During this webinar sponsored by Aurora Scientific, Dr. Burgués will discuss how he and his team are leveraging various signal processing and machine learning techniques in order to decode the fine-scale structure of turbulent chemical plumes using low-cost chemical sensors. Specifically, he will discuss three signal processing methods they developed to improve MOX sensor dynamics, and share the experimental setups they used to test their theories. Finally, he will share data from recent experiments and elaborate on the conclusions of their studies and how robotic plume tracking technology might apply to industrial and air quality monitoring, research and more.
For more information, please visit: https://insidescientific.com/webinar/decoding-turbulent-chemical-plumes-improved-signal-processing-machine-learning-aurora-scientific
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
The Platform for Advanced Characterisation - Grenoble (PAC-G) supports Industrial companies such as Airbus in the qualification of electronic components. For instance, PAC-G helps investigate the threat of the thermal neutrons induced SEU rate at ground level and at aircraft altitudes.
The PAC-G offer an easy access to two high quality neutron facilities dedicated to neutron-induced Single Event Effects (SEE) tests. Fast and Thermal neutron tests are required to assess the reliability of highly integrated devices for critical applications; high energy neutrons can in addition help to prepare proton and heavy ion tests. The PAC-G allows you to have access, on the same site, to a broad spectrum of neutron energies from fast to thermal neutrons (14 MeV, 2.5 MeV and 25 meV).
Indatech Beyond Spectroscopy is an innovative company, with expertise in optical measurements for on-line monitoring and controlling industrial processes. Raman NIR UV Spectroscopy; Hyperspectral imaging; Spatialy Resolved Spectroscopy
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
The Platform for Advanced Characterisation - Grenoble (PAC-G) supports Industrial companies such as Airbus in the qualification of electronic components. For instance, PAC-G helps investigate the threat of the thermal neutrons induced SEU rate at ground level and at aircraft altitudes.
The PAC-G offer an easy access to two high quality neutron facilities dedicated to neutron-induced Single Event Effects (SEE) tests. Fast and Thermal neutron tests are required to assess the reliability of highly integrated devices for critical applications; high energy neutrons can in addition help to prepare proton and heavy ion tests. The PAC-G allows you to have access, on the same site, to a broad spectrum of neutron energies from fast to thermal neutrons (14 MeV, 2.5 MeV and 25 meV).
Indatech Beyond Spectroscopy is an innovative company, with expertise in optical measurements for on-line monitoring and controlling industrial processes. Raman NIR UV Spectroscopy; Hyperspectral imaging; Spatialy Resolved Spectroscopy
Evaluation on Performance of Photoelectric Smoke Detectors in the Zone Detect...civej
Most people believe that detector actuation time increases with the age of a device, but the current test
results suggest otherwise. According to government requirements, the standard actuation time limit for
photoelectric smoke detectors is 60 seconds or less in the zoned detection system; however, this experiment
discovered that new detectors all exhibited actuation times between 10 and 15 seconds. The actuation time
of the detectors decreased with the age of the devices. The current study also determined that if the
actuation time was 4 seconds or less, then the detector should be replaced because of the high chance of
false alarms. In short, detectors with actuation times between 4 and 15 seconds are ideal and should be
viewed as the standard for fire safety equipment. In addition, replacing detectors every 6 years in a zoned
system is suggested by this research, which found a greater chance of false alarms after 6 years of detector
use.
PHOENIX AUDIO TECHNOLOGIES - A large Audio Signal Algorithm PortfolioHTCS LLC
Phoenix Audio Technology has the attached publication available which lists their Audio Signal Algorithm Portfolio, e.g. Multi Sensor Processing, Blind Source Separation, Echo and Reference Channel Canceling, Single Sensor Processing, Multi Resolution Analysis, Single Power Compression, Direction Finding, Data Tracking, Data Fusion, and more.
Medical Imaging - Opportunities for Business Seminar
24/01/12
Session 2 Technology Showcase
Three technologies developed or enhances at the University of Leicester are presented
Demo request dan pemesanan produk, hubungi PT Siwali Swantika. Jakarta : 021-45850618 | Surabaya : 031-842124. Kunjungi website kami di www.siwali.com, untuk detail informasi spesifikasi dan model alat.
Paper presented @Tyrrhenian Workshop on the Internet of Things 2009
ZigBee is probably the most popular IEEE 802.15.4 implementation used for Wireless Sensor Networks (WSN). The radio communication can also be used for localization purposes using fixed network devices as reference points. In this paper, the authors describe a procedure for automatically configuring a ZigBee-based localization appli-cation with environment-optimized parameters.
Evaluation on Performance of Photoelectric Smoke Detectors in the Zone Detect...civej
Most people believe that detector actuation time increases with the age of a device, but the current test
results suggest otherwise. According to government requirements, the standard actuation time limit for
photoelectric smoke detectors is 60 seconds or less in the zoned detection system; however, this experiment
discovered that new detectors all exhibited actuation times between 10 and 15 seconds. The actuation time
of the detectors decreased with the age of the devices. The current study also determined that if the
actuation time was 4 seconds or less, then the detector should be replaced because of the high chance of
false alarms. In short, detectors with actuation times between 4 and 15 seconds are ideal and should be
viewed as the standard for fire safety equipment. In addition, replacing detectors every 6 years in a zoned
system is suggested by this research, which found a greater chance of false alarms after 6 years of detector
use.
PHOENIX AUDIO TECHNOLOGIES - A large Audio Signal Algorithm PortfolioHTCS LLC
Phoenix Audio Technology has the attached publication available which lists their Audio Signal Algorithm Portfolio, e.g. Multi Sensor Processing, Blind Source Separation, Echo and Reference Channel Canceling, Single Sensor Processing, Multi Resolution Analysis, Single Power Compression, Direction Finding, Data Tracking, Data Fusion, and more.
Medical Imaging - Opportunities for Business Seminar
24/01/12
Session 2 Technology Showcase
Three technologies developed or enhances at the University of Leicester are presented
Demo request dan pemesanan produk, hubungi PT Siwali Swantika. Jakarta : 021-45850618 | Surabaya : 031-842124. Kunjungi website kami di www.siwali.com, untuk detail informasi spesifikasi dan model alat.
Paper presented @Tyrrhenian Workshop on the Internet of Things 2009
ZigBee is probably the most popular IEEE 802.15.4 implementation used for Wireless Sensor Networks (WSN). The radio communication can also be used for localization purposes using fixed network devices as reference points. In this paper, the authors describe a procedure for automatically configuring a ZigBee-based localization appli-cation with environment-optimized parameters.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Ultra sonic range finding for distance measuring in coal miningeSAT Journals
Abstract Measuring distances has always been a challenge in coal mines as it involves a lot of risks and disturbances. One method to measure the distances without any hindrances in sensitive places like coal mines is via Ultra Sonic waves which generates 40 KHz sound pulse that travels with the speed of sound to the object and returns it echo that helps in calculating the distance, which further display on the LCD display. The medium required here is air medium. This project performs the distance measuring techniques, required in coal mines. This technique is proven to be very helpful in places where human reach is not possible or difficult. Keywords: UltraSonic Sensors, Range Finding, AVR Microcontroller.
Why Use SAW Sensors and Tags?
- Frequency/time are measured with greatest accuracy compared to any other physical measurement (10-10 - 10-14).
- External stimuli affects device parameters (frequency, phase, amplitude, delay)
- Operate from cryogenic to >1000oC
- Ability to both measure a stimuli and to wirelessly, passively transmit information
- Frequency range ~10 MHz – 3 GHz
- Monolithic structure fabricated with current IC photolithography techniques, small, rugged
The autonomous Test Bench is the growing field of
testing device. The Rapid production firms require rapid testing
infrastructure. Many firms till now use legacy system. The
Autonomous Test Bench is a Rapid Application Development tool
to accelerate the device testing rapid. To implementation ATB
(Autonomous Test Bench) the major requirement is to measure
the target object distance from robotic arm to trigger the device
(like push button, gripping something etc.) Not only Robotic
system, many fields of industry are required to capture ultrasonic
scan data. Sometimes it should be wireless system which may be
positioned anywhere. This paper describes a novel way to capture
surrounded ultrasonic scan data. The device is portable and
wireless and as well as cost effective. To measure object distance,
ultrasonic peripatetic scanner uses two servo motors to scan the
object horizontally and vertically. The main controller is a credit
card sized computer Raspberry pi with high processing capability
and portability. The programs are written using Python which is
an interpreted language.
An Approach to Spectrum Sensing in Cognitive Radio IOSR Journals
Recent research shows that more than 70% of the available spectrum is not utilized
efficiently. The bandwidth becomes expensive due to a shortage of frequencies. Therefore for efficient
utilization of spectrum, we need to sniff the spectrum to determine whether it is being used by primary user or
not. The term cognitive radio refers to the adoption of radio parameters using the sensed information
of the spectrum. There are various spectrum sensing techniques proposed in the literature but still there is
room for researchers in this field to explore more sophisticated approaches. There are three major
categories of spectrum sensing techniques; transmitter detection, receiver detection and interference
temperature detection. This thesis presents a survey of techniques suggested in the literature for
spectrum sensing with a performance analysis of transmitter-based detection techniques.
An Approach to Spectrum Sensing in Cognitive RadioIOSR Journals
Abstract: Recent research shows that more than 70% of the available spectrum is not utilized efficiently. The bandwidth becomes expensive due to a shortage of frequencies. Therefore for efficient utilization of spectrum, we need to sniff the spectrum to determine whether it is being used by primary user or not. The term cognitive radio refers to the adoption of radio parameters using the sensed information of the spectrum. There are various spectrum sensing techniques proposed in the literature but still there is room for researchers in this field to explore more sophisticated approaches. There are three major categories of spectrum sensing techniques; transmitter detection, receiver detection and interference temperature detection. This thesis presents a survey of techniques suggested in the literature for spectrum sensing with a performance analysis of transmitter-based detection techniques. Keywords— Include at least 5 keywords or phrases
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Next-Generation Safety Assessment Tools for Advancing In Vivo to In Vitro Tra...InsideScientific
Join Prof. Victoria Hutter and Dr. Louis Scott as they showcase the application of high-content imaging and advanced cell lines for drug safety assessment.
Safety concerns play a significant role in the unsuccessful progression of candidate compounds in the later stages of drug development. Establishing the connection between in vitro endpoints and human health outcomes is essential.
In this webinar, Prof. Victoria Hutter and Dr. Louis Scott present a novel tool for in vitro safety assessment in drug development. The morph_ONE™ assay provides a human-centric approach to potentially fill specific regulatory gaps concerning safety issues. This tool is capable of profiling both human and rat alveolar macrophages, offering valuable insights for hazard identification and toxicity assessments. By bridging the divide between cellular effects and overall risk, it has the potential to enhance our understanding of safety-related aspects in drug development.
Key Topics Include:
- Explore distinct in vitro screening techniques for evaluating the safety of emerging inhaled products, facilitating early and informed decisions in compound selection and development.
- How high-content image analysis (HCIA) cell painting assays can be used as a forward-looking high-throughput screening tool, distinguishing unique response patterns in alveolar macrophages.
- Understand the use of the ImmuPHAGE™ and ImmuLUNG™ models in conducting customized evaluations focused on inhalation safety.
A Ready-to-Analyze High-Plex Spatial Signature Development Workflow for Cance...InsideScientific
In this webinar, Aditya Pratapa and Lorcan Sherry present a new workflow for analyzing multiplex immunoflurescence images.
Spatial Signatures are a new class of highly predictive biomarkers that measure the interactions and cellular densities of tumor and immune cells that compose the tumor microenvironment. Based on multiplex immunofluorescence, spatial signatures provide a deeper understanding of complex interactions between tumors and the immune system, enabling improved patient stratification for immunotherapies. A significant hurdle to date has been in developing a data analysis workflow that is straightforward and user-friendly to transform the data rich images into meaningful quantitative spatial signatures.
