Search results for: power production performance

Authors: B. M. Moda, L. F. Secco

Abstract:

Through free and fair elections and others less democratic processes, Latin America has been gradually turning into a right-wing political region. In order to understand these recent changes, this paper aims to discuss the origin and the traits of the pink wave in the subcontinent, the reasons for its current rollback and future projections for left-wing in the region. The methodology used in this paper will be descriptive and analytical combined with secondary sources mainly from the social and political sciences fields. The canons of the Washington Consensus was implemented by the majority of the Latin American governments in the 80s and 90s under the social democratic and right-wing parties. The neoliberal agenda caused political, social and economic dissatisfaction bursting into a new political configuration for the region. It started in 1998 when Hugo Chávez took the office in Venezuela through the Fifth Republic Movement under the socialist flag. From there on, Latin America was swiped by the so-called ‘pink wave’, term adopted to define the rising of self-designated left-wing or center-left parties with a progressive agenda. After Venezuela, countries like Chile, Brazil, Argentina, Uruguay, Bolivia, Equator, Nicaragua, Paraguay, El Salvador and Peru got into the pink wave. The success of these governments was due a post-neoliberal agenda focused on cash transfers programs, increasing of public spending, and the straightening of national market. The discontinuation of the preference for the left-wing started in 2012 with the coup against Fernando Lugo in Paraguay. In 2015, the chavismo in Venezuela lost the majority of the legislative seats. In 2016, an impeachment removed the Brazilian president Dilma Rousself from office who was replaced by the center-right vice-president Michel Temer. In the same year, Mauricio Macri representing the right-wing party Proposta Republicana was elected in Argentina. In 2016 center-right and liberal, Pedro Pablo Kuczynski was elected in Peru. In 2017, Sebastián Piñera was elected in Chile through the center-right party Renovación Nacional. The pink wave current rollback points towards some findings that can be arranged in two fields. Economically, the 2008 financial crisis affected the majority of the Latin American countries and the left-wing economic policies along with the end of the raw materials boom and the subsequent shrinking of economic performance opened a flank for popular dissatisfaction. In Venezuela, the 2014 oil crisis reduced the revenues for the State in more than 50% dropping social spending, creating an inflationary spiral, and consequently loss of popular support. Politically, the death of Hugo Chavez in 2013 weakened the ‘socialism of the twenty first century’ ideal, which was followed by the death of Fidel Castro, the last bastion of communism in the subcontinent. In addition, several cases of corruption revealed during the pink wave governments made the traditional politics unpopular. These issues challenge the left-wing to develop a future agenda based on innovation of its economic program, improve its legal and political compliance practices, and to regroup its electoral forces amid the social movements that supported its ascension back in the early 2000s.

Keywords: Latin America, political parties, left-wing, right-wing, pink wave

Procedia PDF Downloads 214

Authors: Michelle Eichinger, Upali Nanda

Abstract:

Behavior choices during college years can establish the pattern of lifelong healthy living. Nearly 1/3rd of American college students are either overweight (25 < BMI < 30) or obese (BMI > 30). In addition, overweight/obesity contributes to depression, which is a rising epidemic among college students, affecting academic performance and college drop-out rates. Overweight and obesity result in an imbalance of energy consumption (diet) and energy expenditure (physical activity). Overweight/obesity is a significant contributor to heart disease, diabetes, stroke, physical disabilities and some cancers, which are the leading causes of death and disease in the US. There has been a significant increase in obesity and obesity-related disorders such as type 2 diabetes, hypertension, and dyslipidemia among people in their teens and 20s. Historically, the evidence-based interventions for obesity prevention focused on changing the health behavior at the individual level and aimed at increasing awareness and educating people about nutrition and physical activity. However, it became evident that the environmental context of where people live, work and learn was interdependent to healthy behavior change. As a result, a comprehensive approach was required to include altering the social and built environment to support healthy living. College campus provides opportunities to support lifestyle behavior and form a health-promoting culture based on some key point of decisions such as stairs/ elevator, walk/ bike/ car, high-caloric and fast foods/balanced and nutrient-rich foods etc. At each point of decision, design, can help/hinder the healthier choice. For example, stair well design and motivational signage support physical activity; grocery store/market proximity influence healthy eating etc. There is a need to collate the vast information that is in planning and public health domains on a range of successful point of decision prompts, and translate it into architectural guidelines that help define the edge condition for critical point of decision prompts. This research study aims to address healthy behaviors through the built environment with the questions, how can we make the healthy choice an easy choice through the design of critical point of decision prompts? Our hypothesis is that well-designed point of decision prompts in the built environment of college campuses can promote healthier choices by students, which can directly impact mental and physical health related to obesity. This presentation will introduce a combined health and architectural framework aimed to influence healthy behaviors through design applied for college campuses. The premise behind developing our concept, point-of-decision design (PODD), is healthy decision-making can be built into, or afforded by our physical environments. Using effective design intervention strategies at these 'points-of-decision' on college campuses to make the healthy decision the default decision can be instrumental in positively impacting health at the population level. With our model, we aim to advance health research by utilizing point-of-decision design to impact student health via core sectors of influences within college settings, such as campus facilities and transportation. We will demonstrate how these domains influence patterns/trends in healthy eating and active living behaviors among students. how these domains influence patterns/trends in healthy eating and active living behaviors among students.

Keywords: architecture and health promotion, college campus, design strategies, health in built environment

Procedia PDF Downloads 192

Authors: Lassi Lehto, Jaakko Kahkonen, Juha Oksanen, Tapani Sarjakoski

Abstract:

The use of raster-formatted data sets in geospatial analysis is increasing rapidly. At the same time, geographic data are being introduced into disciplines outside the traditional domain of geoinformatics, like climate change, intelligent transport, and immigration studies. These developments call for better methods to deliver raster geodata in an efficient and easy-to-use manner. Data cube technologies have traditionally been used in the geospatial domain for managing Earth Observation data sets that have strict requirements for effective handling of time series. The same approach and methodologies can also be applied in managing other types of geospatial data sets. A cloud service-based geodata cube, called GeoCubes Finland, has been developed to support online delivery and analysis of most important geospatial data sets with national coverage. The main target group of the service is the academic research institutes in the country. The most significant aspects of the GeoCubes data repository include the use of multiple resolution levels, cloud-optimized file structure, and a customized, flexible content access API. Input data sets are pre-processed while being ingested into the repository to bring them into a harmonized form in aspects like georeferencing, sampling resolutions, spatial subdivision, and value encoding. All the resolution levels are created using an appropriate generalization method, selected depending on the nature of the source data set. Multiple pre-processed resolutions enable new kinds of online analysis approaches to be introduced. Analysis processes based on interactive visual exploration can be effectively carried out, as the level of resolution most close to the visual scale can always be used. In the same way, statistical analysis can be carried out on resolution levels that best reflect the scale of the phenomenon being studied. Access times remain close to constant, independent of the scale applied in the application. The cloud service-based approach, applied in the GeoCubes Finland repository, enables analysis operations to be performed on the server platform, thus making high-performance computing facilities easily accessible. The developed GeoCubes API supports this kind of approach for online analysis. The use of cloud-optimized file structures in data storage enables the fast extraction of subareas. The access API allows for the use of vector-formatted administrative areas and user-defined polygons as definitions of subareas for data retrieval. Administrative areas of the country in four levels are available readily from the GeoCubes platform. In addition to direct delivery of raster data, the service also supports the so-called virtual file format, in which only a small text file is first downloaded. The text file contains links to the raster content on the service platform. The actual raster data is downloaded on demand, from the spatial area and resolution level required in each stage of the application. By the geodata cube approach, pre-harmonized geospatial data sets are made accessible to new categories of inexperienced users in an easy-to-use manner. At the same time, the multiresolution nature of the GeoCubes repository facilitates expert users to introduce new kinds of interactive online analysis operations.

Keywords: cloud service, geodata cube, multiresolution, raster geodata

Procedia PDF Downloads 112

Authors: Utkarsh A. Mishra, Ankit Bansal

Abstract:

At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

Procedia PDF Downloads 200

Authors: Clara Tramuta, Lucia Decastelli, Elisa Barcucci, Sandra Fragassi, Samantha Lupi, Enrico Arletti, Melissa Bizzarri, Daniela Manila Bianchi

Abstract:

Introdution: Food allergies occurs, in the Western World, 2% of adults and up to 8% of children. The protection of allergic consumers is guaranted, in Eurrope, by Regulation (EU) No 1169/2011 of the European Parliament which governs the consumer's right to information and identifies 14 food allergens to be mandatory indicated on the label. Among these, mustard is a popular spice added to enhance the flavour and taste of foods. It is frequently present as an ingredient in spice blends, marinades, salad dressings, sausages, and other products. Hypersensitivity to mustard is a public health problem since the ingestion of even low amounts can trigger severe allergic reactions. In order to protect the allergic consumer, high performance methods are required for the detection of allergenic ingredients. Food safety laboratories rely on validated methods that detect hidden allergens in food to ensure the safety and health of allergic consumers. Here we present the test results for the validation and accreditation of a Real time PCR assay (RT-PCR: SPECIALfinder MC Mustard, Generon), for the detection of mustard traces in food. Materials and Methods. The method was tested on five classes of food matrices: bakery and pastry products (chocolate cookies), meats (ragù), ready-to-eat (mixed salad), dairy products (yogurt), grains, and milling products (rice and barley flour). Blank samples were spiked starting with the mustard samples (Sinapis Alba), lyophilized and stored at -18 °C, at a concentration of 1000 ppm. Serial dilutions were then prepared to a final concentration of 0.5 ppm, using the DNA extracted by ION Force FAST (Generon) from the blank samples. The Real Time PCR reaction was performed by RT-PCR SPECIALfinder MC Mustard (Generon), using CFX96 System (BioRad). Results. Real Time PCR showed a limit of detection (LOD) of 0.5 ppm in grains and milling products, ready-to-eat, meats, bakery, pastry products, and dairy products (range Ct 25-34). To determine the exclusivity parameter of the method, the ragù matrix was contaminated with Prunus dulcis (almonds), peanut (Arachis hypogaea), Glycine max (soy), Apium graveolens (celery), Allium cepa (onion), Pisum sativum (peas), Daucus carota (carrots), and Theobroma cacao (cocoa) and no cross-reactions were observed. Discussion. In terms of sensitivity, the Real Time PCR confirmed, even in complex matrix, a LOD of 0.5 ppm in five classes of food matrices tested; these values are compatible with the current regulatory situation that does not consider, at international level, to establish a quantitative criterion for the allergen considered in this study. The Real Time PCR SPECIALfinder kit for the detection of mustard proved to be easy to use and particularly appreciated for the rapid response times considering that the amplification and detection phase has a duration of less than 50 minutes. Method accuracy was rated satisfactory for sensitivity (100%) and specificity (100%) and was fully validated and accreditated. It was found adequate for the needs of the laboratory as it met the purpose for which it was applied. This study was funded in part within a project of the Italian Ministry of Health (IZS PLV 02/19 RC).

Keywords: allergens, food, mustard, real time PCR

Procedia PDF Downloads 139

Authors: H. K. Esfahani, B. Datta

Abstract:

Groundwater is one of the most important natural resources in many parts of the world; however it is widely polluted due to human activities. Currently, effective and reliable groundwater management and remediation strategies are obtained using characterization of groundwater pollution sources, where the measured data in monitoring locations are utilized to estimate the unknown pollutant source location and magnitude. However, accurately identifying characteristics of contaminant sources is a challenging task due to uncertainties in terms of predicting source flux injection, hydro-geological and geo-chemical parameters, and the concentration field measurement. Reactive transport of chemical species in contaminated groundwater systems, especially with multiple species, is a complex and highly non-linear geochemical process. Although sufficient concentration measurement data is essential to accurately identify sources characteristics, available data are often sparse and limited in quantity. Therefore, this inverse problem-solving method for characterizing unknown groundwater pollution sources is often considered ill-posed, complex and non- unique. Different methods have been utilized to identify pollution sources; however, the linked simulation-optimization approach is one effective method to obtain acceptable results under uncertainties in complex real life scenarios. With this approach, the numerical flow and contaminant transport simulation models are externally linked to an optimization algorithm, with the objective of minimizing the difference between measured concentration and estimated pollutant concentration at observation locations. Concentration measurement data are very important to accurately estimate pollution source properties; therefore, optimal design of the monitoring network is essential to gather adequate measured data at desired times and locations. Due to budget and physical restrictions, an efficient and effective approach for groundwater pollutant source characterization is to design an optimal monitoring network, especially when only inadequate and arbitrary concentration measurement data are initially available. In this approach, preliminary concentration observation data are utilized for preliminary source location, magnitude and duration of source activity identification, and these results are utilized for monitoring network design. Further, feedback information from the monitoring network is used as inputs for sequential monitoring network design, to improve the identification of unknown source characteristics. To design an effective monitoring network of observation wells, optimization and interpolation techniques are used. A simulation model should be utilized to accurately describe the aquifer properties in terms of hydro-geochemical parameters and boundary conditions. However, the simulation of the transport processes becomes complex when the pollutants are chemically reactive. Three dimensional transient flow and reactive contaminant transport process is considered. The proposed methodology uses HYDROGEOCHEM 5.0 (HGCH) as the simulation model for flow and transport processes with chemically multiple reactive species. Adaptive Simulated Annealing (ASA) is used as optimization algorithm in linked simulation-optimization methodology to identify the unknown source characteristics. Therefore, the aim of the present study is to develop a methodology to optimally design an effective monitoring network for pollution source characterization with reactive species in polluted aquifers. The performance of the developed methodology will be evaluated for an illustrative polluted aquifer sites, for example an abandoned mine site in Queensland, Australia.

Keywords: monitoring network design, source characterization, chemical reactive transport process, contaminated mine site

Procedia PDF Downloads 212

Authors: Wonil Nam, Xiang Ren, Inyoung Kim, Masoud Agah, Wei Zhou

Abstract:

Despite its ultrasensitive detection capability, surface-enhanced Raman spectroscopy (SERS) faces challenges as a quantitative biochemical analysis tool due to the significant dependence of local field intensity in hotspots on nanoscale geometric variations of plasmonic nanostructures. Therefore, despite enormous progress in plasmonic nanoengineering of high-performance SERS devices, it is still challenging to quantitatively correlate the measured SERS signals with the actual molecule concentrations at hotspots. A significant effort has been devoted to developing SERS calibration methods by introducing internal standards. It has been achieved by placing Raman tags at plasmonic hotspots. Raman tags undergo similar SERS enhancement at the same hotspots, and ratiometric SERS signals for analytes of interest can be generated with reduced dependence on geometrical variations. However, using Raman tags still faces challenges for real-world applications, including spatial competition between the analyte and tags in hotspots, spectral interference, laser-induced degradation/desorption due to plasmon-enhanced photochemical/photothermal effects. We show that electronic Raman scattering (ERS) signals from metallic nanostructures at hotspots can serve as the internal calibration standard to enable quantitative SERS analysis and improve biostatistical analysis. We perform SERS with Au-SiO₂ multilayered metal-insulator-metal nano laminated plasmonic nanostructures. Since the ERS signal is proportional to the volume density of electron-hole occupation in hotspots, the ERS signals exponentially increase when the wavenumber is approaching the zero value. By a long-pass filter, generally used in backscattered SERS configurations, to chop the ERS background continuum, we can observe an ERS pseudo-peak, IERS. Both ERS and SERS processes experience the |E|⁴ local enhancements during the excitation and inelastic scattering transitions. We calibrated IMRS of 10 μM Rhodamine 6G in solution by IERS. The results show that ERS calibration generates a new analytical value, ISERS/IERS, insensitive to variations from different hotspots and thus can quantitatively reflect the molecular concentration information. Given the calibration capability of ERS signals, we performed label-free SERS analysis of living biological systems using four different breast normal and cancer cell lines cultured on nano-laminated SERS devices. 2D Raman mapping over 100 μm × 100 μm, containing several cells, was conducted. The SERS spectra were subsequently analyzed by multivariate analysis using partial least square discriminant analysis. Remarkably, after ERS calibration, MCF-10A and MCF-7 cells are further separated while the two triple-negative breast cancer cells (MDA-MB-231 and HCC-1806) are more overlapped, in good agreement with the well-known cancer categorization regarding the degree of malignancy. To assess the strength of ERS calibration, we further carried out a drug efficacy study using MDA-MB-231 and different concentrations of anti-cancer drug paclitaxel (PTX). After ERS calibration, we can more clearly segregate the control/low-dosage groups (0 and 1.5 nM), the middle-dosage group (5 nM), and the group treated with half-maximal inhibitory concentration (IC50, 15 nM). Therefore, we envision that ERS calibrated SERS can find crucial opportunities in label-free molecular profiling of complicated biological systems.

Keywords: cancer cell drug efficacy, plasmonics, surface-enhanced Raman spectroscopy (SERS), SERS calibration

Procedia PDF Downloads 117

Authors: Simone Dell'Agnello

Abstract:

There are laser retroreflectors on the Moon and no laser retroreflectors on Mars. Here we describe the design, construction, qualification and imminent deployment of next-generation, optimized laser retroreflectors on the Moon and on Mars (where they will be the first ones). These instruments are positioned by time-of-flight measurements of short laser pulses, the so-called 'laser ranging' technique. Data analysis is carried out with PEP, the Planetary Ephemeris Program of CfA (Center for Astrophysics). Since 1969 Lunar Laser Ranging (LLR) to Apollo/Lunokhod laser retro-reflector (CCR) arrays supplied accurate tests of General Relativity (GR) and new gravitational physics: possible changes of the gravitational constant Gdot/G, weak and strong equivalence principle, gravitational self-energy (Parametrized Post Newtonian parameter beta), geodetic precession, inverse-square force-law; it can also constraint gravitomagnetism. Some of these measurements also allowed for testing extensions of GR, including spacetime torsion, non-minimally coupled gravity. LLR has also provides significant information on the composition of the deep interior of the Moon. In fact, LLR first provided evidence of the existence of a fluid component of the deep lunar interior. In 1969 CCR arrays contributed a negligible fraction of the LLR error budget. Since laser station range accuracy improved by more than a factor 100, now, because of lunar librations, current array dominate the error due to their multi-CCR geometry. We developed a next-generation, single, large CCR, MoonLIGHT (Moon Laser Instrumentation for General relativity high-accuracy test) unaffected by librations that supports an improvement of the space segment of the LLR accuracy up to a factor 100. INFN also developed INRRI (INstrument for landing-Roving laser Retro-reflector Investigations), a microreflector to be laser-ranged by orbiters. Their performance is characterized at the SCF_Lab (Satellite/lunar laser ranging Characterization Facilities Lab, INFN-LNF, Frascati, Italy) for their deployment on the lunar surface or the cislunar space. They will be used to accurately position landers, rovers, hoppers, orbiters of Google Lunar X Prize and space agency missions, thanks to LLR observations from station of the International Laser Ranging Service in the USA, in France and in Italy. INRRI was launched in 2016 with the ESA mission ExoMars (Exobiology on Mars) EDM (Entry, descent and landing Demonstration Module), deployed on the Schiaparelli lander and is proposed for the ExoMars 2020 Rover. Based on an agreement between NASA and ASI (Agenzia Spaziale Italiana), another microreflector, LaRRI (Laser Retro-Reflector for InSight), was delivered to JPL (Jet Propulsion Laboratory) and integrated on NASA’s InSight Mars Lander in August 2017 (launch scheduled in May 2018). Another microreflector, LaRA (Laser Retro-reflector Array) will be delivered to JPL for deployment on the NASA Mars 2020 Rover. The first lunar landing opportunities will be from early 2018 (with TeamIndus) to late 2018 with commercial missions, followed by opportunities with space agency missions, including the proposed deployment of MoonLIGHT and INRRI on NASA’s Resource Prospectors and its evolutions. In conclusion, we will extend significantly the CCR Lunar Geophysical Network and populate the Mars Geophysical Network. These networks will enable very significantly improved tests of GR.

