447 research outputs found
High-throughput screening of encapsulated islets using wide-field lens-free on-chip imaging
Islet microencapsulation is a promising solution to diabetes treatment, but
its quality control based on manual microscopic inspection is extremely
low-throughput, highly variable and laborious. This study presents a
high-throughput islet-encapsulation quality screening system based on lens-free
on-chip imaging with a wide field-of-view of 18.15 cm^2, which is more than 100
times larger than that of a lens-based optical microscope, enabling it to image
and analyze ~8,000 microcapsules in a single frame. Custom-written image
reconstruction and processing software provides the user with clinically
important information, such as microcapsule count, size, intactness, and
information on whether each capsule contains an islet. This high-throughput and
cost-effective platform can be useful for researchers to develop better
encapsulation protocols as well as perform quality control prior to
transplantation
Terahertz Pulse Shaping Using Diffractive Surfaces
Recent advances in deep learning have been providing non-intuitive solutions
to various inverse problems in optics. At the intersection of machine learning
and optics, diffractive networks merge wave-optics with deep learning to design
task-specific elements to all-optically perform various tasks such as object
classification and machine vision. Here, we present a diffractive network,
which is used to shape an arbitrary broadband pulse into a desired optical
waveform, forming a compact pulse engineering system. We experimentally
demonstrate the synthesis of square pulses with different temporal-widths by
manufacturing passive diffractive layers that collectively control both the
spectral amplitude and the phase of an input terahertz pulse. Our results
constitute the first demonstration of direct pulse shaping in terahertz
spectrum, where a complex-valued spectral modulation function directly acts on
terahertz frequencies. Furthermore, a Lego-like physical transfer learning
approach is presented to illustrate pulse-width tunability by replacing part of
an existing network with newly trained diffractive layers, demonstrating its
modularity. This learning-based diffractive pulse engineering framework can
find broad applications in e.g., communications, ultra-fast imaging and
spectroscopy.Comment: 27 pages, 6 figure
Spectrally-Encoded Single-Pixel Machine Vision Using Diffractive Networks
3D engineering of matter has opened up new avenues for designing systems that
can perform various computational tasks through light-matter interaction. Here,
we demonstrate the design of optical networks in the form of multiple
diffractive layers that are trained using deep learning to transform and encode
the spatial information of objects into the power spectrum of the diffracted
light, which are used to perform optical classification of objects with a
single-pixel spectroscopic detector. Using a time-domain spectroscopy setup
with a plasmonic nanoantenna-based detector, we experimentally validated this
machine vision framework at terahertz spectrum to optically classify the images
of handwritten digits by detecting the spectral power of the diffracted light
at ten distinct wavelengths, each representing one class/digit. We also report
the coupling of this spectral encoding achieved through a diffractive optical
network with a shallow electronic neural network, separately trained to
reconstruct the images of handwritten digits based on solely the spectral
information encoded in these ten distinct wavelengths within the diffracted
light. These reconstructed images demonstrate task-specific image decompression
and can also be cycled back as new inputs to the same diffractive network to
improve its optical object classification. This unique machine vision framework
merges the power of deep learning with the spatial and spectral processing
capabilities of diffractive networks, and can also be extended to other
spectral-domain measurement systems to enable new 3D imaging and sensing
modalities integrated with spectrally encoded classification tasks performed
through diffractive optical networks.Comment: 21 pages, 5 figures, 1 tabl
Rapid Sensing of Hidden Objects and Defects using a Single-Pixel Diffractive Terahertz Processor
Terahertz waves offer numerous advantages for the nondestructive detection of
hidden objects/defects in materials, as they can penetrate through most
optically-opaque materials. However, existing terahertz inspection systems are
restricted in their throughput and accuracy (especially for detecting small
features) due to their limited speed and resolution. Furthermore, machine
vision-based continuous sensing systems that use large-pixel-count imaging are
generally bottlenecked due to their digital storage, data transmission and
image processing requirements. Here, we report a diffractive processor that
rapidly detects hidden defects/objects within a target sample using a
single-pixel spectroscopic terahertz detector, without scanning the sample or
forming/processing its image. This terahertz processor consists of passive
