GaN-based sensor nodes for in situ detection of gases

A system for detecting chemical/biological substances and a detection method. The system comprises a plurality of sensing units or nodes and a radiofrequency link. Each unit has several sensors with different sensing curves. Each sensor is able to transmit information related to the sensed substance on a specific frequency. The sensors preferably comprise AlGaN/GaN high electron mobility transistors

Arrays of Nano Tunnel Junctions as Infrared Image Sensors

Infrared image sensors based on high density rectangular planar arrays of nano tunnel junctions have been proposed. These sensors would differ fundamentally from prior infrared sensors based, variously, on bolometry or conventional semiconductor photodetection. Infrared image sensors based on conventional semiconductor photodetection must typically be cooled to cryogenic temperatures to reduce noise to acceptably low levels. Some bolometer-type infrared sensors can be operated at room temperature, but they exhibit low detectivities and long response times, which limit their utility. The proposed infrared image sensors could be operated at room temperature without incurring excessive noise, and would exhibit high detectivities and short response times. Other advantages would include low power demand, high resolution, and tailorability of spectral response. Neither bolometers nor conventional semiconductor photodetectors, the basic detector units as proposed would partly resemble rectennas. Nanometer-scale tunnel junctions would be created by crossing of nanowires with quantum-mechanical-barrier layers in the form of thin layers of electrically insulating material between them (see figure). A microscopic dipole antenna sized and shaped to respond maximally in the infrared wavelength range that one seeks to detect would be formed integrally with the nanowires at each junction. An incident signal in that wavelength range would become coupled into the antenna and, through the antenna, to the junction. At the junction, the flow of electrons between the crossing wires would be dominated by quantum-mechanical tunneling rather than thermionic emission. Relative to thermionic emission, quantum mechanical tunneling is a fast process

High-Sensitivity GaN Microchemical Sensors

Systematic studies have been performed on the sensitivity of GaN HEMT (high electron mobility transistor) sensors using various gate electrode designs and operational parameters. The results here show that a higher sensitivity can be achieved with a larger W/L ratio (W = gate width, L = gate length) at a given D (D = source-drain distance), and multi-finger gate electrodes offer a higher sensitivity than a one-finger gate electrode. In terms of operating conditions, sensor sensitivity is strongly dependent on transconductance of the sensor. The highest sensitivity can be achieved at the gate voltage where the slope of the transconductance curve is the largest. This work provides critical information about how the gate electrode of a GaN HEMT, which has been identified as the most sensitive among GaN microsensors, needs to be designed, and what operation parameters should be used for high sensitivity detection

E2F and p53 Induce Apoptosis Independently during Drosophila Development but Intersect in the Context of DNA Damage

In mammalian cells, RB/E2F and p53 are intimately connected, and crosstalk between these pathways is critical for the induction of cell cycle arrest or cell death in response to cellular stresses. Here we have investigated the genetic interactions between RBF/E2F and p53 pathways during Drosophila development. Unexpectedly, we find that the pro-apoptotic activities of E2F and p53 are independent of one another when examined in the context of Drosophila development: apoptosis induced by the deregulation of dE2F1, or by the overexpression of dE2F1, is unaffected by the elimination of dp53; conversely, dp53-induced phenotypes are unaffected by the elimination of dE2F activity. However, dE2F and dp53 converge in the context of a DNA damage response. Both dE2F1/dDP and dp53 are required for DNA damage-induced cell death, and the analysis of rbf1 mutant eye discs indicates that dE2F1/dDP and dp53 cooperatively promote cell death in irradiated discs. In this context, the further deregulation in the expression of pro-apoptotic genes generates an additional sensitivity to apoptosis that requires both dE2F/dDP and dp53 activity. This sensitivity differs from DNA damage-induced apoptosis in wild-type discs (and from dE2F/dDP-induced apoptosis in un-irradiated rbf1 mutant eye discs) by being dependent on both hid and reaper. These results show that pro-apoptotic activities of dE2F1 and dp53 are surprisingly separable: dp53 is required for dE2F-dependent apoptosis in the response to DNA damage, but it is not required for dE2F-dependent apoptosis caused simply by the inactivation of rbf1

Impact of aortic valve effective height following valve-sparing root replacement on postoperative insufficiency and reoperation