Keywords: general relativity, laser retroreflectors, lunar laser ranging, Mars geodesy

Procedia PDF Downloads 248

Authors: Kareem Abdelwahed, Ahmed Salama, Ahmed Rabie, Ahmed Hamdy, Waleed Abdelfattah, Ahmed Abd El-Rahman

Abstract:

Conventional vapor-compression refrigeration systems rely on typical refrigerants, such as CFC, HCFC and ammonia. Despite of their suitable thermodynamic properties and their stability in the atmosphere, their corresponding global warming potential and ozone depletion potential raise concerns about their usage. Thus, the need for new refrigeration systems, which are environment-friendly, inexpensive and simple in construction, has strongly motivated the development of thermoacoustic energy conversion systems. A thermoacoustic refrigerator (TAR) is a device that is mainly consisting of a resonator, a stack and two heat exchangers. Typically, the resonator is a long circular tube, made of copper or steel and filled with Helium as a the working gas, while the stack has short and relatively low thermal conductivity ceramic parallel plates aligned with the direction of the prevailing resonant wave. Typically, the resonator of a standing-wave refrigerator has one end closed and is bounded by the acoustic driver at the other end enabling the propagation of half-wavelength acoustic excitation. The hot and cold heat exchangers are made of copper to allow for efficient heat transfer between the working gas and the external heat source and sink respectively. TARs are interesting because they have no moving parts, unlike conventional refrigerators, and almost no environmental impact exists as they rely on the conversion of acoustic and heat energies. Their fabrication process is rather simpler and sizes span wide variety of length scales. The viscous and thermal interactions between the stack plates, heat exchangers' plates and the working gas significantly affect the flow field within the plates' channels, and the energy flux density at the plates' surfaces, respectively. Here, the design, the manufacture and the testing of a compact refrigeration system that is based on the thermoacoustic energy-conversion technology is reported. A 1-D linear acoustic model is carefully and specifically developed, which is followed by building the hardware and testing procedures. The system consists of two harmonically-oscillating pistons driven by a simple 1-HP rotary drive mechanism operating at a frequency of 42Hz -hereby, replacing typical expensive linear motors and loudspeakers-, and a thermoacoustic stack within which the energy conversion of sound into heat is taken place. Air at ambient conditions is used as the working gas while the amplitude of the driver's displacement reaches 19 mm. The 30-cm-long stack is a simple porous ceramic material having 100 square channels per square inch. During operation, both oscillating-gas pressure and solid-stack temperature are recorded for further analysis. Measurements show a maximum temperature difference of about 27 degrees between the stack hot and cold ends with a Carnot coefficient of performance of 11 and estimated cooling capacity of five Watts, when operating at ambient conditions. A dynamic pressure of 7-kPa-amplitude is recorded, yielding a drive ratio of 7% approximately, and found in a good agreement with theoretical prediction. The system behavior is clearly non-linear and significant non-linear loss mechanisms are evident. This work helps understanding the operation principles of thermoacoustic refrigerators and presents a keystone towards developing commercial thermoacoustic refrigerator units.

Keywords: refrigeration system, rotary drive mechanism, standing-wave, thermoacoustic refrigerator

Procedia PDF Downloads 352

Authors: Danyi Wang, Andrew Schriefer, Dennis O'Rourke, Brajendra Kumar, Yang Liu, Fei Zhong, Juergen Scheuenpflug, Zheng Feng

Abstract:

Purpose: It has been recognized that the microbiome plays critical roles in disease pathogenesis, including cancer, autoimmune disease, and multiple sclerosis. To develop a clinical-grade assay for exploring microbiome-derived clinical biomarkers across disease areas, a two-phase approach is implemented. 1) Identification of the optimal sample preparation reagents using pre-mixed bacteria and healthy donor stool samples coupled with proprietary Sigma-Aldrich® bioinformatics solution. 2) Exploratory analysis of patient samples for enabling precision medicine. Study Procedure: In phase 1 study, we first compared the 16S sequencing results of two ATCC® microbiome standards (MSA 2002 and MSA 2003) across five different extraction kits (Kit A, B, C, D & E). Both microbiome standards samples were extracted in triplicate across all extraction kits. Following isolation, DNA quantity was determined by Qubit assay. DNA quality was assessed to determine purity and to confirm extracted DNA is of high molecular weight. Bacterial 16S ribosomal ribonucleic acid (rRNA) amplicons were generated via amplification of the V3/V4 hypervariable region of the 16S rRNA. Sequencing was performed using a 2x300 bp paired-end configuration on the Illumina MiSeq. Fastq files were analyzed using the Sigma-Aldrich® Microbiome Platform. The Microbiome Platform is a cloud-based service that offers best-in-class 16S-seq and WGS analysis pipelines and databases. The Platform and its methods have been extensively benchmarked using microbiome standards generated internally by MilliporeSigma and other external providers. Data Summary: The DNA yield using the extraction kit D and E is below the limit of detection (100 pg/µl) of Qubit assay as both extraction kits are intended for samples with low bacterial counts. The pre-mixed bacterial pellets at high concentrations with an input of 2 x106 cells for MSA-2002 and 1 x106 cells from MSA-2003 were not compatible with the kits. Among the remaining 3 extraction kits, kit A produced the greatest yield whereas kit B provided the least yield (Kit-A/MSA-2002: 174.25 ± 34.98; Kit-A/MSA-2003: 179.89 ± 30.18; Kit-B/MSA-2002: 27.86 ± 9.35; Kit-B/MSA-2003: 23.14 ± 6.39; Kit-C/MSA-2002: 55.19 ± 10.18; Kit-C/MSA-2003: 35.80 ± 11.41 (Mean ± SD)). Also, kit A produced the greatest yield, whereas kit B provided the least yield. The PCoA 3D visualization of the Weighted Unifrac beta diversity shows that kits A and C cluster closely together while kit B appears as an outlier. The kit A sequencing samples cluster more closely together than both the other kits. The taxonomic profiles of kit B have lower recall when compared to the known mixture profiles indicating that kit B was inefficient at detecting some of the bacteria. Conclusion: Our data demonstrated that the DNA extraction method impacts DNA concentration, purity, and microbial communities detected by next-generation sequencing analysis. Further microbiome analysis performance comparison of using healthy stool samples is underway; also, colorectal cancer patients' samples will be acquired for further explore the clinical utilities. Collectively, our comprehensive qualification approach, including the evaluation of optimal DNA extraction conditions, the inclusion of positive controls, and the implementation of a robust qualified bioinformatics pipeline, assures accurate characterization of the microbiota in a complex matrix for deciphering the deep biology and enabling precision medicine.

Keywords: 16S rRNA sequencing, analytical validation, bioinformatics pipeline, metagenomics

Procedia PDF Downloads 140

Authors: Wissam Saliba, Mandy Nicholson

Abstract:

Secretory carcinoma (SC) is a rare type of salivary gland cancer. It was first realized as a distinct type of malignancy in 2010and wasinitially termed “mammary analogue secretory carcinoma” because of similarities with secretory breast cancer. The name was later changed to SC. Most SCs originate in parotid glands, and most harbour a rare gene mutation: ETV6-NTRK3. This mutation is rare in common cancers and common in rare cancers; it is present in most secretory carcinomas. Disease outcomes for SC are usually described as favourable as many cases of SC are lowgrade (LG), and cancer growth is slow. In early stages, localized therapy is usually indicated (surgery and/or radiation). Despitea favourable prognosis, a sub-set of casescan be much more aggressive.These cases tend to be of high-grade(HG).HG casesare associated with a poorer prognosis.Management of such cases can be challenging due to limited evidence for effective systemic therapy options. This case report describes the clinical management of a 46-year-oldmale patient with a unique case of SC. He was initially diagnosed with a low/intermediate grade carcinoma of the left parotid gland in 2009; he was treated with surgery and adjuvant radiation. Surgical pathology favoured primary salivary adenocarcinoma, and 2 lymph nodes were positive for malignancy. SC was not yet realized as a distinct type of cancerat the time of diagnosis, and the pathology reportvalidated this gap by stating that the specimen lacked features of the defined types of salivary carcinoma.Slow-growing pulmonary nodules were identified in 2017. In 2020, approximately 11 years after the initial diagnosis, the patient presented with malignant pleural effusion. Pathology from a pleural biopsy was consistent with metastatic poorly differentiated cancer of likely parotid origin, likely mammary analogue secretory carcinoma. The specimen was sent for Next Generation Sequencing (NGS); ETV6-NTRK3 gene fusion was confirmed, and systemic therapy was initiated.One cycle ofcarboplatin/paclitaxel was given in June 2020. He was switched to Larotrectinib (NTRK inhibitor (NTRKi)) later that month. Larotrectinib continued for approximately 9 months, with discontinuation in March 2021 due to disease progression. A second-generation NTRKi (Selitrectinib) was accessed and prescribedthrough a single patient study. Selitrectinib was well tolerated. The patient experienced a complete radiological response within~4 months. Disease progression occurred once again in October 2021. Progression was slow, and Selitrectinib continuedwhile the medical team performed a thorough search for additional treatment options. In January 2022, a liver lesion biopsy was performed, and NGS showed an NTRKG623R solvent-front resistance mutation. Various treatment pathways were considered. The patient pursuedanother investigational NTRKi through a clinical trial, and Selitrectinib was discontinued in July 2022. Excellent performance status was maintained throughout the entire course of treatment.It can be concluded that NTRK inhibitors provided satisfactory treatment efficacy and tolerance for this patient with high-grade transformation and NTRK gene fusion cancer. In the future, more clinical research is needed on systemic treatment options for high-grade transformations in NTRK gene fusion SCs.

Keywords: secretory carcinoma, high-grade transformations, NTRK gene fusion, NTRK inhibitor

Procedia PDF Downloads 93

Authors: Victor Kang, Sirene Bellahnid, Amy Al-Simaani

Abstract:

Efficient documentation and completion of clerical tasks are pillars of efficient patient-centered care in acute settings such as the emergency department (ED). Medical scribes aid physicians with documentation, navigation of electronic health records, results gathering, and communication coordination with other healthcare teams. However, the use of medical scribes is not widespread, with some hospitals even continuing to discontinue their programs. One reason for this could be the lack of studies that have outlined concrete improvements in efficiency and patient and provider satisfaction in emergency departments before and after incorporating scribes. Methods: We conducted a review of the literature concerning the implementation of a medical scribe program and emergency department performance. For this review, a narrative synthesis accompanied by textual commentaries was chosen to present the selected papers. PubMed was searched exclusively. Initially, no date limits were set, but seeing as the electronic medical record was officially implemented in Canada in 2013, studies published after this date were preferred as they provided insight into the interplay between its implementation and scribes on quality improvement. Results: Throughput, efficiency, and cost-effectiveness were the most commonly used parameters in evaluating scribes in the Emergency Department. Important throughput metrics, specifically door-to-doctor and disposition time, were significantly decreased in emergency departments that utilized scribes. Of note, this was shown to be the case in community hospitals, where the burden of documentation and clerical tasks would fall directly upon the attending physician. Academic centers differ in that they rely heavily on residents and students; so the implementation of scribes has been shown to have limited effect on these metrics. However, unique to academic centers was the provider’s perception of incrased time for teaching was unique to academic centers. Consequently, providers express increased work satisfaction in relation to time spent with patients and in teaching. Patients, on the other hand, did not demonstrate a decrease in satisfaction in regards to the care that was provided, but there was no significant increase observed either. Of the studies we reviewed, one of the biggest limitations was the lack of significance in the data. While many individual studies reported that medical scribes in emergency rooms improved relative value units, patient satisfaction, provider satisfaction, and increased number of patients seen, there was no statistically significant improvement in the above criteria when compiled in a systematic review. There is also a clear publication bias; very few studies with negative results were published. To prove significance, data from more emergency rooms with scribe programs would need to be compiled which also includes emergency rooms who did not report noticeable benefits. Furthermore, most data sets focused only on scribes in academic centers. Conclusion: Ultimately, the literature suggests that while emergency room physicians who have access to medical scribes report higher satisfaction due to lower clerical burdens and can see more patients per shift, there is still variability in terms of patient and provider satisfaction. Whether or not this variability exists due to differences in training (in-house trainees versus contractors), population profile (adult versus pediatric), setting (academic versus community), or which shifts scribe work cannot be determined based on the studies that exist. Ultimately, more scribe programs need to be evaluated to determine whether these variables affect outcomes and prove whether scribes significantly improve emergency room efficiency.

Keywords: emergency medicine, medical scribe, scribe, documentation

Procedia PDF Downloads 80

Authors: Hsing-Hua Stella Chang, Mong-Ching Lin, Cher-Min Fong

Abstract:

There has recently been a notable rise in the number of emerging-market industrial small and medium-sized enterprises (SMEs) that have managed to upgrade their operations. Evolving from original equipment manufacturing (OEM) into value-added original or own brand manufacturing (OBM) in such firms represents a specific process of internationalization. The OEM-OBM upgrade requires development of a firm’s own brand. In this respect, the extant literature points out that emerging-market industrial marketers (latecomers) have developed some marketing capabilities, of which branding has been identified as one of the most important. In specific, an industrial non-brand marketer (OEM) marks the division of labor between manufacturing and branding (as part of marketing). In light of this discussion, this research argues that branding capability plays a critical role in supporting the evolution of manufacture upgrade. This is because a smooth transformation from OEM to OBM entails the establishment of strong brands through which branding capability is developed. Accordingly, branding capability can be exemplified as a series of processes and practices in relation to mobilizing branding resources and orchestrating branding activities, which will result in the establishment of business relationships, greater acceptance of business partners (channels, suppliers), and increased industrial brand equity in the firm as key resource advantages). For the study purpose, Taiwan was chosen as the research context, representing a typical case that exemplifies the industrial development path of more-established emerging markets, namely, transformation from OEM to OBM. This research adopted a two-phase research design comprising exploratory (a qualitative study) and confirmatory approaches (a survey study) The findings show that: Country-specific advantage is positively related to branding capability for internationalizing SMEs. Firm-specific advantage is positively related to branding capability for internationalizing SMEs. Hsing-Hua Stella Chang is Assistant Professor with National Taichung University of Education, International Master of Business Administration, (Yingcai Campus) No.227, Minsheng Rd., West Dist., Taichung City 40359, Taiwan, R.O.C. (phone: 886-22183612; e-mail: [email protected]). Mong-Ching Lin is PhD candidate with National Sun Yat-Sen University, Department of Business Management, 70 Lien-hai Rd., Kaohsiung 804, Taiwan, R.O.C. (e-mail: [email protected]). Cher-Min Fong is Full Professor with National Sun Yat-Sen University, Department of Business Management, 70 Lien-hai Rd., Kaohsiung 804, Taiwan, R.O.C. (e-mail: [email protected]). Branding capability is positively related to international performance for internationalizing SMEs. This study presents a pioneering effort to distinguish industrial brand marketers from non-brand marketers in exploring the role of branding capability in the internationalizing small and medium-sized industrial brand marketers from emerging markets. Specifically, when industrial non-brand marketers (OEMs) enter into a more advanced stage of internationalization (i.e., OBM), they must overcome disadvantages (liabilities of smallness, foreignness, outsidership) that do not apply in the case of incumbent developed-country MNEs with leading brands. Such critical differences mark the urgency and significance of distinguishing industrial brand marketers from non-brand marketers on issues relating to their value-adding branding and marketing practices in international markets. This research thus makes important contributions to the international marketing, industrial branding, and SME internationalization literature.

Keywords: brand marketers, branding capability, emerging markets, SME internationalization

Procedia PDF Downloads 65

Authors: Chia-Jung Chen, Yu-Chi Hsu, June-Dong Lin, Kun-Chen Chan, Chieh-Tien Wang, Li-Ching Wu, Chung-Feng Liu

Abstract:

With fast advances in healthcare technology, various total laboratory automation (TLA) processes have been proposed. However, adopting TLA needs quite high funding. This study explores an early adoption experience by Taiwan’s large-scale hospital group, the Chimei Hospital Group (CMG), which owns three branch hospitals (Yongkang, Liouying and Chiali, in order by service scale), based on the five stages of Everett Rogers’ Diffusion Decision Process. 1.Knowledge stage: Over the years, two weaknesses exists in laboratory department of CMG: 1) only a few examination categories (e.g., sugar testing and HbA1c) can now be completed and reported within a day during an outpatient clinical visit; 2) the Yongkang Hospital laboratory space is dispersed across three buildings, resulting in duplicated investment in analysis instruments and inconvenient artificial specimen transportation. Thus, the senior management of the department raised a crucial question, was it time to process the redesign of the laboratory department? 2.Persuasion stage: At the end of 2013, Yongkang Hospital’s new building and restructuring project created a great opportunity for the redesign of the laboratory department. However, not all laboratory colleagues had the consensus for change. Thus, the top managers arranged a series of benchmark visits to stimulate colleagues into being aware of and accepting TLA. Later, the director of the department proposed a formal report to the top management of CMG with the results of the benchmark visits, preliminary feasibility analysis, potential benefits and so on. 3.Decision stage: This TLA suggestion was well-supported by the top management of CMG and, finally, they made a decision to carry out the project with an instrument-leasing strategy. After the announcement of a request for proposal and several vendor briefings, CMG confirmed their laboratory automation architecture and finally completed the contracts. At the same time, a cross-department project team was formed and the laboratory department assigned a section leader to the National Taiwan University Hospital for one month of relevant training. 4.Implementation stage: During the implementation, the project team called for regular meetings to review the results of the operations and to offer an immediate response to the adjustment. The main project tasks included: 1) completion of the preparatory work for beginning the automation procedures; 2) ensuring information security and privacy protection; 3) formulating automated examination process protocols; 4) evaluating the performance of new instruments and the instrument connectivity; 5)ensuring good integration with hospital information systems (HIS)/laboratory information systems (LIS); and 6) ensuring continued compliance with ISO 15189 certification. 5.Confirmation stage: In short, the core process changes include: 1) cancellation of signature seals on the specimen tubes; 2) transfer of daily examination reports to a data warehouse; 3) routine pre-admission blood drawing and formal inpatient morning blood drawing can be incorporated into an automatically-prepared tube mechanism. The study summarizes below the continuous improvement orientations: (1) Flexible reference range set-up for new instruments in LIS. (2) Restructure of the specimen category. (3) Continuous review and improvements to the examination process. (4) Whether installing the tube (specimen) delivery tracks need further evaluation.

Keywords: innovation decision process, total laboratory automation, health care

Procedia PDF Downloads 402

Authors: Ghulam Mustafa Halepota, Zaib Dahar

Abstract:

Background: Low acceptance of FP services, particularly in hard to reach areas where geographic, economic, or social barriers limit-service uptake. Moreover, limited resources appeared to be a reflection of dismal contraceptive use in Pakistan. People’s Primary Health Care Initiative (PPHI) is a Public Private Partnership Program of Government of Sindh which aims to improve maternal child health through accessible family planning services in far flung areas. In 2015 PPHI launched special family planning camps to have achieved a rapid improvement in CPR. On quarterly basis, these camps focus on Long Acting Reversible Contraceptives (LARC). These camps are arranged at 250 BHU Plus (24/7 MCHCs). The Organization manages 1140 primary health care facilities all over Sindh province and focuses on maternal, newborn and child health which includes antenatal care, labor/delivery, postnatal care, family planning, immunization, nutrition, BEmONC, CEmONC, diagnostic laboratories, ambulance services. Under the FPRH program, the organization launched special family planning camps in far flung areas to achieve a rapid improvement in CPR-committed to FP 2020 goal. Objective: To assess the performance of special FP camps for the improvement of long acting reversible contraceptive in hard to reach areas. Methodology: Outreach camps are organized on quarterly basis in 250 BHUs and maternal and child health centers (available-24/7). Using observational study design, the study reports 2 years data of special FP camps conducted in 23 various districts of Sindh during April 2015-April 2017. These special camps served a range of modern contraceptive methods including IUCDs, implants, condoms, pills, and injections. Moreover, 125 male medical officers are trained across Sindh in LARC and 554 female have been trained in implants and IUCD insertions. MSI Impact calculator was used to determine health and demographic impact of services. Results: This intervention has brought exceptional results, and the response has been overwhelming in time. Total 2048 special camps during 2015 till April 2017 have been carried out. 231796 MWRAs visited camps 91% opted modern FP, of which 45% opted Implants, 6% selected IUCDs from LARC (long term reversible contraceptive) from short term, 17% opted injectable 18% choose pills, and 12% used condoms. This intervention created a high contraceptive impact in rural Sindh an estimated 125048 FP users have been created, of this 111846 LARC users and 13498 are SARC users, through this intervention an estimated 55774 unintended pregnancies, 36299 live births, 9394, 80 maternal deaths, 926 and 6077 unsafe abortion have been averted. Moreover, the intervention created an economic impact and saved 2,409,563 direct health expenditure on each woman with reproductive age. Conclusion: Special FP Camps along with routine services is an effective and acceptable model for increase in provision of long-acting and permanent methods in hard to reach areas. This innovative approach by PHHI-Sindh has also been adopted in other provinces of Pakistan.

