This PDF file contains the front matter associated with SPIE Proceedings Volume 9112, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and Conference Committee listing.

A rapid test for an infectious disease that can be used at point-of-care at a physician’s office, a pharmacy, or in the field is critical for the prompt and appropriate therapeutic intervention. Ultimately by treating infections early on will decrease transmission of the pathogen. In contrast to metabolic diseases or cancer where multiple biomarkers are required, infectious disease targets (e.g. antigen, antibody, nucleic acid) are simple and specific for the pathogen causing the disease. Our laboratory has focused on three major infectious disease; HIV, Tuberculosis, and Malaria. These diseases are pandemic in much of the world thus putting natives, tourists and military personnel at risk for becoming infected, and upon returning to the U.S., transmitting these diseases to their contacts. Our devices are designed to detect antigens, antibodies or nucleic acids in blood or saliva samples in less than 30 minutes. An overview describing the current status of each of the three diagnostic platforms is presented. These microfluidic point-of-care devices will be relatively inexpensive, disposable, and user friendly.

This manuscript describes programmable Bio-Nano-Chip (p-BNC) approach that serves as miniaturized assay platform designed for the rapid detection and quantitation of multiple analytes in biological fluids along with the specific applications in salivary diagnostics intended for the point of need (PON). Included here are oral fluid-based tests for local periodontal disease, systemic cardiac disease and multiplexed tests for drugs of abuse.

Microfluidic tools are advancing capabilities in screening diagnostics for use in near-patient settings. Here, we review three case studies to illustrate the flexibility and analytical power offered by microanalytical tools. We first overview a near-patient tool for detection of protein markers found in cerebrospinal fluid (CSF), as a means to identify the presence of cerebrospinal fluid in nasal mucous – an indication that CSF is leaking into the nasal cavity. Microfluidic design allowed integration of several up-stream preparatory steps and rapid, specific completion of the human CSF protein assay. Second, we overview a tear fluid based assay for lactoferrin, a protein produced in the lacrimal gland, then secreted into tear fluid. Tear Lf is a putative biomarker for primary SS. A critical contribution of this and related work being measurement of Lf, even in light of well-known and significant matrix interactions and losses during the tear fluid collection and preparation. Lastly, we review a microfluidic barcode platform that enables rapid measurement of multiple infectious disease biomarkers in human sera. The assay presents a new approach to multiplexed biomarker detection, yet in a simple straight microchannel – thus providing a streamlined, simplified microanalytical platform, as is relevant to robust operation in diagnostic settings. We view microfluidic design and analytical chemistry as the basis for emerging, sophisticated assays that will advance not just screening diagnostic technology, but confirmatory assays, sample preparation and handling, and thus introduction and utilization of new biomarkers and assay formats.

Human saliva contains a rich mixture of biomolecules. Proteins are a major component of this mixture. Given their role as the molecular effectors within biological systems, ranging from catalysis to transport to structure, proteins have great potential as biomarkers of health and disease. The ability to collect these salivary biomarkers easily using non-invasive means makes saliva proteins even more attractive for diagnostic applications. Thousands of proteins are now to be known to be present in human saliva – discovered using proteomic technologies. Emerging technologies are now making it possible to go beyond large-scale cataloging of salivary proteins. These include approaches to catalog protein contributions from the community of microorganisms residing in the oral cavity (metaproteomics) that may reflect the health state of the human host. New mass spectrometry-based proteomics methods are also emerging, shifting the emphasis from large-scale discovery experiments to hypothesis-driven assays for profiling proteins of interest within saliva, enabling validation of their association with specific health conditions. This paper provides a brief overview of efforts to catalog the proteome of human saliva. Recent developments making possible characterization of the metaproteome of human saliva will be discussed, and technologies driving new mass spectrometry-based assays for targeted analysis of proteins within complex samples, such as saliva.