In this webinar, Aditya and Lorcan review the key features of the new PhenoImager HT 2.0 data analysis workflow. This workflow introduces a simplified framework from scanning to analyzing spectrally unmixed multiplex immunofluorescence images generated on the PhenoImager HT platform. The ready-to-analyze data can be directly imported into image analysis software such as Visiopharm. This presentation covers key aspects of data analysis elements such as image QC, segmentation, phenotyping, and verification – all essential for creating outputs that support the development of a spatial signature.
Key Topics Include:
- Understand Akoya’s new HT 2.0 data analysis workflow
- The challenges in multiplex immunofluorescence analysis and the use of AI and cell
lineage segmentation considerations
- Explore OracleBio’s image analysis workflow incorporating Visiopharm
- Evaluation of analysis data to facilitate spatial profiling and interpretation
Molecule Transport across Cell Membranes: Electrochemical Quantification at t...InsideScientific
In this webinar, Dr. Sabine Kuss will discuss the importance of transmembrane molecule exchange and how to detect and quantify membrane transport of molecules in cells.
Complex biological processes, such as the transport of molecules across cell membranes, are difficult to understand using purely biological methodologies. Investigating cellular transport processes is challenging, because of the highly complex chemical composition of cells and the diffusion of molecules in and around cells at low concentrations. The development and advancement of electroanalytical methods over the last two decades has enabled the monitoring of living cells and their interaction with the environment, including external stimuli, such as pharma-molecules.
This presentation emphasizes electrochemical and electrophysiological methods of detection and quantification but also makes a comparison to other bioanalytical approaches. Join us to discover a substantial diversity in methods used to monitor the transport of cell metabolites, crucial for cell survival, and pharmaceutical compounds, involved in cell characteristics such as drug resistance.
Key Topics Include:
- Understanding transmembrane molecule transport through bioanalytical methods
- Electrochemical approaches to monitor molecule transport across cell membranes
- What bioanalytical and especially electrochemical approaches can reveal
- Challenges associated with instrument limitations
Exploring Predictive Biomarkers and ERK1/2 Phosphorylation: A New Horizon in ...InsideScientific
In this webinar, Dr. Victor Arrieta highlights the link between p-ERK activation and improved survival in rGBM patients using anti-PD-1 immunotherapy.
Recurrent glioblastoma (rGBM) has displayed a varied response to anti-PD-1 immunotherapy, necessitating the identification of predictive biomarkers. Through extensive analyses and 3 clinical studies, we have identified that activation of the MAPK/ERK signaling pathway, particularly ERK1/2 phosphorylation (p-ERK), is associated with longer overall survival (OS) in rGBM patients receiving PD-1 blockade. Initially, enrichment of BRAF/PTPN11 mutations was reported in 30% of responsive rGBM patients, prompting the investigation of p-ERK as a potential marker beyond these mutations.
Our research has unraveled an association between p-ERK abundance and better clinical outcomes following PD-1 blockade, with p-ERK mainly localized in tumor cells. Notably, high p-ERK GBMs contained unique microglia and macrophage phenotypes with elevated MHC class II expression, suggesting a novel interplay between MAPK activation and the tumor immune microenvironment.
While these insights establish a pivotal role for p-ERK in predicting PD-1 blockade response in rGBM, the implementation in clinical settings calls for further validation and accuracy. Nonetheless, these findings pave the way for more personalized and effective immunotherapy strategies, emphasizing the significance of the tumor microenvironment and its interaction with therapeutic interventions in GBM.
Key Topics Include:
- The activation of the MAPK signaling pathway, specifically ERK1/2 phosphorylation (p-ERK), is identified as a predictive biomarker for longer overall survival in recurrent glioblastoma (eGBM) patients undergoing PD-1 blockade
- High p-ERK tumors in rGBM present a distinct myeloid cell phenotype with elevated MHC class II expression, signifying a connection between MAPK pathway activation and the immune microenvironment
- The implementation of p-ERK as a predictive biomarker in clinical settings requires further validation and exploration of variables impacting its evaluation
Exploring Estrogen’s Role in Metabolism and the Use of 13C-Labeled Nutrients ...InsideScientific
Dr. Reilly Enos and Dr. Eran Levin discuss estrogen's metabolic impact and how isotopic labeling and 13C-labeled nutrients can be used for animal physiology and nutrition research.
Reilly Enos, PhD – Harnessing the power of estrogen to regulate metabolic processes
Dr. Reilly Enos’ research focuses on the role that sex steroids and their receptors play in regulating metabolic processes, particularly in the setting of obesity. In this webinar, Dr. Enos will discuss his research on tissue-specific fluctuations of sex steroids throughout the estrous cycle in mice, provide insights into the importance of the quantity of estrogen necessary to impact physiological processes, as well as an understanding of the central versus peripheral effects of estrogen action.
Eran Levin, PhD – Unlocking Insights: Utilizing 13C Labeled Nutrients for Cutting-Edge Physiology and Nutrition Research
Dr. Eran Levin will discuss the potential of using 13C-labeled nutrients in physiology and nutrition research in animal models. Specifically, he will share practical tips for designing and conducting experiments using isotopic labeling techniques and demonstrate how they can provide unprecedented insights into metabolic pathways, nutrient utilization, and behaviors in both vertebrate and invertebrate models including insects, reptiles, and mammals.
Key Topics Include:
- The role that estrogen plays in regulating metabolic and behavioral processes in males and females
- The tissue-specific fluctuations of sex steroids throughout the estrous cycle
- Insight into the importance of tissue-specificity in developing hormonal therapies
- The importance of estrogen quantity in regulating physiological processes
- Understand the diverse range of 13C labeled nutrients available
- Specific applications of labeled amino acids in studies of protein metabolism, cellular signaling, and typical nutrient utilization
- How to integrate 13C labeling techniques with respirometry for a comprehensive assessment of metabolic processes, energy expenditure, and substrate utilization in animal models
- How to calculate metabolic rates in free-flying animals using 13C bicarbonate
Longitudinal Plasma Samples: Paving the Way for Precision OncologyInsideScientific
Experts present a cell-free plasma biobank and describe the role of longitudinal plasma samples for cancer research, disease monitoring, and biomarker development.
