Ancillary Imaging Tests for Confirmation of Brain Death

Brain death is an irreversible termination of functions of the entire brain including brain stem. The American Association of Neurology has defined brain death with three cardinal criteria, namely cessation of the functions of brain including brain stem, coma or unresponsiveness, and apnea. Ancillary testing is done in situations where clinical criteria of brain death cannot be determined by neurological examination or by apnea test. Ancillary tests for determining brain death can be primarily divided into two groups. One group includes tests that can test brain’s electrical functions and the other group includes tests that can document cerebral blood flow in the brain on imaging. In this chapter, we present characteristics of the ideal ancillary test in the diagnosis of brain death and also describe various types of ancillary imaging tests used in the clinical setting for brain death determination and the merits and demerits associated with these techniques

Robust, fast and accurate pH sensing platform solution targeting Single Use application

QbD in biotech and life-sciences necessitates good process metrics in drug discovery, development and manufacturing. Accurate knowledge of pH measurements remains fundamentally important. There is much to be desired with use of conventional glass potentiometric probes for monitoring pH. Challenges being measurement accuracy, system drift, and need for frequent calibration. Additionally glass being fragile compounds the situation further in manufacturing. Glass probes for pH measurement are really unattractive for single use system applications (SUS). Optical based solutions while easy to integrate lack range, need calibration and are a problem in storage (application timing). We demonstrate a robust Platform Solution tested for a variety of applications that includes environs demanding repeated use and SUS. The innovative solution deploys electrochemical based redox chemistry engineered to deliver a scalable (semiconductor technologies) non-glass, calibration-free, drift-free, robust sensing platform. The System Solution is flexible and simply packaged as a 2D ‘sticker’ easily molded into a bag or a 3D probe for insertion in typical 12mm ports in-place for glass probes. Technical performance data will be presented indicating wide performance range (pH 3.0 – 12.0), accuracy (+/- 0.1), covering 5o C – 50o C, calibration-free (factory set, and stable), drift-free (over process duration greater than 35 days), ability to withstand Clean-In-Place (CIP), Steam-In-Place, and gamma irradiation expected of SUS as well as up-stream and down-stream applications. The author will share experience driving six sigma methodologies in successful development of a pH sensing platform

Phase behavior study on gas hydrates formation in gas dominant multiphase pipelines with crude oil and high CO2 mixed gas

The authors are grateful to the CO2RES center for the laboratory facilities in Universiti Teknologi PETRONAS and Yayasan UTP (YUTP) Grant 015LCO154 for financial supporting this research.Peer reviewedPublisher PD

Experimental Studies of Resin Systems for Ablative Thermal Protection System

The present work was initiated to finalise resin for the development of thermal protection system (TPS) for the external surface of a polymeric composite rocket motor case made up of Carbon roving and Epoxy resin. The temperature on the outer surface of the composite case increases due to kinetic heating caused by aerodynamic drag and vehicle velocity. These rocket motor casings are functionally required only in the ascent phase of missile trajectory till motor action time and stage separation. Due to which the experienced heat flux is relatively less, and the temperature on the external composite case is in order of 250 °C - 300 °C depending on missile configuration and trajectory, unlike extreme thermal conditions on ablative nozzle liners exposed to rocket motor exhaust. The maximum allowable temperature in the present study for the Carbon-Epoxy case is 100 °C due to degradation in mechanical properties. The thermal protection system on the external surface will function as a heat-insulating layer based on the working mechanism of ablation. The resin of the thermal protection layer has a substantial impact on the manufacturing process and curing aspects, especially compatibility with the pre-cured carbon epoxy case layer. The generation of test results for thermal stability, cure characteristics and Tg for Epoxy resin has also been included in present studies as an additional objective that provides significant inputs for process development. The test results for Epoxy resin is also used as a basis for the finalisation of resin for the thermal protection layer for processing aspects apart from its basic thermal stability characteristics. The ablative thermal protection working mechanism is based on the ablation phenomenon. In the case of ablation, resin plays a vital role due to pyrolysis and other thermal characteristics. In the present experimental studies, the Phenolic resin and Silicone resin are considered as candidate resin materials for ablative thermal protection system based on available literature and in house experience. The main objective of the present studies is to evaluate thermal stability, char yield after final decomposition through DSC and TGA techniques for both resins as these are fundamental characteristics needed for the present specific application. The test results for specific grades (formulation) of phenolic and Silicone resins are generated and compared. In the present work, the experimental studies to evaluate glass transition temperature (Tg), thermal stability, and cure characteristics for Epoxy resin is also carried through DSC. The test results of specific grade Epoxy resin provides a basis to assess thermal margins for resins selected for ablative thermal protection system and inputs for process development and design requirements. The scope of the present studies is aimed to finalise the resin system for external thermal protection of composite rocket motor case based on thermal characteristics test results and other compatibility aspects with the structural layer

Investigation on Thermodynamic Equilibrium Conditions of Methane Hydrates in Multiphase Gas-Dominant Pipelines

The authors acknowledge the financial support from YUTP Grant (cost center: 015LC0-185).Peer reviewedPublisher PD

Experimental Evaluation of Strength Degradation Temperature for Carbon Epoxy Filament Wound Composite

Polymeric composites have been widely used in various structural and thermal aerospace applications. Polymeric composites having high strength and high modulus reinforcement are ideally suited for lot of critical aerospace applications as structure is designed with high specific strength and high specific modulus. In case of launch vehicles/ missile one such application is design and manufacturing of solid rocket motor casing with polymeric composites as it give high performance and reduces inert weight of propulsion system. The high specific strength and high specific modulus of composite materials makes it ideal choice for designing the composite rocket motor case (CRMC). These are manufactured with filament winding process. As per ASTM D 2290 test method, the apparent tensile strength can be evaluated by preparing ring specimens from filament wound shell which simulates the hoop winding and cylindrical geometry of composite motor case. During flight in trajectory, the temperature on external surface of rocket motor will rise due to kinetic heating as result of aerodynamic drag. The mechanical properties of FRP composites degrades beyond certain temperature, depending primarily upon resin system and its glass transition temperature (Tg). In present work, the method of ring fabrication using filament winding is used to prepare test samples to experimentally test and evaluate apparent tensile strength with temperature of Carbon Epoxy composite. The tensile test at ambient is also done on specimens made from carbon Epoxy laminate using filament winding technique and are compared with ring test results.. The Glass Transition temperature (Tg) for Carbon Epoxy is also determined with Dry Scanning Calorimetry (DSC) techniqu

Estimation of Thermodynamic Stability of Methane and Carbon Dioxide Hydrates in the Presence of Hydrogen Sulfide

.Peer reviewedPublisher PD

Image-based robot assisted bicompartmental knee arthroplasty versus total knee arthroplasty

Objective: To evaluate the short-term clinical outcomes of image-based robot-assisted bicruciate retaining bicompartmental knee arthroplasty and compare it to robot-assisted total knee arthroplasty in the Indian population. Methods: Between December 2018 and November 2019, five patients (six knees) underwent robot-assisted bicompartmental knee arthroplasty (BCKA). These patients were demographically matched with five patients (six knees) who underwent robot-assisted total knee arthroplasty (TKA) during the same period. Clinical outcomes of these twelve knees were assessed in the form of knee society score (KSS) score, Oxford knee score (OKS), and forgotten joint score (FJS) after a minimum follow-up period of 25 months. The data between the two cohorts were compared and analyzed. Results: Scores obtained from both cohorts were subjected to statistical analysis. SPSS software was utilized and the Mann Whitney U-test was utilized to compare the two groups. There was no statistically significant difference found between the two groups in terms of functional outcome. Conclusion: Image-based robot-assisted BCKA is a bone stock preserving and more physiological procedure which can be a promising alternative to patients presenting with isolated arthritis of only two compartments of the knee. Although long-term, larger trials are warranted to establish it as an alternative, our pilot study shows an equally favorable outcome as TKA, making it an exciting new avenue in the field of arthroplasty

DSI++: Updating Transformer Memory with New Documents

Differentiable Search Indices (DSIs) encode a corpus of documents in model parameters and use the same model to answer user queries directly. Despite the strong performance of DSI models, deploying them in situations where the corpus changes over time is computationally expensive because reindexing the corpus requires re-training the model. In this work, we introduce DSI++, a continual learning challenge for DSI to incrementally index new documents while being able to answer queries related to both previously and newly indexed documents. Across different model scales and document identifier representations, we show that continual indexing of new documents leads to considerable forgetting of previously indexed documents. We also hypothesize and verify that the model experiences forgetting events during training, leading to unstable learning. To mitigate these issues, we investigate two approaches. The first focuses on modifying the training dynamics. Flatter minima implicitly alleviate forgetting, so we optimize for flatter loss basins and show that the model stably memorizes more documents ($+12\%$). Next, we introduce a generative memory to sample pseudo-queries for documents and supplement them during continual indexing to prevent forgetting for the retrieval task. Extensive experiments on novel continual indexing benchmarks based on Natural Questions (NQ) and MS MARCO demonstrate that our proposed solution mitigates forgetting significantly. Concretely, it improves the average Hits@10 by $+21.1\%$ over competitive baselines for NQ and requires $6$ times fewer model updates compared to re-training the DSI model for incrementally indexing five corpora in a sequence.Comment: Accepted at EMNLP 2023 main conferenc

Presence of early CKD-related metabolic complications predict progression of stage 3 CKD: a case-controlled study

Only a subset of patients who enter stage 3 chronic kidney disease (CKD) progress to stage 4. Identifying which patients entering stage 3 are most likely to progress could improve outcomes, by allowing more appropriate referrals for specialist care, and spare those unlikely to progress the adverse effects and costliness of an unnecessarily aggressive approach. We hypothesized that compared to non-progressors, patients who enter stage 3 CKD and ultimately progress have experienced greater loss of renal function, manifested by impairment of metabolic function (anemia, worsening acidosis and mineral abnormalities), than is reflected in the eGFR at entry to stage 3. The purpose of this case-controlled study was to design a prediction model for CKD progression using laboratory values reflecting metabolic status. Using data extracted from the electronic health record (EHR), two cohorts of patients in stage 3 were identified: progressors (eGFR declined >3 ml/min/1.73m2/year; n = 117) and non-progressors (eGFR declined <1 ml/min/1.73m2; n = 364). Initial laboratory values recorded a year before to a year after the time of entry to stage 3, reflecting metabolic complications (hemoglobin, bicarbonate, calcium, phosphorous, and albumin) were obtained. Average values in progressors and non-progressors were compared. Classification algorithms (Naïve Bayes and Logistic Regression) were used to develop prediction models of progression based on the initial lab data. At the entry to stage 3 CKD, hemoglobin, bicarbonate, calcium, and albumin values were significantly lower and phosphate values significantly higher in progressors compared to non-progressors even though initial eGFR values were similar. The differences were sufficiently large that a prediction model of progression could be developed based on these values. Post-test probability of progression in patients classified as progressors or non-progressors were 81% (73% − 86%) and 17% (13% − 23%), respectively. Our studies demonstrate that patients who enter stage 3 and ultimately progress to stage 4 manifest a greater degree of metabolic complications than those who remain stable at the onset of stage 3 when eGFR values are equivalent. Lab values (hemoglobin, bicarbonate, phosphorous, calcium and albumin) are sufficiently different between the two cohorts that a reasonably accurate predictive model can be developed