Search results for: post processing

Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

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Authors: Mariia Karizhenskaia, Tanvi Nandani, Ali Tafazoli Moghadam

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Hospice palliative care (HPC) is one of the most complicated philosophies of care in which physical, social/cultural, and spiritual aspects of human life are intermingled with an undeniably significant role in every aspect. Among these dimensions of care, culture possesses an outstanding position in the process and goal determination of HPC. This study shows the importance of cultural elements in the establishment of effective and optimized structures of HPC in the Canadian healthcare environment. Our systematic search included Medline, Google Scholar, and St. Lawrence College Library, considering original, peer-reviewed research papers published from 1998 to 2023 to identify recent national literature connecting culture and palliative care delivery. The most frequently presented feature among the articles is the role of culture in the efficiency of the HPC. It has been shown frequently that including the culturespecific parameters of each nation in this system of care is vital for its success. On the other hand, ignorance about the exclusive cultural trends in a specific location has been accompanied by significant failure rates. Accordingly, implementing a culture-wise adaptable approach is mandatory for multicultural societies. The following outcome of research studies in this field underscores the importance of culture-oriented education for healthcare staff. Thus, all the practitioners involved in HPC will recognize the importance of traditions, religions, and social habits for processing the care requirements. Cultural competency training is a telling sample of the establishment of this strategy in health care that has come to the aid of HPC in recent years. Another complexity of the culturized HPC nowadays is the long-standing issue of racialization. Systematic and subconscious deprivation of minorities has always been an adversity of advanced levels of care. The last part of the constellation of our research outcomes is comprised of the ethical considerations of culturally driven HPC. This part is the most sophisticated aspect of our topic because almost all the analyses, arguments, and justifications are subjective. While there was no standard measure for ethical elements in clinical studies with palliative interventions, many research teams endorsed applying ethical principles for all the involved patients. Notably, interpretations and projections of ethics differ in varying cultural backgrounds. Therefore, healthcare providers should always be aware of the most respectable methodologies of HPC on a case-by-case basis. Cultural training programs have been utilized as one of the main tactics to improve the ability of healthcare providers to address the cultural needs and preferences of diverse patients and families. In this way, most of the involved health care practitioners will be equipped with cultural competence. Considerations for ethical and racial specifications of the clients of this service will boost the effectiveness and fruitfulness of the HPC. Canadian society is a colorful compilation of multiple nationalities; accordingly, healthcare clients are diverse, and this divergence is also translated into HPC patients. This fact justifies the importance of studying all the cultural aspects of HPC to provide optimal care on this enormous land.

Keywords: cultural competence, end-of-life care, hospice, palliative care

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Authors: Amarendar Reddy Addula

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Definition of Artificial Intelligence: Artificial intelligence is the simulation of mortal intelligence processes by machines, especially computer systems. Explicit operations of AI comprise expert systems, natural language processing, and speech recognition, and machine vision. Artificial Intelligence (AI) is an original medium for digital business, according to a new report by Gartner. The last 10 times represent an advance period in AI’s development, prodded by the confluence of factors, including the rise of big data, advancements in cipher structure, new machine literacy ways, the materialization of pall computing, and the vibrant open- source ecosystem. Influence of AI to a broader set of use cases and druggies and its gaining fashionability because it improves AI’s versatility, effectiveness, and rigidity. Edge AI will enable digital moments by employing AI for real- time analytics closer to data sources. Gartner predicts that by 2025, further than 50 of all data analysis by deep neural networks will do at the edge, over from lower than 10 in 2021. Responsible AI is a marquee term for making suitable business and ethical choices when espousing AI. It requires considering business and societal value, threat, trust, translucency, fairness, bias mitigation, explainability, responsibility, safety, sequestration, and nonsupervisory compliance. Responsible AI is ever more significant amidst growing nonsupervisory oversight, consumer prospects, and rising sustainability pretensions. Generative AI is the use of AI to induce new vestiges and produce innovative products. To date, generative AI sweats have concentrated on creating media content similar as photorealistic images of people and effects, but it can also be used for law generation, creating synthetic irregular data, and designing medicinals and accoutrements with specific parcels. AI is the subject of a wide- ranging debate in which there's a growing concern about its ethical and legal aspects. Constantly, the two are varied and nonplussed despite being different issues and areas of knowledge. The ethical debate raises two main problems the first, abstract, relates to the idea and content of ethics; the alternate, functional, and concerns its relationship with the law. Both set up models of social geste, but they're different in compass and nature. The juridical analysis is grounded on anon-formalistic scientific methodology. This means that it's essential to consider the nature and characteristics of the AI as a primary step to the description of its legal paradigm. In this regard, there are two main issues the relationship between artificial and mortal intelligence and the question of the unitary or different nature of the AI. From that theoretical and practical base, the study of the legal system is carried out by examining its foundations, the governance model, and the nonsupervisory bases. According to this analysis, throughout the work and in the conclusions, International Law is linked as the top legal frame for the regulation of AI.

Keywords: artificial intelligence, ethics & human rights issues, laws, international laws

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Authors: Clorinda Hogan, Shaun Abbott, Mark Halaki, Marcela Torres Catiglioni, Goshi Yamauchi, Lachlan Mitchell, James Salter, Michael Romann, Stephen Cobley

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Introduction: Common annual age-group competition structures unintentionally introduce participation inequalities, performance (dis)advantages and selection biases due to the effect of maturational variation between youth swimmers. On this basis, there are implications for improving performance evaluation strategies. Therefore the aim was to: (1) To determine maturity timing distributions in female youth swimming; (2) quantify the relationship between maturation status and 100-m FC performance; (3) apply Maturational-based Corrective Adjustment Procedures (Mat-CAPs) for removal of maturational status performance influences. Methods: (1) Cross-sectional analysis of 663 female (10-15 years) swimmers who underwent assessment of anthropometrics (mass, height and sitting height) and estimations of maturity timing and offset. (2) 100-m front-crawl performance (seconds) was assessed at Australian regional, state, and national-level competitions between 2016-2020. To determine the relationship between maturation status and 100-m front-crawl performance, MO was plotted against 100-m FC performance time. The expected maturity status - performance relationship for females aged 10-15 years of age was obtained through a quadratic function (y = ax2 + bx + c) from unstandardized coefficients. The regression equation was subsequently used for Mat-CAPs. (3) Participants aged 10-13 years were categorised into maturity-offset categories. Maturity offset distributions for Raw (‘All’, ‘Top 50%’ & ‘Top 25%’) and Correctively Adjusted swim times were examined. Chi-square, Cramer’s V and ORs determined the occurrence of maturation biases for each age group and selection level. Results—: (1) Maturity timing distributions illustrated overrepresentation of ‘normative’ maturing swimmers (11.82 ± 0.40 years), with a descriptive shift toward the early maturing relative to the normative population. (2) A curvilinear relationship between maturity-offset and swim performance was identified (R2 = 0.53, P < 0.001) and subsequently utilised for Mat-CAPs. (3) Raw maturity offset categories identified partial maturation status skewing towards biologically older swimmers at 10/11 and 12 years, with effect magnitudes increasing in the ‘Top 50%’ and ‘25%’ of performance times. Following Mat-CAPs application, maturity offset biases were removed in similar age groups and selection levels. When adjusting performance times for maturity offset, Mat-CAPs was successful in mitigating against maturational biases until approximately 1-year post Peak Height Velocity. The overrepresentation of ‘normative’ maturing female swimmers contrasted with the substantial overrepresentation of ‘early’ maturing male swimmers found previously in 100-m front-crawl. These findings suggest early maturational timing is not advantageous in females, but findings associated with Aim 2, highlight how advanced maturational status remained beneficial to performance. Observed differences between female and male maturational biases may relate to the differential impact of physiological development during pubertal years. Females experience greater increases of fat mass and potentially differing changes in body shape which can negatively affect swim performance. Conclusions: Transient maturation status-based participation and performance advantages were apparent within a large sample of Australian female youth 100-m FC swimmers. By removing maturity status performance biases within female youth swimming, Mat-CAPs could help improve participation experiences and the accuracy of identifying genuinely skilled female youth swimmers.

Keywords: athlete development, long-term sport participation, performance evaluation, talent identification, youth competition

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Authors: Till Gramberg, Erwin Gross, Christoph Birenbaum

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This paper presents the approach of the Easy2IoT research project. Easy2IoT aims to enable companies in the prefabrication sheet metal and sheet metal processing industry to enter the Industrial Internet of Things (IIoT) with a low-threshold and cost-effective approach. It focuses on the development of physical hardware and software to easily capture machine activities from on a sawing machine, benefiting various stakeholders in the SME value chain, including machine operators, tool manufacturers and service providers. The methodological approach of Easy2IoT includes an in-depth requirements analysis and customer interviews with stakeholders along the value chain. Based on these insights, actions, requirements and potential solutions for smart services are derived. The focus is on providing actionable recommendations, competencies and easy integration through no-/low-code applications to facilitate implementation and connectivity within production networks. At the core of the project is a novel, non-invasive measurement and analysis system that can be easily deployed and made IIoT-ready. This system collects machine data without interfering with the machines themselves. It does this by non-invasively measuring the tension on a sawing machine. The collected data is then connected and analyzed using artificial intelligence (AI) to provide smart services through a platform-based application. Three Smart Services are being developed within Easy2IoT to provide immediate benefits to users: Wear part and product material condition monitoring and predictive maintenance for sawing processes. The non-invasive measurement system enables the monitoring of tool wear, such as saw blades, and the quality of consumables and materials. Service providers and machine operators can use this data to optimize maintenance and reduce downtime and material waste. Optimize Overall Equipment Effectiveness (OEE) by monitoring machine activity. The non-invasive system tracks machining times, setup times and downtime to identify opportunities for OEE improvement and reduce unplanned machine downtime. Estimate CO2 emissions for connected machines. CO2 emissions are calculated for the entire life of the machine and for individual production steps based on captured power consumption data. This information supports energy management and product development decisions. The key to Easy2IoT is its modular and easy-to-use design. The non-invasive measurement system is universally applicable and does not require specialized knowledge to install. The platform application allows easy integration of various smart services and provides a self-service portal for activation and management. Innovative business models will also be developed to promote the sustainable use of the collected machine activity data. The project addresses the digitalization gap between large enterprises and SME. Easy2IoT provides SME with a concrete toolkit for IIoT adoption, facilitating the digital transformation of smaller companies, e.g. through retrofitting of existing machines.

Keywords: smart services, IIoT, IIoT-platform, industrie 4.0, big data

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Authors: Sarah Niklas, Lynne Chester, Mark Diesendorf

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Geopolitical tensions, climate change and recent movements favouring a transformative shift in institutional power structures have influenced the economics of conventional energy supply for decades. This study takes a multi-dimensional approach to illustrate the potential of renewable energy (RE) technology to provide a pathway to a low-carbon economy driven by ecologically sustainable, independent and socially just energy. This comparative analysis identifies economic, political and social drivers that shaped the adoption of RE policy in two significantly different economies, Germany and Australia, with strong and weak commitments to RE respectively. Two complementary political-economy theories frame the document-based analysis. Régulation Theory, inspired by Marxist ideas and strongly influenced by contemporary economic problems, provides the background to explore the social relationships contributing the adoption of RE within the macro-economy. Varieties of Capitalism theory, a more recently developed micro-economic approach, examines the nature of state-firm relationships. Together these approaches provide a comprehensive lens of analysis. Germany’s energy policy transformed substantially over the second half of the last century. The development is characterised by the coordination of societal, environmental and industrial demands throughout the advancement of capitalist regimes. In the Fordist regime, mass production based on coal drove Germany’s astounding economic recovery during the post-war period. Economic depression and the instability of institutional arrangements necessitated the impulsive seeking of national security and energy independence. During the postwar Flexi-Fordist period, quality-based production, innovation and technology-based competition schemes, particularly with regard to political power structures in and across Europe, favoured the adoption of RE. Innovation, knowledge and education were institutionalized, leading to the legislation of environmental concerns. Lastly the establishment of government-industry-based coordinative programs supported the phase out of nuclear power and the increased adoption of RE during the last decade. Australia’s energy policy is shaped by the country’s richness in mineral resources. Energy policy largely served coal mining, historically and currently one of the most capital-intense industry. Assisted by the macro-economic dimensions of institutional arrangements, social and financial capital is orientated towards the export-led and strongly demand-oriented economy. Here energy policy serves the maintenance of capital accumulation in the mining sector and the emerging Asian economies. The adoption of supportive renewable energy policy would challenge the distinct role of the mining industry within the (neo)-liberal market economy. The state’s protective role of the mining sector has resulted in weak commitment to RE policy and investment uncertainty in the energy sector. Recent developments, driven by strong public support for RE, emphasize the sense of community in urban and rural areas and the emergence of a bottom-up approach to adopt renewables. Thus, political economy frameworks on both the macro-economic (Regulation Theory) and micro-economic (Varieties of Capitalism theory) scales can together explain the strong commitment to RE in Germany vis-à-vis the weak commitment in Australia.

Keywords: political economy, regulation theory, renewable energy, social relationships, energy transitions

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Authors: Igor A. Krichtafovitch

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The evolutionary processes are not linear. Long periods of quiet and slow development turn to rather rapid emergences of new species and even phyla. During Cambrian explosion, 22 new phyla were added to the previously existed 3 phyla. Contrary to the common credence the natural selection or a survival of the fittest cannot be accounted for the dominant evolution vector which is steady and accelerated advent of more complex and more intelligent living organisms. Neither Darwinism nor alternative concepts including panspermia and intelligent design propose a satisfactory solution for these phenomena. The proposed hypothesis offers a logical and plausible explanation of the evolutionary processes in general. It is based on two postulates: a) the Biosphere is a single living organism, all parts of which are interconnected, and b) the Biosphere acts as a giant biological supercomputer, storing and processing the information in digital and analog forms. Such supercomputer surpasses all human-made computers by many orders of magnitude. Living organisms are the product of intelligent creative action of the biosphere supercomputer. The biological evolution is driven by growing amount of information stored in the living organisms and increasing complexity of the biosphere as a single organism. Main evolutionary vector is not a survival of the fittest but an accelerated growth of the computational complexity of the living organisms. The following postulates may summarize the proposed hypothesis: biological evolution as a natural life origin and development is a reality. Evolution is a coordinated and controlled process. One of evolution’s main development vectors is a growing computational complexity of the living organisms and the biosphere’s intelligence. The intelligent matter which conducts and controls global evolution is a gigantic bio-computer combining all living organisms on Earth. The information is acting like a software stored in and controlled by the biosphere. Random mutations trigger this software, as is stipulated by Darwinian Evolution Theories, and it is further stimulated by the growing demand for the Biosphere’s global memory storage and computational complexity. Greater memory volume requires a greater number and more intellectually advanced organisms for storing and handling it. More intricate organisms require the greater computational complexity of biosphere in order to keep control over the living world. This is an endless recursive endeavor with accelerated evolutionary dynamic. New species emerge when two conditions are met: a) crucial environmental changes occur and/or global memory storage volume comes to its limit and b) biosphere computational complexity reaches critical mass capable of producing more advanced creatures. The hypothesis presented here is a naturalistic concept of life creation and evolution. The hypothesis logically resolves many puzzling problems with the current state evolution theory such as speciation, as a result of GM purposeful design, evolution development vector, as a need for growing global intelligence, punctuated equilibrium, happening when two above conditions a) and b) are met, the Cambrian explosion, mass extinctions, happening when more intelligent species should replace outdated creatures.

