Advanced functional materials and manufacturing processes

Guest Editors Jessica Winter, Jawwad Darr, and John Wang introduce the Materials Advances themed collection on advanced functional materials and manufacturing processes

Generalizable semi-supervised learning method to estimate mass from sparsely annotated images

Mass flow estimation is of great importance to several industries, and it can be quite challenging to obtain accurate estimates due to limitation in expense or general infeasibility. In the context of agricultural applications, yield monitoring is a key component to precision agriculture and mass flow is the critical factor to measure. Measuring mass flow allows for field productivity analysis, cost minimization, and adjustments to machine efficiency. Methods such as volume or force-impact have been used to measure mass flow; however, these methods are limited in application and accuracy. In this work, we use deep learning to develop and test a vision system that can accurately estimate the mass of sugarcane while running in real-time on a sugarcane harvester during operation. The deep learning algorithm that is used to estimate mass flow is trained using very sparsely annotated images (semi-supervised) using only final load weights (aggregated weights over a certain period of time). The deep neural network (DNN) succeeds in capturing the mass of sugarcane accurately and surpasses older volumetric-based methods, despite highly varying lighting and material colors in the images. The deep neural network is initially trained to predict mass on laboratory data (bamboo) and then transfer learning is utilized to apply the same methods to estimate mass of sugarcane. Using a vision system with a relatively lightweight deep neural network we are able to estimate mass of bamboo with an average error of 4.5% and 5.9% for a select season of sugarcane.Comment: 22 pages, 21 figures, Computers and Electronics in Agriculture. arXiv admin note: text overlap with arXiv:1908.0438

Volumetric based mass flow estimation on sugarcane harvesters

Yield monitors on harvesters are a key component of precision agriculture. Mass flow estimation is the critical factor to measure, and having this allows for field productivity analysis, adjustments to machine efficiency, and cost minimization by ensuring trucks are filled maximally without exceeding weight limits. Several common technologies used on grain harvesters, including impact plate sensors, are accurate enough on combines to be valuable but suffer from issues such as drift. Sugarcane is composed of a mixture of billets and trash, which is a very dispersed material with much less consistency than grains. In this study, a 3d point cloud approach is used to estimate volume, from which a calibration factor is derived [density] to translate to mass. The system was proved in concept in a controlled environment using bamboo, achieving an R2 of 97.4% when fitting average volume flow per test against average mass flow after correcting for bulk density changes with volume. The system was also tested on field data, which was collected from nearly 1700 wagon loads from the southern U.S. and Brazil over the course of 3 seasons in both green and burnt cane. Results indicated that the concept is very robust with good accuracy, having seasonal CVs for density values ranging from 6.9% to 16.2%. The camera concept proves relatively robust to environmental conditions. The same approach could be used in sugar beets, potatoes or other sparse/non-flowing crops with highly varying material properties, where traditional mass flow sensors do not work.Comment: 14 pages, 6 figures, computers and electronics in agriculture journa

Rate Response Assessment from Various Granular VRT Applicators

Variable-rate technology (VRT) adds complexity to application equipment, thereby confounding the assessment of applicator performance. The intent of this investigation was to assess the rate response of various VRT granular applicators: two spinner spreaders (A and B), and two pneumatic applicators (C and D). Variable-rate (VR) tests were conducted to quantify the rate response characteristics (delay and transition times) for the applicators. A sigmoidal function was used to model the rate response for five of the six tests. Applicator A exhibited a linear response during decreasing rate changes. Results indicated that only applicator B demonstrated consistent delay and transition times, enabling the use of a single “look-ahead” time for rate response time correction. Contouring of prescription maps increased the transition times for applicator D by enlarging the adjustment area between management zones. Rate changes were quicker for the two newer VR control systems, signifying advancement in hydraulic control valve technology. This research illustrates the need for standard testing protocols for VRT systems to help guide VRT software developers, equipment manufacturers, and end users

Synthesis and magnetic properties of a copper cube : [Cu4(OH)4(C16H18N2)4]4+ (ClO4)4 C3H6O [C16H18N2 = (E)-1,6-[di(pyridin-4-yl)hex-3-ene

We are grateful to the National Mass Spectrometry Service Center for mass spectra and to the UK National Crystallography Service for data sets. Supplementary Figure S1-S4: IR and UV/Vis spectra of compound 1Peer reviewedPublisher PD

Preclinical development of G1T38: A novel, potent and selective inhibitor of cyclin dependent kinases 4/6 for use as an oral antineoplastic in patients with CDK4/6 sensitive tumors

Inhibition of the p16INK4a/cyclin D/CDK4/6/RB pathway is an effective therapeutic strategy for the treatment of estrogen receptor positive (ER+) breast cancer. Although efficacious, current treatment regimens require a dosing holiday due to severe neutropenia potentially leading to an increased risk of infections, as well as tumor regrowth and emergence of drug resistance. Therefore, a next generation CDK4/6 inhibitor that can inhibit proliferation of CDK4/6-dependent tumors while minimizing neutropenia could reduce both the need for treatment holidays and the risk of inducing drug resistance

Age-related differences in human skin proteoglycans

Previous work has shown that versican, decorin and a catabolic fragment of decorin, termed decorunt, are the most abundant proteoglycans in human skin. Further analysis of versican indicates that four major core protein species are present in human skin at all ages examined from fetal to adult. Two of these are identified as the V0 and V1 isoforms, with the latter predominating. The other two species are catabolic fragments of V0 and V1, which have the amino acid sequence DPEAAE as their carboxyl terminus. Although the core proteins of human skin versican show no major age-related differences, the glycosaminoglycans (GAGs) of adult skin versican are smaller in size and show differences in their sulfation pattern relative to those in fetal skin versican. In contrast to human skin versican, human skin decorin shows minimal age-related differences in its sulfation pattern, although, like versican, the GAGs of adult skin decorin are smaller than those of fetal skin decorin. Analysis of the catabolic fragments of decorin from adult skin reveals the presence of other fragments in addition to decorunt, although the core proteins of these additional decorin catabolic fragments have not been identified. Thus, versican and decorin of human skin show age-related differences, versican primarily in the size and the sulfation pattern of its GAGs and decorin in the size of its GAGs. The catabolic fragments of versican are detected at all ages examined, but appear to be in lower abundance in adult skin compared with fetal skin. In contrast, the catabolic fragments of decorin are present in adult skin, but are virtually absent from fetal skin. Taken together, these data suggest that there are age-related differences in the catabolism of proteoglycans in human skin. These age-related differences in proteoglycan patterns and catabolism may play a role in the age-related changes in the physical properties and injury response of human ski

Cancer stem cells: Mediators of tumorigenesis and metastasis in head and neck squamous cell carcinoma

BackgroundCancer stem cells (CSCs) represent a subpopulation of cells responsible for tumor growth. Their role in head and neck squamous cell carcinoma (HNSCC) tumorigenesis and metastasis remains uncertain.MethodsWound healing and an orthotopic animal model were used to study cells expressing the CSC phenotype (CD44high and aldehyde dehydrogenase [ALDH]+) and assess mobility, tumorigenesis, and metastasis. A prospective collection of 40 patient‐derived primary HNSCC specimens were analyzed for CSC‐proportion compared to clinical variables.ResultsCSCs exhibited significantly faster wound closure and greater tumorigenesis and regional metastasis in vivo than non‐CSCs. In primary patient tumors, size and advanced stage were correlated with elevated proportion of CSCs, however, not with survival.ConclusionHNSCC stem cells mediate tumorigenesis and regional metastasis in vivo. In primary patient tumors, CSC‐proportion was associated with tumor size and stage, but not with metastatic spread or survival. CSC burden alone may only represent a minor variable in understanding CSCs and metastasis. © 2014 Wiley Periodicals, Inc. Head Neck 37: 317–326, 2015Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110728/1/hed23600.pd