Gluten proteins contained in the cereals barley, rye and wheat cause an inflammatory disorder called celiac disease in genetically predisposed individuals. Certain immunogenic gluten domains are resistant to degradation by mammalian digestive enzymes. Enzymes with the ability to target such domains are potentially of clinical use. Of particular interest are gluten-degrading enzymes that would be naturally present in the human body, e.g. associated with resident microbial species. This manuscript describes a selective gluten agar approach and four enzyme activity assays, including a gliadin zymogram assay, designed for the selection and discovery of novel gluten-degrading microorganisms from human biological samples. Resident and harmless bacteria and/or their derived enzymes could potentially find novel applications in the treatment of celiac disease, in the form of a probiotic agent or as a dietary enzyme supplement.

With the advent of an increased emphasis on the potential to utilize biomarkers in saliva for systemic diseases, the issue of existing oral disease is an important consideration that could adversely affect the interpretation of diagnostic results obtained from saliva. We addressed the question does a patient’s oral inflammation status confound biomarker levels used in diagnosis of acute myocardial infarction (AMI). The results demonstrated that multiple serum biomarkers and a few salivary biomarkers reflected the cardiac event. Importantly, oral health of the individual had minimal impact on the validity of the serum or salivary biomarker effectiveness.

Traumatic brain injury (TBI) and Post Traumatic Stress Disorder (PTSD) are common conditions. In Iraq and Afghanistan, explosive blast related TBI became prominent among US service members but the vast majority of TBI was still due to typical causes such as falls and sporting events. PTS has long been a focus of the US military mental health providers. Combat Stress Teams have been integral to forward deployed units since the beginning of the Global War on Terror. Military medical management of disease and injury follows standard of care clinical practice guidelines (CPG) established by civilian counterparts. However, when civilian CPGs do not exist or are not applicable to the military environment, new practice standards are created. Such is the case for mild TBI. In 2009, the VA-DoD CPG for management of mild TBI/concussion was published and a system-wide clinical care program for mild TBI/concussion was introduced. This was the first large scale effort on an entire medical care system to address all severities of TBI in a comprehensive organized way. In 2010, the VA-DoD CPG for management of PTSD was published. Nevertheless, both TBI and PTS are still incompletely understood. Investment in terms of money and effort has been committed by the DoD to their study. The Defense and Veterans Brain Injury Center, National Intrepid Center of Excellence and the Defense Centers of Excellence for Psychological Health and Traumatic Brain Injury are prominent examples of this effort. These are just beginnings, a work in progress ready to leverage advances made scientifically and always striving to provide the very best care to its military beneficiaries.

Cranial Nerve NonInvasive NeuroModulation (CN-NINM) is a primary and complementary multi-targeted rehabilitation therapy that appears to initiate the recovery of multiple damaged or suppressed brain functions affected by neurological disorders. It is deployable as a simple, home-based device (portable neuromodulation stimulator, or PoNS^TM) and training regimen following initial patient training in an outpatient clinic. It may be easily combined with many existing rehabilitation therapies, and may reduce or eliminate the need for more aggressive invasive procedures or possibly decrease total medication intake.

CN-NINM uses sequenced patterns of electrical stimulation on the tongue. Our hypothesis is that CN-NINM induces neuroplasticity by noninvasive stimulation of two major cranial nerves: trigeminal (CN-V), and facial (CN-VII). This stimulation excites a natural flow of neural impulses to the brainstem (pons varolli and medulla), and cerebellum, to effect changes in the function of these targeted brain structures, extending to corresponding nuclei of the brainstem.

CN-NINM represents a synthesis of a new noninvasive brain stimulation technique with applications in physical medicine, cognitive, and affective neurosciences. Our new stimulation method appears promising for treatment of a full spectrum of movement disorders, and for both attention and memory dysfunction associated with traumatic brain injury.

Crewmembers of current and future long duration spaceflights require drugs to overcome the deleterious effects of weightlessness, sickness and injuries. Unfortunately, recent studies have shown that some of the drugs currently used may degrade more rapidly in space, losing their potency well before their expiration dates. To complicate matters, the degradation products of some drugs can be toxic. Consequently there is a need for an analyzer that can determine if a drug is safe at the time of use, as well as to monitor and understand space-induced degradation, so that drug types, formulations, and packaging can be improved. Towards this goal we have been investigating the ability of Raman spectroscopy to monitor and quantify drug degradation. Here we present preliminary data by measuring acetaminophen, and its degradation product, p-aminophenol, as pure samples, and during forced degradation reactions.

Major decisions regarding life and death are routinely made on the modern battlefield, where visual function of the individual soldier can be of critical importance in the decision-making process. Glasses in the combat environment have considerable disadvantages: degradation of short term visual performance can occur as dust and sweat accumulate on lenses during a mission or patrol; long term visual performance can diminish as lenses become increasingly scratched and pitted; during periods of intense physical trauma, glasses can be knocked off the soldier’s face and lost or broken. Although refractive surgery offers certain benefits on the battlefield when compared to wearing glasses, it is not without potential disadvantages. As a byproduct of refractive surgery, elevated optical aberrations can be induced, causing decreases in contrast sensitivity and increases in the symptoms of glare, halos, and starbursts. Typically, these symptoms occur under low light level conditions, the same conditions under which most military operations are initiated. With the advent of wavefront aberrometry, we are now seeing correction not only of myopia and astigmatism but of other, smaller optical aberrations that can cause the above symptoms. In collaboration with the Warfighter Refractive Eye Surgery Program and Research Center (WRESP-RC) at Fort Belvoir and Walter Reed National Military Medical Center (WRNMMC), the overall objective of this study is to determine the impact of wavefront guided (WFG) versus wavefront-optimized (WFO) photorefractive keratectomy (PRK) on military task visual performance. Psychophysical perception testing was conducted before and after surgery to measure each participant’s performance regarding target detection and identification using thermal imagery. The results are presented here.

Raman spectra were taken from whole sheep’s blood with varying levels of acetylcholinesterase (AChE) inhibition using 229 and 532 nm laser excitation wavelengths. AChE levels were inhibited using the organophosphates malathion, paraoxon-ethyl, and octamethyldiphosphoramide and confirmed using the Ellman method. This AChE activity level was investigated with the Raman spectra and analyzed using a partial least squares calibration and cross validation to determine if the AChE activity could be predicted from the Raman spectrum. Correlation scores of 0.78 and 0.26 between the measured and predicted AChE activity were observed using 229 and 532 nm excitation, respectively. A estimate limit of detection was found to be approximately 0.01 ΔA/min.

Hyperspectral imaging is a potential noninvasive technology for detecting, separating and identifying various substances. In the forensic and military medicine and other CBRNE related use it could be a potential method for analyzing blood and for scanning other human based fluids. For example, it would be valuable to easily detect whether some traces of blood are from one or more persons or if there are some irrelevant substances or anomalies in the blood. This article represents an experiment of separating four persons' blood stains on a white cotton fabric with a SWIR hyperspectral camera and FT-NIR spectrometer. Each tested sample includes standardized 75 _l of 100 % blood. The results suggest that on the basis of the amount of erythrocytes in the blood, different people's blood might be separable by hyperspectral analysis. And, referring to the indication given by erythrocytes, there might be a possibility to find some other traces in the blood as well. However, these assumptions need to be verified with wider tests, as the number of samples in the study was small. According to the study there also seems to be several biological, chemical and physical factors which affect alone and together on the hyperspectral analyzing results of blood on fabric textures, and these factors need to be considered before making any further conclusions on the analysis of blood on various materials.

A portable analytical system for the characterization of liquid environmental samples and beverages in food control was realized. The key element is the implementation of contactless conductivity detection on lab-on-a-chip basis ensuring the system to be operated in a label free mode. Typical target molecules such as small ionic species like Li⁺, Na⁺, K⁺, SO4 2^- or NO₃^-, organic acids in wine whose concentration and ratio to each other documents the wine quality, or caffeine or phosphate in coke were detected. Results from sample matrices like various beverages as water, cola, tea, wine and milk, water from heaters, environmental samples and blood will be presented.

Once viewed solely as a tool to analyse biomolecular interactions, biosensors are gaining widespread interest for diagnostics, biological defense, environmental and quality assurance in agriculture/food industries. Advanced micro fabrication techniques have facilitated integration of microfluidics with sensing functionalities on the same chip making system automation more convenient1. Biosensor devices relying on lab-on-a-chip technologies and nanotechnology has attracted much of attention in recent years for biological defense research and development. However, compared with the numerous publications and patents available, the commercialization of biosensors technology has significantly lagged behind the research output. This paper reviews the reasons behind the slow commercialisation of biosensors with an insight to the critical stages of a biosensor development from the sensor chip fabrication to surface chemistry applications and nanotechnology applications in sensing with case studies. In addition, the paper includes the description of a new biodetection platform based on Real-time Electrochemical Profiling^TM (REP^TM) that comprises novel electrode arrays and nanoparticle based sensing. The performance of the REP^TM platform has been tested for the detection of Planktothrix agardhii, one of the toxic bloom-forming cyanobacteria, usually found in shallow fresh water sources that can be used for human consumption. The optimised REP^TM assay allowed the detection of P. agardhii DNA down to 6 pM. This study, showed the potential of REP^TM as a new biodetection platform for toxic bacteria and hence further studies will involve the development of a portable multi-analyte biosensor based on REP^TM technology for on-site testing.

Peptide-based biological recognition elements are valuable tools for detection in biodefense systems. The utilization of such biomolecules for detection purposes relies on the ability to immobilize them on the surface of a detection platform in a predictable and reliable manner that facilitates target binding. Numerous immobilization methods have been used to improve the performance of peptide-based biosensors; however, the molecular details of how surface attachment affects structure and activity require further investigation to establish general approaches for obtaining consistent sensor surfaces. This has been largely due to the lack of analytical techniques. Using surface spectroscopy techniques, we examined the secondary structure of peptides tethered to solid support. Different tethering parameters were investigated by substituting a cysteine residue to the N-terminus or C-terminus in cationic antimicrobial peptides, and its effects on antimicrobial activity against gram-negative bacteria, E. coli. Spectroscopic analysis showed that surface immobilization drives transition of peptides secondary structures, resulting in different interfacial behaviors that may influence the secondary structure of the peptides once they interact with the bacterial cells. We have begun to gain insight into how surface attachment may have direct implications for peptide presentation and function and is an important advance in preparing a robust sensing interface.

Peripheral Quantitative Computed Tomography (pQCT) is a non-invasive imaging technology that is well-suited for quantification of bone structural and material properties. Because of its increasing use and applicability, the development of automated quantification methods for pQCT images is an appealing field of research. In this paper we introduce a software system for hard and soft tissue quantification in the lower leg using pQCT imaging data. The main stages of our approach are the segmentation and identification of bone, muscle and fat, and the computation of densitometric and geometric variables of each regional tissue type. Our system was validated against reference area and densitometric measurements over a set of test images and produced encouraging results.

The reactive sensing principle applied to hybrid plasmonic whispering gallery mode biosensor has recently demonstrated detection of individual protein cancer markers. The rough surface of a gold nanoparticle affixed to the resonator surface acts like a nanoscopic antenna, significantly boosts the local electric field within the cavity mode. Adsorption of a target protein onto this nanoscopic antenna results in an enhanced response of the resonator system to the binding event. We have demonstrated detection of individual protein molecules (66 kDa) with good signal-to-noise (S/N > 10), and project that detection of proteins as small as 5 kDa are possible.

A novel miniature dual cavity Fabry–Perot sensor is presented for simultaneous measurements of pressure and temperature in this work. Both of the pressure and the temperature sensing cavities are fabricated by using a single step UV molding process which is simple, cost-effective, and safe procedure. The pressure sensor is composed of an UV molded cavity covered by a metal/polymer composite diaphragm for a high pressure sensitivity with a miniature sensor size. The temperature sensor is made of a short segment of UV curable polymer, which renders a high temperature sensitivity due to the material’s large thermal expansion. By exploiting the material characteristic of the polymer around 90% of size-reduction could be achieved with 88.5% of temperature sensitivity of the previously reported sensor made of pure silica. The overall sensor size is around 150 μm in diameter and 55 μm in length. Experimental studies show that the sensor has a good linearity over a pressure range of 1.0 to 4.0 psi with a pressure sensitivity of 0.137 μm/psi at 28 °C, and a temperature range of 28.0 °C to 42.4 °C with a temperature sensitivity of 0.0026 μm/◦C. The sensor can be applied to many biomedical applications that require pressure and temperature simultaneous measurements with minimum intrusiveness.