Keywords: supercomputer, biological evolution, Darwinism, speciation

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Authors: Chao-Yang Huang, Rwey-Hua Cherng, Chung-Lin Fu, Yuan-Lung Lo

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Solar energy is one of the replaceable choices to reduce the CO2 emission produced by conventional power plants in the modern society. As an island which is frequently visited by strong typhoons and earthquakes, it is an urgent issue for Taiwan to make an effort in revising the local regulations to strengthen the safety design of photovoltaic systems. Currently, the Taiwanese code for wind resistant design of structures does not have a clear explanation on photovoltaic systems, especially when the systems are arranged in arrayed format. Furthermore, when the arrayed photovoltaic system is mounted on the rooftop, the approaching flow is significantly altered by the building and led to different pressure pattern in the different area of the photovoltaic system. In this study, L-shape arrayed photovoltaic system is mounted on the ground of the wind tunnel and then mounted on the building rooftop. The system is consisted of 60 PV models. Each panel model is equivalent to a full size of 3.0 m in depth and 10.0 m in length. Six pressure taps are installed on the upper surface of the panel model and the other six are on the bottom surface to measure the net pressures. Wind attack angle is varied from 0° to 360° in a 10° interval for the worst concern due to wind direction. The sampling rate of the pressure scanning system is set as high enough to precisely estimate the peak pressure and at least 20 samples are recorded for good ensemble average stability. Each sample is equivalent to 10-minute time length in full scale. All the scale factors, including timescale, length scale, and velocity scale, are properly verified by similarity rules in low wind speed wind tunnel environment. The purpose of L-shape arrayed system is for the understanding the pressure characteristics at the corner area. Extreme value analysis is applied to obtain the design pressure coefficient for each net pressure. The commonly utilized Cook-and-Mayne coefficient, 78%, is set to the target non-exceedance probability for design pressure coefficients under Gumbel distribution. Best linear unbiased estimator method is utilized for the Gumbel parameter identification. Careful time moving averaging method is also concerned in data processing. Results show that when the arrayed photovoltaic system is mounted on the ground, the first row of the panels reveals stronger positive pressure than that mounted on the rooftop. Due to the flow separation occurring at the building edge, the first row of the panels on the rooftop is most in negative pressures; the last row, on the other hand, shows positive pressures because of the flow reattachment. Different areas also have different pressure patterns, which corresponds well to the regulations in ASCE7-16 describing the area division for design values. Several minor observations are found according to parametric studies, such as rooftop edge effect, parapet effect, building aspect effect, row interval effect, and so on. General comments are then made for the proposal of regulation revision in Taiwanese code.

Keywords: aerodynamic force coefficient, ground-mounted, roof-mounted, wind tunnel test, photovoltaic

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Authors: Diane Ghanem, Arjun Gupta, Rohan Vijayan, Ali Uneri, Babar Shafiq

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Introduction: Ankle sprains and fractures often result in syndesmosis injuries. Unstable syndesmotic injuries result from relative motion between the distal ends of the tibia and fibula, anatomic juncture which should otherwise be rigid, and warrant operative management. Clinical and radiological evaluations of intraoperative syndesmosis stability remain a challenging task as traditional 2D fluoroscopy is limited to a uniplanar translational displacement. The purpose of this pilot cadaveric study is to compare the 2D fluoroscopy and 3D cone beam computed tomography (CBCT) stress-induced syndesmosis displacements. Methods: Three fresh-frozen lower legs underwent 2D fluoroscopy and 3D CIOS CBCT to measure syndesmosis position before dissection. Syndesmotic injury was simulated by resecting the (1) anterior inferior tibiofibular ligament (AITFL), the (2) posterior inferior tibiofibular ligament (PITFL) and the inferior transverse ligament (ITL) simultaneously, followed by the (3) interosseous membrane (IOM). Manual external rotation and Cotton stress test were performed after each of the three resections and 2D and 3D images were acquired. Relevant 2D and 3D parameters included the tibiofibular overlap (TFO), tibiofibular clear space (TCS), relative rotation of the fibula, and anterior-posterior (AP) and medial-lateral (ML) translations of the fibula relative to the tibia. Parameters were measured by two independent observers. Inter-rater reliability was assessed by intraclass correlation coefficient (ICC) to determine measurement precision. Results: Significant mismatches were found in the trends between the 2D and 3D measurements when assessing for TFO, TCS and AP translation across the different resection states. Using 3D CBCT, TFO was inversely proportional to the number of resected ligaments while TCS was directly proportional to the latter across all cadavers and ‘resection + stress’ states. Using 2D fluoroscopy, this trend was not respected under the Cotton stress test. 3D AP translation did not show a reliable trend whereas 2D AP translation of the fibula was positive under the Cotton stress test and negative under the external rotation. 3D relative rotation of the fibula, assessed using the Tang et al. ratio method and Beisemann et al. angular method, suggested slight overall internal rotation with complete resection of the ligaments, with a change < 2mm - threshold which corresponds to the commonly used buffer to account for physiologic laxity as per clinical judgment of the surgeon. Excellent agreement (>0.90) was found between the two independent observers for each of the parameters in both 2D and 3D (overall ICC 0.9968, 95% CI 0.995 - 0.999). Conclusions: The 3D CIOS CBCT appears to reliably depict the trend in TFO and TCS. This might be due to the additional detection of relevant rotational malpositions of the fibula in comparison to the standard 2D fluoroscopy which is limited to a single plane translation. A better understanding of 3D imaging may help surgeons identify the precise measurements planes needed to achieve better syndesmosis repair.

Keywords: 2D fluoroscopy, 3D computed tomography, image processing, syndesmosis injury

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Authors: Lara Bettinelli, Bernhard Glatz, Josef Fink

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Planning engineers and researchers use various calculation models with different levels of complexity, calculation efficiency and accuracy in dynamic calculations of railway bridges under high-speed traffic. When choosing a vehicle model to depict the dynamic loading on the bridge structure caused by passing high-speed trains, different goals are pursued: On the one hand, the selected vehicle models should allow the calculation of a bridge’s vibrations as realistic as possible. On the other hand, the computational efficiency and manageability of the models should be preferably high to enable a wide range of applications. The commonly adopted and straightforward vehicle model is the moving load model (MLM), which simplifies the train to a sequence of static axle loads moving at a constant speed over the structure. However, the MLM can significantly overestimate the structure vibrations, especially when resonance events occur. More complex vehicle models, which depict the train as a system of oscillating and coupled masses, can reproduce the interaction dynamics between the vehicle and the bridge superstructure to some extent and enable the calculation of more realistic bridge accelerations. At the same time, such multi-body models require significantly greater processing capacities and precise knowledge of various vehicle properties. The European standards allow for applying the so-called additional damping method when simple load models, such as the MLM, are used in dynamic calculations. An additional damping factor depending on the bridge span, which should take into account the vibration-reducing benefits of the vehicle-bridge interaction, is assigned to the supporting structure in the calculations. However, numerous studies show that when the current standard specifications are applied, the calculation results for the bridge accelerations are in many cases still too high compared to the measured bridge accelerations, while in other cases, they are not on the safe side. A proposal to calculate the additional damping based on extensive dynamic calculations for a parametric field of simply supported bridges with a ballasted track was developed to address this issue. In this contribution, several different approaches to determine the additional damping of the supporting structure considering the vehicle-bridge interaction when using the MLM are compared with one another. Besides the standard specifications, this includes the approach mentioned above and two additional recently published alternative formulations derived from analytical approaches. For a bridge catalogue of 65 existing bridges in Austria in steel, concrete or composite construction, calculations are carried out with the MLM for two different high-speed trains and the different approaches for additional damping. The results are compared with the calculation results obtained by applying a more sophisticated multi-body model of the trains used. The evaluation and comparison of the results allow assessing the benefits of different calculation concepts for the additional damping regarding their accuracy and possible applications. The evaluation shows that by applying one of the recently published redesigned additional damping methods, the calculation results can reflect the influence of the vehicle-bridge interaction on the design-relevant structural accelerations considerably more reliable than by using normative specifications.