Through liquid biopsies, it is now possible to repeatedly and non-invasively interrogate the molecular landscape of solid tumors via a blood draw over the whole treatment course. Until now, liquid biopsies can be used for screening, disease monitoring and prognosis. Circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs) have been the most explored targets in this technology for commercial applications up to the present time.
In collaboration with a continuously expanding oncology network, Indivumed Services has established a unique high-quality cell-free plasma biobank that is exclusively focused on collecting longitudinal whole blood samples from cancer patients. This allows molecular insight by providing quick access to longitudinal plasma from cancer patients that have undergone treatment. ctDNA can then be isolated from longitudinal cell-free plasma to allow for monitoring of disease progression by providing diagnostic and prognostic information, potentially in real time.
Key Topics Include:
- Gain insights into Indivumed Services’ longitudinal plasma collection process
- Understand the advantages and benefits of utilizing longitudinal plasma samples for cancer research
- Explore applications of longitudinal plasma samples for biomarker research and development of companion diagnostics
Fully Characterized, Standardized Human Induced Pluripotent Stem Cell Line an...InsideScientific
In this webinar, experts present a standardized stem cell line and its differentiation into neural cells for disease modeling and assay development.
Reproducible research with human induced pluripotent stem cells (iPSCs) depends on thoroughly characterized and quality-controlled cell lines. In this webinar, Dr. Andrew Gaffney and Dr. Erin Knock from STEMCELL Technologies describe the generation of a standardized induced pluripotent stem cell (iPSC) line. Developed with the upcoming ISSCR Standards Initiative characterization guidelines in mind, this highly characterized line is karyotypically stable, demonstrates trilineage differentiation potential, and expresses undifferentiated cell markers. Further, STEMCELL has developed a highly pure, ready-to-use neural progenitor cell product expressing PAX6 and SOX1 over multiple passages.
Dr. Knock shows how these multipotent cells are suitable for customized downstream differentiation to various CNS cell types, such as forebrain neurons, midbrain neurons, and astrocytes. These progenitor cells are the ideal controls for standardizing downstream differentiation protocols, modeling diseases, and assay development.
Key Topics Include:
- Discover how STEMCELL’s induced pluripotent stem cell lines are derived and characterized
- Learn how to differentiate induced pluripotent stem cell lines into all three germ layers
- Explore the features of STEMCELL’s neural progenitor cell product
- Differentiate neural progenitor cells into a variety of neural cell types, including neurons and glia
How to Create CRISPR-Edited T Cells More Efficiently for Tomorrow's Cell Ther...InsideScientific
Ian Foster and Steven Loo-Yong-Kee discuss Artisan Bio's STAR-CRISPR system for optimized gene editing in cell therapy, with a focus on the genetifc modification of T cells for cancer immunotherapy.
Cell therapy is an emerging field with great promise for the treatment of various diseases. One of the most exciting areas of cell therapy is the use of T cells that have been genetically modified to recognize and kill cancer cells. While the use of T cells for cancer immunotherapy has tremendous promise, there is still room for improvement. The efficiency, expansion, and functionality of T cells can be enhanced by genetic modification using the STAR-CRISPR system.
Artisan Bio is a biotechnology company focused on developing a CRISPR-mediated editing platform to improve the efficacy and safety of cell therapy products. In this webinar, we will provide a comprehensive overview of Artisan Bio’s STAR-CRISPR system, which is designed to improve the specificity and efficiency of gene editing for cell therapies. We will explain the system’s key components and how we are using a risk-based approach to optimize and validate the editing platform. The webinar will focus on Artisan Bio’s approach to building T cell OS/APPS through iterative improvements to achieve best-in-class editing capabilities and improved cell health metrics.
Key Topics Include:
- Learn about Artisan Bio’s proprietary high-performance STAR-CRISPR system for improving the specificity and efficiency of gene editing for cell therapies
- Explore Artisan Bio’s risk-based, systems approach to technology development, including how to implement Design of Experiments (DoE) and Quality by Design (QbD) principles to optimize and validate any process
- Case study of the application of QbD to Artisan Bio’s STAR-CRISPR platform to edit T cells for cancer immunotherapy with preliminary data showing improved efficacy, expansion, and functionality
Peripheral and Cerebral Vascular Responses Following High-Intensity Interval ...InsideScientific
Dr. Bert Bond and Max Weston will present an overview on their study investigating the effects high-intensity interval exercise has on cerebrovascular health.
Physical activity reduces the risk of developing cardiovascular diseases (CVD) and dementia. This benefit cannot be explained by changes in traditional CVD risk factors alone, and direct improvements in vascular health are thought to play a key role. However, our understanding of how exercise can be optimized for improvements in blood-vessel health is limited.
High-intensity interval exercise (HIIE) is known to improve peripheral vascular function, and there is a growing interest in the effects of HIIE on cerebrovascular health. However, it is not clear whether the acute improvements in peripheral vascular function following HIIE are also seen in the major blood-vessels of the brain.
In the Bond lab’s study, 30 minutes of HIIE completed at both 75% and 90% V̇O2max improved peripheral vascular function 1 and 3h following exercise in healthy young adults, compared with work-matched continuous moderate-intensity exercise and a sedentary control condition. By contrast, cerebrovascular function was unchanged following all conditions. This is the first study to identify that acute improvements in peripheral vascular function following high-intensity interval exercise are not mirrored by improvements in cerebrovascular function in healthy young adults.
Leveraging Programmable CRISPR-Associated Transposases for Next-Generation Ge...InsideScientific
Dr. Sam Sternberg discusses a novel CRISPR-Cas9 system using programmable, RNA-guided transposase, and highlights its implications for kilobase-scale genome engineering in cell and gene therapies.
The utility of programmable, RNA-guided CRISPR-Cas systems in genome engineering continues to evolve. Nature has afforded scientists novel and diverse gene editing functionality, from nuclease-dependent CRISPR-Cas9 to second-generation base and prime editors that do not produce double-strand breaks.
In this webinar, Dr. Sam Sternberg describes a new CRISPR-Cas9 paradigm relying on nuclease-deficient bacterial transposons that catalyze RNA-guided integration of mobile genetic elements into the genome. The discovery of a fully programmable, RNA-guided transposase lays the foundation for kilobase-scale genome engineering with broad applications for developing cell and gene therapies.
Key Topics Include:
- The basics of first- and second-generation CRISPR-Cas technologies from a scientist at the forefront of their development
- Mechanisms, accommodation, and cell type diversity of CRISPR-Cas programmable transposition
- How transposase factor coordination enables highly specific, genome-wide DNA integration to target sites
- Implications of programmable transposases that obviate the need for DNA double-strand breaks and homologous recombination
Simple Tips to Significantly Improve Rodent Surgical OutcomesInsideScientific
Dr. Marcel Perret-Gentil presents six simple-to-implement techniques to significantly improve surgical outcomes.
You may feel proficient, even confident in performing rodent surgery; however, you may be surprised how simple improvements can have a huge impact to your animal’s recovery and data. The presentation is designed for individuals who have minimal or no rodent surgical skills but is also a great opportunity for those with considerable experience wanting to improve outcomes as well as teach such key principles.
Key Topics Include:
- Improve surgical outcomes that will lessen post-op morbidity and mortality
- Improve data yield after rodent surgery
- Implementation of key principles into a rodent surgical program
Cardiovascular Autonomic Dysfunction in the Post-COVID Landscape: Detection a...InsideScientific
A world-wide spread of the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has triggered a pandemic and generated over 600 million reported cases around the globe. A substantial portion of patients who suffered Corona Virus Disease 2019 (COVID-19) have not recovered completely but continue to experience lingering symptoms for months to years. This novel clinical syndrome has been termed Long COVID or Post-acute Sequalae of COVID-19 (PASC).
Observational studies have indicated that in about one third of cases PASC can be associated with cardiovascular (CV) autonomic dysfunction including postural orthostatic tachycardia syndrome, inappropriate sinus tachycardia, orthostatic hypotension, reflex syncope and microvascular dysfunction. The presence of CV autonomic dysfunction in PASC is important to detect since although frequently overlooked, it may be effectively treated in contrast to many other Long COVID-related symptoms.
This webinar highlights CV dysautonomia as a specific sequalae of acute COVID-19 and guides the audience in the diagnostic work-up of PASC patients with suspected cardiovascular complications.
Creating Better Gene-Edited Cell Lines with the FAST-HDR SystemInsideScientific
Cell lines are the core of biological research. Scientists need cell lines for drug development, basic biology research, safety testing, and biologic therapeutic production. Since the 1980s, genetic manipulation has allowed researchers to tailor cell lines to the experiment or production purpose. Over time, the requirements for these cell lies have risen. In many cases, the cells require multiple genetic edits and must produce data that passes FDA. Moreover, the current funding environment often requires rapid delivery of these cells so scientists can produce data to support further budget and/or investment. This is particularly acute for knock-in cell lines. Current technologies may take months to complete a cell line, allow a limited number of edits, and often have off-target effects that are not suitable for FDA filings. ExpressCells uses its patented FAST-HDR plasmid--along with CRISPR, to address these problems. The FAST-HDR process can precisely knock-in multiple genes (while supporting other types of genetic modifications), ensure precise placement of these edits, and deliver them months faster than competing technologies.
This webinar will discuss the basis of the FAST-HDR technology and illustrate several uses. The first part is a presentation by Oscar Perez-Leal, MD, the inventor of the technology. Oscar will discuss the problems he faced as a researcher and how FAST-HDR was designed to address them. He will outline the details of the technology, the history of its development, and several examples where he used FAST-HDR. The second part is a conversation with Jon Weidanz, PhD. Jon will outline the challenges he faced at AbeXXa and how he selected a FAST-HDR custom cell line for his project. He'll outline the learnings from using this cell line, some of which were unexpected, but valuable to future development.
By attending this program, attendees will:
- Understand the current challenges in creating custom gene-edited cell lines
- Know the technology underlying the FAST-HDR gene-editing system, including its use with CRISPR
- Be able to describe the advantages of the FAST-HDR system
- Learn about several case studies using gene-edited cell lines
Functional Recovery of the Musculoskeletal System Following Injury - Leveragi...InsideScientific
Watch Dr. Sarah Greising discuss the current pathophysiologic understanding of the skeletal muscle remaining following traumatic musculoskeletal injuries.
Volumetric muscle loss (VML) injuries result in the abrupt loss of skeletal muscle fibers, causing chronic functional disability in part due to limited muscle regeneration and vast co-morbidities. With a focus on clinically relevant outcome measurements for skeletal muscle function in both small and large animal models of VML injury, this webinar presents various near-term interventions for the restoration of tissue function following complex injuries. Interventions evaluated focus on regenerative rehabilitation approaches using regenerative pharmaceuticals to correct underlying muscle pathophysiology.
Designing Causal Inference Studies Using Real-World DataInsideScientific
In this webinar, experts provide an overview of causal inference, along with step-by-step guidance to designing these studies using real-world healthcare data.
Causal inference is used to answer cause and effect research questions and yield estimates of effect. Causal study design considerations and statistical methods address the effects of confounding variables and other potential biases and allow researchers to answer questions such as, “Does treatment A produce better patient outcomes compared to Treatment B?”
Causal study interpretations have traditionally been restricted to randomized controlled trials; however, causal inference applied to observational healthcare data is growing in importance, driven by the need for generalizable and rapidly delivered real-world evidence to inform regulatory, payer, and patient/provider decision making. The application of causal inference methods leads to stronger and more powerful evidence. When these techniques are applied to observational data, the results generated are both from and for the real world.
Presenters walk through several real-world case studies including the PCORI-funded BESTMED study and a collaborative study with a prominent pharmacy payer.
Social Media Data: Opportunities and Insights for Clinical ResearchInsideScientific
Many new data are emerging in recent years - real time data is collected through digital health technologies, including apps and wearables, monitoring data, social media data, public datasets, and patient organization data, in addition to primary and secondary datasets.
Real life data are highly informative and can be used to address a range of challenges throughout the product life cycle. Data from social media can generate valuable insights as patients often gather in digital communities to get answers and share their experiences. Conversations on social networks merit special consideration as they can have real world influence over treatment management decisions.
Social media data can reveal the motivations that impact patient healthcare decisions and behaviors through each stage of the care pathway. These data provide both the patient and caregiver perspectives at the same time. For this reason, conversations on social networks offer an opportunity to deepen our understanding on:
- The fears and hopes associated with patient treatments
- Daily needs and difficulties patients are facing in managing their disease
- The impact of disease on patient health related quality of life
- Identification in real life of the stages of the care pathway and patient perceptions
- Reactions to health policies
Watch this webinar for insights on how to collect, use, analyze, and interpret social media data in different contexts. Our experts share knowledge from over fifteen years of successfully developing and adapting algorithms to treat this kind of data.
We Are More Than What We Eat Dietary Interventions Depend on Sex and Genetic ...InsideScientific
To learn more visit: https://insidescientific.com/webinar/we-are-more-than-what-we-eat-dietary-interventions-depend-on-sex-and-genetic-background/
Despite evidence that sex and genetic background are key factors in the response to diet, most studies of how diet regulates metabolic health and even longevity in mice examine only a single strain and sex.
Using multiple strains and both male and female mice, Dr Lamming's team has found that improvements in metabolic health and in longevity in response to reduced levels of protein or specific amino acids strongly depend on sex and strain. While some phenotypes were conserved across strains and sexes, including increased glucose tolerance and energy expenditure, they observed high variability in adiposity, insulin sensitivity, and circulating hormones. Using a multi-omics approach, they identified mega-clusters of differentially expressed hepatic genes, metabolites, and lipids associated with each phenotype, gaining new insight into role of the energy balance hormone FG21 in the response to protein restriction.
Antibody Discovery by Single B Cell Screening on Beacon®InsideScientific
Amy Sheng, PhD provides an overview of antibody screening platforms and presents applications and case studies using the Beacon® platform for antibody discovery.
Single B cell screening is a powerful and efficient strategy for generating antigen-specific monoclonal antibodies. Distinguished with fluorescence-activated B cell sorting, the Beacon® platform is based on plasma cell screening, making it easier to obtain antibody genes.
The Beacon® single-cell optofluidic system combines a unique optoelectro positioning (OEP) technology with novel microfluidic technology. It can be used to accurately select single cells on a chip, perform multiple single-cell assays, and export target cells based on specific results. The Beacon® optofluidic platform preserves the diversity of B cells, generating high-quality positive hits at an early stage of discovery and avoiding the loss of “good clones”.
Key Topics Include:
- B cell differentiation and development
- Pros and cons of mainstream antibody screening platforms
- Mechanisms, applications, and case studies using the Beacon® platform for antibody screening
- Sino Biological’s capacity using the Beacon® platform
Experimental Design Considerations to Optimize Chronic Cardiovascular Telemet...InsideScientific
Phil Griffiths, PhD, presents a summary of chronic cardiovascular telemetry studies and considerations for experimental design.
Ensuring you collect the best and most physiologically accurate data from your chronic telemetry experiments requires careful planning and experimental design. This webinar will give an insight into the practical aspects of designing chronic animal experiments to set you on the best path for success. The benefits of chronic studies, how to select the most appropriate sample size for your study, some basic tips and tricks for data acquisition and handling, and how to ensure high animal welfare are discussed.
Key Topics Include:
- What are the benefits of chronic over acute studies?
- How to decide the best sample sizes and the length of experiments?
- Basic tips for data acquisition and handling
- How to maintain high animal welfare standards
Strategic Approaches to Age-Related Metabolic Insufficiency and Transition in...InsideScientific
In this webinar, Dr. Dennis Turner delves into dementia syndrome, the metabolic changes that occur, and the importance of proper physiological monitoring of animal models.
Brain metabolism transforms with normal aging, and transient, dynamic metabolic insufficiency may underlie critical progression from aging into dementia syndrome and Alzheimer’s disease (AD). Age-related brain metabolism balances vascular-related substrate supply and transport mechanisms into extracellular space to neurons with cellular metabolic needs and utilization. Dynamic metabolic insufficiency can occur when there is intermittent supply-demand mismatch.
Adequacy of neurovascular coupling to provide sufficient cerebral blood flow (CBF) to meet neuronal demand in vivo in a mouse AD model, compared to aged controls were studied. Dr. Turner’s lab analyzed the response to maximal neuronal metabolic demands, spreading depression and anoxia, using imaging, CBF measurements, and oxygen and glucose levels. These in vivo studies require human-similar anesthesia conditions, through monitoring temperature, blood pressure/pulse oximetry, and respiration, to maintain homeostasis. The lab confirmed abnormal neurovascular coupling in a mouse model of AD in response to these metabolic challenges, showing disruption much earlier in dementia than in equivalently aged individuals. Chronic metabolic treatments could influence dementia syndrome progression.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Decoding Turbulent Chemical Plumes With Improved Signal Processing and Machine Learning
1. Decoding Turbulent Chemical Plumes
with Improved Signal Processing and
Machine Learning
Javier Burgués, MSc, PhD
Post Doctoral Researcher
Institute for BioEngineering
of Catalonia
Chris Rand
Senior Product Consultant
Aurora Scientific
2. Decoding Turbulent Chemical Plumes
with Improved Signal Processing and
Machine Learning
Join Dr. Javier Burgués as he demonstrates
how he has built faster and more reliable MOX
sensors for tracking turbulent chemical plumes.
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5. Javier Burgués, MSc, PhD
Decoding Turbulent Chemical Plumes
with Improved Signal Processing and
Machine Learning
Post Doctoral Researcher
Institute for BioEngineering of Catalonia
Copyright 2020 J. Burgués and InsideScientific. All Rights Reserved.
7. Olfactory robots
Applications
• Source localization (SL)
• Concentration mapping (CM)
• Emission quantification (EQ)
• Robots equipped with one or more chemical
sensors.
• First prototypes in the early 1990s using
terrestrial robots.
• In recent years, nano-drones with miniature
sensors have become more popular.
Scenarios
• Industrial emission monitoring
• Air quality monitoring in cities
• Atmospheric research, volcanology
• Search and rescue
• …J. Burgués et al., Sensors, 2019, 19(3), 478
8. Structure of a turbulent plume
Celani et al. , Physical Review X, 2014
• Chaotic collection of gas patches
• Smooth gradients only observable after
long-term averaging (~10 min)
Spatial structure of plume
Dekker et al., Jnl Exp Bio., 2011
1 s
Temporal structure of plume
• Fast fluctuations of the instantaneous
concentration (up to 10 KHz)
• Intensity and duration of peaks are indicative of
the source-receptor (SR) distance.
Sensors with high
temporal resolution
Key requirement:
9. 5 s
Metal oxide (MOX) gas sensors
• Olfactory robots typically mount metal oxide
(MOX) sensors due to small form factor, simplicity,
cost and high sensitivity.
• MOX sensors are based on physicochemical
reactions happening on an active sensing layer.
• These reactions are slow.
• MOX sensors can be modelled as leaky integrators
(1st order low-pass filter) of the input stimuli.
330 Hz
0.1 Hz
y 𝑡 = 𝛼 ∙ 𝑦 𝑡 − 1 + 1 − 𝛼 ∙ 𝑥(𝑡)
MOX𝑥(𝑡) 𝑦(𝑡)
Related to time constant of the sensor
10. Improving the sensor dynamics by signal processing
• Key idea: If the transference function ℎ(𝑡) of the sensor is known, it could be inverted to
reconstruct the (fast) input stimuli based on the (slow) sensor output.
D. Martinez et al., Sensors, 2019, 19, 4029
𝐻(𝑓) 𝐻(𝑓)−1
ℎ(𝑡) ℎ(𝑡)−1
• The challenge is to determine the impulse response, ℎ(𝑡)
Very difficult to
produce in the lab
11. Goals of this work
1. Develop signal processing methods to improve the MOX sensor dynamics.
a. Low-pass differentiator (LPD) filter
b. Linear deconvolution model
c. Blind deconvolution
2. Extract features from the fast response that are informative of the source-
receptor (SR) distance in a turbulent plume.
3. Evaluate the performance of such features in real data acquired with mobile
robots and fixed sensor networks.
12. Method 1: Low pass differentiation (LPD)
𝑓
H−1
(𝑓)
𝑓𝑐
𝑈(𝑓)
derivative
Low-pass derivative (LPD)
noise
𝒇 𝒄 is the key
parameter to
be estimated
• Assuming that h(t) is an integrator of the concentration,
a differentiator filter will invert that operation.
MOX
𝑥(𝑡) 𝑦(𝑡) 𝑥(𝑡)
𝑑
𝑑𝑡
• However, differentiation is a risky signal processing operation that amplifies high-frequency noise.
• Differentiation must be restricted to the signal bandwidth Low-pass differentiator (LPD) filter
• How to estimate the signal bandwidth? Fast photo-ionization detector (PID)
13. Method 2: Empirical modelling of h(t)
• Generating a delta in concentration is very difficult to achieve.
• However, we can easily generate a step function.
• The derivative of a step function is a delta function.
• Therefore, the impulse response can be obtained as the derivative of the step response.
Stimulate the sensor with a
step-like function
Model the response and
differentiate it to obtain ℎ(𝑡)
𝑑
𝑑𝑡
14. Method 3: Blind deconvolution
D. Martinez et al., Sensors, 2019, 19, 4029
• The previous methods require the PID signal (ground truth) to optimize the model parameters.
• However, in a real application the PID signal may not available.
• Key idea: If two sensors are excited by the same input 𝑥(𝑡), the deconvolved
outputs 𝑥1(𝑡) and 𝑥2(𝑡) should converge to the same result.
MOX1
𝑥(𝑡)
𝑦1(𝑡)
𝑦2(𝑡)MOX2
+
−
𝑥1(𝑡)
𝑥2(𝑡)
𝑒(𝑡)
MOX1
-1
MOX2
-
1
• Minimization of 𝑒(𝑡) should provide the best signal reconstruction.
16. 2.1. Dataset #1 – Open-environment
• Chemical source is a beaker with liquid analyte
(ethanol or acetone)
• Pressurized air stream creates a turbulent plume.
• Sensing platform integrates 4 MOX sensors and a
fast photoionization detector (PID) with 330 Hz
bandwidth (for ground truth).
• 9 receptor locations (distance range : 15 – 135cm)
• 5 minutes of measurement at each receptor.
J. Burgués et al., ISOEN, 2019, doi:
10.1109/ISOEN.2019.8823158
17. • 5 receptor locations (SR distance: 25 – 150 cm)
• 3 wind speeds (10, 21 and 30 cm/s)
• 10 chemical substances (Acetone, Ethanol, etc.)
• 4 minutes of measurement at each receptor.
• 20 trials per distance/wind/gas combination.
• No ground truth available.
A.Vergara et al., Sens. Act. B:Chem, 2013, 185, p. 462-477
2.2. Dataset #2 –WindTunnel
18. 2.3. Dataset #3 – Small Office
Room
• 25m2 office room
• 27 MOX sensors deployed in a
3x3x3 grid
• SR distance range: 0.25 – 5.5 m
• 10 experiments of 90 min
duration each.
• Variations in source position,
release rate and wind.
J. Burgués et al., Sens. Act. B:Chem, 2020,
304, p.127309.
19. 2.4. Dataset #4 – Large Robotics Laboratory
• Robotics laboratory (160 m2)
• Nano-drone equipped with 2 MOX
sensors.
• Pre-defined exploration strategy.
• 1 chemical substance (Ethanol)
• 3 experiments of ~3 min duration
• Variations in source position,
release rate and wind.
J. Burgués et al., Sensors, 2019, 19(3), 478, doi.org/10.3390/s19030478
22. 3.1.1. Optimization of the low-pass differentiator (LPD) filter
Filtered MOX
99% confidence
99% confidence
Raw (15 cm)
Raw (135 cm)
Filtered (15 cm)
Filtered (135 cm)
7.5 s
0.4 s
20-fold
improvement in
response time
Dataset #1 (open-environment)
Optimize 𝒇 𝒄 for maximum cross-covariance between the
filtered signal and the ground truth (PID):
𝐶𝑜𝑣 𝑥𝑦 𝑚 = 𝐸 𝒙[𝑛] − 𝜇 𝒙 𝒚[𝑛 + 𝑚] − 𝜇 𝒚
𝑇
Test multiple LPD filters with different values of 𝒇 𝒄
J. Burgués & S. Marco, IEEE Access, 2019
J. Burgués et al., ISOEN, 2019
23. 3.1.2. Empirical modelling of h(t)
D. Martinez et al., Sensors, 2019, 19, 4029
Blind deconvolution using two MOX sensors
Supervised deconvolution
using a PID as ground truth
ℎ 𝑡 = 1 − 𝑒−
𝑡
𝜏
Step response
Time constant
Sensor stimulation
25. 3.2.1 Transient feature extraction for SR distance prediction
Filtered MOX
Bouts
• The “bouts” are the rising edges of the LPD-filtered signal
with amplitude higher than the noise threshold (𝒃 𝒕𝒉𝒓).
• The bout frequency (BF) encodes the SR distance:
• The higher is the BF, the closer is the source.
• Figure of merit: Root mean squared error in prediction:
J. Burgués & S. Marco, Sens. Act. B:Chem, 2020
26. 3.2.2. SR distance prediction results
Effect of window size Prediction error under different wind speeds
J. Burgués & S. Marco, IEEE Access, 2019
J. Burgués & S. Marco, Sens. Act. B:Chem, 2020
Effect of 𝒇 𝒄 and 𝒃 𝒕𝒉𝒓
• Joint optimization of 𝑓𝑐 and 𝑏𝑡ℎ𝑟 leads to the best RMSEP.
• Predictive models based on BF require longer
measurement windows than those based on statistical
descriptors of the signals.
• Optimized BF models can be relatively
insensitive to variations in wind speed.
Algorithm is publicly available
28. 3.3.1. SR distance prediction in dataset #3 (small office room)
J. Burgués & S. Marco, Sens. Act. B:Chem, 2020, 304, p.127309. (Dataset & code publicly available)
• Real-time signals of 27 MOX sensors during 90 minutes of gas release.
• Gas distribution maps (mean, variance, bout frequency) computed every 5 minutes.
• Gas source localization using the cell with maximum value in each of the maps.
29. 3.3.2. SR distance prediction in dataset #3 (small office room)
• Maximum
• Variance
• Bout Frequency
Localization error in Experiment 2
• BF provides lowest error considering all
experiments.
• BF reduces overall error by 25% w.r.t.
variance estimator.
Overall results
Max
Var
BF
• Statistical descriptors of the signal (mean,
variance, etc.) are sensitive to timestamp.
• Bout frequency (BF) continuously provides low
error estimates (1.3 m)
31. 3.4.1. SR distance prediction in dataset #4 (large indoor lab)
J. Burgués et al., Sensors, 2019, 19(3), 478, doi.org/10.3390/s19030478
• Scenario: 160 m2 indoor laboratory.
• Predefined navigation path (3D).
• Average flight speed: 1 m/s
• External localization system: RF beacons.
• 3D map of instantaneous concentration.
• 3D map of bouts (blue circles)
32. 3.4.2. SR distance prediction in dataset #4 (large indoor lab)
• Localization errors using optimized BF: 0.7 - 2.2 m
• Measuring near the source is key.
• Proper selection of 𝑏𝑡ℎ𝑟 is required for maximum
sensitivity and noise rejection.
J. Burgués et al., Sensors, 2019, 19(3), 478, doi.org/10.3390/s19030478
Impact of 𝒃 𝒕𝒉𝒓 on the bout map (Blue: low 𝒃 𝒕𝒉𝒓 ; green: high 𝒃 𝒕𝒉𝒓)
33. • Improving the bandwidth of low-cost chemical sensors is necessary to successfully apply them in
mobile robots for gas sensing tasks.
• In this work, we developed signal processing techniques to boost the bandwidth of MOX sensors
by a factor 20 and machine learning algorithms to extract dynamic features which are indicative of
the source-receptor distance.
• The results have been validated in four different scenarios, including wind tunnels and 3D indoor
spaces, using fixed and mobile sensing platforms (nano-drones)
• The proposed algorithms enable the use of low-cost gas sensors for source localization,
concentration mapping and emission quantification in environmental and safety applications.
Summary and conclusions
34. Javier Burgués, MSc, PhD
Decoding Turbulent Chemical Plumes
with Improved Signal Processing and
Machine Learning
Post Doctoral Researcher
Institute for BioEngineering of Catalonia
Copyright 2020 J. Burgués and InsideScientific. All Rights Reserved.
jburgues@ibecbarcelona.eu
/Javier_Burgues
/jburgues8
35. Javier Burgués, MSc, PhD
Post Doctoral Researcher
Institute for BioEngineering
of Catalonia
Chris Rand
Senior Product Consultant
Aurora Scientific
Thank You! CLICK HERE to learn
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