Difference between revisions of "Main Page/Featured article of the week/2024"
Shawndouglas (talk | contribs) (Added last week's article of the week) |
Shawndouglas (talk | contribs) (Added last week's article of the week) |
||
(5 intermediate revisions by the same user not shown) | |||
Line 17: | Line 17: | ||
<!-- Below this line begin pasting previous news --> | <!-- Below this line begin pasting previous news --> | ||
<h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: March 18–24:</h2> | <h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: April 12–28:</h2> | ||
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Tomich Sustain23 15-8.png|260px]]</div> | |||
'''"[[Journal:Why do we need food systems informatics? Introduction to this special collection on smart and connected regional food systems|Why do we need food systems informatics? Introduction to this special collection on smart and connected regional food systems]]"''' | |||
Public interest in where food comes from and how it is produced, processed, and distributed has increased over the last few decades, with even greater focus emerging during the [[COVID-19]] [[pandemic]]. Mounting evidence and experience point to disturbing weaknesses in our food systems’ abilities to support human livelihoods and wellbeing, and alarming long-term trends regarding both the environmental footprint of food systems and mounting vulnerabilities to shocks and stressors. How can we tackle the “wicked problems” embedded in a food system? More specifically, how can convergent research programs be designed and resulting knowledge implemented to increase inclusion, sustainability, and resilience within these complex systems ... ('''[[Journal:Why do we need food systems informatics? Introduction to this special collection on smart and connected regional food systems|Full article...]]''')<br /> | |||
|- | |||
|<br /><h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: April 15–21:</h2> | |||
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Tab1 Williamson F1000Res2023 10.png|240px]]</div> | |||
'''"[[Journal:Data management challenges for artificial intelligence in plant and agricultural research|Data management challenges for artificial intelligence in plant and agricultural research]]"''' | |||
[[Artificial intelligence]] (AI) is increasingly used within plant science, yet it is far from being routinely and effectively implemented in this domain. Particularly relevant to the development of novel food and agricultural technologies is the development of validated, meaningful, and usable ways to integrate, compare, and [[Data visualization|visualize]] large, multi-dimensional datasets from different sources and scientific approaches. After a brief summary of the reasons for the interest in data science and AI within plant science, the paper identifies and discusses eight key challenges in [[Information management|data management]] that must be addressed to further unlock the potential of AI in crop and agronomic research, and particularly the application of [[machine learning]] (ML), which holds much promise for this domain ... ('''[[Journal:Data management challenges for artificial intelligence in plant and agricultural research|Full article...]]''')<br /> | |||
|- | |||
|<br /><h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: April 08–14:</h2> | |||
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Manisha HighConComp2023 3-3.jpg|240px]]</div> | |||
'''"[[Journal:A blockchain-driven IoT-based food quality traceability system for dairy products using a deep learning model|A blockchain-driven IoT-based food quality traceability system for dairy products using a deep learning model]]"''' | |||
Food [[traceability]] is a critical factor that can ensure food safety while enhancing the credibility of the manufactured product, thus achieving heightened user satisfaction and loyalty. The perishable food supply chain (PFSC) requires paramount care for ensuring [[Quality (business)|quality]] owing to the limited product life. The PFSC comprises of multiple organizations with varied interests and is more likely to be hesitant in sharing the traceability details among one another owing to a lack of trust, which can be overcome by using blockchain. In this research, an efficient scheme using a blockchain-enabled deep [[wikipedia:Residual neural network|residual network]] (BC-DRN) is developed to provide food traceability for dairy products. Here, food traceability is determined by using various modular tools ... ('''[[Journal:A blockchain-driven IoT-based food quality traceability system for dairy products using a deep learning model|Full article...]]''')<br /> | |||
|- | |||
|<br /><h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: April 01–07:</h2> | |||
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Patel JofClinDiagRes2023 17-9.jpg|140px]]</div> | |||
'''"[[Journal:Effect of good clinical laboratory practices (GCLP) quality training on knowledge, attitude, and practice among laboratory professionals: Quasi-experimental study|Effect of good clinical laboratory practices (GCLP) quality training on knowledge, attitude, and practice among laboratory professionals: Quasi-experimental study]]"''' | |||
Good clinical laboratory practices (GCLP) play a vital role in early and accurate diagnosis, providing high-quality data and timely [[Sample (material)|sample]] processing. Adhering to a robust [[quality management system]] (QMS) that complies with GCLP standards is crucial for [[laboratory]] personnel in a [[clinical laboratory]] to deliver outstanding healthcare services and reliable, reproducible reports. [The aim of this study is to] assess the knowledge, attitude, and practice (KAP) of laboratory professionals towards [[Quality (business)|quality]] in the laboratory through GCLP training... ('''[[Journal:Effect of good clinical laboratory practices (GCLP) quality training on knowledge, attitude, and practice among laboratory professionals: Quasi-experimental study|Full article...]]''')<br /> | |||
|- | |||
|<br /><h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: March 25–31:</h2> | |||
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Scroggie DigDisc2023 2.gif|240px]]</div> | |||
'''"[[Journal:GitHub as an open electronic laboratory notebook for real-time sharing of knowledge and collaboration|GitHub as an open electronic laboratory notebook for real-time sharing of knowledge and collaboration]]"''' | |||
[[Electronic laboratory notebook]]s (ELNs) have expanded the utility of the paper [[laboratory notebook]] beyond that of a simple record keeping tool. Open ELNs offer additional benefits to the scientific community, including increased transparency, reproducibility, and [[Data integrity|integrity]]. A key element underpinning these benefits is facile and expedient knowledge sharing which aids communication and collaboration. In previous projects, we have used [[LabTrove]] and [[Vendor:LabArchives, LLC|LabArchives]] as open ELNs, in partnership with GitHub (an open-source web-based platform originally developed for collaborative coding) for communication and discussion. Here we present our personal experiences using GitHub as the central platform for many aspects of the scientific process ... ('''[[Journal:GitHub as an open electronic laboratory notebook for real-time sharing of knowledge and collaboration|Full article...]]''')<br /> | |||
|- | |||
|<br /><h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: March 18–24:</h2> | |||
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Nieminen GigaScience2023 12.jpeg|240px]]</div> | <div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Nieminen GigaScience2023 12.jpeg|240px]]</div> | ||
'''"[[Journal:SODAR: Managing multiomics study data and metadata|SODAR: Managing multiomics study data and metadata]]"''' | '''"[[Journal:SODAR: Managing multiomics study data and metadata|SODAR: Managing multiomics study data and metadata]]"''' |
Revision as of 16:49, 29 April 2024
If you're looking for other "Article of the Week" archives: 2014 - 2015 - 2016 - 2017 - 2018 - 2019 - 2020 - 2021 - 2022 - 2023 - 2024 |
Featured article of the week archive - 2024
Welcome to the LIMSwiki 2024 archive for the Featured Article of the Week.
Featured article of the week: April 12–28:Public interest in where food comes from and how it is produced, processed, and distributed has increased over the last few decades, with even greater focus emerging during the COVID-19 pandemic. Mounting evidence and experience point to disturbing weaknesses in our food systems’ abilities to support human livelihoods and wellbeing, and alarming long-term trends regarding both the environmental footprint of food systems and mounting vulnerabilities to shocks and stressors. How can we tackle the “wicked problems” embedded in a food system? More specifically, how can convergent research programs be designed and resulting knowledge implemented to increase inclusion, sustainability, and resilience within these complex systems ... (Full article...)
|