Keywords: Additional Damping Method, Bridge Dynamics, High-Speed Railway Traffic, Vehicle-Bridge-Interaction

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Authors: Sivananth Murugesan, I. Regupathi, B. Vishwas Prabhu, Ankit Devatwal, Vishnu Sivan Pillai

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Pectinase is an important enzyme which has a wide range of applications including textile processing and bioscouring of cotton fibers, coffee and tea fermentation, purification of plant viruses, oil extraction etc. Selective separation and purification of pectinase from fermentation broth and recover the enzyme form process stream for reuse are cost consuming process in most of the enzyme based industries. It is difficult to identify a suitable medium to enhance enzyme activity and retain its enzyme characteristics during such processes. The cost effective, selective separation of enzymes through the modified Liquid-liquid extraction is of current research interest worldwide. Reverse micellar extraction, globally acclaimed Liquid-liquid extraction technique is well known for its separation and purification of solutes from the feed which offers higher solute specificity and partitioning, ease of operation and recycling of extractants used. Surfactant concentrations above critical micelle concentration to an apolar solvent form micelles and addition of micellar phase to water in turn forms reverse micelles or water-in-oil emulsions. Since, electrostatic interaction plays a major role in the separation/purification of solutes using reverse micelles. These interaction parameters can be altered with the change in pH, addition of cosolvent, surfactant and electrolyte and non-electrolyte. Even though many chemical based commercial surfactant had been utilized for this purpose, the biosurfactants are more suitable for the purification of enzymes which are used in food application. The present work focused on the partitioning of pectinase from the synthetic aqueous solution within the reverse micelle phase formed by a biosurfactant, Soybean Lecithin dissolved in chloroform. The critical micelle concentration of soybean lecithin/chloroform solution was identified through refractive index and density measurements. Effect of surfactant concentrations above and below the critical micelle concentration was considered to study its effect on enzyme activity, enzyme partitioning within the reverse micelle phase. The effect of pH and electrolyte salts on the partitioning behavior was studied by varying the system pH and concentration of different salts during forward and back extraction steps. It was observed that lower concentrations of soybean lecithin enhanced the enzyme activity within the water core of the reverse micelle with maximizing extraction efficiency. The maximum yield of pectinase of 85% with a partitioning coefficient of 5.7 was achieved at 4.8 pH during forward extraction and 88% yield with a partitioning coefficient of 7.1 was observed during backward extraction at a pH value of 5.0. However, addition of salt decreased the enzyme activity and especially at higher salt concentrations enzyme activity declined drastically during both forward and back extraction steps. The results proved that reverse micelles formed by Soybean Lecithin and chloroform may be used for the extraction of pectinase from aqueous solution. Further, the reverse micelles can be considered as nanoreactors to enhance enzyme activity and maximum utilization of substrate at optimized conditions, which are paving a way to process intensification and scale-down.

Keywords: pectinase, reverse micelles, soybean lecithin, selective partitioning

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Authors: Mohiuddin Ahsanul Kabir Chowdhury, Nafisa Lira Huq, Afroza Khanom, Rafiqul Islam, Abdullah Nurus Salam Khan, Farhana Karim, Nabila Zaka, Shams El Arifeen, Sk. Masum Billah

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After having astounding achievements in reducing maternal mortality and achieving the target for Millennium Development Goal (MDG) 5, the Government of Bangladesh has set new target to reduce Maternal Mortality Ratio (MMR) to 70 per 100,000 live births aligning with targets of Sustainable Development Goals (SDGs). Aversion of deaths from maternal complication by ensuring quality health care could be an important path to accelerate the rate of reduction of MMR. This formative research was aimed at exploring the provision of quality maternal health services at different level of health facilities. The study was conducted in 1 district hospital (DH) and 4 Upazila health complexes (UHC) of Kurigram district of Bangladesh, utilizing both quantitative and qualitative research methods. We conducted 14 key informant interviews with facility managers and 20 in-depth interviews with health care providers and support staff. Besides, we observed 387 normal deliveries from which we found 17 cases of post partum haemorrhage (PPH) and 2 cases of eclampsia during the data collection period extended from July-September 2016. The quantitative data were analyzed by using descriptive statistics, and the qualitative component underwent thematic analysis with the broad themes of facility readiness for maternal complication management, and management of complications. Inadequacy in human resources has been identified as the most important bottleneck to provide quality care to manage maternal complications. The DH had a particular paucity of human resources in medical officer cadre where about 61% posts were unfilled. On the other hand, in the UHCs the positions mostly empty were obstetricians (75%, paediatricians (75%), staff nurses (65%), and anaesthetists (100%). The workload on the existing staff is increased because of the persistence of vacant posts. Unavailability of anesthetists and consultants does not permit the health care providers (HCP) of lower cadres to perform emergency operative procedures and forces them to refer the patients although referral system is not well organized in rural Bangladesh. Insufficient bed capacity, inadequate training, shortage of emergency medicines etc. are other hindrance factors for facility readiness. Among the 387 observed delivery case, 17 (4.4%) were identified as PPH cases, and only 2 cases were found as eclampsia/pre-eclampsia. The majority of the patients were treated with uterine message (16 out of 17, 94.1%) and injectable Oxytocin (14 out of 17, 82.4%). The providers of DH mentioned that they can manage the PPH because of having provision for diagnostic and blood transfusion services, although not as 24/7 services. Regarding management of eclampsia/pre-eclampsia, HCPs provided Diazepam, MgSO4, and other anti-hypertensives. The UHCs did not have MgSO4 at stock even, and one facility manager admitted that they treat eclampsia with Diazepam only. The nurses of the UHCs were found to be afraid to handle eclampsia cases. The upcoming interventions must ensure refresher training of service providers, continuous availability of essential medicine and equipment needed for complication management, availability of skilled health workforce, availability of functioning blood transfusion unit and pairing of consultants and anaesthetists to reach the newly set targets altogether.

Keywords: Bangladesh, health facilities, maternal complications, quality of care

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Authors: Emma J. Dale, Christina D. Buesching, Kevin R. Theis, David W. Macdonald

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This study investigates the oral and intestinal microbiomes of wild-living European badgers (Meles meles) and will relate inter-individual differences to social contact networks, somatic and reproductive fitness, varying susceptibility to bovine tuberculous (bTB) and to the olfactory advertisement. Badgers are an interesting model for this research, as they have great variation in body condition, despite living in complex social networks and having access to the same resources. This variation in somatic fitness, in turn, affects breeding success, particularly in females. We postulate that microbiota have a central role to play in determining the successfulness of an individual. Our preliminary results, characterising the microbiota of individual badgers, indicate unique compositions of microbiota communities within social groups of badgers. This basal information will inform further questions related to the extent microbiota influence fitness. Hitherto, the potential role of microbiota has not been considered in determining host condition, but also other key fitness variables, namely; communication and resistance to disease. Badgers deposit their faeces in communal latrines, which play an important role in olfactory communication. Odour profiles of anal and subcaudal gland secretions are highly individual-specific and encode information about group-membership and fitness-relevant parameters, and their chemical composition is strongly dependent on symbiotic microbiota. As badgers sniff/ lick (using their Vomeronasal organ) and over-mark faecal deposits of conspecifics, these microbial communities can be expected to vary with social contact networks. However, this is particularly important in the context of bTB, where badgers are assumed to transmit bTB to cattle as well as conspecifics. Interestingly, we have found that some individuals are more susceptible to bTB than are others. As acquired immunity and thus potential susceptibility to infectious diseases are known to depend also on symbiotic microbiota in other members of the mustelids, a role of particularly oral microbiota can currently not be ruled out as a potential explanation for inter-individual differences in infection susceptibility of bTB in badgers. Tri annually badgers are caught in the context of a long-term population study that began in 1987. As all badgers receive an individual tattoo upon first capture, age, natal as well as previous and current social group-membership and other life history parameters are known for all animals. Swabs (subcaudal ‘scent gland’, anal, genital, nose, mouth and ear) and fecal samples will be taken from all individuals, stored at -80oC until processing. Microbial samples will be processed and identified at Wayne State University’s Theis (Host-Microbe Interactions) Lab, using High Throughput Sequencing (16S rRNA-encoding gene amplification and sequencing). Acknowledgments: Gas-Chromatography/ Mass-spectrometry (in the context of olfactory communication) analyses will be performed through an established collaboration with Dr. Veronica Tinnesand at Telemark University, Norway.

Keywords: communication, energetics, fitness, free-ranging animals, immunology

Procedia PDF Downloads 178

Authors: Dean Sinković, Tea Golja, Morena Paulišić

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Upon the end of the vicious war in former Yugoslavia in 1995, international development community widely promoted microfinance as the key development framework to eradicate poverty, create jobs, increase income. Widespread claims were made that microfinance institutions would play vital role in creating a bedrock for sustainable ‘bottom-up’ economic development trajectory, thus, helping newly formed states to find proper way from economic post-war depression. This uplifting neoliberal narrative has no empirical support in the Republic of Croatia. Firstly, the type of enterprises created via microfinance sector are small, unskilled, labor intensive, no technology and with huge debt burden. This results in extremely high failure rates of microenterprises and poor individuals plunging into even deeper poverty, acute indebtedness and social marginalization. Secondly, evidence shows that microcredit is exact reflection of dangerous and destructive sub-prime lending model with ‘boom-to-bust’ scenarios in which benefits are solely extracted by the tiny financial and political elite working around the microfinance sector. We argue that microcredit providers are not proper financial structures through which developing countries should look way out of underdevelopment and poverty. In order to achieve sustainable long-term growth goals, public policy needs to focus on creating, supporting and facilitating the small and mid-size enterprises development. These enterprises should be technically sophisticated, capable of creating new capabilities and innovations, with managerial expertise (skills formation) and inter-connected with other organizations (i.e. clusters, networks, supply chains, etc.). Evidence from South-East Europe suggest that such structures are not created via microfinance model but can be fostered through various forms of social enterprises. Various legal entities may operate as social enterprises: limited liability private company, limited liability public company, cooperative, associations, foundations, institutions, Mutual Insurances and Credit union. Our main hypothesis is that cooperatives are potential agents of social and economic transformation and community development in the region. Financial cooperatives are structures that can foster more efficient allocation of financial resources involving deeper democratic arrangements and more socially just outcomes. In Croatia, pioneers of the first social enterprises were civil society organizations whilst forming a separated legal entity. (i.e. cooperatives, associations, commercial companies working on the principles of returning the investment to the founder). Ever since 1995 cooperatives in Croatia have not grown by pursuing their own internal growth but mostly by relying on external financial support. The greater part of today’s registered cooperatives tend to be agricultural (39%), followed by war veterans cooperatives (38%) and others. There are no financial cooperatives in Croatia. Due to the above mentioned we look at the historical developments and the prevailing social enterprises forms and discuss their advantages and disadvantages as potential agents for social and economic transformation and community development in the region. There is an evident lack of understanding of this business model and of its potential for social and economic development followed by an unfavorable institutional environment. Thus, we discuss the role of governance and management in the formation of social enterprises in Croatia, stressing the challenges for the governance of the country’s social enterprise movement.

Keywords: financial cooperatives, governance and management models, microfinance institutions, social enterprises

Procedia PDF Downloads 262

Authors: Angelos Evangelou, Katerina Loizou, Loukas Koutsokeras, Orestes Marangos, Giorgos Constantinides, Stylianos Yiatros, Katerina Sofocleous, Vasileios Drakonakis

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Owing to their outstanding strength to weight properties, carbon fiber reinforced polymer (CFRPs) composites have attracted significant attention finding use in various fields (sports, automotive, transportation, etc.). The current momentum indicates that there is an increasing demand for their employment in high value bespoke applications such as avionics and electronic casings, damage sensing structures, EMI (electromagnetic interference) structures that dictate the use of materials with increased electrical conductivity both in-plane and through the thickness. Several efforts by research groups have focused on enhancing the through-thickness electrical conductivity of FRPs, in an attempt to combine the intrinsically high relative strengths exhibited with improved z-axis electrical response as well. However, only a limited number of studies deal with printing of nano-enhanced polymer inks to produce a pattern on dry fabric level that could be used to fabricate CFRPs with improved through thickness electrical conductivity. The present study investigates the employment of screen-printing process on technical dry fabrics using nano-reinforced polymer-based inks to achieve the required through thickness conductivity, opening new pathways for the application of fiber reinforced composites in niche products. Commercially available inks and in-house prepared inks reinforced with electrically conductive nanoparticles are employed, printed in different patterns. The aim of the present study is to investigate both the effect of the nanoparticle concentration as well as the droplet patterns (diameter, inter-droplet distance and coverage) to optimize printing for the desired level of conductivity enhancement in the lamina level. The electrical conductivity is measured initially at ink level to pinpoint the optimum concentrations to be employed using a “four-probe” configuration. Upon printing of the different patterns, the coverage of the dry fabric area is assessed along with the permeability of the resulting dry fabrics, in alignment with the fabrication of CFRPs that requires adequate wetting by the epoxy matrix. Results demonstrated increased electrical conductivities of the printed droplets, with increase of the conductivity from the benchmark value of 0.1 S/M to between 8 and 10 S/m. Printability of dense and dispersed patterns has exhibited promising results in terms of increasing the z-axis conductivity without inhibiting the penetration of the epoxy matrix at the processing stage of fiber reinforced composites. The high value and niche prospect of the resulting applications that can stem from CFRPs with increased through thickness electrical conductivities highlights the potential of the presented endeavor, signifying screen printing as the process to to nano-enable z-axis electrical conductivity in composite laminas. This work was co-funded by the European Regional Development Fund and the Republic of Cyprus through the Research and Innovation Foundation (Project: ENTERPRISES/0618/0013).

Keywords: CFRPs, conductivity, nano-reinforcement, screen-printing

Procedia PDF Downloads 140

Authors: Mohanad Elemary, Imose Itua, Rajeswari B. Matam

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Virologists and public health experts have been predicting potential pandemics from coronaviruses for decades. The viruses which caused the SARS and MERS pandemics and the Nipah virus led to many lost lives, but still, the COVID-19 pandemic caused by the SARS-CoV2 virus surprised many scientific communities, experts, and governments with its ease of transmission and its pathogenicity. Governments of various countries reacted by locking down entire populations to their homes to combat the devastation caused by the virus, which led to a loss of livelihood and economic hardship to many individuals and organizations. To revive national economies and support their citizens in resuming their lives, governments focused on the development and use of contact tracing apps as a digital way to track and trace exposure. Google and Apple introduced the Exposure Notification Systems (ENS) framework. Independent organizations and countries also developed different frameworks for contact tracing apps. The efficiency, popularity, and adoption rate of these various apps have been different across countries. In this paper, we present a critical analysis of the different contact tracing apps with respect to their efficiency, adoption rate and general perception, and the governmental strategies and policies, which led to the development of the applications. When it comes to the European countries, each of them followed an individualistic approach to the same problem resulting in different realizations of a similarly functioning application with differing results of use and acceptance. The study conducted an extensive review of existing literature, policies, and reports across multiple disciplines, from which a framework was developed and then validated through interviews with six key stakeholders in the field, including founders and executives in digital health startups and corporates as well as experts from international organizations like The World Health Organization. A framework of best practices and tactics is the result of this research. The framework looks at three main questions regarding the contact tracing apps; how to develop them, how to deploy them, and how to regulate them. The findings are based on the best practices applied by governments across multiple countries, the mistakes they made, and the best practices applied in similar situations in the business world. The findings include multiple strategies when it comes to the development milestone regarding establishing frameworks for cooperation with the private sector and how to design the features and user experience of the app for a transparent, effective, and rapidly adaptable app. For the deployment section, several tactics were discussed regarding communication messages, marketing campaigns, persuasive psychology, and the initial deployment scale strategies. The paper also discusses the data privacy dilemma and how to build for a more sustainable system of health-related data processing and utilization. This is done through principles-based regulations specific for health data to allow for its avail for the public good. This framework offers insights into strategies and tactics that could be implemented as protocols for future public health crises and emergencies whether global or regional.

Keywords: contact tracing apps, COVID-19, digital health applications, exposure notification system

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Authors: Saule Mussabekova

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A number of chemical elements widely presented in the nature is seldom met in people and vice versa. This is a peculiarity of accumulation of elements in the body, and their selective use regardless of widely changed parameters of external environment. Microelemental identification of human hair and particularly dead body is a new step in the development of modern forensic medicine which needs reliable criteria while identifying the person. In the condition of technology-related pressing of large industrial cities for many years and specific for each region multiple-factor toxic effect from many industrial enterprises it’s important to assess actuality and the role of researches of human hair while assessing degree of deposition with specific pollution. Hair is highly sensitive biological indicator and allows to assess ecological situation, to perform regionalism of large territories of geological and chemical methods. Besides, monitoring of concentrations of chemical elements in the regions of Kazakhstan gives opportunity to use these data while performing forensic medical identification of dead bodies of unknown persons. Methods based on identification of chemical composition of hair with further computer processing allowed to compare received data with average values for the sex, age, and to reveal causally significant deviations. It gives an opportunity preliminary to suppose the region of residence of the person, having concentrated actions of policy for search of people who are unaccounted for. It also allows to perform purposeful legal actions for its further identification having created more optimal and strictly individual scheme of personal identity. Hair is the most suitable material for forensic researches as it has such advances as long term storage properties with no time limitations and specific equipment. Besides, quantitative analysis of micro elements is well correlated with level of pollution of the environment, reflects professional diseases and with pinpoint accuracy helps not only to diagnose region of temporary residence of the person but to establish regions of his migration as well. Peculiarities of elemental composition of human hair have been established regardless of age and sex of persons residing on definite territories of Kazakhstan. Data regarding average content of 29 chemical elements in hair of population in different regions of Kazakhstan have been systemized. Coefficients of concentration of studies elements in hair relative to average values around the region have been calculated for each region. Groups of regions with specific spectrum of elements have been emphasized; these elements are accumulated in hair in quantities exceeding average indexes. Our results have showed significant differences in concentrations of chemical elements for studies groups and showed that population of Kazakhstan is exposed to different toxic substances. It depends on emissions to atmosphere from industrial enterprises dominating in each separate region. Performed researches have showed that obtained elemental composition of human hair residing in different regions of Kazakhstan reflects technogenic spectrum of elements.

Keywords: analysis of elemental composition of hair, forensic medical research of hair, identification of unknown dead bodies, microelements

Procedia PDF Downloads 137

Authors: Sonia Boscenco, Zihan Wang, Euclides José de Mendoça Filho, João Paulo Hoppe, Irina Pokhvisneva, Geoffrey B.C. Hall, Michael J. Meaney, Patricia Pelufo Silveira

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Entropy can be described as a measure of the number of states of a system, and when used in the context of physiological time-based signals, it serves as a measure of complexity. In functional connectivity data, entropy can account for the moment-to-moment variability that is neglected in traditional functional magnetic resonance imaging (fMRI) analyses. While brain fMRI resting state entropy has been associated with some pathological conditions like schizophrenia, no investigations have explored the association between brain entropy measures and individual differences in child behavior in healthy children. We describe a novel exploratory approach to evaluate brain fMRI resting state data in two child cohorts, and MAVAN (N=54, 4.5 years, 48% males) and GUSTO (N = 206, 4.5 years, 48% males) and its associations to child behavior, that can be used in future research in the context of child exposures and long-term health. Following rs-fMRI data pre-processing and Shannon entropy calculation across 32 network regions of interest to acquire 496 unique functional connections, partial correlation coefficient analysis adjusted for sex was performed to identify associations between entropy data and Strengths and Difficulties questionnaire in MAVAN and Child Behavior Checklist domains in GUSTO. Significance was set at p < 0.01, and we found eight significant associations in GUSTO. Negative associations were found between two frontoparietal regions and cerebellar posterior and oppositional defiant problems, (r = -0.212, p = 0.006) and (r = -0.200, p = 0.009). Positive associations were identified between somatic complaints and four default mode connections: salience insula (r = 0.202, p < 0.01), dorsal attention intraparietal sulcus (r = 0.231, p = 0.003), language inferior frontal gyrus (r = 0.207, p = 0.008) and language posterior superior temporal gyrus (r = 0.210, p = 0.008). Positive associations were also found between insula and frontoparietal connection and attention deficit / hyperactivity problems (r = 0.200, p < 0.01), and insula – default mode connection and pervasive developmental problems (r = 0.210, p = 0.007). In MAVAN, ten significant associations were identified. Two positive associations were found = with prosocial scores: the salience prefrontal cortex and dorsal attention connection (r = 0.474, p = 0.005) and the salience supramarginal gyrus and dorsal attention intraparietal sulcus (r = 0.447, p = 0.008). The insula and prefrontal connection were negatively associated with peer problems (r = -0.437, p < 0.01). Conduct problems were negatively associated with six separate connections, the left salience insula and right salience insula (r = -0.449, p = 0.008), left salience insula and right salience supramarginal gyrus (r = -0.512, p = 0.002), the default mode and visual network (r = -0.444, p = 0.009), dorsal attention and language network (r = -0.490, p = 0.003), and default mode and posterior parietal cortex (r = -0.546, p = 0.001). Entropy measures of resting state functional connectivity can be used to identify individual differences in brain function that are correlated with variation in behavioral problems in healthy children. Further studies applying this marker into the context of environmental exposures are warranted.

Keywords: child behaviour, functional connectivity, imaging, Shannon entropy

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Authors: Fatima Arrutia, Francisco Amador Riera

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The meat industry generates large volumes of blood as a result of meat processing. Several industrial procedures have been implemented in order to treat this by-product, but are focused on the production of low-value products, and in many cases, blood is simply discarded as waste. Besides, in addition to economic interests, there is an environmental concern due to bloodborne pathogens and other chemical contaminants found in blood. Consequently, there is a dire need to find extensive uses for blood that can be both applicable to industrial scale and able to yield high value-added products. Blood has been recognized as an important source of protein. The main blood serum protein in mammals is serum albumin. One of the top trends in food market is functional foods. Among them, bioactive peptides can be obtained from protein sources by microbiological fermentation or enzymatic and chemical hydrolysis. Bioactive peptides are short amino acid sequences that can have a positive impact on health when administered. The main drawback for bioactive peptide production is the high cost of the isolation, purification and characterization techniques (such as chromatography and mass spectrometry) that make unaffordable the scale-up. On the other hand, membrane technologies are very suitable to apply to the industry because they offer a very easy scale-up and are low-cost technologies, compared to other traditional separation methods. In this work, the possibility of obtaining bioactive peptide fractions from serum albumin by means of a simple procedure of only 2 steps (hydrolysis and membrane filtration) was evaluated, as an exploratory study for possible industrial application. The methodology used in this work was, firstly, a tryptic hydrolysis of serum albumin in order to release the peptides from the protein. The protein was previously subjected to a thermal treatment in order to enhance the enzyme cleavage and thus the peptide yield. Then, the obtained hydrolysate was filtered through a nanofiltration/ultrafiltration flat rig at three different pH values with two different membrane materials, so as to compare membrane performance. The corresponding permeates were analyzed by liquid chromatography-tandem mass spectrometry technology in order to obtain the peptide sequences present in each permeate. Finally, different concentrations of every permeate were evaluated for their in vitro antihypertensive and antioxidant activities though ACE-inhibition and DPPH radical scavenging tests. The hydrolysis process with the previous thermal treatment allowed achieving a degree of hydrolysis of the 49.66% of the maximum possible. It was found that peptides were best transmitted to the permeate stream at pH values that corresponded to their isoelectric points. Best selectivity between peptide groups was achieved at basic pH values. Differences in peptide content were found between membranes and also between pH values for the same membrane. The antioxidant activity of all permeates was high compared with the control only for the highest dose. However, antihypertensive activity was best for intermediate concentrations, rather than higher or lower doses. Therefore, although differences between them, all permeates were promising regarding antihypertensive and antioxidant properties.

