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Traditionally concrete strength determination has been a costly and time-consuming process, relying on periodic laboratory testing using compression tests on concrete-filled cylinders. To address these challenges, an innovative framework has been developed using the Internet of Things (IoT) technology-based low-cost wireless sensors. These sensors have been programmed to integrate with a real-time data monitoring platform using the Firebase cloud computing application. This framework allows remote real-time concrete compressive strength monitoring while reducing the need for on-site laboratory testing. This aspect can ultimately add digital competencies to the construction industry. The IoT-based data is further integrated with the Building Information Modeling (BIM) model of the structure, developing its Digital Twin (DT), which enables the concerned authorities to remotely access the concrete compressive strength parameters, particularly in the early stages. The proposed system presents notable advantages compared to traditional methods by enabling remote real-time monitoring of concrete strength parameters in the BIM environment and facilitating informed decision-making to optimize the construction schedule utilizing the Active BIM system. It serves as a pioneering advancement in internet/remote applications designed to monitor early-age compressive strength. By assisting project managers in timely actions such as formwork removal, post-tensioning, curing termination, and reshores removal, it generates significant cost savings in terms of labor and expedites the completion of construction activities.

The exterior beam-column joint (BCJ) within reinforced concrete (RC) frame structures is acknowledged as a vulnerable component prone to seismic failure. This article proposes a practical and economical strengthening method for exterior BCJs using a perforated steel haunch system. This method is designed to mitigate damage in BCJs and improve the seismic performance of the structure. Employing finite element modeling (FEM) techniques, the study evaluates the impact of perforated steel haunches on the BCJs’ behavior and performance. The investigation involves creating nine distinct models, each representing a BCJ with a steel haunch system. These models include a control model without any perforations and eight variations with different levels of perforation (ranging from 10% to 50%) within the steel haunch system. Furthermore, the study analyzes the influence of perforation shapes on the connections’ performance, considering square, circular, hexagonal, and triangular shapes. The results reveal that utilizing a steel haunch without perforations significantly increases the load-carrying capacity of a BCJ by about 89%. Additionally, circular or square-shaped perforations, up to 30–35% within the steel haunch, effectively prevent the joints’ failure and promote the ductile behavior. These findings hold the potential to advance the design methodology for RC joints subjected to seismic loads, thereby enhancing the structural resilience in earthquake-prone regions.

Thermolectric cooling offers several advantages over conventional refrigeration systems due to its light weight, environmental friendliness, silent operation, and no moving parts. In this work, a thermoelectric water cooling system is created in which water flowing at various flowrates removes heat produced on the hot side of the Peltier module. The cooling effect and coefficient of performance (COP) of the cooling system are experimentally determined at various flowrates of water on the hot side of the module. The cooling effect produced in water increases with the increase in flowrate. A similar trend is noticed for the COP of the system. The maximum cooling effect produced in water is 1363 W at 43 mL/s. The maximum COP of the system is 3.99.

The traditional methods of marking construction site layouts using manual techniques such as chalk lines are prone to human errors, resulting in discrepancies between blueprints and actual layouts. This has serious implications for project delivery, construction, costs and, eventually, project success. However, this issue can be resolved through autonomous robots and construction automation in line with Industry 4.0 and 5.0 goals. Construction automation enables workers to concentrate on the construction phase and not worry about manual site markups. This leads to an enhancement in their productivity. This study aims to improve the floor layout printing technique by introducing a framework that integrates building information modeling (BIM) and the Internet of Things (IoT), i.e., BIM–IoT and autonomous mobile robots (AMR). The development process focuses on three key components: a marking tool, an IoT-based AMR and BIM. The BIM-based tools extract and store coordinates on the cloud platform. The AMR, developed using ESP32 and connected to the Google Firestore cloud platform, leverages IoT technology to retrieve the data and draw site layout lines accordingly. Further, this research presents a prototype of an automated robot capable of accurately printing construction site layouts. A design science research (DSR) method is employed in this study that includes a comprehensive review of the existing literature and usage of AMRs in construction layout printing. Subsequently building upon the extant literature, an AMR is developed and experiments are conducted to evaluate the system’s performance. The experiment reveals that the system’s precision falls within a range of ±15 mm and its angle accuracy is within ±4 degrees. Integrating robotic automation, IoT and BIM technologies enhances the efficiency and precision of construction layout printing. The findings provide insights into the potential benefits of deploying AMRs in construction projects, reducing site layout errors and improving construction productivity. This study also adds to the body of knowledge around construction automation in line with Industry 4.0 and 5.0 endeavors.

Abstract Recent animal studies have drawn concerns regarding most commonly used anesthetics and their long-term cytotoxic effects, specifically on the nervous tissue. It is therefore imperative that the search continues for agents that are non-toxic at both the cellular and behavioural level. One such agent appears to be dexmedetomidine (DEX) which has not only been found to be less neurotoxic but has also been shown to protect neurons from cytotoxicity induced by other anesthetic agents. However, DEX’s effects on the growth and synaptic connectivity at the individual neuronal level, and the underlying mechanisms have not yet been fully resolved. Here, we tested DEX for its impact on neuronal growth, synapse formation (in vitro) and learning and memory in a rodent model. Rat cortical neurons were exposed to a range of clinically relevant DEX concentrations (0.05–10 µM) and cellular viability, neurite outgrowth, synaptic assembly and mitochondrial morphology were assessed. We discovered that DEX did not affect neuronal viability when used below 10 µM, whereas significant cell death was noted at higher concentrations. Interestingly, in the presence of DEX, neurons exhibited more neurite branching, albeit with no differences in corresponding synaptic puncta formation. When rat pups were injected subcutaneously with DEX 25 µg/kg on postnatal day 7 and again on postnatal day 8, we discovered that this agent did not affect hippocampal-dependent memory in freely behaving animals. Our data demonstrates, for the first time, the non-neurotoxic nature of DEX both in vitro and in vivo in an animal model providing support for its utility as a safer anesthetic agent. Moreover, this study provides the first direct evidence that although DEX is growth permissive, causes mitochondrial fusion and reduces oxygen reactive species production, it does not affect the total number of synaptic connections between the cortical neurons in vitro.

Seawater desalination is an affordable and viable solution to the growing freshwater scarcity problem in water scarce regions. The current study focuses on cost analysis of Vacuum Membrane Distillation (VMD) setup for removing salts from water. The membrane used in the flat sheet VMD module was Polytetrafluoroethylene (PTFE) with 250 mm × 200 mm dimensions and 165 µm thickness. The experiments were carried out with variations in parameters such as velocity, pressure, concentration, and temperature. For the cost analysis, the operational, maintenance, instrumentation, and capital cost of the lab model was considered and then upscaled. A range of experiments was performed for NaCl and KCl under variations of operating parameters. It was noted that, for the NaCl solution, the increase in temperature from 50 °C to 70 °C doubled the permeate flux. However, for the conditions tested, the concentration shift from 0.25 M to 0.75 M decreased the permeate flux by 1.4% because the increase in ion concentrations along the membrane lowers the vapor pressure, restricting the permeate flux. The results trend for the KCl solution was similar to the NaCl; at temperature T1, it was noted that increased concentration from 0.25 M to 0.75 M significantly reduces the permeate flow. The reduction in permeate flow was nonlinear for a given pressure 30 kPa and velocity 5.22 m/s, but linear for all other variables. It was also observed that with an increase in temperature from 60 °C to 70 °C, the permeate flux for concentration 0.25 M was 49% for all the combinations of pressure and velocity. In addition, permeate flow increased 53% from temperature 50 °C to 60 °C and 49% from temperature 60 °C to 70 °C for both the solutions at a concentration of 0.25 M. This shows that the temperature also had a profound impact on the permeate flux. The economic analysis and market survey shows that the cost of clean water at the lab level was high which can be significantly reduced using a large-scale setup providing 1,000,000 L/H of distilled water.

The watershed area of the Mangla Reservoir spans across the Himalayan region of India and Pakistan, primarily consisting of the Jhelum River basin. The area is rugged with highly elevated, hilly terrain and relatively thin vegetation cover, which significantly increases the river’s sediment output, especially during the monsoon season, leading to a decline in the reservoir’s storage capacity. This work assesses the soil erosion risk in the Jhelum River watershed (Azad Jammu and Kashmir (AJ&K), Pakistan) using the Revised Universal Soil Loss Equation of (RUSLE). The RUSLE components, including the conservation support or erosion control practice factor (P), soil erodibility factor (K), slope length and slope steepness factor (LS), rainfall erosivity factor (R), and crop cover factor (C), were integrated to compute soil erosion. Soil erosion risk and intensity maps were generated by computing the RUSLE parameters, which were then integrated with physical factors such as terrain units, elevation, slope, and land uses/cover to examine how these factors affect the spatial patterns of soil erosion loss. The 2021 rainfall data were utilized to compute the rainfall erosivity factor (R), and the soil erodibility (K) map was created using the world surface soil map prepared by the Food and Agriculture Organization (FAO). The slope length and slope steepness factor (LS) were generated in the highly rough terrain using Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM). The analysis revealed that the primary land use in the watershed was cultivated land, accounting for 27% of the area, and slopes of 30% or higher were present across two-thirds of the watershed. By multiplying the five variables, the study determined that the annual average soil loss was 23.47 t ha−1 yr−1. In areas with dense mixed forest cover, soil erosion rates ranged from 0.23 t ha−1 yr−1 to 25 t ha−1 yr−1. The findings indicated that 55.18% of the research area has a low erosion risk, 18.62% has a medium erosion risk, 13.66% has a high risk, and 11.6% has a very high erosion risk. The study’s findings will provide guidelines to policy/decision makers for better management of the Mangla watershed.

Abstract Anesthetics are deemed necessary for all major surgical procedures. However, they have also been found to exert neurotoxic effects when tested on various experimental models, but the underlying mechanisms remain unknown. Earlier studies have implicated mitochondrial fragmentation as a potential target of anesthetic-induced toxicity, although clinical strategies to protect their structure and function remain sparse. Here, we sought to determine if preserving mitochondrial networks with a non-toxic, short-life synthetic peptide—P110, would protect cortical neurons against both inhalational and intravenous anesthetic-induced neurotoxicity. This study provides the first direct and comparative account of three key anesthetics (desflurane, propofol, and ketamine) when used under identical conditions, and demonstrates their impact on neonatal, rat cortical neuronal viability, neurite outgrowth and synaptic assembly. Furthermore, we discovered that inhibiting Fis1-mediated mitochondrial fission reverses anesthetic-induced aberrations in an agent-specific manner. This study underscores the importance of designing mitigation strategies invoking mitochondria-mediated protection from anesthetic-induced toxicity in both animals and humans.

Precision agriculture is getting immense attention from researchers and farmers across the world due to the threatening situation of the demand and production gap. Evolution in the electromechanical system and the emergence of intelligent monitoring and conditioning systems have enabled closing the gap to make agronomy quicker, lesser prone to infestations, and still profitable at the same time. Whereas the Internet of Things (IoT) has enabled access to relevant data remotely and automates essential response systems to any threat or requirement by a plant in a particular environment. This study concentrates on gathering such advanced mechatronic techniques in the agricultural sector and analyses of the benefits and disadvantages of the modern method.

Anesthetics have been shown to cause cytotoxicity, cell death, affect neuronal growth and connectivity in animal models; however, their effects on learning and memory remain to be fully defined. Here, we examined the effects of the inhalation anesthetic sevoflurane (SEV)—both in vivo by examining learning and memory in freely behaving animals, and in vitro using cultured neurons to assess its impact on viability, mitochondrial structure, and function. We demonstrate here that neonatal exposure to sub-clinically used concentrations of SEV results in significant, albeit subtle and previously unreported, learning and memory deficits in adult animals. These deficits involve neuronal cell death, as observed in cell culture, and are likely mediated through perturbed mitochondrial structure and function. Parenthetically, both behavioural deficits and cell death were prevented when the animals and cultured neurons were pre-treated with the anesthetic adjuvant Dexmedetomidine (DEX). Taken together, our data provide direct evidence for sevoflurane-induced cytotoxic effects at the neuronal level while perturbing learning and memory at the behavioural level. In addition, our data underscore the importance of adjuvant agents such as DEX that could potentially counter the harmful effects of commonly used anesthetic agents for better clinical outcomes.

Cholinergic neuronal networks in the hippocampus play a key role in the regulation of learning and memory in mammals. Perturbations of these networks, in turn, underlie neurodegenerative diseases. However, the mechanisms remain largely undefined. We have recently demonstrated that an in vitro MEN1 gene deletion perturbs nicotinic cholinergic plasticity at the hippocampal glutamatergic synapses. Furthermore, MEN1 neuronal conditional knockout in freely behaving animals has also been shown to result in learning and memory deficits, though the evidence remains equivocal. In this study, using an AVV viral vector transcription approach, we provide direct evidence that MEN1 gene deletion in the CA1 region of the hippocampus indeed leads to contextual fear conditioning deficits in conditional knockout animals. This loss of function was, however, recovered when the same animals were re-injected to overexpress MEN1. This study provides the first direct evidence for the sufficiency and necessity of MEN1 in fear conditioning, and further endorses the role of menin in the regulation of cholinergic synaptic machinery in the hippocampus. These data underscore the importance of further exploring and revisiting the cholinergic hypothesis that underlies neurodegenerative diseases that affect learning and memory.

Proper and uniform seed depth within the optimum range increases crop germination rate, which directly affects yield. Seed depth mainly depends on seed placement techniques. In conventional seed drill and planters, variations and fluctuations in seeding depth were recorded. This issue can be resolved by adaption of intelligent crop sowing machinery. A real-time seed depth control system was designed and developed to monitor and maintain the required seed depth. The developed system was installed on a tractor-mounted conventional seed drill. The materials used were ultrasonic sensors, a micro-controller, an RTC module, buzzers, an LCD, an SD card module, a power battery, and switch buttons. The system read height difference as a reference value. The seeding depth data was stored in the SD card. The results showed by introducing real time depth control system in existing seeders, it is possible to achieve desired plant population and homogeneous germination. The average cumulative germination rate (GR) of wheat with the seed depth control system was 126 plants/m2, and with a conventional seed drill (without SDCS) 117 plants/m2. The yield of wheat with the seed depth control system was 1225 kg/acre, and with the conventional seed drill (without SDCS) 1124 kg/acre in an arid region. Result shows that the crop yield could be enhanced by proper seed placement at the required seed depth by using the seed depth control system. Further field trials on different soils, regions and environmental conditions could improve the results.

The incidence of depression among humans is growing worldwide, and so is the use of selective serotonin reuptake inhibitors (SSRIs), such as sertraline hydrochloride. Our fundamental understanding regarding the mechanisms by which these antidepressants function and their off-target synaptic effects remain poorly defined, owing to the complexity of the mammalian brain. As all brain functions rely on proper synaptic connections between neurons, we examined the effect of sertraline on synaptic transmission, short-term potentiation underlying synaptic plasticity and synapse formation using identified neurons from the mollusk Lymnaea stagnalis. Through direct electrophysiological recordings, made from soma-soma paired neurons, we demonstrate that whereas sertraline does not affect short-term potentiation, it reduces the efficacy of synaptic transmission at both established and newly formed cholinergic synapses between identified neurons. Furthermore, Lymnaea neurons cultured in the presence of sertraline exhibited a decreased incidence of synaptogenesis. Our study provides the first direct functional evidence that sertraline exerts non-specific effects—outside of its SSRI role—when examined at the resolution of single pre- and post-synaptic neurons.

Several past studies have shown the use of glass fibre-reinforced polymer (GFRP) bars to alleviate the reinforced steel rusting issue in different concrete structures. However, the practise of GFRP bars in concrete columns has not yet achieved a sufficient confidence level due to the lack of a theoretical model found in the literature. The objective of the current study is to introduce a novel prediction model for the axial capability of concrete columns made with bars of GFRP. For this purpose, two different approaches, such as data envelopment analysis (DEA) and artificial neural networks (ANNs) modelling, are used on a collected dataset of 266 concrete column specimens made with GFRP bars from previous literature works. Eight parameters were used to predict the axial performance of GFRP-based RC columns. The proposed DEA and ANNs predictions demonstrated a good correlation with the testing dataset, having R2 values of 0.811 and 0.836, respectively. A comparative analysis of the DEA and ANNs models is undertaken, and it was found that the suggested models are capable of accurately forecasting the structural response of GFRP-made RC column structures. Then, a comprehensive parametric analysis of 266 GFRP-based columns was performed to study the effect of different materials and their geometrical shape.

At present, low tensile mechanical properties and a high carbon footprint are considered the chief drawbacks of plain cement concrete (PCC). At the same time, the combination of supplementary cementitious material (SCM) and reinforcement of fiber filaments is an innovative and eco-friendly approach to overcome the tensile and environmental drawbacks of plain cement concrete (PCC). The combined and individual effect of fly ash (FA) and Alkali resistance glass fiber (ARGF) with several contents on the mechanical characteristics of M20 grade plain cement concrete was investigated in this study. A total of 20 concrete mix proportions were prepared with numerous contents of FA (i.e., 0, 10, 20, 30 and 40%) and ARGF (i.e., 0, 0.5, 1 and 1.5%). The curing of these concrete specimens was carried out for 7 and 28 days. For the analysis of concrete mechanical characteristics, the following flexural, split tensile, and compressive strength tests were applied to these casted specimens. The outcomes reveal that the mechanical properties increase with the addition of fibers and decrease at 30 and 40% replacement of cement with fly ash. Replacement of cement at higher percentages (i.e., 30 and 40) negatively affects the mechanical properties of concrete. On the other hand, the addition of fibers positively enhanced the flexural and tensile strength of concrete mixes with and without FA in contrast to compressive strength. In the end, it was concluded that the combined addition of these two materials enhances the strength and toughness of plain cement concrete, supportive of the application of an eco-friendly circular economy. The relationship among the mechanical properties of fiber-reinforced concrete was successfully generated at each percentage of fly ash. The R-square for general relationships varied from (0.48–0.90) to (0.68–0.96) for each percentage of FA fiber reinforced concrete. Additionally, the accumulation of fibers effectively boosts the mechanical properties of all concrete mixes.

Water is one of the necessary ingredients for construction materials. Billions of gallons of clean water are wasted during the development of fired clay bricks. Similarly, the waste of clean water is a global issue. In this study, we develop fired clay bricks with the help of wastewater for the first time and compare these with clay bricks produced using groundwater, which is the conventional method. Both destructive (i.e., compressive strength (CS)) and non-destructive (i.e., ultrasonic pulse velocity (UPV)) tests are conducted on all fired clay brick specimens as per the American Society for Testing and Materials (ASTM). Physical (i.e., dimensions) and durability (water absorption, efflorescence, etc.) tests are also conducted. All kinds of brick satisfied the standard requirements of physical and durability characteristics. Similar or better strength of bricks were achieved using wastewater. The study concludes that the testing results of wastewater bricks were significantly 15–25% higher compared with groundwater-fired clay bricks. A large amount of wastewater can be used to develop bricks, and clean water can be saved to attain circular economy goals. Therefore, this study will help not only in developing low-cost bricks but also in saving clean water.

Due to rapid depletion of fossil fuels availability and huge environmental pollution, focus is now changing from traditional method of power generation to the non-conventional DERs located at distribution voltage level. Technological advancement and more researches in the use of DERs result in the formation of microgrids and active distribution network. Small DER units when placed in a network near to load, makes the network stable as it can work in islanding mode in case of any fault outside the network. This paper proposes a scheme for reduction in losses and improvement of bus voltages in the active distribution network. A DG in the form of small renewable energy resources such as solar PV, wind, biomass, is placed optimally for reduction of losses in the network. However, placement of DG does not result in fulfilment of reactive power needs of the network, resulting in under voltage at several buses. This under voltage problem is solved by the optimal placement of DSTATCOM. DLF technique is used in this paper for load flow calculations and LSF along with voltage deviation is used in objective function for optimal location of DG on MATLAB platform. The methodology is tested on 33-bus radial distribution system. Keywords: Distributed generation, DSTATCOM, Loss Sensitivity Factor, Direct Load Flow, Optimal location

Human–Robot Interaction (HRI) for collaborative robots has become an active research topic recently. Collaborative robots assist human workers in their tasks and improve their efficiency. However, the worker should also feel safe and comfortable while interacting with the robot. In this paper, we propose a human-following motion planning and control scheme for a collaborative robot which supplies the necessary parts and tools to a worker in an assembly process in a factory. In our proposed scheme, a 3-D sensing system is employed to measure the skeletal data of the worker. At each sampling time of the sensing system, an optimal delivery position is estimated using the real-time worker data. At the same time, the future positions of the worker are predicted as probabilistic distributions. A Model Predictive Control (MPC)-based trajectory planner is used to calculate a robot trajectory that supplies the required parts and tools to the worker and follows the predicted future positions of the worker. We have installed our proposed scheme in a collaborative robot system with a 2-DOF planar manipulator. Experimental results show that the proposed scheme enables the robot to provide anytime assistance to a worker who is moving around in the workspace while ensuring the safety and comfort of the worker.

Self-Compacting Concrete (SCC) is a unique kind of concrete that tends to consolidate in terms of its weight. In this study, the prime target is to investigate the durability properties of SCC developed using eco-friendly economical waste binding materials as partial replacement to costly cement. This circular economy concept will not only help in the development of green concrete but will also help to improve the climatic condition by reducing the use and production of cement. An economical design methodology has been applied to produce environmentally friendly construction material. This research focuses on the application of Alum Sludge (AS) and Brick Dust (BD) in Self-Compacting Concrete (SCC). Both materials are waste materials containing binding properties. Performance of SCC developed using these two materials was tested considering mechanical properties of concrete using the destructive testing technique. Results showed that BD and AS can be utilized for up to 12% and 9% of replacement of cement, respectively, to achieve equal or higher compressive, tensile, and flexural strength. The application of BD and AS has demonstrated a subsequent improvement of SCC’s mechanical properties, i.e., compressive, tensile, and flexural strength. This study will help the production of composite green materials with the help of eco-friendly and economical waste materials for sustainable infrastructure development.

