BIST/Digital-Compatible Testing of RF Devices Using Distortion Model Fitting

Testing of Radio Frequency (RF) circuits for nonlinearity specifications generally requires the use of multiple test measurements thereby contributing to increased test cost. Prior RF test methods have suffered from significant test calibration effort (training for supervised learners) when using compact tests or from increased test time due to direct specification measurement. On the other hand, due to aggressive technology scaling, there are plenty of digital transistors available that can be used to simplify testing of Analog/Mixed-Signal (AMS) and RF devices. In this paper, an RF test methodology is developed that: (a) allows RF devices to be tested for several distortion specifications using distortion model fitting algorithms in test time comparable to what can be achieved using supervised learning techniques while retaining the accuracy of direct specification measurement, (b) allows multiple RF specifications to be determined concurrently from a single data acquisition and (c) allows digital-compatible testing/BIST to be performed using digital testers or on-chip built in self-test (BIST) circuitry. With regard to (a), a key benefit is that no training of supervised learning algorithm is necessary. The proposed method based on distortion model fitting is shown to give excellent results across common RF performance metrics while providing ~10× improvements in test time compared to previous methods.     

An Adaptive Transmission Mode Selection Scheme for Cellular Underlaid D2D Communication

In this paper, we propose to use Artificial Bee Colony (ABC) optimization to solve the joint mode selection, channel assignment, and power allocation (JMSCPA) problem to maximize system throughput and spectral efficiency. JMSCPA is a problem where the allocation of channel and power depends on the mode selection. Such problems require two step solution and are called bi-level optimization problems. As bi-level optimization increases the complexity and computational time, we propose a modified version of single-level ABC algorithm aided with the adaptive transmission mode selection algorithm to allocate the cellular, reuse, and dedicated modes to the DUs along with channel and power allocation based on the network traffic load scenarios. A single variable, represented by the users (CUs and DUs) is used to allocate mode selection, and channel allocation to solve the JMSCPA problem, leading to a simpler solution with faster convergence, and significant reduction in the computational complexity which scales linearly with the number of users. Further, the proposed solution avoids premature stagnation of conventional ABC into local minima by incorporating a modification in its update procedure. The efficacy of the ABC-aided approach, as compared to the results reported in the literature, is validated by extensive numerical investigations under different simulation scenarios.

     

The phase behavior and the Flory-Huggins interaction parameter of blends containing amorphous poly(resorcinol phthalate-block-carbonate), poly(bisphenol-A carbonate) and poly(ethylene terephthalate)

The phase behavior of the blends of poly(ethylene terephthalate) (PET) and poly(Resorcinol Phthalate-block-Carbonate) (RPC) and the blends of PET and poly(Bisphenol-A Carbonate) (PC) was investigated by dynamic mechanical analysis (DMA), differential scanning calorimetry (DSC), and transmission electron microscopy (TEM). Blends of high molecular weight PET and RPC copolymer with 20 mol% resorcinol phthalate (RPC20) showed two glass transition temperatures in DMA and DSC but the cold crystallization rate of PET phase was substantially lowered as compared to neat PET, indicating partial miscibility at all compositions. The RPC20 with M_w = 31,500 g/mol formed miscible blends with PET when PET has weight-average molecular weight <9500 g/mol. The Flory-Huggins interaction parameter between PET and RPC20 was calculated to be 0.029 ± 0.003 by using the Flory-Huggins equation at critical composition and molecular weight. PC with M_w = 30,000 g/mol formed miscible blends with PET only when PET had molecular weight <2800 g/mol, indicating PC/PET blends were much less miscible than RPC20/PET blends. Group contribution methods agreed well with the experimental results obtained both in the present study and a previous study [1], predicting that the addition of a resorcinol phthalate block to a PC backbone should increase the miscibility of PC and PET.     

Spectral and kinetic characterization of orange-red emitting Sr3Al2O6:Eu/Smphosphor