Keywords: bioactive peptides, bovine serum albumin, hydrolysis, membrane filtration

Procedia PDF Downloads 188

Authors: Cristina Maria Mendoza Sanchez, Maria Angeles Navarro Perán

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Introduction: Nursing as a profession, from its initial formation and after its development in practice, has been built and identified mainly from its technical competence and professionalization within the positivist approach of the XIX century that provides a conception of the disease built on the basis of to the biomedical paradigm, where the care provided is more focused on the physiological processes and the disease than on the suffering person understood as a whole. The main issue that is in need of study here is a review of the nursing profession's history to get to know how the nursing profession was before the XIX century. It is unclear if there were organizations or people with knowledge about looking after others or if many people survived by chance. The holistic care, in which the appearance of the disease directly affects all its dimensions: physical, emotional, cognitive, social and spiritual. It is not a concept from the 21st century. It is common practice, most probably since established life in this world, with the final purpose of covering all these perspectives through quality care. Objective: In this paper, we describe and analyze the history of education in nursing learning in terms of reviewing and analysing theoretical foundations of clinical teaching and learning in nursing, with the final purpose of determining and describing the development of the nursing profession along the history. Method: We have done a descriptive systematic review study, doing a systematically searched of manuscripts and articles in the following health science databases: Pubmed, Scopus, Web of Science, Temperamentvm and CINAHL. The selection of articles has been made according to PRISMA criteria, doing a critical reading of the full text using the CASPe method. A compliment to this, we have read a range of historical and contemporary sources to support the review, such as manuals of Florence Nightingale and John of God as primary manuscripts to establish the origin of modern nursing and her professionalization. We have considered and applied ethical considerations of data processing. Results: After applying inclusion and exclusion criteria in our search, in Pubmed, Scopus, Web of Science, Temperamentvm and CINAHL, we have obtained 51 research articles. We have analyzed them in such a way that we have distinguished them by year of publication and the type of study. With the articles obtained, we can see the importance of our background as a profession before modern times in public health and as a review of our past to face challenges in the near future. Discussion: The important influence of key figures other than Nightingale has been overlooked and it emerges that nursing management and development of the professional body has a longer and more complex history than is generally accepted. Conclusions: There is a paucity of studies on the subject of the review to be able to extract very precise evidence and recommendations about nursing before modern times. But even so, as more representative data, an increase in research about nursing history has been observed. In light of the aspects analyzed, the need for new research in the history of nursing emerges from this perspective; in order to germinate studies of the historical construction of care before the XIX century and theories created then. We can assure that pieces of knowledge and ways of care were taught before the XIX century, but they were not called theories, as these concepts were created in modern times.

Keywords: nursing history, nursing theory, Saint John of God, Florence Nightingale, learning, nursing education

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Authors: S. A. Krutovertsev, A. E. Tarasova, L. S. Krutovertseva, O. M. Ivanova

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The aim of the work was to get stable sensitive films with good sensitivity to ethanolamine (C2H7NO) in air. Ethanolamine is used as adsorbent in different processes of gas purification and separation. Besides it has wide industrial application. Chemical sensors of sorption type are widely used for gas analysis. Their behavior is determined by sensor characteristics of sensitive sorption layer. Forming conditions and characteristics of chemical gas sensors based on nanostructured modified silica films activated by different admixtures have been studied. As additives molybdenum containing polyoxometalates of the eighteen series were incorporated in silica films. The method of hydrolythic polycondensation from tetraethyl orthosilicate solutions was used for forming such films in this work. The method’s advantage is a possibility to introduce active additives directly into an initial solution. This method enables to obtain sensitive thin films with high specific surface at room temperature. Particular properties make polyoxometalates attractive as active additives for forming of gas-sensitive films. As catalyst of different redox processes, they can either accelerate the reaction of the matrix with analyzed gas or interact with it, and it results in changes of matrix’s electrical properties Polyoxometalates based films were deposited on the test structures manufactured by microelectronic planar technology with interdigitated electrodes. Modified silica films were deposited by a casting method from solutions based on tetraethyl orthosilicate and polyoxometalates. Polyoxometalates were directly incorporated into initial solutions. Composite nanostructured films were deposited by drop casting method on test structures with a pair of interdigital metal electrodes formed at their surface. The sensor’s active area was 4.0 x 4.0 mm, and electrode gap was egual 0.08 mm. Morphology of the layers surface were studied with Solver-P47 scanning probe microscope (NT-MDT, Russia), the infrared spectra were investigated by a Bruker EQUINOX 55 (Germany). The conditions of film formation varied during the tests. Electrical parameters of the sensors were measured electronically in real-time mode. Films had highly developed surface with value of 450 m2/g and nanoscale pores. Thickness of them was 0,2-0,3 µm. The study shows that the conditions of the environment affect markedly the sensors characteristics, which can be improved by choosing of the right procedure of forming and processing. Addition of polyoxometalate into silica film resulted in stabilization of film mass and changed markedly of electrophysical characteristics. Availability of Mn3P2Mo18O62 into silica film resulted in good sensitivity and selectivity to ethanolamine. Sensitivity maximum was observed at weight content of doping additive in range of 30–50% in matrix. With ethanolamine concentration changing from 0 to 100 ppm films’ conductivity increased by 10-12 times. The increase of sensor’s sensitivity was received owing to complexing reaction of tested substance with cationic part of polyoxometalate. This fact results in intramolecular redox reaction which sharply change electrophysical properties of polyoxometalate. This process is reversible and takes place at room temperature.

Keywords: ethanolamine, gas analysis, polyoxometalate, silica film

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Authors: Amanda Kavner, Richard Lamb

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Faster growth in science and technology of other nations may make staying globally competitive more difficult without shifting focus on how science is taught in US classes. An integral part of learning science involves visual and spatial thinking since complex, and real-world phenomena are often expressed in visual, symbolic, and concrete modes. The primary barrier to spatial thinking and visual literacy in Science, Technology, Engineering, and Math (STEM) fields is representational competence, which includes the ability to generate, transform, analyze and explain representations, as opposed to generic spatial ability. Although the relationship is known between the foundational visual literacy and the domain-specific science literacy, science literacy as a function of science learning is still not well understood. Moreover, the need for a more reliable measure is necessary to design resources which enhance the fundamental visuospatial cognitive processes behind scientific literacy. To support the improvement of students’ representational competence, first visualization skills necessary to process these science representations needed to be identified, which necessitates the development of an instrument to quantitatively measure visual literacy. With such a measure, schools, teachers, and curriculum designers can target the individual skills necessary to improve students’ visual literacy, thereby increasing science achievement. This project details the development of an artificial neural network capable of measuring science literacy using functional Near-Infrared Spectroscopy (fNIR) data. This data was previously collected by Project LENS standing for Leveraging Expertise in Neurotechnologies, a Science of Learning Collaborative Network (SL-CN) of scholars of STEM Education from three US universities (NSF award 1540888), utilizing mental rotation tasks, to assess student visual literacy. Hemodynamic response data from fNIRsoft was exported as an Excel file, with 80 of both 2D Wedge and Dash models (dash) and 3D Stick and Ball models (BL). Complexity data were in an Excel workbook separated by the participant (ID), containing information for both types of tasks. After changing strings to numbers for analysis, spreadsheets with measurement data and complexity data were uploaded to RapidMiner’s TurboPrep and merged. Using RapidMiner Studio, a Gradient Boosted Trees artificial neural network (ANN) consisting of 140 trees with a maximum depth of 7 branches was developed, and 99.7% of the ANN predictions are accurate. The ANN determined the biggest predictors to a successful mental rotation are the individual problem number, the response time and fNIR optode #16, located along the right prefrontal cortex important in processing visuospatial working memory and episodic memory retrieval; both vital for science literacy. With an unbiased measurement of science literacy provided by psychophysiological measurements with an ANN for analysis, educators and curriculum designers will be able to create targeted classroom resources to help improve student visuospatial literacy, therefore improving science literacy.

