Engineering Science Research Articles

Impact of digital technologies on the development of insurance activities

Innovative technologies have rapidly entered the life of people and society as a whole, particularly in the economic sphere. One of the economic sectors where the need to utilize digital technologies prevails is insurance. Innovative technologies contribute to the improvement of all processes in the insurance market. The positive development of insurance largely depends on the introduction and use of digital technologies. This article is devoted to analyzing and evaluating the impact of digital technologies on the development of insurance activities. This article examines the impact of digital technologies on insurance activities. The main objective is to describe the main technologies themselves and their application in risk assessment, loss prevention and improvement of insurance services processes. In order to achieve this task, we have reviewed sources on the topic, considered projects and studies in the field of application of digital technologies in insurance activities, and analyzed the data obtained. The work resulted in the presentation of digital science technologies used in the operations of insurance companies, such as artificial intelligence, internet of things, blockchain, and how these technologies can be applied in risk assessment, loss prevention and improvement of insurance service processes. The results can be used by insurance companies applying various digital technologies in their operations, namely online sales of insurance policies, data collection and analysis, artificial intelligence and machine learning to develop the insurance market.

Deep Learning of Transition Probability Densities for Stochastic Asset Models with Applications in Option Pricing

Transition probability density functions (TPDFs) are fundamental to computational finance, including option pricing and hedging. Advancing recent work in deep learning, we develop novel neural TPDF generators through solving backward Kolmogorov equations in parametric space for cumulative probability functions. The generators are ultra-fast, very accurate and can be trained for any asset model described by stochastic differential equations. These are “single solve,” so they do not require retraining when parameters of the stochastic model are changed (e.g., recalibration of volatility). Once trained, the neural TDPF generators can be transferred to less powerful computers where they can be used for e.g. option pricing at speeds as fast as if the TPDF were known in a closed form. We illustrate the computational efficiency of the proposed neural approximations of TPDFs by inserting them into numerical option pricing methods. We demonstrate a wide range of applications including the Black-Scholes-Merton model, the standard Heston model, the SABR model, and jump-diffusion models. These numerical experiments confirm the ultra-fast speed and high accuracy of the developed neural TPDF generators. This paper was accepted by Kay Giesecke, finance. Funding: H. Su received research funding support from Nottingham Business School at Nottingham Trent University. M. V. Tretyakov was supported by the Engineering and Physical Sciences Research Council [Grant EP/X022617/1]. D. P. Newton received research funding support from the School of Management at Bath University. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.01448 .

Stability, modulation instability and traveling wave solutions of (3+1)dimensional Schrödinger model in physics

The nonlinear Schrödinger equation is one of the most important physical model in optical fiber theory for comprehension of the fluctuations of optical bullet development. In this study, the exact bullet solutions for the (3+1)-dimensional Schrödinger equation which demonstrate the bullet behaviours in optical fibers can be accumulated through the Sardar sub-equation method and the unified method. The applied strategies may retrieve several kinds of optical bullet solutions within one frameworks as well as is quite simple and reliable. Mathematica are utilised for describing the dynamics of different wave structures as 3D, 2D, and contour visualisations for a given set of parameters. As a result, we are able to develop a variety of travelling wave structures namely the periodic, singular and V shaped soliton wave solutions. The stability analysis for the derived results is analysed efficiently while the modulation instability for the governing model has also been studied to demonstrate the reliability of the research. The approaches implemented here works perfectly and can be extended to deal with many advanced models in contemporary areas of science and engineering. The solutions attain by using these techniques are robust, unique and straight forward and has applications in different fields of physics, engineering and mathematical science. Specially physical applications of these obtain results are in the transmission of data in optical fibers. We also add the graphics for the better understanding of the attain solutions behaviour.

From Nature to Technology: Exploring the Potential of Plant-Based Materials and Modified Plants in Biomimetics, Bionics, and Green Innovations.

This review explores the extensive applications of plants in areas of biomimetics and bioinspiration, highlighting their role in developing sustainable solutions across various fields such as medicine, materials science, and environmental technology. Plants not only serve essential ecological functions but also provide a rich source of inspiration for innovations in green nanotechnology, biomedicine, and architecture. In the past decade, the focus has shifted towards utilizing plant-based and vegetal waste materials in creating eco-friendly and cost-effective materials with remarkable properties. These materials are employed in making advancements in drug delivery, environmental remediation, and the production of renewable energy. Specifically, the review discusses the use of (nano)bionic plants capable of detecting explosives and environmental contaminants, underscoring their potential in improving quality of life and even in lifesaving applications. The work also refers to the architectural inspirations drawn from the plant world to develop novel design concepts that are both functional and aesthetic. It elaborates on how engineered plants and vegetal waste have been transformed into value-added materials through innovative applications, especially highlighting their roles in wastewater treatment and as electronic components. Moreover, the integration of plants in the synthesis of biocompatible materials for medical applications such as tissue engineering scaffolds and artificial muscles demonstrates their versatility and capacity to replace more traditional synthetic materials, aligning with global sustainability goals. This paper provides a comprehensive overview of the current and potential uses of living plants in technological advancements, advocating for a deeper exploration of vegetal materials to address pressing environmental and technological challenges.

Meaning, Concept and Application of Bioinformatics

Bioinformatics, originating from the term coined in 1979 by Paulien Hogeweg and Ben Hesper, is a burgeoning interdisciplinary field at the nexus of biology, computer science, and information technology. It encompasses the collection, classification, storage, and analysis of vast biological datasets using computational methods, aiming to unravel the complexities of biological systems. This abstract provides a comprehensive overview of bioinformatics, emphasizing its definition, scope, branches, aims, research areas, databases, and applications, particularly highlighting its role in drug discovery through structural bioinformatics. Bioinformatics integrates diverse branches such as computational biology, genomics, proteomics, structural biology, systems biology, pharmacogenomics, and bioprogramming. Each branch applies mathematical modeling, molecular interactions analysis, or genomic data interpretation to advance understanding in biology and medicine. Key aims include applying advanced computational technologies to biological problems, presenting complex data clearly, and providing robust statistical tools for genomic analysis. The field also fosters collaborations across academic, commercial, and government sectors to leverage resources and expertise. Research areas span computational evolutionary analysis, genome annotation, gene expression analysis, cancer mutation studies, and comparative genomics, illuminating disease mechanisms and evolutionary relationships. Bioinformatics databases play a crucial role by storing and organizing biological data. Primary repositories like GenBank and the Protein Data Bank (PDB), secondary databases such as SWISS-Prot, and specialized databases support research and clinical applications by providing access to genomic, proteomic, and structural information. In drug discovery, structural bioinformatics techniques like homology modeling, molecular docking, and simulations predict protein structures, analyze interactions, and aid in designing therapies. These computational methods accelerate drug development, optimize drug-target interactions, and reduce costs associated with bringing new drugs to market. Overall, bioinformatics drives innovation in biological sciences and healthcare by leveraging computational methods to interpret biological data. As technology advances, bioinformatics will continue to play a pivotal role in addressing global health challenges, advancing personalized medicine, and facilitating groundbreaking discoveries in biology and medicine. The evolving field of bioinformatics promises continued growth and impact, shaping the future of biological research and its applications in improving human health and understanding the natural world. Keywords: Bioinformatics, Computational biology, Structural bioinformatics, Drug discovery, Genomics.

Effect of Lattice Structure on Mechanical Properties of Ti-6Al-4V-Ta Alloy for Improved Antibacterial Properties

This study investigates the effect of a tantalum addition and lattice structure design on the mechanical and antibacterial properties of Ti-6Al-4V alloys. TPMS lattice structures, such as Diamond, Gyroid, and Primitive, were generated by MSLattice 1.0 software and manufactured using laser powder bed fusion (LPBF). The results indicate that Gyroid and Primitive structures at a 40% density exhibit superior ultimate compressive strength, which closely emulates bone’s biomechanical properties. To be precise, adding 8% tantalum (Ta) significantly increases the material’s elastic modulus and energy absorption, enhancing the material’s suitability for dynamic load-bearing implants. Nevertheless, the Ta treatment reduces bacterial biofilm formation, especially on Gyroid surfaces, suggesting its potential for infection management. Overall, all findings provide critical insights into the development of advanced implant materials, contributing to the fields of additive manufacturing, materials science, and biomedical engineering and paving the way for improved patient outcomes in orthopedic applications.

Dielectric property exploration in kesterite nanolattice: Insights from Monte Carlo Simulations

This study investigates the dielectric behavior of a kesterite nanolattice using Monte Carlo simulations. The findings reveal the influence of exchange coupling interactions and the external electric field on the dielectric properties of the kesterite nanolattice. Furthermore, the results indicate a nearly linear correlation between the blocking temperature and both the exchange coupling interactions and the external electric field, underscoring their crucial role in manipulating the phase transitions of the nanolattice. These insights enhance our understanding of the kesterite nanolattice's performance and offer valuable directions for future research in mixed nanolattices for nanomaterial science and electrical device engineering.

DEVELOPMENTAL CONTROL OF SOME PHYSIOLOGICAL FACTORS ON REPRODUCTIVE BIOLOGY AND RUDIMENTARY EMBRYOS PHENOMENON IN CARROT SEEDS

This study was aimed to investigate delayed germination and immature embryos of carrot seeds; This research was implemented at vegetable field of College of Agricultural Engineering Sciences - University of Baghdad during two sequent seasons (fall and spring). The experiment was conducted using factorial within Randomized Complete Block Design arrangement with three factors and replicates (3X3X2). The aqueous barley sprouts extract (B0, B1) (0, 100 g.L-1) represented the first factor. Trehalose (T0, T1, T2) (0, 50, 75 mmole.L-1) represented the second factor. Calcium (C0, C1, C2) (0, 1, 2 ml.L-1) represented the third factor. Results showed the effectiveness of third order interaction treatment B1T2C1 in increasing germination speed and percent for the seeds of royal umbel (92, 97%); secondary umbel (90.67, 94.67%); and tertiary umbel (75.68, 86.33%). The mentioned treatment increased embryo length for the seeds of primary (royal) umbel (1628.3 µm), secondary umbel (1620.3 µm); and tertiary umbel (874.7 µm ). in compare with the lowest percents that found in B0T0C2 treatment.

EVALUATION OF OAT VARIETIES UNDER SUFFICIENT AND INSUFFICIENT IRRIGATION

This study was aimed to investigate the genetic variations of Oat cultivars under in sufficient of irrigation. A field experiment was carried out at the fields of with College of Agricultural Engineering Sciences ;University of Baghdad - Al-Jadriya during 2020-2021 seasons. The experiment was carried out using a Completely Block designwithin split-plot arrangement using three replicates under two treatments (verities and irrigation intervals). The main plots were irrigation intervals with moisture(50%, 25%, and 10%), while sub-plots were the varieties (Genzania, Anatolia, Plmula, Algoda, and Al-Shifa).The results showed that the third irrigation level had 75% flowering at highest averages93.67 days , and the V4 variety had the lowest average to weight of 250 grains about (7.67 g ).While there was a significant differencesamong irrigation interval 75% flowering compared with other traits ( 22.8) ,(24.6 )and ( 7.75) respectively. While the Alogoda produced the highest yield (7.49 ton .h-1) compared with the lowest Plmula gave (5.83 ton h-1)There are differences among of varieties under irrigation intervals. The highest genotypic coefficient to yield (94.7%) and the highest value of heritability was (98.75%).to the flowering.