Keywords: inequalities, special camps, family planning services, hard to reach areas

Procedia PDF Downloads 156

Authors: Ivan Maguire, Alan Barrett, Alex Forte, Sandra Kwiatkowska, Rohit Mishra, Jens Ducrèe, Fiona Regan

Abstract:

Biofouling is defined as the gradual accumulation of Biomimetics refers to the use and imitation of principles copied from nature. Biomimetics has found interest across many commercial disciplines. Among many biological objects and their functions, aquatic animals deserve a special attention due to their antimicrobial capabilities resulting from chemical composition, surface topography or other behavioural defences, which can be used as an inspiration for antifouling technology. Marine biofouling has detrimental effects on seagoing vessels, both commercial and leisure, as well as on oceanographic sensors, offshore drilling rigs, and aquaculture installations. Sensor optics, membranes, housings and platforms can become fouled leading to problems with sensor performance and data integrity. While many anti-fouling solutions are currently being investigated as a cost-cutting measure, biofouling settlement may also be prevented by creating a surface that does not satisfy the settlement conditions. Brill (Scophthalmus rhombus) is a small flatfish occurring in marine waters of Mediterranean as well as Norway and Iceland. It inhabits sandy and muddy coastal waters from 5 to 80 meters. Its skin colour changes depending on environment, but generally is brownish with light and dark freckles, with creamy underside. Brill is oval in shape and its flesh is white. The aim of this study is to translate the unique micro-topography of the brill scale, to design marine inspired biomimetic surface coating and test it against a typical fouling organism. Following extensive study of scale topography of the brill fish (Scophthalmus rhombus) and the settlement behaviour of the diatom species Psammodictyon sp. via SEM, two state-of-the-art antifouling surface solutions were designed and investigated; A brill fish scale bioinspired surface pattern platform (BFD), and generic and uniformly-arrayed, circular micropillar platform (MPD), with offsets based on diatom species settlement behaviour. The BFD approach consists of different ~5 μm by ~90 μm Brill-replica patterns, grown to a 5 μm height, in a linear array pattern. The MPD approach utilises hexagonal-packed cylindrical pillars 10.6 μm in diameter, grown to a height of 5 μm, with vertical offset of 15 μm and horizontal offset of 26.6 μm. Photolithography was employed for microstructure growth, with a polydimethylsiloxane (PDMS) chip-based used as a testbed for diatom adhesion on both platforms. Settlement and adhesion tests were performed using this PDMS microfluidic chip through subjugation to centrifugal force via an in-house developed ‘spin-stand’ which features a motor, in combination with a high-resolution camera, for real-time observing diatom release from PDMS material. Diatom adhesion strength can therefore be determined based on the centrifugal force generated at varying rotational speeds. It is hoped that both the replica and bio-inspired solutions will give comparable anti-fouling results to these synthetic surfaces, whilst also assisting in determining whether anti-fouling solutions should predominantly be investigating either fully bioreplica-based, or a bioinspired, synthetically-based design.

Keywords: anti-fouling applications, bio-inspired microstructures, centrifugal microfluidics, surface modification

Procedia PDF Downloads 296

Authors: Kuldeep Rawat, Michael O'Shea, Maureen McGough

Abstract:

The paper will discuss a National Institute of Justice (NIJ) funded project to provide cost-effective aviation technologies and research to support counter-poaching operations related to endangered, protected, and/or regulated wildlife. The goal of this project is to provide cost-effective aviation technology and research support to Kenya Wildlife Service (KWS) in their counter-poaching efforts. In pursuit of this goal, Elizabeth City State University (ECSU) is assisting the National Institute of Justice (NIJ) in enhancing the Kenya Wildlife Service’s aviation technology and related capacity to meet its counter-poaching mission. Poaching, at its core, is systemic as poachers go to the most extreme lengths to kill high target species such as elephant and rhino. These high target wildlife species live in underdeveloped or impoverished nations, where poachers find fewer barriers to their operations. In Kenya, with fifty-nine (59) parks and reserves, spread over an area of 225,830 square miles (584,897 square kilometers) adequate surveillance on the ground is next to impossible. Cost-effective aviation surveillance technologies, based on a comprehensive needs assessment and operational evaluation, are needed to curb poaching and effectively prevent wildlife trafficking. As one of the premier law enforcement Air Wings in East Africa, KWS plays a crucial role in Kenya, not only in counter-poaching and wildlife conservation efforts, but in aerial surveillance, counterterrorism and national security efforts as well. While the Air Wing has done, a remarkable job conducting aerial patrols with limited resources, additional aircraft and upgraded technology should significantly advance the Air Wing’s ability to achieve its wildlife protection mission. The project includes: (i) Needs Assessment of the KWS Air Wing, to include the identification of resources, current and prospective capacity, operational challenges and priority goals for expansion, (ii) Acquisition of Low-Cost Aviation Technology to meet priority needs, and (iii) Operational Evaluation of technology performance, with a focus on implementation and effectiveness. The Needs Assessment reflects the priorities identified through two site visits to the KWS Air Wing in Nairobi, Kenya, as well as field visits to multiple national parks receiving aerial support and interviewing/surveying KWS Air wing pilots and leadership. Needs Assessment identified some immediate technology needs that includes, GPS with upgrades, including weather application, Night flying capabilities, to include runway lights and night vision technology, Cameras and surveillance equipment, Flight tracking system and/or Emergency Position Indicating Radio Beacon, Lightweight ballistic-resistant body armor, and medical equipment, to include a customized stretcher and standard medical evacuation equipment. Results of this assessment, along with significant input from the KWS Air Wing, will guide the second phase of this project: technology acquisition. Acquired technology will then be evaluated in the field, with a focus on implementation and effectiveness. Results will ultimately be translated for any rural or tribal law enforcement agencies with comparable aerial surveillance missions and operational environments, and jurisdictional challenges, seeking to implement low-cost aviation technology. Results from Needs Assessment phase, including survey results and our ongoing technology acquisition and baseline operational evaluation will be discussed in the paper.

Keywords: aerial surveillance mission, aviation technology, counter-poaching, wildlife protection

Procedia PDF Downloads 255

Authors: Jeremie Coullon, Robert J. Webber

Abstract:

We introduce a Markov chain Monte Carlo (MCMC) sam-pler for infinite-dimensional inverse problems. Our sam-pler is based on the affine invariant ensemble sampler, which uses interacting walkers to adapt to the covariance structure of the target distribution. We extend this ensem-ble sampler for the first time to infinite-dimensional func-tion spaces, yielding a highly efficient gradient-free MCMC algorithm. Because our ensemble sampler does not require gradients or posterior covariance estimates, it is simple to implement and broadly applicable. In many Bayes-ian inverse problems, Markov chain Monte Carlo (MCMC) meth-ods are needed to approximate distributions on infinite-dimensional function spaces, for example, in groundwater flow, medical imaging, and traffic flow. Yet designing efficient MCMC methods for function spaces has proved challenging. Recent gradi-ent-based MCMC methods preconditioned MCMC methods, and SMC methods have improved the computational efficiency of functional random walk. However, these samplers require gradi-ents or posterior covariance estimates that may be challenging to obtain. Calculating gradients is difficult or impossible in many high-dimensional inverse problems involving a numerical integra-tor with a black-box code base. Additionally, accurately estimating posterior covariances can require a lengthy pilot run or adaptation period. These concerns raise the question: is there a functional sampler that outperforms functional random walk without requir-ing gradients or posterior covariance estimates? To address this question, we consider a gradient-free sampler that avoids explicit covariance estimation yet adapts naturally to the covariance struc-ture of the sampled distribution. This sampler works by consider-ing an ensemble of walkers and interpolating and extrapolating between walkers to make a proposal. This is called the affine in-variant ensemble sampler (AIES), which is easy to tune, easy to parallelize, and efficient at sampling spaces of moderate dimen-sionality (less than 20). The main contribution of this work is to propose a functional ensemble sampler (FES) that combines func-tional random walk and AIES. To apply this sampler, we first cal-culate the Karhunen–Loeve (KL) expansion for the Bayesian prior distribution, assumed to be Gaussian and trace-class. Then, we use AIES to sample the posterior distribution on the low-wavenumber KL components and use the functional random walk to sample the posterior distribution on the high-wavenumber KL components. Alternating between AIES and functional random walk updates, we obtain our functional ensemble sampler that is efficient and easy to use without requiring detailed knowledge of the target dis-tribution. In past work, several authors have proposed splitting the Bayesian posterior into low-wavenumber and high-wavenumber components and then applying enhanced sampling to the low-wavenumber components. Yet compared to these other samplers, FES is unique in its simplicity and broad applicability. FES does not require any derivatives, and the need for derivative-free sam-plers has previously been emphasized. FES also eliminates the requirement for posterior covariance estimates. Lastly, FES is more efficient than other gradient-free samplers in our tests. In two nu-merical examples, we apply FES to challenging inverse problems that involve estimating a functional parameter and one or more scalar parameters. We compare the performance of functional random walk, FES, and an alternative derivative-free sampler that explicitly estimates the posterior covariance matrix. We conclude that FES is the fastest available gradient-free sampler for these challenging and multimodal test problems.

Keywords: Bayesian inverse problems, Markov chain Monte Carlo, infinite-dimensional inverse problems, dimensionality reduction

Procedia PDF Downloads 138

Authors: Fahimeh Palizban, Farshad Noravesh, Amir Hossein Saeidian, Mahya Mehrmohamadi

Abstract:

In the recent decade, the emergence of liquid biopsy has significantly improved cancer monitoring and detection. Dying cells, including those originating from tumors, shed their DNA into the blood and contribute to a pool of circulating fragments called cell-free DNA. Accordingly, identifying the tissue origin of these DNA fragments from the plasma can result in more accurate and fast disease diagnosis and precise treatment protocols. Open chromatin regions are important epigenetic features of DNA that reflect cell types of origin. Profiling these features by DNase-seq, ATAC-seq, and histone ChIP-seq provides insights into tissue-specific and disease-specific regulatory mechanisms. There have been several studies in the area of cancer liquid biopsy that integrate distinct genomic and epigenomic features for early cancer detection along with tissue of origin detection. However, multimodal analysis requires several types of experiments to cover the genomic and epigenomic aspects of a single sample, which will lead to a huge amount of cost and time. To overcome these limitations, the idea of predicting OCRs from WGS is of particular importance. In this regard, we proposed a computational approach to target the prediction of open chromatin regions as an important epigenetic feature from cell-free DNA whole genome sequence data. To fulfill this objective, local sequencing depth will be fed to our proposed algorithm and the prediction of the most probable open chromatin regions from whole genome sequencing data can be carried out. Our method integrates the signal processing method with sequencing depth data and includes count normalization, Discrete Fourie Transform conversion, graph construction, graph cut optimization by linear programming, and clustering. To validate the proposed method, we compared the output of the clustering (open chromatin region+, open chromatin region-) with previously validated open chromatin regions related to human blood samples of the ATAC-DB database. The percentage of overlap between predicted open chromatin regions and the experimentally validated regions obtained by ATAC-seq in ATAC-DB is greater than 67%, which indicates meaningful prediction. As it is evident, OCRs are mostly located in the transcription start sites (TSS) of the genes. In this regard, we compared the concordance between the predicted OCRs and the human genes TSS regions obtained from refTSS and it showed proper accordance around 52.04% and ~78% with all and the housekeeping genes, respectively. Accurately detecting open chromatin regions from plasma cell-free DNA-seq data is a very challenging computational problem due to the existence of several confounding factors, such as technical and biological variations. Although this approach is in its infancy, there has already been an attempt to apply it, which leads to a tool named OCRDetector with some restrictions like the need for highly depth cfDNA WGS data, prior information about OCRs distribution, and considering multiple features. However, we implemented a graph signal clustering based on a single depth feature in an unsupervised learning manner that resulted in faster performance and decent accuracy. Overall, we tried to investigate the epigenomic pattern of a cell-free DNA sample from a new computational perspective that can be used along with other tools to investigate genetic and epigenetic aspects of a single whole genome sequencing data for efficient liquid biopsy-related analysis.

Keywords: open chromatin regions, cancer, cell-free DNA, epigenomics, graph signal processing, correlation clustering

Procedia PDF Downloads 127

Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

Abstract:

Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

Procedia PDF Downloads 50

Authors: Keivan Davami, Michael Munther, Lloyd Hackel

Abstract:

The control of properties and material behavior by implementing thermal-mechanical processes is based on mechanical deformation and annealing according to a precise schedule that will produce a unique and stable combination of grain structure, dislocation substructure, texture, and dispersion of precipitated phases. The authors recently developed a thermal-mechanical technique to stabilize the microstructure of additively manufactured nickel-based superalloys even after exposure to high temperatures. However, the mechanism(s) that controls this stability is still under investigation. Laser peening (LP), also called laser shock peening (LSP), is a shock based (50 ns duration) post-processing technique used for extending performance levels and improving service life of critical components by developing deep levels of plastic deformation, thereby generating high density of dislocations and inducing compressive residual stresses in the surface and deep subsurface of components. These compressive residual stresses are usually accompanied with an increase in hardness and enhance the material’s resistance to surface-related failures such as creep, fatigue, contact damage, and stress corrosion cracking. While the LP process enhances the life span and durability of the material, the induced compressive residual stresses relax at high temperatures (>0.5Tm, where Tm is the absolute melting temperature), limiting the applicability of the technology. At temperatures above 0.5Tm, the compressive residual stresses relax, and yield strength begins to drop dramatically. The principal reason is the increasing rate of solid-state diffusion, which affects both the dislocations and the microstructural barriers. Dislocation configurations commonly recover by mechanisms such as climbing and recombining rapidly at high temperatures. Furthermore, precipitates coarsen, and grains grow; virtually all of the available microstructural barriers become ineffective.Our results indicate that by using “cyclic” treatments with sequential LP and annealing steps, the compressive stresses survive, and the microstructure is stable after exposure to temperatures exceeding 0.5Tm for a long period of time. When the laser peening process is combined with annealing, dislocations formed as a result of LPand precipitates formed during annealing have a complex interaction that provides further stability at high temperatures. From a scientific point of view, this research lays the groundwork for studying a variety of physical, materials science, and mechanical engineering concepts. This research could lead to metals operating at higher sustained temperatures enabling improved system efficiencies. The strengthening of metals by a variety of means (alloying, work hardening, and other processes) has been of interest for a wide range of applications. However, the mechanistic understanding of the often complex processes of interactionsbetween dislocations with solute atoms and with precipitates during plastic deformation have largely remained scattered in the literature. In this research, the elucidation of the actual mechanisms involved in the novel cyclic LP/annealing processes as a scientific pursuit is investigated through parallel studies of dislocation theory and the implementation of advanced experimental tools. The results of this research help with the validation of a novel laser processing technique for high temperature applications. This will greatly expand the applications of the laser peening technology originally devised only for temperatures lower than half of the melting temperature.

Keywords: laser shock peening, mechanical properties, indentation, high temperature stability

Procedia PDF Downloads 130

Authors: Mohamed Gazzeh, Bradley Null, Fethi Tlili, Hichem Besbes

Abstract:

The burgeoning global ownership of personal vehicles has posed a significant strain on urban infrastructure, notably parking facilities, leading to traffic congestion and environmental concerns. Effective parking management systems (PMS) are indispensable for optimizing urban traffic flow and reducing emissions. The most commonly deployed systems nowadays rely on computer vision technology. This paper explores the integration of radar sensors and simulation in the context of smart parking management. We concentrate on radar sensors due to their versatility and utility in automotive applications, which extends to PMS. Additionally, radar sensors play a crucial role in driver assistance systems and autonomous vehicle development. However, the resource-intensive nature of radar data collection for algorithm development and testing necessitates innovative solutions. Simulation, particularly the monoDrive simulator, an internal development tool used by NI the Test and Measurement division of Emerson, offers a practical means to overcome this challenge. The primary objectives of this study encompass simulating radar sensors to generate a substantial dataset for algorithm development, testing, and, critically, assessing the transferability of models between simulated and real radar data. We focus on occupancy detection in parking as a practical use case, categorizing each parking space as vacant or occupied. The simulation approach using monoDrive enables algorithm validation and reliability assessment for virtual radar sensors. It meticulously designed various parking scenarios, involving manual measurements of parking spot coordinates, orientations, and the utilization of TI AWR1843 radar. To create a diverse dataset, we generated 4950 scenarios, comprising a total of 455,400 parking spots. This extensive dataset encompasses radar configuration details, ground truth occupancy information, radar detections, and associated object attributes such as range, azimuth, elevation, radar cross-section, and velocity data. The paper also addresses the intricacies and challenges of real-world radar data collection, highlighting the advantages of simulation in producing radar data for parking lot applications. We developed classification models based on Support Vector Machines (SVM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), exclusively trained and evaluated on simulated data. Subsequently, we applied these models to real-world data, comparing their performance against the monoDrive dataset. The study demonstrates the feasibility of transferring models from a simulated environment to real-world applications, achieving an impressive accuracy score of 92% using only one radar sensor. This finding underscores the potential of radar sensors and simulation in the development of smart parking management systems, offering significant benefits for improving urban mobility and reducing environmental impact. The integration of radar sensors and simulation represents a promising avenue for enhancing smart parking management systems, addressing the challenges posed by the exponential growth in personal vehicle ownership. This research contributes valuable insights into the practicality of using simulated radar data in real-world applications and underscores the role of radar technology in advancing urban sustainability.

Keywords: autonomous vehicle simulator, FMCW radar sensors, occupancy detection, smart parking management, transferability of models

Procedia PDF Downloads 61

Authors: Mian Huang, Chi Ma, Junyu Lin, William Lu

Abstract:

Introduction: Bone health attracts more attention recently and an intelligent question and answer (QA) chatbot for osteoporosis is helpful for science popularization. With Generative Pretrained Transformer (GPT) technology developing, we build an osteoporosis corpus dataset and then fine-tune LLaMA, a famous open-source GPT foundation large language model(LLM), on our self-constructed osteoporosis corpus. Evaluated by clinical orthopedic experts, our fine-tuned model outperforms vanilla LLaMA on osteoporosis QA task in Chinese. Three-dimensional quantitative computed tomography (QCT) measured bone mineral density (BMD) is considered as more accurate than DXA for BMD measurement in recent years. We develop an automatic Phantom-less QCT(PL-QCT) that is more efficient for BMD measurement since no need of an external phantom for calibration. Combined with LLM on osteoporosis, our PL-QCT provides efficient and accurate BMD measurement for our chatbot users. Material and Methods: We build an osteoporosis corpus containing about 30,000 Chinese literatures whose titles are related to osteoporosis. The whole process is done automatically, including crawling literatures in .pdf format, localizing text/figure/table region by layout segmentation algorithm and recognizing text by OCR algorithm. We train our model by continuous pre-training with Low-rank Adaptation (LoRA, rank=10) technology to adapt LLaMA-7B model to osteoporosis domain, whose basic principle is to mask the next word in the text and make the model predict that word. The loss function is defined as cross-entropy between the predicted and ground-truth word. Experiment is implemented on single NVIDIA A800 GPU for 15 days. Our automatic PL-QCT BMD measurement adopt AI-associated region-of-interest (ROI) generation algorithm for localizing vertebrae-parallel cylinder in cancellous bone. Due to no phantom for BMD calibration, we calculate ROI BMD by CT-BMD of personal muscle and fat. Results & Discussion: Clinical orthopaedic experts are invited to design 5 osteoporosis questions in Chinese, evaluating performance of vanilla LLaMA and our fine-tuned model. Our model outperforms LLaMA on over 80% of these questions, understanding ‘Expert Consensus on Osteoporosis’, ‘QCT for osteoporosis diagnosis’ and ‘Effect of age on osteoporosis’. Detailed results are shown in appendix. Future work may be done by training a larger LLM on the whole orthopaedics with more high-quality domain data, or a multi-modal GPT combining and understanding X-ray and medical text for orthopaedic computer-aided-diagnosis. However, GPT model gives unexpected outputs sometimes, such as repetitive text or seemingly normal but wrong answer (called ‘hallucination’). Even though GPT give correct answers, it cannot be considered as valid clinical diagnoses instead of clinical doctors. The PL-QCT BMD system provided by Bone’s QCT(Bone’s Technology(Shenzhen) Limited) achieves 0.1448mg/cm2(spine) and 0.0002 mg/cm2(hip) mean absolute error(MAE) and linear correlation coefficient R2=0.9970(spine) and R2=0.9991(hip)(compared to QCT-Pro(Mindways)) on 155 patients in three-center clinical trial in Guangzhou, China. Conclusion: This study builds a Chinese osteoporosis corpus and develops a fine-tuned and domain-adapted LLM as well as a PL-QCT BMD measurement system. Our fine-tuned GPT model shows better capability than LLaMA model on most testing questions on osteoporosis. Combined with our PL-QCT BMD system, we are looking forward to providing science popularization and early morning screening for potential osteoporotic patients.

