Results 71 to 80 of about 5,174,905 (327)

Understanding requirements engineering process: a challenge for practice and education [PDF]

open access: yes, 2005
Reviews of the state of the professional practice in Requirements Engineering (RE) stress that the RE process is both complex and hard to describe, and suggest there is a significant difference between competent and "approved" practice.
Armarego, J., Nguyen, L., Swatman, P.
core   +1 more source

A Product Line Systems Engineering Process for Variability Identification and Reduction

open access: yes, 2018
Software Product Line Engineering has attracted attention in the last two decades due to its promising capabilities to reduce costs and time to market through reuse of requirements and components.
Dickerson, Charles   +4 more
core   +1 more source

A Cre‐dependent lentiviral vector for neuron subtype‐specific expression of large proteins

open access: yesFEBS Letters, EarlyView.
We designed a versatile and modular lentivector comprising a Cre‐dependent switch and self‐cleaving 2A peptide and tested it for co‐expression of GFP and a 2.8 kb gene of interest (GOI) in mouse cortical parvalbumin (PV+) interneurons and midbrain dopamine (TH+) neurons.
Weixuan Xue   +6 more
wiley   +1 more source

Modelling and managing reliability growth during the engineering design process [PDF]

open access: yes, 2010
[This is a keynote speech presented at the 2nd International Conference on Design Engineering and Science, discussing modelling and managing reliability growth during the engineering process.] Reliability is vital for safe and efficient operation of ...
Quigley, J.L., Walls, Lesley
core  

A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems [PDF]

open access: yes, 2019
We propose a set of compositional design patterns to describe a large variety of systems that combine statistical techniques from machine learning with symbolic techniques from knowledge representation.
Teije, Annette ten, van Harmelen, Frank
core   +2 more sources

Targeting EZH2 reverses thyroid cell dedifferentiation and enhances iodide uptake in anaplastic thyroid cancer

open access: yesFEBS Letters, EarlyView.
Anaplastic thyroid cancer (ATC) lacks iodide uptake ability due to MAPK activation increasing the expression of the histone methyltransferase EZH2, which represses thyroid differentiation genes (TDGs) such as the sodium iodide symporter (NIS). Dual inhibition of MAPK (U0126) and EZH2 (EPZ6438/Tazemetostat) reverses this mechanism, thus restoring TDG ...
Diego Claro de Mello   +6 more
wiley   +1 more source

Generative artificial intelligence in chemical engineering spans multiple scales

open access: yesFrontiers in Chemical Engineering
Recent advances in generative artificial intelligence (GenAI), particularly large language models (LLMs), are profoundly impacting many fields. In chemical engineering, GenAI plays a pivotal role in the design, scale-up, and optimization of chemical and ...
Benjamin Decardi-Nelson   +6 more
doaj   +1 more source

Innentitelbild: Strain Engineering of a MXene/CNT Hierarchical Porous Hollow Microsphere Electrocatalyst for a High‐Efficiency Lithium Polysulfide Conversion Process (Angew. Chem. 5/2021) [PDF]

open access: bronze, 2021
Xin Wang   +13 more
openalex   +1 more source

By dawn or dusk—how circadian timing rewrites bacterial infection outcomes

open access: yesFEBS Letters, EarlyView.
The circadian clock shapes immune function, yet its influence on infection outcomes is only beginning to be understood. This review highlights how circadian timing alters host responses to the bacterial pathogens Salmonella enterica, Listeria monocytogenes, and Streptococcus pneumoniae revealing that the effectiveness of immune defense depends not only
Devons Mo   +2 more
wiley   +1 more source

USE OF NEURAL NETWORKS IN PROCESS ENGINEERING Thermodynamics, diffusion, and process control and simulation applications

open access: yesCT&F Ciencia, Tecnología & Futuro, 1998
This article presents the current status of the use of Artificial Neural Networks (ANNs) in process engineering applications where common mathematical methods do not completely represent the behavior shown by experimental observations, results, and plant
F OTERO
doaj  

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