Built-in-self-test of RF front-end circuitry

Fuelled by the ever increasing demand for wireless products and the advent of deep submicron CMOS, RF ICs have become fairly commonplace in the semiconductor market. This has given rise to a new breed of Systems-On-Chip (SOCs) with RF front-ends tightly integrated along with digital, analog and mixed signal circuitry. However, the reliability of the integrated RF front-end continues to be a matter of significant concern and considerable research. A major challenge to the reliability of RF ICs is the fact that their performance is also severely degraded by wide tolerances in on-chip passives and package parasitics, in addition to process related faults. Due to the absence of contact based testing solutions in embedded RF SOCs (because the very act of probing may affect the performance of the RF circuit), coupled with the presence of very few test access nodes, a Built In Self Test approach (BiST) may prove to be the most efficient test scheme. However due to the associated challenges, a comprehensive and low-overhead BiST methodology for on-chip testing of RF ICs has not yet been reported in literature. In the current work, an approach to RF self-test that has hitherto been unexplored both in literature and in the commercial arena is proposed. A sensitive current monitor has been used to extract variations in the supply current drawn by the circuit-under-test (CUT). These variations are then processed in time and frequency domain to develop signatures. The acquired signatures can then be mapped to specific behavioral anomalies and the locations of these anomalies. The CUT is first excited by simple test inputs that can be generated on-chip. The current monitor extracts the corresponding variations in the supply current of the CUT, thereby creating signatures that map to various performance metrics of the circuit. These signatures can then be post-processed by low overhead on-chip circuitry and converted into an accessible form. To be successful in the RF domain any BIST architecture must be minimally invasive, reliable, offer good fault coverage and present low real estate and power overheads. The current-based self-test approach successfully addresses all these concerns. The technique has been applied to RF Low Noise Amplifiers, Mixers and Voltage Controlled Oscillators. The circuitry and post-processing techniques have also been demonstrated in silicon (using the IBM 0.25 micron RF CMOS process). The entire self-test of the RF front-end can be accomplished with a total test time of approximately 30µs, which is several orders of magnitude better than existing commercial test schemes

Generalized Design of Diffractive Optical Elements Using Neural Networks

Diffractive optical elements (DOE) utilize diffraction to manipulate light in optical systems. These elements have a wide range of applications including optical interconnects, coherent beam addition, laser beam shaping and refractive optics aberration correction. Due to the wide range of applications, optimal design of DOE has become an important research problem. In the design of the DOEs, existing techniques utilize the Fresnel diffraction theory to compute the phase at the desired location at the output plane. This process involves solving nonlinear integral equations for which various numerical methods along with robust optimization algorithms exist in literature. However all the algorithms proposed so far assume that the size and the spacing of the elements as independent variables in the design of optimal diffractive gratings. Therefore search algorithms need to be called every time the required geometry of the elements changes, resulting in a computationally expensive design procedure for systems utilizing a large number of DOEs. In this work we have developed a novel algorithm that uses neural networks with possibly multiple hidden layers to overcome this limitation and arrives at a general solution for the design of the DOEs for a given application. Inputs to this network are the spacing between the elements and the input/output planes. The network outputs the phase gratings that are required to obtain the desired intensity at the specified location in the output plane. The network was trained using the back-propagation technique. The training set was generated by using GS algorithm approach as described in literature. The mean square error obtained is comparable to conventional techniques but with much lower computational costs

New Ar-Ar ages of southern Indian kimberlites and a lamproite and their geochemical evolution

The kimberlites and lamproites of southern India are thought to have formed in the most prolific known period of Precambrian ultramafic/ultrapotassic magmatism at around 1100 Ma. This study reports new age data for southern Indian ultrapotassic rocks (kimberlites and lamproites), a controversial topic due to the wide range of published age data and disagreements over the reliability of previously published ages. In this study we obtained new high-precision Ar–Ar data that better constrain the ages of southern Indian ultrapotassic rocks. Dates from three samples are presented, including two kimberlites from Wajrakarur kimberlite field and one lamproite from the Krishna lamproite field. These age data are then combined with bulk-rock geochemical and Nd isotopic data to provide further constraints on the source region and primary magma composition of southern Indian kimberlites and lamproites. Previously, the Chelima lamproite (ca. 1400 Ma) was considered to be one of the oldest lamproites in the world. However, our age data suggest that at least one lamproite (Pochampalle) was generated in the same region 100 Ma before the Chelima event. The Pochampalle lamproite was emplaced around ~1500 Ma as shown by the Ar–Ar data in this study, roughly 250 Ma before the other Krishna lamproites. It would seem that the Pochampalle lamproite was also derived from an isotopically distinct source region with a lower 143Nd/144Nd ratio than other lamproites in the Krishna field. These findings not only have implications for regional ultramafic/ultrapotassic magmatism, but also demonstrate that the mantle processes for producing lamproitic melts existed earlier than previously thought

Rapid and Sensitive Detection of Lung Cancer Biomarker Using Nanoporous Biosensor Based on Localized Surface Plasmon Resonance Coupled with Interferometry

We propose a nanobiosensor to evaluate a lung cancer-specific biomarker. The nanobiosensor is based on an anodic aluminum oxide (AAO) chip and functions on the principles of localized surface plasmon resonance (LSPR) and interferometry. The pore-depth of the fabricated nanoporous AAO chip was 1 µm and was obtained using a two-step electrochemical anodization process. The sensor chip is sensitive to the refractive index (RI) changes of the surrounding medium and also provides simple and label-free detection when specific antibodies are immobilized on the gold-deposited surface of the AAO chip. In order to confirm the effectiveness of the sensor, the antibodies were immobilized on the surface of the AAO chip, and the lung cancer-specific biomarker was applied atop of the immobilized-antibody layer using the self-assembled monolayer method. The nanoporous AAO chip was used as a sensor system to detect serum amyloid A1, which is a lung cancer-specific biomarker. The specific reaction of the antigen-antibody contributes to the change in the RI. This in turn causes a shift in the resonance spectrum in the refractive interference pattern. The limit of detection (LOD) was found to be 100 ag/mL and the biosensor had high sensitivity over a wide concentration range

Dufulin Activates HrBP1 to Produce Antiviral Responses in Tobacco

BACKGROUND: Dufulin is a new antiviral agent that is highly effective against plant viruses and acts by activating systemic acquired resistance (SAR) in plants. In recent years, it has been used widely to prevent and control tobacco and rice viral diseases in China. However, its targets and mechanism of action are still poorly understood. METHODOLOGY/PRINCIPAL FINDINGS: Here, differential in-gel electrophoresis (DIGE) and classical two-dimensional electrophoresis (2-DE) techniques were combined with mass spectrometry (MS) to identify the target of Dufulin. More than 40 proteins were found to be differentially expressed (≥1.5 fold or ≤1.5 fold) upon Dufulin treatment in Nicotiana tabacum K(326). Based on annotations in the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, these proteins were found to be related to disease resistance. Directed acyclic graph (DAG) analysis of the various pathways demonstrated harpin binding protein-1 (HrBP1) as the target of action of Dufulin. Additionally, western blotting, semi-quantitative reverse transcription polymerase chain reaction (RT-PCR), and real time PCR analyses were also conducted to identify the specific mechanism of action of Dufulin. Our results show that activation of HrBP1 triggers the salicylic acid (SA) signaling pathway and thereby produces antiviral responses in the plant host. A protective assay based on lesion counting further confirmed the antiviral activity of Dufulin. CONCLUSION: This study identified HrBP1 as a target protein of Dufulin and that Dufulin can activate the SA signaling pathway to induce host plants to generate antiviral responses

Predictors of unfavorable responses to therapy in rifampicin-sensitive pulmonary tuberculosis using an integrated approach of radiological presentation and sputum mycobacterial burden

INTRODUCTION: Despite the exalted status of sputum mycobacterial load for gauging pulmonary tuberculosis treatment and progress, Chest X-rays supplement valuable information for taking instantaneous therapeutic decisions, especially during the COVID-19 pandemic. Even though literature on individual parameters is overwhelming, few studies have explored the interaction between radiographic parameters denoting severity with mycobacterial burden signifying infectivity. By using a sophisticated approach of integrating Chest X-ray parameters with sputum mycobacterial characteristics, evaluated at all the three crucial time points of TB treatment namely pre-treatment, end of intensive phase and completion of treatment, utilizing the interactive Cox Proportional Hazards model, we aimed to precisely deduce predictors of unfavorable response to TB treatment. MATERIALS AND METHOD: We extracted de-identified data from well characterized clinical trial cohorts that recruited rifampicin-sensitive Pulmonary TB patients without any comorbidities, taking their first spell of anti-tuberculosis therapy under supervision and meticulous follow up for 24 months post treatment completion, to accurately predict TB outcomes. Radiographic data independently obtained, interpreted by two experienced pulmonologists was collated with demographic details and, sputum smear and culture grades of participants by an independent statistician and analyzed using the Cox Proportional Hazards model, to not only adjust for confounding factors including treatment effect, but also explore the interaction between radiological and bacteriological parameters for better therapeutic application. RESULTS: Of 667 TB patients with data available, cavitation, extent of involvement, lower zone involvement, smear and culture grade at baseline were significant parameters predisposing to an unfavorable TB treatment outcome in the univariate analysis. Reduction in radiological lesions in Chest X-ray by at least 50% at 2 months and 75% at the end of treatment helped in averting unfavorable responses. Smear and Culture conversion at the end of 2 months was highly significant as a predictor (p2 zones, were 3.05 (95% CI: 1.12–8.23) and 1.92 (95% CI: 0.72–5.08) respectively. Patients without cavitation, zonal involvement 2 zones and 3+ smear grade individually and independently forecasted a poorer TB outcome. The interaction model revealed that Zonal involvement confined to 2 zones, without a cavity and smear grade up to 2+, constituting “minimal disease”, had a better prognosis. Radiological clearance >50% along with smear conversion at the end of intensive phase of treatment, observed to be a reasonable alternative to culture conversion in predicting a successful outcome. These parameters may potentially take up key positions as stratification factors for future trials contemplating on shorter TB regimens

Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care—An experience from South India

BACKGROUND: We retrospectively data-mined the case records of Reverse Transcription Polymerase Chain Reaction (RT-PCR) confirmed COVID-19 patients hospitalized to a tertiary care centre to derive mortality predictors and formulate a risk score, for prioritizing admission. METHODS AND FINDINGS: Data on clinical manifestations, comorbidities, vital signs, and basic lab investigations collected as part of routine medical management at admission to a COVID-19 tertiary care centre in Chengalpattu, South India between May and November 2020 were retrospectively analysed to ascertain predictors of mortality in the univariate analysis using their relative difference in distribution among ‘survivors’ and ‘non-survivors’. The regression coefficients of those factors remaining significant in the multivariable logistic regression were utilised for risk score formulation and validated in 1000 bootstrap datasets. Among 746 COVID-19 patients hospitalised [487 “survivors” and 259 “non-survivors” (deaths)], there was a slight male predilection [62.5%, (466/746)], with a higher mortality rate observed among 40–70 years age group [59.1%, (441/746)] and highest among diabetic patients with elevated urea levels [65.4% (68/104)]. The adjusted odds ratios of factors [OR (95% CI)] significant in the multivariable logistic regression were SaO(2)3; 3.01 (1.61–5.83), Age ≥50 years;2.52 (1.45–4.43), Pulse Rate ≥100/min: 2.02 (1.19–3.47) and coexisting Diabetes Mellitus; 1.73 (1.02–2.95) with hypertension and gender not retaining their significance. The individual risk scores for SaO(2)3–11, Age ≥50 years-9, Pulse Rate ≥100/min-7 and coexisting diabetes mellitus-6, acronymed collectively as ‘OUR-ARDs score’ showed that the sum of scores ≥ 25 predicted mortality with a sensitivity-90%, specificity-64% and AUC of 0.85. CONCLUSIONS: The ‘OUR ARDs’ risk score, derived from easily assessable factors predicting mortality, offered a tangible solution for prioritizing admission to COVID-19 tertiary care centre, that enhanced patient care but without unduly straining the health system

Redirecting research efforts on the diversification-performance linkage: The search for synergy

We review the literature on the diversification-performance (D-P) relationship to a) propose that the time is ripe for a renewed attack on understanding the relationship between diversification and firm performance, and b) outline a new approach to attacking the question. Our paper makes four main contributions. First, through a review of the literature we establish the inherent complexities in the D-P relationship and the methodological challenges confronted by the literature in reaching its current conclusion of a non-linear relationship between diversification and performance. Second, we argue that to better guide managers the literature needs to develop along a complementary path – whereas past research has often focused on answering the big question of does diversification affect firm performance, this second path would focus more on identifying the precise micro-mechanisms through which diversification adds or subtracts value. Third, we outline a new approach to the investigation of this topic, based on (a) identifying the precise underlying mechanisms through which diversification affects performance; (b) identifying performance outcomes that are “proximate” to the mechanism that the researcher is studying, and (c) identifying an appropriate research design that can enable a causal claim. Finally, we outline a set of directions for future research

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection