Macro-Scale Molecular Communications

The use of electromagnetic (EM) waves to transmit information has allowed our society to collaborate and share information on a scale that was unimaginable just a few decades ago. But as with any technology, there are areas where EM-based communications do not function well. For example, underwater and underground communications where EM waves experience high attenuation. This limitation has generated interest in an alternative mode of information transmission, molecular communications. In this thesis, after giving a survey of micro- and macro-scale molecular communications, the two most important aspects of molecular communications are identified: macroscale molecular communications and the experimental analysis of molecular communications. Molecular communication has been dominated so far by interest in the nano-scale, where the application focus is on drug-delivery and DNA communications, etc. Studies in the macro-scale are relatively rare compared to nano- and micro-scale research. This thesis looks closely at macro-scale molecular communication and attempts to improve our understanding of this novel communication paradigm. To achieve this, a mathematical model was developed, based on the advective-diffusion equation (ADE). The model was compared with experimental results, and showed a strong correlation. In addition, a model was developed to simulate molecular communication in both 1D and 3D environments. To generate the modulated chemicals and transmit them in the environment, an inhouse- built odour generator was used, and to detect the chemicals in the environment a mass spectrometer (MS) with a quadrupole mass analyser (QMA) was employed. Mass spectrometers have the ability to distinguish multiple chemicals in the environment concurrently, making them ideal detectors for use in molecular communications. Based on the experimental setup, various aspects of the communication paradigm are investigated in the three main sections. The first section focuses on the fundamental parameters that govern the propagation of molecules in a flow. The second section delves into the communication properties of this new form of information transfer. The final section studies aspects of simultaneous multiple-chemical transmission. Based on this multiple-chemical transmission, modulation methods are developed that exploit this new approach for use in molecular communications

Modulation Analysis in Macro-Molecular Communications

Molecular communication (MC) involves the transmission of information using particles (i.e., molecules). Research into the field has been dominated by micro-scale, and most of the effects of macro-scale communication have yet to be studied. In this paper, the modulation and transmission of MC at macro-scale are investigated. For the transmitter, an in-house-built odor generator was used, and as the detector, a mass spectrometer with a quadrupole mass analyzer was employed. Various 2-level, 4-level, and 8-level modulation schemes were tested experimentally. A simulation framework, developed for the first time, was used for comparison with the experimental results. It was shown that communication can be modeled using a variant of the advection-diffusion equation and that it gives good agreement with the experimental results. A symbol-error-rate (SER) analysis of both the experimental and simulation results was analyzed. It was found that increasing the distance has a detrimental effect on both the channel capacity and the SER, whereas velocity and diffusivity have a decreasing effect on the SER and an increasing effect on the channel capacity. A channel model was developed based on the asymmetric behavior of the communications, and the optimal sampling period was developed that subsequently permitted analysis of the ISI of the communications scheme

Analysis of Multi-Chemical Transmission in the Macro-Scale

Molecular communications (MC) offers an alternative to established methods (i.e., electromagnetic waves), in areas where the latter might prove ineffective (e.g., underwater or underground) due to the environment’s effect on the transmitted signal. In such environments the use of particle (i.e., chemical) based communication may offer a better solution. One of the unique attributes of MC is its ability to employ chemicals as messengers, and transmitting multiple chemicals concurrently offers the potential to significantly increase the information content of the message. In this work, for the first time, the transmission of multiple chemicals with unique mass-to-charge ratios, was studied experimentally and modeled theoretically. Three modulation methods have been proposed and analyzed based on exploiting the uniqueness of the messenger chemicals. Molecular transmission was achieved using an in-house-built odor generator and detection was accomplished by means of a quadrupole mass analyzer. The noise was analyzed for multi-MC and was shown to possess additive white Gaussian noise characteristics with different mean (), but similar variance (2) values. It was shown experimentally that multiple chemical transmission is both feasible and advantageous compared to single chemical transmission and the proposed modulation methods exhibit unique advantages that can be used for different scenarios