BACKGROUND: This study evaluated the impact of anatomic aortic root parameters during valve-sparing root replacement on the probability of postoperative aortic insufficiency and freedom from aortic valve reoperation. METHODS: From 1995 to 2020, 177 patients underwent valve-sparing root replacement (163 reimplantations, 14 remodeling). Preoperative and postoperative echocardiograms were analyzed to measure annulus and sinus diameters, effective height of leaflet coaptation, and degree of aortic insufficiency. Logistic regression was used to evaluate predictors of 2+ or greater late postoperative aortic insufficiency. Fine-Gray regression determined predictors for aortic valve reintervention. RESULTS: The study population included 122 (69%) men with a mean age of 43 ± 15 years. A total of 119 patients (67%) had an identified connective tissue disorder. The cumulative incidence of aortic valve reoperation was estimated as 7% at 5 years and 12% at 10 years. The probability of 2+ or greater late postoperative aortic insufficiency was inversely related to effective height during valve-sparing root replacement (P = .018). As postoperative effective height fell below 11 mm, the probability of 2+ or greater aortic insufficiency exceeded 10%. On multivariable logistic regression, effective height (odds ratio, 0.53; 0.33-0.86; P = .010), preoperative annulus diameter (odds ratio, 1.44; 1.13-1.82; P = .003), and degree of preoperative aortic insufficiency (odds ratio, 2.57; 1.45-4.52; P = .001) were associated with increased incidence of 2+ or greater late postoperative aortic insufficiency. On multivariable Fine-Gray regression, risk factors for aortic valve reintervention included preoperative annulus diameter (subdistribution hazard ratio, 1.28 [1.03-1.59], P = .027), history of 3+ or greater aortic insufficiency (subdistribution hazard ratio, 4.28; 1.60-11.44; P = .004), and 2+ or greater early postoperative aortic insufficiency (subdistribution hazard ratio, 5.22; 2.29-11.90; P \u3c .001). CONCLUSIONS: Measures to increase effective height during valve-sparing root replacement may decrease the risk of more than mild postoperative aortic insufficiency after repair and the need for aortic valve reoperation

In-situ crack and keyhole pore detection in laser directed energy deposition through acoustic signal and deep learning

Cracks and keyhole pores are detrimental defects in alloys produced by laser directed energy deposition (LDED). Laser-material interaction sound may hold information about underlying complex physical events such as crack propagation and pores formation. However, due to the noisy environment and intricate signal content, acoustic-based monitoring in LDED has received little attention. This paper proposes a novel acoustic-based in-situ defect detection strategy in LDED. The key contribution of this study is to develop an in-situ acoustic signal denoising, feature extraction, and sound classification pipeline that incorporates convolutional neural networks (CNN) for online defect prediction. Microscope images are used to identify locations of the cracks and keyhole pores within a part. The defect locations are spatiotemporally registered with acoustic signal. Various acoustic features corresponding to defect-free regions, cracks, and keyhole pores are extracted and analysed in time-domain, frequency-domain, and time-frequency representations. The CNN model is trained to predict defect occurrences using the Mel-Frequency Cepstral Coefficients (MFCCs) of the lasermaterial interaction sound. The CNN model is compared to various classic machine learning models trained on the denoised acoustic dataset and raw acoustic dataset. The validation results shows that the CNN model trained on the denoised dataset outperforms others with the highest overall accuracy (89%), keyhole pore prediction accuracy (93%), and AUC-ROC score (98%). Furthermore, the trained CNN model can be deployed into an in-house developed software platform for online quality monitoring. The proposed strategy is the first study to use acoustic signals with deep learning for insitu defect detection in LDED process.Comment: 36 Pages, 16 Figures, accepted at journal Additive Manufacturin

A Systematic Review of the Cost-Effectiveness of Chemotherapy Regimens

Background The rising cost of chemotherapy dramatically increases the burden on healthcare and presents new challenges in achieving optimal patient outcomes. New treatments, in general, are more specialized but show minor progress in regards to efficacy. Accordingly, the threat of overpaying for chemotherapy regimens has increased. There is a need for a comprehensive review to compile relevant studies in order to inform clinician decisions on the basis of cost-effectiveness and quality of life. Objectives Therefore, the aim of this project is to assess the cost-effectiveness of anticancer medications with a special focus on the quality of life of patients undergoing chemotherapy, with the intent to form recommendations that unite evidence-based literature with clinical practice. The long term goal is to create a clinical reference for prescribers to use in order to make more informed decisions on chemotherapy regimens. Methodology In line with the objectives above, eligibility criteria was established to refine the database results. An initial literature search will be conducted to verify appropriateness of the eligibility criteria and search terms. Upon finalizing study selection parameters, abstracts will be reviewed and full text articles will be retrieved. Grey literature will be searched to eliminate publication bias. Hand searchers will be performed to ensure all studies in relevant journals will be retrieved. Selected articles will be reviewed and rated based on a modified GRADE approach. Studies will be synthesized based on GRADE score and pharmacoeconomic analysis. Analysis ­­ Studies will be given a preference status based on their GRADE score and pharmacoeconomic analysis. Final recommendations will be made at the professional judgements of the researchers based on pharmacoeconomic data extracted from studies weighted by preference status