279 research outputs found
A novel chondroitin sulfate hydrogel for nerve repair
No full textBrachial plexus injuries affect numerous patients every year, with very debilitating results. The majority of these cases are very severe, and involve damage to the nerve roots. To date, repair strategies for these injuries address only gross tissue damage, but do not supply cells with adequate regeneration signals. As a result, functional recovery is often severely lacking. Therefore, a chondroitin sulfate hydrogel that delivers neurotrophic signals to damaged neurons is proposed as a scaffold to support nerve root regeneration. Capillary electrophoresis studies revealed that chondroitin sulfate can physically bind with a variety of neurotrophic factors, and cultures of chick dorsal root ganglia demonstrated robust neurite outgrowth in chondroitin sulfate hydrogels. Outgrowth in chondroitin sulfate gels was greater than that observed in control gels of hyaluronic acid. Furthermore, the chondroitin sulfate hydrogel’s binding activity with nerve growth factor could be enhanced by incorporation of a synthetic bioactive peptide, as revealed by fluorescence recovery after photobleaching. This enhanced binding was observed only in chondroitin sulfate gels, and not in hyaluronic acid control gels. This enhanced binding activity resulted in enhanced dorsal root ganglion neurite outgrowth in chondroitin sulfate gels. Finally, the growth of regenerating dorsal root ganglia in these gels was imaged using label-free coherent anti-Stokes scattering microscopy. This technique generated detailed, high-quality images of live dorsal root ganglion neurites, which were comparable to fixed, F-actin-stained samples. Taken together, these results demonstrate the viability of this chondroitin sulfate hydrogel to serve as an effective implantable scaffold to aid in nerve root regeneration
BACK TO THE FUTURE: A WILLINGNESS TO PLAY REEXAMINED
No full textAs the Central Arizona project is being completed and contracts are being negotiated, economic analysis continues to show that neither agriculture nor municipalities would benefit from the project if repayment actually is required according to previously suggested schedules. Earlier analyses were either ignored or condemned as farmers were willing to play a water development game in the face of uncertain future repayment requirements. The game of playing for subsidized water continues even as the buyers now face real costs rather than just some future possibility of incurring costs. Recent analysis is being used to help negotiate favorable delivery and repayment contracts. Experience has shown that once the physical development is in place, costs are negotiable.Resource /Energy Economics and Policy,
Data_Sheet_1_Building One-Shot Semi-Supervised (BOSS) Learning Up to Fully Supervised Performance.pdf
No full textReaching the performance of fully supervised learning with unlabeled data and only labeling one sample per class might be ideal for deep learning applications. We demonstrate for the first time the potential for building one-shot semi-supervised (BOSS) learning on CIFAR-10 and SVHN up to attain test accuracies that are comparable to fully supervised learning. Our method combines class prototype refining, class balancing, and self-training. A good prototype choice is essential and we propose a technique for obtaining iconic examples. In addition, we demonstrate that class balancing methods substantially improve accuracy results in semi-supervised learning to levels that allow self-training to reach the level of fully supervised learning performance. Our experiments demonstrate the value with computing and analyzing test accuracies for every class, rather than only a total test accuracy. We show that our BOSS methodology can obtain total test accuracies with CIFAR-10 images and only one labeled sample per class up to 95% (compared to 94.5% for fully supervised). Similarly, the SVHN images obtains test accuracies of 97.8%, compared to 98.27% for fully supervised. Rigorous empirical evaluations provide evidence that labeling large datasets is not necessary for training deep neural networks. Our code is available at https://github.com/lnsmith54/BOSS to facilitate replication.</p
Development of affinity-based delivery of NGF from a chondroitin sulfate biomaterial
No full textChondroitin sulfate is a major component of the extracellular matrix in both the central and peripheral nervous systems. Chondroitin sulfate is upregulated at injury, thus methods to promote neurite extension through chondroitin sulfate-rich matrices and synthetic scaffolds are needed. We describe the use of both chondroitin sulfate and a novel chondroitin sulfate-binding peptide to control the release of nerve growth factor. Interestingly, the novel chondroitin sulfate-binding peptide enhances the controlled release properties of the chondroitin sulfate gels. While introduction of chondroitin sulfate into a scaffold inhibits primary cortical outgrowth, the combination of chondroitin sulfate, chondroitin sulfate-binding peptide and nerve growth factor promotes primary cortical neurite outgrowth in chondroitin sulfate gels
Search for a feebly interacting particle X in the decay K + → π + X
No full textA search for the K+ → π+X decay, where X is a long-lived feebly interacting particle, is performed through an interpretation of the K+ → π+νν ̄ analysis of data collected in 2017 by the NA62 experiment at CERN. Two ranges of X masses, 0–110 MeV/c2 and 154–260 MeV/c2, and lifetimes above 100 ps are considered. The limits set on the branching ratio, BR(K+ → π+X), are competitive with previously reported searches in the first mass range, and improve on current limits in the second mass range by more than an order of magnitude
An unshielded radio-frequency atomic magnetometer with sub-femtoTesla sensitivity
No full textWe demonstrate a radio-frequency potassium-vapor magnetometer operating with sensitivities of 0.3 fT/
Hz
at 0.5 MHz and 0.9 fT/
Hz
at 1.31 MHz in the absence of radio-frequency and mu-metal or magnetic shielding. The use of spatially separated magnetometers, two voxels within the same cell, permits for the subtraction of common mode noise and the retention of a gradient signal, as from a local source. At 0.5 MHz the common mode noise was white and measured to be 3.4 fT/
Hz
; upon subtraction the noise returned to the values observed when the magnetometer was shielded. At 1.31 MHz, the common mode noise was from a nearby radio station and was reduced by a factor of 33 upon subtraction, limited only by the radio signal picked up by receiver electronics. Potential applications include in-the-field low-field magnetic resonance, such as the use of nuclear quadrupole resonance for the detection of explosives
Improved calorimetric particle identification in NA62 using machine learning techniques
No full textMeasurement of the ultra-rare K+→ π+νν ̄ decay at the NA62 experiment at CERN requires high-performance particle identification to distinguish muons from pions. Calorimetric identification currently in use, based on a boosted decision tree algorithm, achieves a muon misidentification probability of 1.2 × 10 −5 for a pion identification efficiency of 75% in the momentum range of 15–40 GeV/c. In this work, calorimetric identification performance is improved by developing an algorithm based on a convolutional neural network classifier augmented by a filter. Muon misidentification probability is reduced by a factor of six with respect to the current value for a fixed pion-identification efficiency of 75%. Alternatively, pion identification efficiency is improved from 72% to 91% for a fixed muon misidentification probability of 10 −5
In-flight search for K+ → π+νν: First NA62 results
No full textNA62 has searched for the K+ → π+νν decay using a new kaon decay in-flight technique. One candidate event, compatible with the Standard Model prediction, has been observed from a sample of 1.2 ×1011 decays. Assuming that the event is background, an upper limit of 1.4 ×10−9 (95% CL) has been placed. Prospects for further improvements of the measurement are given
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