Parameter extraction of Extended Floating Gate Field Effect Transistors (EGFETs): Estimating the threshold voltage, series resistance, and mobility degradation from I-V measurements

Extended Floating Gate Field Effect Transistors (EGFETs) are CMOS-compatible floating gate devices capable of detecting charges on their sensing area by the relative shifts in current-voltage (I-V) characteristics. The I-V shifts are generally computed by measuring the EGFET parameters in the strong inversion region of operation. This could lead to errors in estimating the device sensitivity because the simple I-V model ignores the mobility degradation and series resistance effects in EGFETs. Our goal is to model these parasitic effects and present methods to extract the key device parameters. We derive an analytical I-V model for EGFETs in the linear region of transistor operation, accounting for both the mobility degradation and series resistance effects. Based on the analytical model, three methods are presented to estimate the key parameters, namely the threshold voltage, series resistance, surface roughness parameter, low-field mobility, and effective mobility from the I-V characteristics, gate transconductance, and drain conductance. The peak transconductance method is used as a benchmark for comparing the extracted threshold voltages. Silicon-based EGFET devices are fabricated, and their I-V characteristics are measured with deionized water and three polyelectrolytes. From the I-V data, the parameter extraction methods are used to compute the values of the key parameters, and the suitability of each method is discussed. The gate transconductance methods show good agreement between the values for the key parameters, while the drain transconductance method gives lower values of the key parameters. There is scope to improve the presented methods by incorporating the effects of substrate bias and asymmetric series resistance for new extended-gate device architectures, including solution-based organic field-effect transistors.Comment: 19 pages, 8 figures, preprin

Models and Application of Firefighting Vulnerability

AbstractGeographic information systems (GIS) have been applied to analyze the efficiency and effectiveness of public facility services such as fire stations, police stations and day-care centers. Regardless of the scientific contribution of such an approach, there are numerous limitations to follow the rules or optimized suggestions due to high land price and other societal factors. In the present study, we narrowed the scope to firefighting services: how to decrease firefighting dismissals and help firefighters recognize the situation of fire events before arriving at the fire scenes. The absolute time from the fire station to the fire scene was considered to be the Mobility Kill Zone. Narrow roads and illegal parking were classified as the Operation Kill Zone. Areas with identified hazardous commodities and toxic substances were classified as the Identified Hazardous Zone. The areas cluttered with fire safety management objects were classified as the Fire Vulnerability Zone. Four models were suggested in our previous research and in the present study, we elaborated upon the models and examined new information technology (IT) to implement the models in rural and urban areas

Functional Neural Correlates of Attentional Deficits in Amnestic Mild Cognitive Impairment

Although amnestic mild cognitive impairment (aMCI; often considered a prodromal phase of Alzheimer’s disease, AD) is most recognized by its implications for decline in memory function, research suggests that deficits in attention are present early in aMCI and may be predictive of progression to AD. The present study used functional magnetic resonance imaging to examine differences in the brain during the attention network test between 8 individuals with aMCI and 8 neurologically healthy, demographically matched controls. While there were no significant behavioral differences between groups for the alerting and orienting functions, patients with aMCI showed more activity in neural regions typically associated with the networks subserving these functions (e.g., temporoparietal junction and posterior parietal regions, respectively). More importantly, there were both behavioral (i.e., greater conflict effect) and corresponding neural deficits in executive control (e.g., less activation in the prefrontal and anterior cingulate cortices). Although based on a small number of patients, our findings suggest that deficits of attention, especially the executive control of attention, may significantly contribute to the behavioral and cognitive deficits of aMCI