Experimental measurements conducted in the laboratory, involving hyperspectral analysis of water samples taken from public water resources in the New York City metro area, have motivated a reevaluation of issues concerning the potential application of this type of analysis for water monitoring, treatment and evaluation prior to filtration. One issue concerns hyperspectral monitoring of contaminants with respect to types and relative concentrations. This implies a need for better understanding the statistical profiles of water contaminants in terms of spatial-temporal distributions of electromagnetic absorption spectra ranging from the ultraviolet to infrared, which are associated with specific water resources. This issue also implies the need for establishing correlations between hyperspectral signatures and types of contaminants to be found within specific water resources. Another issue concerns the use of absorption spectra for determining changes in chemical and physical characteristics of contaminants after application of water treatments in order to determine levels of toxicity with respect to the environment.

The dynamic sediment distribution in large rivers with dams constructed has often been the focus of considerable attention because of their potential adverse environmental impacts. Sedimentation modeling and environmental assessment of man-made projects are often hindered by the lack of sediment measurements with spatial details. This study aimed to investigate the method used to estimate the suspended sediment concentrations (SSCs) from on-site spectral measurements. The study investigated the spectral signature of river water from the natural channel and Sanmenxia Reservoir on the Yellow River. A field spectral survey was conducted through on-site spectral measurements by using a spectroradimeter and SSC estimation by sampling. Reectance at 750 nm to 950 nm, with all correlation coefficient (r) between SSC and reectance > 0:7, seemed to be the appropriate range for SSC estimation. Simulated Landsat Enhanced Thematic Mapper Plus Band 4 (760 nm to 900 nm) was used to build the single band model for estimating SSC. The results confirmed that the exponential model based on the relationship between SSC and reectance (R² = 0:92, root mean square error [RMSE]= 0:241 g=l) was better than the linear model between reectance and logarithm-transformed SSC (R² = 0:90, RMSE = 0:310 g=l). We also applied the Spectral Mixing Algorithm (SMA) from the tank experiment to the on-site spectral measurements. The result showed that the SMA models performed as well as the single band exponential model (R² = 0:86, RMSE = 0:280 g=l). However, the valid range for application was improved from 1:99 g=l to 347 g=l. This study could provide critical instructional assistance for estimating SSC directly from remote sensing data.

Malaria and dengue fever are the two most common mosquito-transmitted diseases, leading to millions of serious illnesses and deaths each year. Because the mosquito vectors are sensitive to environmental conditions such as temperature, precipitation, and humidity, it is possible to map areas currently or imminently at high risk for disease outbreaks using satellite remote sensing. In this paper we propose the development of an operational geospatial system for malaria and dengue fever early warning; this can be done by bringing together geographic information system (GIS) tools, artificial neural networks (ANN) for efficient pattern recognition, the best available ground-based epidemiological and vector ecology data, and current satellite remote sensing capabilities.
We use Vegetation Health Indices (VHI) derived from visible and infrared radiances measured by satellite-mounted Advanced Very High Resolution Radiometers (AVHRR) and available weekly at 4-km resolution as one predictor of malaria and dengue fever risk in Bangladesh. As a study area, we focus on Bangladesh where malaria and dengue fever are serious public health threats. The technology developed will, however, be largely portable to other countries in the world and applicable to other disease threats. A malaria and dengue fever early warning system will be a boon to international public health, enabling resources to be focused where they will do the most good for stopping pandemics, and will be an invaluable decision support tool for national security assessment and potential troop deployment in regions susceptible to disease outbreaks.

Biochemical pathways characterize various biochemical reaction schemes that involve a set of species and the manner in which they are connected. Determination of schematics that represent these pathways is an important task in understanding metabolism and signal transduction. Examples of these Pathways are: DNA and protein synthesis, and production of several macro-molecules essential for cell survival. A sustained feedback mechanism arises in gene expression and production of mRNA that lead to protein synthesis if the protein so synthesized serves as a transcription factor and becomes a repressor of the gene expression. The cellular regulations are carried out through biochemical networks consisting of reactions and regulatory proteins.

Systems biology is a relatively new area that attempts to describe the biochemical pathways analytically and develop reliable mathematical models for the pathways. A complete understanding of chemical reaction kinetics is prohibitively hard thanks to the nonlinear and highly complex mechanisms that regulate protein formation, but attempting to numerically solve some of the governing differential equations seems to offer significant insight about their biochemical picture. To validate these models, one can perform simple experiments in the lab.

This paper introduces fundamental ideas in biochemical signaling and attempts to take first steps into the understanding of biochemical oscillations. Initially, the two-pool model of calcium is used to describe the dynamics behind the oscillations. Later we present some elementary results showing biochemical oscillations arising from solving differential equations of Elowitz and Leibler using MATLAB software.

With the growing use of wireless devices in almost all day-to-day activities, exposure to radio-frequency radiation has become an immediate health concern. It is imperative that the effects of such radiation not only on humans, but also on other organisms be well understood. In particular, it is critical to understand if RF radiation has any bearing on the gene expression during embryonic development, as this is a crucial and delicate phase for any organism. Owing to possible effects that RF radiation may have on gene expression, it is essential to explore the carcinogenic or teratogenic properties that it may show. This study observed the effects of RF radiation emitted from a cellular telephone on the embryonic development of zebra fish. The expression of the gene shha plays a key role in the early development of the fish. This gene has homologs in humans as well as in other model organisms. Additionally, several biomarkers indicative of cell stress were examined: including lactate dehydrogenase (LDH), superoxide dismutase (SOD), and lipid peroxidation (LPO). Results show a significant decrease in the expression of shha, a significant decrease in LDH activity. There was no significant increase in SOD and LPO activity. No morphological abnormalities were observed in the developing embryos. At present, these results indicate that exposure to cell phone radiation may have a suppressive effect on expression of shha in D. rerio, though such exposure does not appear to cause morphological detriments. More trials are underway to corroborate these results.

We developed a Raman lidar with ultraspectral resolution for automatic airborne monitoring of pipeline leaks and for oil and gas exploration. Test flights indicate that a sensitivity of 6 ppm for methane and 2 ppm for hydrogen sulfide has been reached for leakage detection. The lidar is based on the CARS method with a Ti:Sapphire pump laser and a frequencydoubled YLF:Nd probe beam whose frequency is displaced by a BBO crystal. In ground-based experiments, a detection level of 3 to 10 molecules has been reached.

Recently, a mathematical model of pandemic influenza was proposed including typical control strategies such as antivirals, vaccination and school closure; and considering explicitly the effects of immunity acquired from the early outbreaks on the ulterior outbreaks of the disease. In such model the algebraic expression for the basic reproduction number (without control strategies) and the effective reproduction number (with control strategies) were derived and numerically estimated. A drawback of this model of pandemic influenza is that it ignores the effects of the differential susceptibility due to immunosuppression and the effects of the complexity of the actual contact networks between individuals. We have developed a generalized model which includes such effects of heterogeneity. Specifically we consider the influence of the air network connectivity in the spread of pandemic influenza and the influence of the immunosuppresion when the population is divided in two immune classes. We use an algebraic expression, namely the Tutte polynomial, to characterize the complexity of the contact network. Until now, The influence of the air network connectivity in the spread of pandemic influenza has been studied numerically, but not algebraic expressions have been used to summarize the level of network complexity. The generalized model proposed here includes the typical control strategies previously mentioned (antivirals, vaccination and school closure) combined with restrictions on travel. For the generalized model the corresponding reproduction numbers will be algebraically computed and the effect of the contact network will be established in terms of the Tutte polynomial of the network.

We analyze a mathematical model for the transmission of cholera. The model is already defined and involves variables such as the pathogen agent, which in this case is the bacterium Vibrio cholera, and the human population. The human population is divided into three classes: susceptible, infectious and removed. Using Computer Algebra, specifically Maple we obtain two equilibrium states: the disease free state and the endemic state. Using Maple it is possible to prove that the disease free state is locally asymptotically stable if and only if R0 < 1. Using Maple it is possible to prove that the endemic equilibrium state is locally stable when it exists, it is to say when R0 > 1. Using the package Red-Log of the Computer algebra system Reduce and the SMT-Solver Z3Py it is possible to obtain numerical conditions for the model. The formula for the basic reproductive number makes a synthesis with all epidemic parameters in the model. Also it is possible to make numerical simulations which are very illustrative about the epidemic patters that are expected to be observed in real situations. We claim that these kinds of software are very useful in the analysis of epidemic models given that the symbolic computation provides algebraic formulas for the basic reproductive number and such algebraic formulas are very useful to derive control measures. For other side, computer algebra software is a powerful tool to make the stability analysis for epidemic models given that the all steps in the stability analysis can be made automatically: finding the equilibrium points, computing the jacobian, computing the characteristic polynomial for the jacobian, and applying the Routh-Hurwitz theorem to the characteristic polynomial. Finally, using SMT-Solvers is possible to make automatically checks of satisfiability, validity and quantifiers elimination being these computations very useful to analyse complicated epidemic models.

Computational Algebraic Geometry is applied to the analysis of various epidemic models for Schistosomiasis and Dengue, both, for the case without control measures and for the case where control measures are applied. The models were analyzed using the mathematical software Maple. Explicitly the analysis is performed using Groebner basis, Hilbert dimension and Hilbert polynomials. These computational tools are included automatically in Maple. Each of these models is represented by a system of ordinary differential equations, and for each model the basic reproductive number (R₀) is calculated. The effects of the control measures are observed by the changes in the algebraic structure of R₀, the changes in Groebner basis, the changes in Hilbert dimension, and the changes in Hilbert polynomials. It is hoped that the results obtained in this paper become of importance for designing control measures against the epidemic diseases described. For future researches it is proposed the use of algebraic epidemiology to analyze models for airborne and waterborne diseases.

Tutte polynomials are used to characterize the dynamic and topology of the sexual contact networks, in which pathogens are transmitted as an epidemic. Tutte polynomials provide an algebraic characterization of the sexual contact networks and allow the projection of spread control strategies for sexual transmission diseases. With the usage of Tutte polynomials, it allows obtaining algebraic expressions for the basic reproductive number of different pathogenic agents. Computations are done using the computer algebra software Maple, and it’s GraphTheory Package. The topological complexity of a contact network is represented by the algebraic complexity of the correspondent polynomial. The change in the topology of the contact network is represented as a change in the algebraic form of the associated polynomial. With the usage of the Tutte polynomials, the number of spanning trees for each contact network can be obtained. From the obtained results in the polynomial form, it can be said that Tutte polynomials are of great importance for designing and implementing control measures for slowing down the propagation of sexual transmitted pathologies. As a future research line, the analysis of weighted sexual contact networks using weighted Tutte polynomials is considered.

A model to determinate the reproductive basic number, detonated R_o, for the case of population with heterogeneity in sexual activity and proportionate mixing is solved using computer algebra and SMT solvers. Specifically Maple and Z3 were used. The code for the solution of the model was written in Z3-Python, but it can also be played by Z3-SMT-Lib. R_o represents an algebraic synthesis of every epidemiological parameter. Numerical simulations were done to prove the effectiveness of the model and the code. The algebraic structure of R_o suggests the possible control measurements that should be implemented to avoid the propagation of the sexual transmitted diseases. The obtained results are important on the computational epidemiology field. As a future investigation, it is suggested to apply the STM solvers to analyze models for other kinds of epidemic diseases.

A magnetic resonance is an image obtained by means of an imaging test that uses magnets and radio waves to create body images, however, in some images it’s difficult to recognize organs or foreign agents present in the body. With these Bessel filters the objective is to significantly increase the resolution of magnetic resonance images taken to make them much clearer in order to detect anomalies and diagnose the illness. As it’s known, Bessel filters appear to solve the Schrödinger equation for a particle enclosed in a cylinder and affect the image distorting the colors and contours of it, therein lies the effectiveness of these filters, since the clear outline shows more defined and easy to recognize abnormalities inside the body.

The angiograms are frequently used to find anomalies in the blood vessels. Hence, for improving the quality of the images with an angiogram, a Morse filter will be implemented (based on the model of the Morse Potential) in a brain’s vessels angiogram using both softwares Maple ^® and ImageJ ^®. It will be shown the results of applying a Morse filter to an angiogram of the brain vessels. First, the image was processed with ImageJ using the plug-in Anisotropic Diffusion 2D and then, the filter was implemented. As it is illustrated in the results, the edges of the stringy elements are emphasized. Particularly, this is very useful in the medical image processing of blood vessels, like angiograms, due to the narrowing or obstruction which may be caused by illness like aneurysms, thrombosis or other diseases.

Some special functions of the mathematical physics are using to obtain a mathematical model of the propagation of airborne diseases. In particular we study the propagation of tuberculosis in closed rooms and we model the propagation using the error function and the Bessel function. In the model, infected individual emit pathogens to the environment and this infect others individuals who absorb it.

The evolution in time of the concentration of pathogens in the environment is computed in terms of error functions. The evolution in time of the number of susceptible individuals is expressed by a differential equation that contains the error function and it is solved numerically for different parametric simulations. The evolution in time of the number of infected individuals is plotted for each numerical simulation. On the other hand, the spatial distribution of the pathogen around the source of infection is represented by the Bessel function K0.

The spatial and temporal distribution of the number of infected individuals is computed and plotted for some numerical simulations. All computations were made using software Computer algebra, specifically Maple. It is expected that the analytical results that we obtained allow the design of treatment rooms and ventilation systems that reduce the risk of spread of tuberculosis.

A malaria model with differential susceptibility is analyzed using the optimal control technique. In the model the human population is classified as susceptible, infected and recovered. Susceptibility is assumed dependent on genetic, physiological, or social characteristics that vary between individuals. The model is described by a system of differential equations that relate the human and vector populations, so that the infection is transmitted to humans by vectors, and the infection is transmitted to vectors by humans. The model considered is analyzed using the optimal control method when the control consists in using of insecticide-treated nets and educational campaigns; and the optimality criterion is to minimize the number of infected humans, while keeping the cost as low as is possible. One first goal is to determine the effects of differential susceptibility in the proposed control mechanism; and the second goal is to determine the algebraic form of the basic reproductive number of the model. All computations are performed using computer algebra, specifically Maple. It is claimed that the analytical results obtained are important for the design and implementation of control measures for malaria. It is suggested some future investigations such as the application of the method to other vector-borne diseases such as dengue or yellow fever; and also it is suggested the possible application of free software of computer algebra like Maxima.

Some images corresponding to a diffuse axonal injury (DAI) are processed using several quantum filters such as Hermite Weibull and Morse. Diffuse axonal injury is a particular, common and severe case of traumatic brain injury (TBI). DAI involves global damage on microscopic scale of brain tissue and causes serious neurologic abnormalities. New imaging techniques provide excellent images showing cellular damages related to DAI. Said images can be processed with quantum filters, which accomplish high resolutions of dendritic and axonal structures both in normal and pathological state. Using the Laplacian operators from the new quantum filters, excellent edge detectors for neurofiber resolution are obtained. Image quantum processing of DAI images is made using computer algebra, specifically Maple. Quantum filter plugins construction is proposed as a future research line, which can incorporated to the ImageJ software package, making its use simpler for medical personnel.