We report, for the first time Sm³⁺ doped nanocrystalline Sr₃Al₂O₆ phosphor. Effect of Eu³⁺ doping in the present host is also studied. XRD results match with standard data from JCPDS file confirming cubic structure with Pa3 space group. PL Maximum for Eu/Sm is obtained at 590 nm and 573 nm respectively, and corresponds to orange-red region of electromagnetic spectrum. Morphology of combustion synthesized powder is platelet, while for calcined powders, cubic shaped crystallites are obtained. Information on various trapping parameters is obtained from thermally stimulated Luminescence (TSL) studies. Non-shifting T_m property is applied to define the order of kinetics and is thereafter assumed as 1. T_m − T_stop procedure and repeated initial rise method are applied to estimate apparent activation energies and peak positions. Further, chi-square minimization procedures via computerized glow curve deconvolution (CGCD) technique provide best-fit results. The figure of merit for deconvoluted Eu and Sm doped samples are 0.48% and 0.67% respectively. The apparent activation energies for Eu doped samples are 0.89 eV, 1.05 eV, 1.30 eV, while, for Sm doped samples, the activation energies are 0.84 eV and 1.06 eV. Persistence behavior of the present phosphor is attributed to contribution due to shorter and longer components as are obtained during phosphorescence decay studies. In both the cases; probability of recombination is more in comparison to the retrapping within a quasi continuous framework of trapping sites.     

Metabolomic Evidence for Peroxisomal Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic and debilitating disease characterized by unexplained physical fatigue, cognitive and sensory dysfunction, sleeping disturbances, orthostatic intolerance, and gastrointestinal problems. People with ME/CFS often report a prodrome consistent with infections. Using regression, Bayesian and enrichment analyses, we conducted targeted and untargeted metabolomic analysis of plasma from 106 ME/CFS cases and 91 frequency-matched healthy controls. Subjects in the ME/CFS group had significantly decreased levels of plasmalogens and phospholipid ethers (p < 0.001), phosphatidylcholines (p < 0.001) and sphingomyelins (p < 0.001), and elevated levels of dicarboxylic acids (p = 0.013). Using machine learning algorithms, we were able to differentiate ME/CFS or subgroups of ME/CFS from controls with area under the receiver operating characteristic curve (AUC) values up to 0.873. Our findings provide the first metabolomic evidence of peroxisomal dysfunction, and are consistent with dysregulation of lipid remodeling and the tricarboxylic acid cycle. These findings, if validated in other cohorts, could provide new insights into the pathogenesis of ME/CFS and highlight the potential use of the plasma metabolome as a source of biomarkers for the disease.     

Partial state observers for linear systems with unknown inputs

We consider the problem of constructing partial state observers for discrete-time linear systems with unknown inputs. Specifically, for any given system, we develop a design procedure that characterizes the set of all linear functionals of the system state that can be reconstructed through a linear observer with a given delay. By treating the delay as a design parameter, we allow greater flexibility in estimating state functionals, and are able to obtain a procedure that directly produces the corresponding observer parameters. Our technique is also applicable to continuous-time systems by replacing delayed outputs with differentiated outputs.     

Anti-bacterial properties of collagen-coated glass and polydimethylsiloxane substrates

Attachments of three bacterial species, Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa on chemically modified glass slides and polydimethylsiloxane substrates were investigated with an attempt to find anti-bacterial materials which can prevent bacterial infections. The results showed that the attachment of the first two species was largely reduced on surfaces treated with self-assembled monolayers plus collagen type 1, whereas attachment of Pseudomonas aeruginosa was not affected on all the treated/untreated surfaces. Gentamicin protection assay showed that the fewest Pseudomonas aeruginosa were engulfed by macrophages when the substrates were coated with (3-aminopropyl)triethoxysilane/(3-aminopropyl)trimethoxysilane plus glutaraldehyde plus collagen type 1. Considering that both Pseudomonas aeruginosa and macrophage adhesion were not influenced very much by the chemical modifications, the decreased engulfment of Pseudomonas aeruginosa was attributed to its decreased ability to invade macrophage cells on the two coated substrates. The results indicate that by employing appropriate chemical modifications, bacterial adhesion could be weakened with a decreased bacterial engulfment response of macrophages to the coated substrates, which shows an interesting and promising direction for applicability of this surface modification strategy for future biomedical research on anti-inflammatory/anti-microbial cell-material interactions.     

Polymer Encapsulants Incorporating Light‐Guiding Architectures to Increase Optical Energy Conversion in Solar Cells

The fabrication of a new type of solar cell encapsulation architecture comprising a periodic array of step‐index waveguides is reported. The materials are fabricated through patterning with light in a photoreactive binary blend of crosslinking acrylate and urethane, wherein phase separation induces the spontaneous, directed formation of broadband, cylindrical waveguides. This microstructured material efficiently collects and transmits optical energy over a wide range of entry angles. Silicon solar cells comprising this encapsulation architecture show greater total external quantum efficiencies and enhanced wide‐angle light capture and conversion. This is a rapid, straightforward, and scalable approach to process light‐collecting structures, whereby significant increases in cell performance may be achieved.