Functional deficits of the attentional networks in autism

Attentional dysfunction is among the most consistent observations of autism spectrum disorders (ASD). However, the neural nature of this deficit in ASD is still unclear. In this study, we aimed to identify the neurobehavioral correlates of attentional dysfunction in ASD. We used the Attention Network Test-Revised and functional magnetic resonance imaging to examine alerting, orienting, and executive control functions, as well as the neural substrates underlying these attentional functions in unmedicated, high-functioning adults with ASD (n = 12) and matched healthy controls (HC, n = 12). Compared with HC, individuals with ASD showed increased error rates in alerting and executive control, accompanied by lower activity in the mid-frontal gyrus and the caudate nucleus for alerting, and by the absence of significant functional activation in the anterior cingulate cortex (ACC) for executive control. In addition, greater behavioral deficiency in executive control in ASD was correlated with less functional activation of the ACC. These findings of behavioral and neural abnormalities in alerting and executive control of attention in ASD may suggest core attentional deficits, which require further investigation

Primary Hyperoxaluria in Korean Pediatric Patients

Background Primary hyperoxaluria (PH), a rare inborn error of glyoxylate meta bolism causing overproduction of oxalate, is classified into three genetic subgroups: type 1–3 (PH1–PH3) caused by AGXT, GRHPR, and HOGA1 gene mutations, respectively. We performed a retrospective case series study of Korean pediatric patients with PH. Methods In total, 11 unrelated pediatric patients were recruited and their phenotypes and genotypes were analyzed by a retrospective review of their medical records. Results Mutational analyses revealed biallelic AGXT mutations (PH1) in nine patients and a single heterozygous GRHPR and HOGA1 mutation in one patient each. The c.33dupC was the most common AGXT mutation with an allelic frequency of 44%. The median age of onset was 3 months (range, 2 months–3 years), and eight patients with PH1 presented with end stage renal disease (ESRD). Patients with two truncating mutations showed an earlier age of onset and more frequent retinal involvement than patients with one truncating mutation. Among eight PH1 patients presenting with ESRD, five patients were treated with intensive dialysis followed by liver transplantation (n=5) with/without subsequent kidney transplantation (n=3). Conclusion Most patients presented with severe infantile forms of PH. Patients with two truncating mutations displayed more severe phenotypes than those of patients with one truncating mutation. Sequential liver and kidney transplantation was adopted for PH1 patients presenting with ESRD. A larger nation-wide multicenter study is needed to confirm the genotype-phenotype correlations and outcomes of organ transplantation

New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS)

GEMS will monitor air quality over Asia at unprecedented spatial and temporal resolution from GEO for the first time, providing column measurements of aerosol, ozone and their precursors (nitrogen dioxide, sulfur dioxide and formaldehyde). Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled for launch in late 2019 - early 2020 to monitor Air Quality (AQ) at an unprecedented spatial and temporal resolution from a Geostationary Earth Orbit (GEO) for the first time. With the development of UV-visible spectrometers at sub-nm spectral resolution and sophisticated retrieval algorithms, estimates of the column amounts of atmospheric pollutants (O3, NO2, SO2, HCHO, CHOCHO and aerosols) can be obtained. To date, all the UV-visible satellite missions monitoring air quality have been in Low Earth orbit (LEO), allowing one to two observations per day. With UV-visible instruments on GEO platforms, the diurnal variations of these pollutants can now be determined. Details of the GEMS mission are presented, including instrumentation, scientific algorithms, predicted performance, and applications for air quality forecasts through data assimilation. GEMS will be onboard the GEO-KOMPSAT-2 satellite series, which also hosts the Advanced Meteorological Imager (AMI) and Geostationary Ocean Color Imager (GOCI)-2. These three instruments will provide synergistic science products to better understand air quality, meteorology, the long-range transport of air pollutants, emission source distributions, and chemical processes. Faster sampling rates at higher spatial resolution will increase the probability of finding cloud-free pixels, leading to more observations of aerosols and trace gases than is possible from LEO. GEMS will be joined by NASA's TEMPO and ESA's Sentinel-4 to form a GEO AQ satellite constellation in early 2020s, coordinated by the Committee on Earth Observation Satellites (CEOS)

Why is Silicon getting “Dark”?

Dark silicon refers to an area that cannot be turned on by supplying power on a silicon chip due to power consumption restrictions. It is an area that cannot be turned on at the same time as the Central Processing Unit (CPU), and it becomes a wasteful area that cannot be used without doing anything. [1] As the process of miniaturization progresses, a dark silicon area will be generated on the die (semiconductor body), and the area will increase with further miniaturization. The reason is that the power consumption of the circuits on the chip does not scale down as much as the miniaturization of the process. [1], [2] Even if the CPU core becomes smaller with miniaturization, the power does not become smaller enough to match it. Therefore, the number of CPU cores that can be mounted on the chip gradually decreases. This is the dark silicon problem. The word dark silicon has been one of the buzzwords in the semiconductor industry past decade. It is reminiscent of the "dark matter" of astrophysics, but the darkness is about power. At the 2010 processor conference "Hot Chips," the term was used when the University of California San Diego announced the "Green Droid" chip. Widely used was the paper entitled "Dark Silicon and the End of Multicore Scaling" at the computer architecture symposium "International Symposium on Computer Architecture (ISCA '11)."[3] As you can see from the title of the ISCA paper, dark silicon stands in the way of multi-core scaling. In other words, the dark silicon problem makes it impossible to increase the number of CPU cores with multiple cores. At least bring the end of the symmetric multicore era. Performance PCs and CPUs for servers have been increasing the number of cores, but that era is about to end

Dimensional overlap accounts for independence and integration of stimulus-response compatibility effects

Extensive studies have been conducted to examine various attentional control effects that stem from stimulus stimulus (S-S) and stimulus response (S-R) incompatibility. Among these behavioral paradigms, the best-known are the Stroop effect, the Simon effect, and Posner's cue validity effect. In this study, we designed two behavioral tasks incorporating these effects (Simon-color-Stroop and Simon-spatial-Stroop) guided by a general framework of S-R ensemble, the dimensional overlap theory. We analyzed various attentional effects according to dimensional overlaps among S-S and S-R ensembles and their combinations. We found that behavioral performance was independently affected by various dimensional overlaps in the Simon-color-Stroop task, whereas different sources of dimensional overlap in the Simon-spatial-Stroop task interacted with each other. We argue that the dimensional overlap theory can be extended to serve as a viable unified theory that accounts for diverse attentional effects and their interactions and helps to elucidate neural networks subserving attentional control

Scan4CFU: Low-cost, open-source bacterial colony tracking over large areas and extended incubation times

A hallmark of bacterial populations cultured in vitro is their homogeneity of growth, where the majority of cells display identical growth rate, cell size and content. Recent insights, however, have revealed that even cells growing in exponential growth phase can be heterogeneous with respect to variables typically used to measure cell growth. Bacterial heterogeneity has important implications for how bacteria respond to environmental stresses, such as antibiotics. The phenomenon of antimicrobial persistence, for example, has been linked to a small subpopulation of cells that have entered into a state of dormancy where antibiotics are no longer effective. While methods have been developed for identifying individual non-growing cells in bacterial cultures, there has been less attention paid to how these cells may influence growth in colonies on a solid surface. In response, we have developed a low-cost, open-source platform to perform automated image capture and image analysis of bacterial colony growth on multiple nutrient agar plates simultaneously. The descriptions of the hardware and software are included, along with details about the temperature-controlled growth chamber, high-resolution scanner, and graphical interface to extract and plot the colony lag time and growth kinetics. Experiments were conducted using a wild type strain of Escherichia coli K12 to demonstrate the feasibility and operation of our setup. By automated tracking of bacterial growth kinetics in colonies, the system holds the potential to reveal new insights into understanding the impact of microbial heterogeneity on antibiotic resistance and persistence.This article is published as Pandey, Santosh, Yunsoo Park, Ankita Ankita, and Gregory J. Phillips. "Scan4CFU: Low-cost, open-source bacterial colony tracking over large areas and extended incubation times." HardwareX 10 (2021): e00249. DOI: 10.1016/j.ohx.2021.e00249. Copyright 2021 The Authors. Attribution 4.0 International (CC BY 4.0). Posted with permission