Personalized Notification.

Wearable technology has great potential to develop human-centric healthcare applications. It reshapes our lifestyle by providing information related to physical activities, sleep monitoring, or heartbeat rhythms. In this paper, we present an innovative model for oral healthcare, which is prevention-focused to notify individuals about cleaning teeth activity.

Deep learning models for forecasting dengue fever based on climate data in Vietnam.

Background: Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate change in Vietnam.

Objective: This study aimed to develop an accurate DF prediction model in Vietnam using a wide range of meteorological factors as inputs to inform public health responses for outbreak prevention in the context of future climate change.

AI-Driven Aeronautical Ad Hoc Networks for 6G Wireless: Challenges, Opportunities, and the Road Ahead.

Aeronautical ad hoc network (AANET) has been considered a promising candidate to complete the vision of "Internet in the sky" by supporting high-speed broadband connections on airplanes for 6G networks. However, the specific characteristics of AANET restrict the applicability of conventional topology and routing management algorithms. Here, these conventional methodologies reduce the packet delivery success of AANET with higher transfer delay.

Predictability of Fused 3D-T2-SPACE and 3D-TOF-MRA Images in Identifying Conflict in Trigeminal Neuralgia.

Purpose: To evaluate the efficacy of fused three-dimensional T2 sampling perfection with application-optimized contrasts using different flip-angle evolutions (3D-SPACE) and three-dimensional time-of-flight magnetic resonance angiography (3D-TOF-MRA) sequences for detecting neurovascular compression (NVC) in patients presenting with trigeminal neuralgia (TN).

Methods: A prospective study was carried in 33 consecutive patients (m/f: 17/16; mean age, 56.3 ± 10.

Risk-Aware Identification of Highly Suspected COVID-19 Cases in Social IoT: A Joint Graph Theory and Reinforcement Learning Approach.

The recent outbreak of the coronavirus disease 2019 (COVID-19) has rapidly become a pandemic, which calls for prompt action in identifying suspected cases at an early stage through risk prediction. To suppress its further spread, we exploit the social relationships between mobile devices in the Social Internet of Things (SIoT) to help control its propagation by allocating the limited protective resources to the influential so-called high-degree individuals to stem the tide of precipitated spreading. By exploiting the so-called differential contact intensity and the infectious rate in susceptible-exposed-infected-removed (SEIR) epidemic model, the resultant optimization problem can be transformed into the minimum weight vertex cover (MWVC) problem of graph theory.

Type 2 diabetes mellitus duration and obesity alter the efficacy of autologously transplanted bone marrow-derived mesenchymal stem/stromal cells.

Human bone marrow-derived mesenchymal stem/stromal cells (BM-MSCs) represent promising stem cell therapy for the treatment of type 2 diabetes mellitus (T2DM), but the results of autologous BM-MSC administration in T2DM patients are contradictory. The purpose of this study was to test the hypothesis that autologous BM-MSC administration in T2DM patient is safe and that the efficacy of the treatment is dependant on the quality of the autologous BM-MSC population and administration routes. T2DM patients were enrolled, randomly assigned (1:1) by a computer-based system into the intravenous and dorsal pancreatic arterial groups.

Development of a Spatial Decision Support System for Real-Time Flood Early Warning in the Vu Gia-Thu Bon River Basin, Quang Nam Province, Vietnam.

Vu Gia-Thu Bon (VGTB) river basin is an area where flash flood and heavy flood events occur frequently, negatively impacting the local community and socio-economic development of Quang Nam Province. In recent years, structural and non-structural solutions have been implemented to mitigate damages due to floods. However, under the impact of climate change, natural disasters continue to happen unpredictably day by day.

Monitoring fine root growth to identify optimal fertilization timing in a forest plantation: A case study in Northeast Vietnam.

Fertilizer is applied widely to improve the productivity of plantations. Traditionally, fertilization is conducted in spring and/or in the early rainy season, and it is believed to support the growth of planted trees in the growing season. Little attention to date has been paid on identification of the optimal timing of fertilization and fertilizer dose.

Strategies for Coexistence in Molecular Communication.

Some of the most ambitious applications of molecular communications are expected to lie in nanomedicine and advanced manufacturing. In these domains, the molecular communication system is surrounded by a range of biochemical processes, some of which may be sensitive to chemical species used for communication. Under these conditions, the biological system and the molecular communication system impact each other.

PS-CARA: Context-Aware Resource Allocation Scheme for Mobile Public Safety Networks.

The fifth-generation (5G) communications systems are expecting to support users with diverse quality-of-service (QoS) requirements. Beside these requirements, the task with utmost importance is to support the emergency communication services during natural or man-made disasters. Most of the conventional base stations are not properly functional during a disaster situation, so deployment of emergency base stations such as mobile personal cell (mPC) is crucial.

Impact of a computer-generated alert system prompting review of antibiotic use in hospitals.

Objectives: The aim of this study was to measure the impact on antibiotic use of a computer-generated alert prompting post-prescription review and direct counselling in hospital wards.

Methods: A computer-generated alert on new prescriptions of 15 antibiotics was reviewed weekly by an infectious disease physician for 41 weeks. During the first 6 months of the study, criteria selected for potential intervention were: (i) a planned duration of treatment of > or =10 days; (ii) discordance between the spectrum of the prescribed antibiotic and available microbiological results; or (iii) prescriptions of broad-spectrum beta-lactams, fluoroquinolones, glycopeptides or linezolid.

Enhanced expression of uridine diphosphate-N-acetylglucosaminyl transferase (OGT) in a stable, tetracycline-inducible HeLa cell line using histone deacetylase inhibitors: kinetics of cytosolic OGT accumulation and nuclear translocation.

We have created a stable, tetracycline-inducible HeLa cell line that overexpresses murine uridine diphosphate-N-acetylglucosaminyl transferase (OGT). Tetracycline increased cytosolic OGT activity about 4-fold in a dose-dependent manner (ED(50)=0.03 microg/ml) with enhanced activity observable at 8h and maximal activity observable by 40h.

Measurement of UDP-N-acetylglucosaminyl transferase (OGT) in brain cytosol and characterization of anti-OGT antibodies.

UDP-N-acetylglucosaminyl transferase (OGT) catalyzes O-linked glycosylation of cytosolic and nuclear proteins, but enzyme studies have been hampered by the lack of a rapid, sensitive, and economical OGT assay. Employed assay methods typically involved the use of HPLC, formic acid, and large amounts of expensive radiolabeled [3H]UDP-N-acetylglucosaminyl ([3H]UDP-GlcNAc). In the current study, we have developed an OGT assay that circumvents many of these problems through four critical assay improvements: (1) identification of an abundant and enriched source of OGT enzyme (rat brain tissue), (2) utilization of a rapid method for efficiently removing salts and sugar nucleotides from cytosol (polyethylene glycol precipitation of active enzyme), (3) expression of a recombinant p62 acceptor substrate designed to facilitate purification (polyhistidine metal-chelation site), and (4) development of two alternative methods to rapidly separate free [3H]UDP-GlcNAc from 3H-p62ST acceptor peptide (trichloroacetic acid precipitation and metal-chelation affinity purification).