A Novel ML-Based Symbol Detection Pipeline for Molecular Communication

Molecular Communication (MC) is the process of sending information by the use of particles instead of electromagnetic (EM) waves. This change in paradigm allows the use of MC in areas where EM transmission is undesirable. These include underground, underwater and even intra-body communications. While this novel paradigm promises new areas for communication, one of the major setbacks is its relatively low throughput caused by the propagation speed. This can be improved by decreasing the symbol duration; however, this can be a detriment to the correct decoding of symbols. This paper proposes a novel symbol detection pipeline to increase the possible throughput without increasing the error rate of the communication. This is based on a machine-learning algorithm for classification tasks using an L-point discrete time moving average filter and a wide range of features. Extensive simulations with long sequences at different signal-to-noise ratio (SNR) values were performed to determine how well the proposed method detects symbols. The results show that our method can detect symbols received when On-Off Keying (OOK) modulations are used with a 10 dB gain, even when transmissions with untrained SNR values occur

A chemical alphabet for macromolecular communications.

Molecular communications in macroscale environments is an emerging field of study driven by the intriguing prospect of sending coded information over olfactory networks. For the first time, this article reports two signal modulation techniques (on–off keying—OOK, and concentration shift keying—CSK) which have been used to encode and transmit digital information using odors over distances of 1–4 m. Molecular transmission of digital data was experimentally investigated for the letter “r” with a binary value of 01110010 (ASCII) for a gas stream network channel (up to 4 m) using mass spectrometry (MS) as the main detection-decoding system. The generation and modulation of the chemical signals was achieved using an automated odor emitter (OE) which is based on the controlled evaporation of a chemical analyte and its diffusion into a carrier gas stream. The chemical signals produced propagate within a confined channel to reach the demodulator—MS. Experiments were undertaken for a range of volatile organic compounds (VOCs) with different diffusion coefficient values in air at ambient conditions. Representative compounds investigated include acetone, cyclopentane, and n-hexane. For the first time, the binary code ASCII (American Standard Code for Information Interchange) is combined with chemical signaling to generate a molecular representation of the English alphabet. Transmission experiments of fixed-width molecular signals corresponding to letters of the alphabet over varying distances are shown. A binary message corresponding to the word “ion” was synthesized using chemical signals and transmitted within a physical channel over a distance of 2 m

The impact of immediate breast reconstruction on the time to delivery of adjuvant therapy: the iBRA-2 study

Background: Immediate breast reconstruction (IBR) is routinely offered to improve quality-of-life for women requiring mastectomy, but there are concerns that more complex surgery may delay adjuvant oncological treatments and compromise long-term outcomes. High-quality evidence is lacking. The iBRA-2 study aimed to investigate the impact of IBR on time to adjuvant therapy. Methods: Consecutive women undergoing mastectomy ± IBR for breast cancer July–December, 2016 were included. Patient demographics, operative, oncological and complication data were collected. Time from last definitive cancer surgery to first adjuvant treatment for patients undergoing mastectomy ± IBR were compared and risk factors associated with delays explored. Results: A total of 2540 patients were recruited from 76 centres; 1008 (39.7%) underwent IBR (implant-only [n = 675, 26.6%]; pedicled flaps [n = 105,4.1%] and free-flaps [n = 228, 8.9%]). Complications requiring re-admission or re-operation were significantly more common in patients undergoing IBR than those receiving mastectomy. Adjuvant chemotherapy or radiotherapy was required by 1235 (48.6%) patients. No clinically significant differences were seen in time to adjuvant therapy between patient groups but major complications irrespective of surgery received were significantly associated with treatment delays. Conclusions: IBR does not result in clinically significant delays to adjuvant therapy, but post-operative complications are associated with treatment delays. Strategies to minimise complications, including careful patient selection, are required to improve outcomes for patients

The Dementias Platform UK (DPUK) Data Portal

Abstract: The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure ‘lab’ using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee