Article models work hardening response in TRIP HEAs under tensile deformation, which reflects the hardening due to synergistic activity of multiple deformation mechanisms, using a five-parameter work hardening model.

Data management plan for the grant, "Ultra-High Temperature Stable Morphing Materials for Hypersonic Applications"

Article using ab initio calculations and experimental observations to show that {332}<113> twinning can be described as a polymorphic solid-state transformation able to produce either twinned or martensitic structures with a unified transformation path.

Article presents for the first time the influence of a hierarchically decomposed B2 + A2 structure in an AlCo0.5Cr0.5FeNi HEA on the formation of magnetic vortex states within individual A2 (disordered BCC) precipitates, which are distributed in an ordered B2 matrix that is weakly ferromagnetic.

This article is a study where the authors integrated the multi-omics datasets such as copy number aberration, DNA methylation, gene and microRNA expression to identify the signature microRNA-gene associations from frequently aberrated DNA regions across pan-cancer utilizing a LASSO-based regression approach.

Article presents a motion-sensing device with the capability of harvesting energy from low-frequency motion activities. Based on the high surface area reverse electrowetting-on-dielectric (REWOD) energy harvesting technique, mechanical modulation of the liquid generates an AC signal, which is modeled analytically and implemented in Matlab and COMSOL.

Article investigating the effect of the relative motion of nano CaCO3 reinforced bamboo pulp fiber (BPF)/HDPE composite components on the mechanical performance.

Article says that plasmonic and phase transition has been blended to gain the infrared radiative switching which is tunable with temperature or voltage supply. This is applied via vanadium dioxide, tungsten trioxide, and molybdenum trioxide as transition metal oxides (TMO), the authors state that the work expands the usage of transition metal oxides in infrared region with larger contrast.

Data management plan for the grant, "REU Site: TaMaLe - Testing and Machine Learning for Context-Driven Systems: Research Experience for Undergraduates." TaMaLe (Testing and Machine Learning for Context-Driven Systems), a renewal Research Experience for Undergraduates (REU) Site at University of North Texas, engages 10 undergraduate students for 10 weeks with problems in the context-driven system domain. The students explore research problems to improve the reliability and security of context-driven systems. Context-driven systems, such as mobile apps, face constant streams of input from both users and context changes in their environments. Users interact with apps through touch and speech interfaces. These systems also respond to context events that occur in their environments such as changes to network connection, battery level, screen orientation, and more. The combined explosion of possible user events and context event sequences pose new challenges that require cost effective testing solutions. Students and mentors in this REU program work in small teams to develop and empirically evaluate new software testing techniques for context-driven systems using strategies such as reinforcement learning and combinatorial-based techniques.

Article investigates the strength-ductility synergy of high-entropy alloys (HEAs).

This article presents a detailed investigation on the influence of building orientation and feature dimensions in laser powder bed fusion (L-PBF) parts.

Article reviewing several several flexible and stretchable materials used as substrate, stretchable electrical conduits and encapsulation, design modifications for stretchability, fabrication techniques, methods of signal transmission and monitoring, and the power sources for these stretchable bioelectronics. Ultimately, these bioelectronic devices can be used for wide range of applications from skin bioelectronics and biosensing devices, to neural implants for diagnostic or therapeutic purposes.

Article is a study investigating how to obtain the natural frequency of functionally graded porous beams simply supported on an elastic substrate in thermal surroundings by the theory of third-order shear deformation. This article is part of the special issue titled Dynamic Analysis and Vibration Control of Mechanical Structures Coupled with Rotational Systems.

Article is a study analyzing the global perceptions and perspectives towards COVID-19 vaccination using a worldwide Twitter dataset, natural language processing, and machine learning.

Article utilizing Raman spectroscopy and photoluminescence (PL) spectroscopy to analyze the phononic and electronic parameters in suspended bulk WSe₂ sheets, fabricated utilizing photolithography and wet chemical etching. The findings of this work will be beneficial in analyzing thermal, optical, and mechanical properties of WSe₂ in a suspended platform for its application in electronic, thermoelectric, and mechanical sensors in the future.

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 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 article presents a study detecting Tweets that contain racist text by performing the sentiment analysis of Tweets. The proposed GCR-NN model can detect 97% of the tweets that contain racist comments.

Article investigating the mechanical behavior of a metastable high entropy alloy (HEA) with composition Fe39-Mn20-Co20-Cr15-Si5-1Al (at%).

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 review article summarizes the latest neuropathological discoveries at the molecular, cellular, and tissue levels involving both animal and patient studies, aiming to explore epileptogenesis and highlight new potential targets in the diagnosis and treatment of temporal lobe epilepsy (TLE).

Article is a study proposing an original method to quantitatively evaluate the gradient distribution and aggregate structure of fibers on the flexibility and flexural toughness of natural moso (Phyllostachys edulis) bamboo, with a comparison to two other natural woods.

Article proposes a Machine Learning (ML) and Deep Learning based system to detect the presence of two critical disease spreading classes of mosquitoes in order to prevent mosquito-borne infection.

This article surveys previous work on negation with an emphasis on computational approaches.