INTERACTION EFFECT OF CHEMICAL AND ORGANIC FERTILIZERS ON THE YIELD AND YIELD COMPONENTS OF Gundelia rosea AT DIFFERENT PLANT DENSITIES IN THE FIELD

Field experiments were conducted at two locations, Grdarasha Research Field Station, College of Agricultural Engineering Sciences, Salahaddin University – Erbil and Aquban special farm using randomized complete block design (RCBD) during two seasons 2019-2020 and 2020-2021 to study the effect of different plant densities and compost fertilizer of solid waste management and sorting of Akre district-Duhok province and NPK (20:20:20) fertilizer on growth and edible portion characteristics of Gundelia rosea. The results indicated that the plants of the two years age in the both locations produce the highest value of length, dimeter, fresh and dry weight of edible portion with space increasing between plants and rows. While, total fresh and dry weight increased with decreasing the distance between plants and rows. Compost and compost + NPK fertilizer significantly increasing all edible portion parameters in both locations. The interaction between density and fertilizer resulted that D5 and compost and compost +NPK treatment produce the maximum rate of length, dimeter, fresh and dry weight of edible portion, while D1 and compost and compost + NPK record the highest total fresh and dry weight production.

REDUCING THE HEAT STRESS ON MAIZE DURING SPRING SEASON BY USING SOME BIO STIMULANTS

This study was aimed to investigate the effect of bio stimulators )chitosan and Appetizer( in reducing the heat stress on maize during spring season. Field experiment was conducted at the experimental farm, Coll. of Agricultural Engineering Sciences, University of Baghdad, Al-Jadiriya, Iraq, during the seasons of 2020 and 2021. The experiment was laid out in Randomized Complete Blocks Design within split plot arrangement, with three replicates. Where the main plots included two cultivars of maize )Baghdad3 and cultivar 5018(, while the sub plots included five levels of chitosan and Appetizer:(soaking seeds with Chitosan at a concentration of 100 and 500 mg L-1, and spraying with Chitosan 100 mg L-1, and spraying Appetizer in two and three stages in addition to the two control treatments, which are soaking seeds with distilled water and dry seeds. The results showed that the cultivar 5018 was superiored in grain yield 11.82 and 11.08 Mg ha-1 in both seasons. The treatment of spraying Chitosan gave the highest grain yield 13.26 and 12.94 Mg ha-1, spraying the Appetizer in two stages gave 13.32 and 12.54 Mg ha-1 , and spraying Appetizer in three stages gave 13.70 and 12.97 Mg ha-1 for both seasons. The interaction was significant in most of the studied traits. So we recommend the use of Chitosan spray at a concentration of 100 mg L-1 and Appetizer spray at a concentration of 1.25 ml L-1 in two or three stages to reduce the effect of heat stress on maize planted in the spring season to increase grain yield.

Metadiscourse in MOOC Video Lectures: Comparison with University Lectures and Disciplinary Variation

Abstract Based on Hyland’s (2018) interpersonal model of metadiscourse, this study explores MOOC video lecturers’ use of metadiscourse and compares it to traditional university lecturers’. Disciplinary variation in metadiscourse in the MOOC video lectures has also been investigated. The MOOC corpus consists of sixteen MOOCs across three disciplinary areas, including Arts and Humanities, Engineering and Physical Sciences, and Social Sciences. The results suggest that despite slight differences, the most frequently appearing metadiscourse in the MOOC corpus resembles the patterns found in university lectures, which reveals the remarkable similarities in using metadiscourse between MOOCs and traditional face-to-face lectures. However, different instructional contexts and teacher-student relationships indeed contribute to the variance in the employment of metadiscourse. Overall, MOOC video lecturers employed more interactive metadiscourse but less interactional metadiscourse than university lecturers. Cross-disciplinarily, the use of metadiscourse in MOOC video lectures is considerably influenced by disciplinary features. MOOCs containing more discipline-specific content and requiring intensive cognitive effort tend to use more interactive metadiscourse and engagement markers; while for MOOCs that may include more perspectives than basic facts, boosters and attitude markers seem to be employed more frequently. Possible reasons and purposes of the differentiated use of metadiscourse across disciplines are discussed in detail.

The Duality of Raman Scattering.