Polymer composites have been identified as the most innovative and selective materials known in the 21st century. Presently, polymer concrete composites (PCC) made from industrial or agricultural waste are becoming more popular as the demand for high-strength concrete for various applications is increasing. Polymer concrete composites not only provide high strength properties but also provide specific characteristics, such as high durability, decreased drying shrinkage, reduced permeability, and chemical or heat resistance. This paper provides a detailed review of the utilization of polymer composites in the construction industry based on the circular economy model. This paper provides an updated and detailed report on the effects of polymer composites in concrete as supplementary cementitious materials and a comprehensive analysis of the existing literature on their utilization and the production of polymer composites. A detailed review of a variety of polymers, their qualities, performance, and classification, and various polymer composite production methods is given to select the best polymer composite materials for specific applications. PCCs have become a promising alternative for the reuse of waste materials due to their exceptional performance. Based on the findings of the studies evaluated, it can be concluded that more research is needed to provide a foundation for a regulatory structure for the acceptance of polymer composites.

Abstract The foremost issues of 21st century are challenging demand of electrical energy and to control the emission of Green House Gases (GHG) emissions. Renewable energy resources based sustainable microgrid emerges as one of the best feasible solution for future energy demand while considering zero carbon emission, fossil fuel independency, and enhanced reliability. In this paper, optimization and implementation of institutional based sustainable microgrid are discussed based on cost analysis, carbon emission, and availability of energy resources. Various microgrid topologies are considered for addressing the most ideal solution. The metrological data such as irradiance is acquired from solar satellite data of NASA (National Aero Space Agency) while the data for wind speed is taken from synergy enviro engineer’s site. HOMER® simulation tool is used for modelling and optimization purpose.

Anesthesia is a prerequisite for most surgical procedures in both animals and humans. Significant strides have been made in search of effective and safer compounds that elicit rapid induction and recovery from anesthesia. However, recent studies have highlighted possible negative effects of several anesthetic agents on the developing brain. The precise nature of this cytotoxicity remains to be determined mainly due to the complexity and the intricacies of the mammalian brain. Various invertebrates have contributed significantly toward our understanding of how both local and general anesthetics affect intrinsic membrane and synaptic properties. Moreover, the ability to reconstruct in vitro synapses between individually identifiable pre- and postsynaptic neurons is a unique characteristic of molluscan neurons allowing us to ask fundamental questions vis-à-vis the long-term effects of anesthetics on neuronal viability and synaptic connectivity. Here, we highlight some of the salient aspects of various molluscan organisms and their contributions toward our understanding of the fundamental mechanisms underlying the actions of anesthetic agents as well as their potential detrimental effects on neuronal growth and synaptic connectivity. We also present some novel preliminary data regarding a newer anesthetic agent, dexmedetomidine, and its effects on synaptic transmission between Lymnaea neurons. The findings presented here underscore the importance of invertebrates for research in the field of anesthesiology while highlighting their relevance to both vertebrates and humans.

Objective: To assess if 24h urinary cortisol metabolite (UCM) profiles are related to structural cardiac and arterial parameters in those with or at risk of Type 2 diabetes mellitus (T2DM). Design and method: 32 participants, 25-77 years, eGFR> 45 mL/min and no serious illness. Urine was collected over 24 hours. 2D echocardiography and arterial stiffness measures [aortic pulse wave velocity (aPWV) by Arteriograph and cardio-ankle vascular index (CAVI) by VaSera] were performed on the collection day. Steroids were extracted from urine and hydrolysed; derivatives were analysed by GC-MS. Results: Seven UCMs were quantified [tetrahydrocortisol (THF), allo-tetrahydrocortisol (a-THF), tetrahydrocortisone (THE), α-cortol (α-col), β-cortol (β-col), α-cortolone (α-cone), β-cortolone (β-cone)]. Left ventricular mass index (LVMI) correlated positively with 24h cortisol:cortisone metabolites (THF+aTHF+αcol+βcol/THE+αcortolone+βcortolone) and negatively with α:β metabolites (αcol+αcortol/βcol+βcortol), when indexed for body surface area (BSA) and height (r=0.37, 0.48 and r=−0.34, −0.49 respectively). Further, there was a positive relationship between LVMIBSA and THF:THE (r=0.35). aPWV but not CAVI was also related to 24h cortisol:cortisone metabolites (r=0.45). All p