Keywords: GPT, phantom-less QCT, large language model, osteoporosis

Procedia PDF Downloads 47

Authors: Joel A. Gordon, Nazmiye Balta-Ozkan, Seyed Ali Nabavi

Abstract:

Hydrogen-fueled technologies are rapidly advancing as a critical component of the low-carbon energy transition. In countries historically reliant on natural gas for home heating, such as the UK, hydrogen may prove fundamental for decarbonizing the residential sector, alongside other technologies such as heat pumps and district heat networks. While the UK government is set to take a long-term policy decision on the role of domestic hydrogen by 2026, there are considerable uncertainties regarding consumer preferences for ‘hydrogen homes’ (i.e., hydrogen-fueled appliances for space heating, hot water, and cooking. In comparison to other hydrogen energy technologies, such as road transport applications, to date, few studies have engaged with the social acceptance aspects of the domestic hydrogen transition, resulting in a stark knowledge deficit and pronounced risk to policymaking efforts. In response, this study aims to safeguard against undesirable policy measures by revealing the underlying relationships between the factors of domestic hydrogen acceptance and their respective dimensions: attitudinal, socio-political, community, market, and behavioral acceptance. The study employs an online survey (n=~2100) to gauge how different UK householders perceive the proposition of switching from natural gas to hydrogen-fueled appliances. In addition to accounting for housing characteristics (i.e., housing tenure, property type and number of occupants per dwelling) and several other socio-structural variables (e.g. age, gender, and location), the study explores the impacts of consumer heterogeneity on hydrogen acceptance by recruiting respondents from across five distinct groups: (1) fuel poor householders, (2) technology engaged householders, (3) environmentally engaged householders, (4) technology and environmentally engaged householders, and (5) a baseline group (n=~700) which filters out each of the smaller targeted groups (n=~350). This research design reflects the notion that supporting a socially fair and efficient transition to hydrogen will require parallel engagement with potential early adopters and demographic groups impacted by fuel poverty while also accounting strongly for public attitudes towards net zero. Employing a second-order multigroup confirmatory factor analysis (CFA) in Mplus, the proposed hydrogen acceptance model is tested to fit the data through a partial least squares (PLS) approach. In addition to testing differences between and within groups, the findings provide policymakers with critical insights regarding the significance of knowledge and awareness, safety perceptions, perceived community impacts, cost factors, and trust in key actors and stakeholders as potential explanatory factors of hydrogen acceptance. Preliminary results suggest that knowledge and awareness of hydrogen are positively associated with support for domestic hydrogen at the household, community, and national levels. However, with the exception of technology and/or environmentally engaged citizens, much of the population remains unfamiliar with hydrogen and somewhat skeptical of its application in homes. Knowledge and awareness present as critical to facilitating positive safety perceptions, alongside higher levels of trust and more favorable expectations for community benefits, appliance performance, and potential cost savings. Based on these preliminary findings, policymakers should be put on red alert about diffusing hydrogen into the public consciousness in alignment with energy security, fuel poverty, and net-zero agendas.

Keywords: hydrogen homes, social acceptance, consumer heterogeneity, heat decarbonization

Procedia PDF Downloads 90

Authors: Pei Yi Lin

Abstract:

Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

Procedia PDF Downloads 45

Authors: Michael Radwan Omary

Abstract:

Context: This scientific innovation demonstrate organic catalysis engineered media effective desalination of surface and groundwater. The author has developed a technology called “Storm-Water Ions Filtration Treatment” (SWIFTTM) cold reactor modules designed to retrofit typical urban street storm drains or catch basins. SWIFT triggers biochemical redox reactions with water stream-embedded toxic total dissolved solids (TDS) and electrical conductivity (EC). SWIFTTM Catalysts media unlock the sub-molecular bond energy, break down toxic chemical bonds, and neutralize toxic molecules, bacteria and pathogens. Research Aim: This research aims to develop and design lower O&M cost, zero-brine discharge, energy input-free, chemical-free water desalination and disinfection systems. The objective is to provide an effective resilient and sustainable solution to urban storm-water and groundwater decontamination and disinfection. Methodology: We focused on the development of organic, non-chemical, no-plugs, no pumping, non-polymer and non-allergenic approaches for water and waste water desalination and disinfection. SWIFT modules operate by directing the water stream to flow freely through the electrically charged media cold reactor, generating weak interactions with a water-dissolved electrically conductive molecule, resulting in the neutralization of toxic molecules. The system is powered by harvesting sub-molecular bonds embedded in energy. Findings: The SWIFTTM Technology case studies at CSU-CI and CSU-Fresno Water Institute, demonstrated consistently high reduction of all 40 detected waste-water pollutants including pathogens to levels below a state of California Department of Water Resources “Drinking Water Maximum Contaminants Levels”. The technology has proved effective in reducing pollutants such as arsenic, beryllium, mercury, selenium, glyphosate, benzene, and E. coli bacteria. The technology has also been successfully applied to the decontamination of dissolved chemicals, water pathogens, organic compounds and radiological agents. Theoretical Importance: SWIFT technology development, design, engineering, and manufacturing, offer cutting-edge advancement in achieving clean-energy source bio-catalysis media solution, an energy input free water and waste water desalination and disinfection. A significant contribution to institutions and municipalities achieving sustainable, lower cost, zero-brine and zero CO2 discharges clean energy water desalination. Data Collection and Analysis Procedures: The researchers collected data on the performance of the SWIFTTM technology in reducing the levels of various pollutants in water. The data was analyzed by comparing the reduction achieved by the SWIFTTM technology to the Drinking Water Maximum Contaminants Levels set by the state of California. The researchers also conducted live oral presentations to showcase the applications of SWIFTTM technology in storm water capture and decontamination as well as providing clean drinking water during emergencies. Conclusion: The SWIFTTM Technology has demonstrated its capability to effectively reduce pollutants in water and waste water to levels below regulatory standards. The Technology offers a sustainable solution to groundwater and storm-water treatments. Further development and implementation of the SWIFTTM Technology have the potential to treat storm water to be reused as a new source of drinking water and an ambient source of clean and healthy local water for recharge of ground water.

Keywords: catalysis, bio electro interactions, water desalination, weak-interactions

Procedia PDF Downloads 44

Authors: Kalaumari Mayoral-Peña, Ana I. Montejano-Montelongo, Josué Reyes-Muñoz, Gonzalo A. Ortiz-Mancilla, Mayrin Rodríguez-Cruz, Víctor Hernández-Villalobos, Jesús A. Guzmán-López, Santiago García-Jacobo, Iván Licona-Vázquez, Grisel Fierros-Romero, Rosario Flores-Vallejo

Abstract:

The group B-lactamic antibiotics include some of the most frequently used small drug molecules against bacterial infections. Nevertheless, an alarming decrease in their efficacy has been reported due to the emergence of antibiotic-resistant bacteria. Infections caused by bacteria expressing extended Spectrum B-lactamases (ESBLs) are difficult to treat and account for higher morbidity and mortality rates, delayed recovery, and high economic burden. According to the Global Report on Antimicrobial Resistance Surveillance, it is estimated that mortality due to resistant bacteria will ascend to 10 million cases per year worldwide. These facts highlight the importance of developing low-cost and readily accessible detection methods of drug-resistant ESBLs bacteria to prevent their spread and promote accurate and fast diagnosis. Bacterial detection is commonly done using molecular diagnostic techniques, where PCR stands out for its high performance. However, this technique requires specialized equipment not available everywhere, is time-consuming, and has a high cost. Loop-Mediated Isothermal Amplification (LAMP) is an alternative technique that works at a constant temperature, significantly decreasing the equipment cost. It yields double-stranded DNA of several lengths with repetitions of the target DNA sequence as a product. Although positive and negative results from LAMP can be discriminated by colorimetry, fluorescence, and turbidity, there is still a large room for improvement in the point-of-care implementation. DNA origami is a technique that allows the formation of 3D nanometric structures by folding a large single-stranded DNA (scaffold) into a determined shape with the help of short DNA sequences (staples), which hybridize with the scaffold. This research aimed to generate DNA origami structures using LAMP products as scaffolds to improve the sensitivity to detect ESBLs in point-of-care diagnosis. For this study, the coding sequence of the CTM-X-15 ESBL of E. coli was used to generate the LAMP products. The set of LAMP primers were designed using PrimerExplorerV5. As a result, a target sequence of 200 nucleotides from CTM-X-15 ESBL was obtained. Afterward, eight different DNA origami structures were designed using the target sequence in the SDCadnano and analyzed with CanDo to evaluate the stability of the 3D structures. The designs were constructed minimizing the total number of staples to reduce costs and complexity for point-of-care applications. After analyzing the DNA origami designs, two structures were selected. The first one was a zig-zag flat structure, while the second one was a wall-like shape. Given the sequence repetitions in the scaffold sequence, both were able to be assembled with only 6 different staples each one, ranging between 18 to 80 nucleotides. Simulations of both structures were performed using scaffolds of different sizes yielding stable structures in all the cases. The generation of the LAMP products were tested by colorimetry and electrophoresis. The formation of the DNA structures was analyzed using electrophoresis and colorimetry. The modeling of novel detection methods through bioinformatics tools allows reliable control and prediction of results. To our knowledge, this is the first study that uses LAMP products and DNA-origami in combination to delect ESBL-producing bacterial strains, which represent a promising methodology for diagnosis in the point-of-care.