ConspectusFirst predicted more than 100 years ago, Raman scattering is a cornerstone of photonics, spectroscopy, and imaging. The conventional framework of understanding Raman scattering was built on Raman cross section σRaman. Carrying a dimension of area, σRaman characterizes the interaction strength between light and molecules during inelastic scattering. The numerical values of σRaman turn out to be many orders of magnitude smaller in comparison to the linear absorption cross sections σAbsorption of similar molecular systems. Such an enormous gap has been the reason for researchers to believe the extremely feeble Raman scattering ever since its discovery. However, this prevailing picture is conceptually problematic or at least incomplete due to the fact that Raman scattering and linear absorption belong to different orders of light-matter interaction.In this Account, we will summarize an alternate way to think about Raman scattering, which we term stimulated response formulation. To capture the third-order interaction nature of Raman scattering, we introduced stimulated Raman cross section, σSRS, defined as the intrinsic molecular property in response to the external photon fluxes. Foremost, experimental measurement of σSRS turns out to be not weak at all or even larger when fairly compared with electronic counterparts of the same order. The analytical expression for σSRS derived from quantum electrodynamics also supports the measurement and proves that σSRS is intrinsically strong. Hence, σRaman and σSRS can be extremely small and large, respectively, for the same molecule at the same time. Our subsequent theoretical studies show that stimulated response formulation can unify spontaneous emission, stimulated emission, spontaneous Raman, and stimulated Raman via eq 10, in a coherent and symmetric way. In particular, an Einstein-coefficient-like equation, eq 12a, was derived, showing that σRaman can be explicitly expressed as σSRS multiplied by an effective photon flux arising from zero-point fluctuation of the vacuum. The feeble vacuum fluctuation hence explains how σSRS can be intrinsically strong while, at the same time, σRaman ends up being many orders of magnitude smaller when both compared to the electronic counterparts. These two sides of the same coin prompted us to propose "the duality of Raman scattering" (Table 1). Finally, this formulation naturally leads to a quantitative treatment of stimulated Raman scattering (SRS) microscopy, providing an intuitive, molecule-centric explanation as to how SRS microscopy can outperform regular Raman microscopy. Hence, as unveiled by the new formulation, a duality of Raman scattering has emerged, with implications for both fundamental science and practical technology.

Large and Small Polarons in Highly Efficient and Stable Organic‐Inorganic Lead Halide Perovskite Solar Cells: A Review

Polarons, which arise from the intricate interplay between excess electrons and/or holes and lattice vibrations (phonons), represent quasiparticles pivotal to the electronic behavior of materials. This review reaffirms the established classification of small and large polarons, emphasizing its relevance in the context of recent advances in understanding lead halide perovskites' behavior. The distinct characteristics of large and small polarons stem from the electron–phonon interaction range, which exerts a profound influence on materials’ characteristics and functionalities. Concurrently, lead halides have emerged with exceptional opto‐electronic properties, featuring prolonged carrier lifetimes, low recombination rates, high defect tolerance, and moderate charge carrier mobilities; these characteristics make them a compelling contender for integration of optoelectronic devices. In this review, the formation of both small and large polarons within the lattice of lead halide perovskites, elucidating their role in protecting photogenerated charge carriers from recombination processes, is discussed. As optoelectronic devices continue to advance, this review underscores the importance of unraveling polaron dynamics to pave the way for innovative strategies for enhancing the performance of next‐generation photovoltaic technologies. Future research should explore novel polaronic effects using advanced computational and experimental techniques, enhancing our understanding and unlocking new applications in materials science and device engineering.

The Gaussian distribution: Derivation method and its applications in selected examples

Gaussian distribution is the most important and common form of distribution in statistical theory, and its density function has more complicated forms. When Gauss dealt with the problem of measurement error, he derived the form of normal distribution from another angle, and proposed the least squares theory based on the normal distribution of error. This helps solve the problem of the probability density distribution of the error, enabling people to make a better statistical measure of the effect of the size of the error. In short, Gaussian distribution is not only a powerful mathematical tool, but also a connection between theory and practical applications. It is also a bridge between theory and practical application. In practice, the Gaussian distribution has a wide range of applications, in the natural sciences, engineering and social sciences and other fields, the Gaussian distribution is used to describe the continuity of random variables, such as measurement error, temperature change, population intelligence level. In this paper, the author briefly deduces the Gaussian distribution derivation process, from the overall and the measurement error of the simple random samples to cut in, to admit that x is already the estimates that should be taken. Hopefully, it will be helpful to scholars who are interested in this area.

