Article on canopy gaps and understory light spectrum in a Venezuelan Andean cloud forest.

Article describes development of an ultrafine-grained magnesium alloy with an extraordinary strength and ductility combination, exceptional high specific strength, zero yield strength asymmetry and excellent high strain rate superplasticity.

This article investigates twist grain boundaries with molecular dynamic simulations to reveal their atomic structures, energy and interactions with dislocations.

Article (1) developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts, and (2) generating a set of realistic synthetic natural language access control policies (NLACPs) to evaluate the proposed framework.

This article explores the short-term effects of extracellular Zn²⁺ on human smooth muscle cells.

Article is a study proposing an approach for blood cancer disease prediction using the supervised machine learning approach to perform blood cancer prediction with high accuracy using microarray gene data.

This paper discusses capacity allocation in multi-cell UMTS networks.

This presentation discusses user and interference models, wideband code division multiple access (WCDMA) capacity with perfect and imperfect power control, and spreading factors with numerical results.

Patent relating to a clutch driven reaction wheel steering unit.

Article exploring friction stir alloying (FSA) to tune the microstructure and a composition of a TWIP high-entropy alloy by adding Ti, and thus activating site-specific deformation mechanisms that occur concomitantly in a single alloy. This approach presents a novel microstructural architecture to design alloys, an approach that combines and optimizes local compositions such that multiple deformation mechanisms can be activated to enhance engineering properties.

Data management plan for the grant, "Collaborative Research: DMREF: AI-enabled Automated design of ultrastrong and ultraelastic metallic alloys"

Data management plan for the grant, "Collaborative Research: SHF: Small: LEGAS: Learning Evolving Graphs At Scale." This project aims to improve the computation efficiency of graph neural networks (GNNs), which are an emerging class of deep learning models on graphs, with many successful applications, such as, recommendation systems, drug discovery, social network analysis, and code vulnerability detection. This project aims to to design an efficient GNN framework via algorithm and system co-design for both static and dynamic graphs.

Data management plan for the grant, "CPS: Medium: Integrating sensors, controls, and ecotoxicology with decoupled aquaponics using brackish groundwater and desalination concentrate for sustainable food production." This project aims to develop a cyber-physical system (CPS) testbed of integrated sensors, controls, machine learning, and ecotoxicology tools to engineer sustainable food production systems based on aquaculture using brackish water. The testbed includes an automated recirculating aquaculture system integrated with a real-time ecotoxicology system, implementing the system using desalination concentrate to demonstrate that brackish groundwater desalination costs can be offset by using its byproducts for profitable food production. This project will engage students of the local communities in three major ways: developing an exhibit and activity emphasizing interdisciplinary CPS research conducted during the academic year, offering summer research experiences to students from underrepresented groups, and participating in STEM outreach events targeting underrepresented groups.

Article describes the development of bcc-ordered B2 and fcc phases manifested in three different orientation relationships (ORs) in the same microstructure: Kurdjumov–Sachs, Nishiyama–Wasserman and Pitsch.

Article describes how distributed-denial-of-service (DDoS) attacks can cause a great menace to numerous organizations and their stakeholders. The authors assert that the objective of this research work is to take into account a DDoS afflicted SDN specific dataset and detect the malicious traffic by using various machine learning algorithms namely., K-Nearest Neighbours, Logistic Regression, Multilayer Perceptron, Iterative Dichotomiser 3, and Stochastic Gradient Descent.

This article aims to give a summary of the state of the art of non-enzymatic electrochemical sensors used for detection of neurotransmitter that lack an electrochemically active component.

This article discusses document indexing using named entities.

Article explores degradation of Portland concrete and finds that the combination of fly ash with polymers provides significantly improved properties.

This article discusses the development of a high-strength molded fiber material using pulp fibers, which coudl be a good substitute for plastic and solid wood materials.

This article uses iron oxide/alumina heterostructures formed by two-step infiltration of polystyrene-block-polyvinyl pyridine block copolymer with iron and aluminum precursors from the solution and vapor-phases, respectively, to show that the phase and morphology of iron oxide nanoparticles dramatically depend on the approach used to remove the polymer. The article extends the boundaries of structure manipulations in multicomponent heterostructures synthesized using polymer infiltration synthesis and their properties.

This article evaluates the phase-specific electrochemical and friction characteristics of a Zr-based mtallic glass composite, which comprised roughly of 40% by volume crystalline dendrites in an amorphous matrix.

Article describes examination of the appearance, color, chemical composition, and physiology and mechanical properties of densified Abies wood before and after densification treatment using a colorimeter, FTIR and mechanical testing machine.

This article is a review of friction stir additive manufacturing (FSAM) and additive friction stir deposition (AFSD) and provides a systems approach framework and a conceptual process model to guide researchers.

This paper discusses grid-based coordinated routing in wireless sensor networks and compares the energy available in the network over time for different grid sizes. The authors explore the quality of service of wireless sensor networks, how the coordinator nodes are elected, and the size of the grid area that will minimize the total energy consumption and extend the lifetime of the network.