diffractive layers that are optimized using deep learning to modify the
spectrum of the terahertz radiation according to the absence/presence of hidden
structures or defects. After its fabrication, the resulting diffractive
processor all-optically probes the structural information of the sample volume
and outputs a spectrum that directly indicates the presence or absence of
hidden structures, not visible from outside. As a proof-of-concept, we trained
a diffractive terahertz processor to sense hidden defects (including
subwavelength features) inside test samples, and evaluated its performance by
analyzing the detection sensitivity as a function of the size and position of
the unknown defects. We validated its feasibility using a single-pixel
terahertz time-domain spectroscopy setup and 3D-printed diffractive layers,
successfully detecting hidden defects using pulsed terahertz illumination. This
technique will be valuable for various applications, e.g., security screening,
biomedical sensing, quality control, anti-counterfeiting measures and cultural
heritage protection.Comment: 23 Pages, 5 Figure
Electrical properties and I–V characteristics of 5,14-dihydro-5,7,12,14-tetraazapentacene doped Schottky barrier diode
A comparison among PCNL, Miniperc and Ultraminiperc for lower calyceal stones between 1 and 2 cm: A prospective, comparative, multicenter and randomised study
Background: Conventional Percutaneous Lithotripsy (PCNL) has been an effective, successful and easy approach for especially > 1 cm sized calyceal stones however risks of complications and nephron loss are inevitable. Our aim is to compare the efficacy and safety of PCNL, MiniPerc (MP) and UltraMiniPerc (UMP) for lower calyceal stones between 1 and 2 cm with a multicenter prospective randomized study. Methods: Between January 2015 and June 2018, 132 consecutive patients with single lower calyceal stone were enrolled. Patients were randomized in three groups; A: PCNL; B: MP; C: UMP. 44 patients for the Group A, 47 for Group B and 41 for Group C. Exclusion criterias were the presence of coagulation impairments, age of < 18 or > 75, presence of infection or serious comorbidities. Patients were controlled with computerized tomography scan after 3 months. A negative CT or an asymptomatic patient with stone fragments < 3 mm size were the criteria to assess the stone-free status. Patient characteristics, stone free rates (SFR) s, complications and re-treatment rates were analyzed. Results: The mean stone size were 16.38, 16.82 and 15.23 mm respectively in Group A, B and C(p = 0.34). The overall SFR was significantly higher in Group A (86.3%) and B (82.9%) as compared to Group C (78%)(p < 0.05). The re-treatment rate was significantly higher in Group C (12.1%) and complication rates was higher in Group A (13.6%) as compared to others(p < 0.05). The hospitalization was significantly shorter in Group C compared to Group A (p = 0.04). Conclusions: PCNL and MP showed higher efficacy than UMP to obtain a better SFR. Auxiliary and re-treatment rates were higher in UMP. On the other hand for such this kind of stones PCNL had more complications. Overall evaluation favors MP as a better indication in stones 1-2 cm size
A prospective multicenter randomized comparison between Holmium Laser Enucleation of the Prostate (HoLEP) and Thulium Laser Enucleation of the Prostate (ThuLEP)
Purpose: To compare intra and perioperative parameters between HoLEP and ThuLEP in the treatment of benign prostatic hyperplasia and to evaluate clinical and functional outcomes of the two procedures with a 12-month follow-up. Methods: A prospective randomized study was performed on 236 consecutive patients who underwent ThuLEP (n = 115), or HoLEP (n = 121) in three different centers. Intra and perioperative parameters were analyzed: operative time, enucleated tissue weight, irrigation volume, blood loss, catheterization time, hospital stay and complications. Patients were evaluated preoperatively and 3 and 12 months postoperatively with the international prostate symptom score (IPSS), the quality of life (QoL) score, post-void residual volume (PVR), PSA and maximum flow rate (Qmax). Results: Preoperative variables in each study arm did not show any significant difference. Compared to HoLEP, ThuLEP showed similar operative time (63.69 vs 71.66 min, p = 0.245), enucleated tissue weight (48.84 vs 51.13 g, p = 0.321), catheterization time (1.9 vs 2.0 days, p = 0.450) and hospital stay (2.2 vs 2.8 days, p = 0.216), but resulted in less haemoglobin decrease (0.45 vs 2.77 g/dL, p = 0.005). HoLEP presented a significantly higher number of patients with postoperative acute urinary retention and stress incontinence. No significant differences were found in PSA, Qmax, PVR, IPSS and QoL score during follow-up. Conclusion: ThuLEP and HoLEP both relieved lower urinary tract symptoms equally, with high efficacy and safety. ThuLEP detemined reduced blood loss and early postoperative complications. Catheterization time, enucleated tissue, hospital stay, operative time and follow-up parameters did not show any significant difference
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