The association between statin use and non-Hodgkin lymphoma; a systematic review and meta-analysis

Introduction: Statins reduce the cancer risk; however, non-Hodgkin lymphoma (NHL) evidence remains controversial. Therefore, we aimed to evaluate the relationship between statin consumption and NHL risk using a systematic review and meta-analysis. Materials and Methods: In this systematic review and meta-analysis, international databases, including Scopus, PubMed, Web of Science, Cochrane, and Google Scholar search engines, were searched without a time limit up to September 21, 2023. Data analysis was performed using STATA 14 software, and the significance level was considered P<0.05. Results: The results of combining 13 studies (9 case-control studies and 4 cohort studies) with a total sample size of 1142 740 subjects showed that statin consumption could reduce NHL risk by 22% (RR: 0.78; 95% CI: 0.69, 0.88). Statin consumption in cohort studies reduced NHL risk by 14% (RR: 0.86; 95% CI: 0.77, 0.95), but in case-control studies, it reduced NHL risk by 26% (RR: 0.74; 95% CI: 0.62, 0.90). Furthermore, statin consumption reduced diffuse large B-cell lymphoma risk by 24% (RR: 0.76; 95% CI: 0.67, 0.87) and marginal zone risk by 26% (RR: 0.74; 95% CI: 0.59, 0.93). However, it did not affect reducing the risk of chronic lymphocytic leukemia/small lymphocytic lymphoma (RR: 0.94; 95% CI: 0.85, 1.05), follicular (RR: 0.96; 95% CI: 0.83, 1.10), plasma cell neoplasms (RR: 0.97; 95% CI: 0.70, 1.33), T cell lymphoma (RR: 0.81; 95% CI: 0.55, 1.19) and B cell lymphoma (RR: 0.94; 95% CI: 0.44, 2.01). Conclusion: Statin consumption significantly reduced the risk of NHL, diffuse large B-cell lymphoma, and marginal zone but did not affect other NHL types. Registration: This study has been compiled based on the PRISMA checklist, and its protocol was registered on the PROSPERO (CRD42023469126) and Research Registry (UIN: reviewregistry1732) website.

Effective Atomic Numbers of Glass Samples

Effective atomic numbers are a term used to understand the interaction of a compound or material with radiation. In particular, this term is often used for materials with complex structures that can be expressed by a single fixed atomic number. If different elements in a material are present in different concentrations, the effective atomic number of the material can be calculated by considering the contribution of each element. This is a useful method to better understand the response of the material to radiation or the effect of radiation within the material. In particular, when radiation passes through or acts on the material, the effective atomic number plays an important role in determining factors such as the material's radiation exposure properties, absorption or scattering. Effective atomic numbers are used in radiation interaction analyses in various fields such as materials science, medicine, geophysics and industry. This concept is used to express in a simpler way the radiation properties of compounds in which different elements are combined. In this study, the effective atomic numbers of magnesium borosilicate glasses were investigated. Such studies are important in the field of materials science and glass technology because the chemical constituents of glass and their interactions play a decisive role in the properties of glass. Magnesium borosilicate glasses are often used in industrial applications. The properties of these glasses depend on the amount of elements they contain and their chemical structure. Effective atomic numbers can be used to understand the specific properties of a material. By determining the effective atomic numbers of the elements contained in the glass, this study aims to provide an important basis for understanding the properties of the material, such as radiation exposure, electrical properties or optical properties.

Emerging Technology and New Vistas in Library and Information Science: Padma Shri Prof. P. N. Kaula Centenary Volume. Eds. Prof C. R. Karisiddappa, Dr P. K. Gupta and Prof. N. Laxman Rao. Managing Editor Dr. S. P. Sood. 2024, Raj Publishing House, Jaipur. Pages. xii, 278, 22cms. ISBN: 978-93-88997-68-3. Price Rs. 699/-

No Abstract.