Keywords: beta-lactamases, antibiotic resistance, DNA origami, isothermal amplification, LAMP technique, molecular diagnosis

Procedia PDF Downloads 193

Authors: Robert E. Kenney, Efrain Antunez, Samuel Nodal, Ameer Malik, Richard B. Aguilar

Abstract:

Physician burnout has gained much attention during the COVID pandemic. After-hours workload, HCC coding, HEDIS metrics, and clinical documentation negatively impact career satisfaction. These and other influences have increased the rate of physicians leaving the workforce. In addition, roughly 1% of the entire physician workforce will be retiring earlier than expected based on pre-pandemic trends. The two Medical Specialties with the highest rates of burnout are Family Medicine and Primary Care. With a predicted shortage of primary care physicians looming, the need to address physician burnout is crucial. Commonly reported issues leading to clinician burnout are clerical documentation requirements, increased time working on Electronic Health Records (EHR) after hours, and a decrease in work-life balance. Clinicians experiencing burnout with physical and emotional exhaustion are at an increased likelihood of providing lower quality and less efficient patient care. This may include a lack of suitable clinical documentation, medication reconciliation, clinical assessment, and treatment plans. While the annual baseline turnover rates of physicians hover around 6-7%, the COVID pandemic profoundly disrupted the delivery of healthcare. A report found that 43% of physicians switched jobs during the initial two years of the COVID pandemic (2020 and 2021), tripling the expected average annual rate to 21.5 %/yr. During this same time, an average of 4% and 1.5% of physicians retired or left the workforce for a non-clinical career, respectively. The report notes that 35.2% made career changes for a better work-life balance and another 35% reported the reason as being unhappy with their administration’s response to the pandemic. A physician-led primary care-focused health organization, Cano Health (CH), based out of Florida, sought to preemptively address this problem by implementing several supportive measures. Working with >120 clinics and >280 PCPs from Miami to Tampa and Orlando, managing nearly 120,000 Medicare Advantage lives, CH implemented a number of changes to assist with the clinician’s workload. Supportive services such as after hour and home visits by APRNs, in-clinic care managers, and patient educators were implemented. In 2021, assistive Artificial Intelligence Software (AIS) was integrated into the EHR platform. This AIS converts free text within PDF files into a usable (copy-paste) format facilitating documentation. The software also systematically and chronologically organizes clinical data, including labs, medical records, consultations, diagnostic images, medications, etc., into an easy-to-use organ system or chronic disease state format. This reduced the excess time and documentation burden required to meet payor and CMS guidelines. A clinician Documentation Support team was employed to improve the billing/coding performance. The effects of these newly designed workflow interventions were measured via analysis of clinician turnover from CH’s hiring and termination reporting software. CH’s annualized average clinician turnover rate in 2020 and 2021 were 17.7% and 12.6%, respectively. This represents a 30% relative reduction in turnover rate compared to the reported national average of 21.5%. Retirement rates during both years were 0.1%, demonstrating a relative reduction of >95% compared to the national average (4%). This model successfully promoted the retention of clinicians in a Value-Based Care setting.

Keywords: clinician burnout, COVID-19, value-based care, burnout, clinician retirement

Procedia PDF Downloads 65

Authors: Agman Gupta, Rajashekar Badam, Noriyoshi Matsumi

Abstract:

Introduction: Recently, silicon has been recognized as one of the potential alternatives as anode active material in Li-ion batteries (LIBs) to replace the conventionally used graphite anodes. Silicon is abundantly present in the nature, it can alloy with lithium metal, and has a higher theoretical capacity (~4200 mAhg-1) that is approximately 10 times higher than graphite. However, because of a large volume expansion (~400%) upon repeated de-/alloying, the pulverization of Si particles causes the exfoliation of electrode laminate leading to the loss of electrical contact and adversely affecting the formation of solid-electrolyte interface (SEI).1 Functional polymers as binders have emerged as a competitive strategy to mitigate these drawbacks and failure mechanism of silicon anodes.1 A variety of aqueous/non-aqueous polymer binders like sodium carboxy-methyl cellulose (CMC-Na), styrene butadiene rubber (SBR), poly(acrylic acid), and other variants like mussel inspired binders have been investigated to overcome these drawbacks.1 However, there are only a few reports that mention the attempt of addressing all the drawbacks associated with silicon anodes effectively using a single novel functional polymer system as a binder. In this regard, here, we report a novel highly robust n-type bisiminoacenaphthenequinone (BIAN)-paraphenylene-based crosslinked polymer as a binder for Si anodes in lithium-ion batteries (Fig. 1). On its application, crosslinked-BIAN binder was evaluated to provide mechanical robustness to the large volume expansion of Si particles, maintain electrical conductivity within the electrode laminate, and facilitate in the formation of a thin SEI by restricting the extent of electrolyte decomposition on the surface of anode. The fabricated anodic half-cells were evaluated electrochemically for their rate capability, cyclability, and discharge capacity. Experimental: The polymerized BIAN (P-BIAN) copolymer was synthesized as per the procedure reported by our group.2 The synthesis of crosslinked P-BIAN: a solution of P-BIAN copolymer (1.497 g, 10 mmol) in N-methylpyrrolidone (NMP) (150 ml) was set-up to stir under reflux in nitrogen atmosphere. To this, 1,6-dibromohexane (5 mmol, 0.77 ml) was added dropwise. The resultant reaction mixture was stirred and refluxed at 150 °C for 24 hours followed by refrigeration for 3 hours at 5 °C. The product was obtained by evaporating the NMP solvent under reduced pressure and drying under vacuum at 120 °C for 12 hours. The obtained product was a black colored sticky compound. It was characterized by 1H-NMR, XPS, and FT-IR techniques. Results and Discussion: The N 1s XPS spectrum of the crosslinked BIAN polymer showed two characteristic peaks corresponding to the sp2 hybridized nitrogen (-C=N-) at 399.6 eV of the diimine backbone in the BP and quaternary nitrogen at 400.7 eV corresponding to the crosslinking of BP via dibromohexane. The DFT evaluation of the crosslinked BIAN binder showed that it has a low lying lowest unoccupied molecular orbital (LUMO) that enables it to get doped in the reducing environment and influence the formation of a thin (SEI). Therefore, due to the mechanically robust crosslinked matrices as well as its influence on the formation of a thin SEI, the crosslinked BIAN binder stabilized the Si anode-based half-cell for over 1000 cycles with a reversible capacity of ~2500 mAhg-1 and ~99% capacity retention as shown in Fig. 2. The dynamic electrochemical impedance spectroscopy (DEIS) characterization of crosslinked BIAN-based anodic half-cell confirmed that the SEI formed was thin in comparison with the conventional binder-based anodes. Acknowledgement: We are thankful to the financial support provided by JST-Mirai Program, Grant Number: JP18077239

Keywords: self-healing binder, n-type binder, thin solid-electrolyte interphase (SEI), high-capacity silicon anodes, low-LUMO

Procedia PDF Downloads 145

Authors: Doriane Delafosse, Dominique Fontvieille

Abstract:

Background: Wastewater treatment plants (WWTPs) generally display significant efficacy in virus retention yet, are sometimes highly variable, partly in relation to large fluctuating loads at the head of the plant and partly because of episodic dysfunctions in some treatment processes. The problem is especially sensitive when human enteric viruses, such as human Noroviruses Genogroup I or Adenoviruses, are in concern: their release downstream WWTP, in environments often interconnected to recreational areas, may be very harmful to human communities even at low concentrations. It points out the importance of WWTP permanent monitoring from which their internal treatment processes could be adjusted. One way to adjust primary treatments is to add coagulants and flocculants to sewage ahead settling tanks to improve decantation. In this work, sludge produced by three coagulants (two organics, one mineral), four flocculants (three cationic, one anionic), and their combinations were studied for their efficacy in human enteric virus retention. Sewage samples were coming from a WWTP in the vicinity of the laboratory. All experiments were performed three times and in triplicates in laboratory pilots, using Murine Norovirus (MNV-1), a surrogate of human Norovirus, as an internal control (spiking). Viruses were quantified by (RT-)qPCR after nucleic acid extraction from both treated water and sediment. Results: Low values of sludge virus retention (from 4 to 8% of the initial sewage concentration) were observed with each cationic organic flocculant added to wastewater and no coagulant. The largest part of the virus load was detected in the treated water (48 to 90%). However, it was not counterbalancing the amount of the introduced virus (MNV-1). The results pertained to two types of cationic flocculants, branched and linear, and in the last case, to two percentages of cations. Results were quite similar to the association of a linear cationic organic coagulant and an anionic flocculant, though suggesting that differences between water and sludges would sometimes be related to virus size or virus origins (autochthonous/allochthonous). FeCl₃, as a mineral coagulant associated with an anionic flocculant, significantly increased both auto- and allochthonous virus retention in the sediments (15 to 34%). Accordingly, virus load in treated water was lower (14 to 48%) but with a total that still does not reach the amount of the introduced virus (MNV-1). It also appeared that the virus retrieval in a bare 0.1M NaCl suspension varied rather strongly according to the FeCl₃ concentration, suggesting an inhibiting effect on the molecular analysis used to detect the virus. Finally, no viruses were detected in both phases (sediment and water) with the combination branched cationic coagulant-linear anionic flocculant, which was later demonstrated as an effect, here also, of polymers on the virus detection-molecular analysis. Conclusions: The combination of FeCl₃-anionic flocculant gave its highest performance to the decantation-based virus removal process. However, large unbalanced values in spiking experiments were observed, suggesting that polymers cast additional obstacles to both elution buffer and lysis buffer on their way to reach the virus. The situation was probably even worse with autochthonous viruses already embedded into sewage's particulate matter. Polymers and FeCl₃ also appeared to interfere in some steps of molecular analyses. More attention should be paid to such impediments wherever chemical additives are considered to be used to enhance WWTP processes. Acknowledgments: This research was supported by the ABIOLAB laboratory (Montbonnot Saint-Martin, France) and by the ASPOSAN association. Field experiments were possible thanks to the Grand Chambéry WWTP authorities (Chambéry, France).

Keywords: flocculants-coagulants, polymers, enteric viruses, wastewater sedimentation treatment plant

Procedia PDF Downloads 99