Deep learning in data science: Theoretical foundations, practical applications, and comparative analysis

Deep learning has emerged as a transformative technology in data science, revolutionizing various domains through its powerful capabilities. This paper explores the theoretical foundations, practical applications, and comparative analysis of deep learning models. The theoretical foundations section discusses key neural network architectures such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformers, highlighting their unique capabilities in processing different types of data. Optimization algorithms crucial for effective training, including Stochastic Gradient Descent (SGD) and Adam, are examined. Regularization techniques for preventing overfitting and enhancing generalization are also addressed. Practical applications in healthcare, finance, and retail showcase the real-world impact of deep learning. A comparative analysis of performance metrics demonstrates the superiority of deep learning models over traditional methods. Despite their advantages, deep learning models face limitations and challenges, including data dependency and interpretability issues. The paper concludes by emphasizing the ongoing research efforts to mitigate these challenges and ensure the continued advancement of deep learning in data science.

Your New Head of the Undergraduate Medical School - An Introduction from Prof. Malcolm Shepherd

A long time ago….. and by a long time Imean before new Dr Who, before iPhonesand around the first appearance of StarWars Lego …… truly a very long time ago,things were simpler. Not necessarilybetter, different, much simpler….notclearly better, but definitely better!Conversations never ended, lasting longinto the night without conclusion; no onewas blessed with facts, just opinions andpassion. ‘Britain will remain at the centre ofEurope….’‘no way William Shatner (original CaptainKirk for non-geeks) will ever get intospace …’‘Glasgow could never host the biggestcycling event of all time…..’‘no, you could not possibly be allergic tored meat, you are made of red meat…’Of course now smartphones and theinternet have relegated the art ofconversation to a list of facts and dates,and no one speaks to each other without aseries of emojis and hand gestures. Or Imight have got that wrong you tell me…….‘But surely. Old man’ you say, carefullypicking the most contentious topic fromthe list above, Surely you cannot beallergic to red meat, we are all mammals,and the rules of Immunology say youcannot be immune to self.’‘Ah’ says the wise old man (In this scenariobizarrely that is me), ‘a long time ago youwould be correct, but in 2002 strangereports emerged that people with ahistory of tick bites, experiencedanaphylaxis after eating red meat’. Now across the world from Australia toNorth East USA the phenomenon of redmeat allergy causing strange delayedonset anaphylaxis, often as much as 4 hours after eating has been recognised.Breaking many rules of allergy fromrapid onset to variable presentation thestrangest aspect of this allergy is thatsensitisation seems to follow the bite ofparticular species of ticks. One of thoseticks is the indigenous Deer tick in theUK and so yes this allergy is found inrelatively high numbers in Scotland.Don’t worry, it is very very rare, but wehave identified around 40 patients whohave this allergy after being bitten byticks in Scotland.‘So what?’ you may say ‘its so rare whyshould we worry’. Well the truth is thattick populations are growing in the UK.There are a number of reasons, butglobal climate change with warmermoister winters probably play a part.Increased use of rural environmentswith Scotland’s amazing right to roamlegislation and wonderful landscapeincreases the exposure of urban andrural populations to ticks and we areseeing sufferers from all regions of thecountry. Climate change is an engine of change inhealth science and while self-allergymay seem a trivial example, it is a verypowerful concept; our immune systemsturning on ourselves in the face of awarming climate. Allergy medicine is fullof the human consequences of awarming climate from self-allergy topan-allergens crossing botanical speciesand we see new patterns of disease emerging from theenvironmental catastrophe we arefacing. Learning about the engines of change inmedicine and discovering what healthscience can do to limit our global impactwill become an increasingly importantaspect of Medicine as you becomeleaders and innovators of the future. Ihope we can inspire you to think aboutthe ways we can all work to limit this andavoid potential catastrophe.