Keywords: artificial intelligence, artificial neural network, machine learning, science literacy, neuroscience

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Authors: Keshari Shrestha, Philip Vatterott

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Introduction: Drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome is a rare and potentially fatal drug-related syndrome. DRESS classically presents with a diffuse maculopapular rash, fevers, and eosinophilia more than three weeks after drug exposure. DRESS can present with multi-organ involvement, with liver damage being the most common and severe. Pulmonary involvement is a less common manifestation and is associated with poor clinical outcomes. Chest imaging is often nonspecific, and symptoms can range from mild cough to acute respiratory distress syndrome (ARDS) . This is a case of a 49-year-old female with a history of recent clostridium difficile colitis status post treatment with oral vancomycin who presented with rash, acute liver and kidney failure, as well as diffuse nodular alveolar lung opacities concerning for DRESS syndrome with multi-organ involvement. Clinical Course: This patient initially presented to an outside hospital with clostridium difficile colitis, acute liver injury, and acute kidney injury. She developed a desquamating maculopapular rash in the setting of recent oral vancomycin, meloxicam, and furosemide initiation. She was hospitalized on two additional occasions with worsening altered mental status, liver injury, and acute kidney injury and was initiated on intermittent hemodialysis. Notably, she was found to have systemic eosinophilia (4100 cells/microliter) several weeks prior. She was transferred to this institution for further management where she was found to have encephalopathy, jaundice, lower extremity edema, and diffuse bilateral rhonchorous breath sounds on pulmonary examination. The patient was started on methylprednisolone for suspected DRESS syndrome. She underwent an evaluation for alternative causes of her organ failure. Her workup included a negative infectious, autoimmune, metabolic, toxic, and malignant work-up. Abdominal computed tomography (CT) and ultrasound were remarkable for evidence of hepatic steatosis and possible cirrhotic morphology. Additionally, a chest CT demonstrated diffuse and symmetric nodular alveolar lung opacities with peripheral sparing not consistent with acute respiratory distress syndrome or edema. Ultimately, her condition continued to decline, and she required intubation on several occasions. On hospital day 25 she succumbed to distributive shock in the setting of probable sepsis and multi-organ failure. Discussion: DRESS syndrome occurs in 1 in 1,000 to 10,000 patients with a mortality rate of around 10%. Anti-convulsant, anti-bacterial, anti-viral, and sulfonamide drugs are the most common drugs implicated in the development of DRESS syndrome; however, the list of offending agents is extensive . The diagnosis of DRESS syndrome is made after excluding other causes of disease such as infectious and autoimmune etiologies. The RegiSCAR scoring system is used to diagnose DRESS syndrome with 2-3 points indicating possible disease, 4-5 probable disease, and >5 definite disease. This patient scored a 7 on the RegiSCAR scale for eosinophilia, rash, organ involvement, and exclusion of other causes (infectious and autoimmune). While the pharmacologic trigger in this case is unknown, it is speculated to be caused by vancomycin, meloxicam, or furosemide due to the favorable timeline of initiation. Despite aggressive treatment, DRESS syndrome can often be fatal. Because of this, early diagnosis and treatment of patients with suspected DRESS syndrome is imperative.

Keywords: drug reaction with eosinophilia and systemic symptoms, multi-organ failure, pulmonary involvement, renal failure

Procedia PDF Downloads 165

Authors: Dan Kanmegne

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Africa will become the most populated continent by the end of the century, with around 4 billion inhabitants. Food security and climate changes will become continental issues since agricultural practices depend on climate but also contribute to global emissions and land degradation. Agroforestry has been identified as a cost-efficient and reliable strategy to address these two issues. It is defined as the integrated management of trees and crops/animals in the same land unit. Agroforestry provides benefits in terms of goods (fruits, medicine, wood, etc.) and services (windbreaks, fertility, etc.), and is acknowledged to have a great potential for carbon sequestration; therefore it can be integrated into reduction mechanisms of carbon emissions. Particularly in sub-Saharan Africa, the constraint stands in the lack of information about both areas under agroforestry and the characterization (composition, structure, and management) of each agroforestry system at the country level. This study describes and quantifies “what is where?”, earliest to the quantification of carbon stock in different systems. Remote sensing (RS) is the most efficient approach to map such a dynamic technology as agroforestry since it gives relatively adequate and consistent information over a large area at nearly no cost. RS data fulfill the good practice guidelines of the Intergovernmental Panel On Climate Change (IPCC) that is to be used in carbon estimation. Satellite data are getting more and more accessible, and the archives are growing exponentially. To retrieve useful information to support decision-making out of this large amount of data, satellite data needs to be organized so to ensure fast processing, quick accessibility, and ease of use. A new solution is a data cube, which can be understood as a multi-dimensional stack (space, time, data type) of spatially aligned pixels and used for efficient access and analysis. A data cube for Burkina Faso has been set up from the cooperation project between the international service provider WASCAL and Germany, which provides an accessible exploitation architecture of multi-temporal satellite data. The aim of this study is to map and characterize agroforestry systems using the Burkina Faso earth observation data cube. The approach in its initial stage is based on an unsupervised image classification of a normalized difference vegetation index (NDVI) time series from 2010 to 2018, to stratify the country based on the vegetation. Fifteen strata were identified, and four samples per location were randomly assigned to define the sampling units. For safety reasons, the northern part will not be part of the fieldwork. A total of 52 locations will be visited by the end of the dry season in February-March 2020. The field campaigns will consist of identifying and describing different agroforestry systems and qualitative interviews. A multi-temporal supervised image classification will be done with a random forest algorithm, and the field data will be used for both training the algorithm and accuracy assessment. The expected outputs are (i) map(s) of agroforestry dynamics, (ii) characteristics of different systems (main species, management, area, etc.); (iii) assessment report of Burkina Faso data cube.

Keywords: agroforestry systems, Burkina Faso, earth observation data cube, multi-temporal image classification

Procedia PDF Downloads 135

Authors: Reggie Chandra

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Trafficaccidents and traffic signal optimization are correlated. However, 70-90% of the traffic signals across the USA are not synchronized. The reason behind that is insufficient resources to create and implement timing plans. In this work, we will discuss the use of a breakthrough Artificial Intelligence (AI) technology to optimize traffic flow and collect 24/7/365 accurate traffic data using a vehicle detection system. We will discuss what are recent advances in Artificial Intelligence technology, how does AI work in vehicles, pedestrians, and bike data collection, creating timing plans, and what is the best workflow for that. Apart from that, this paper will showcase how Artificial Intelligence makes signal timing affordable. We will introduce a technology that uses Convolutional Neural Networks (CNN) and deep learning algorithms to detect, collect data, develop timing plans and deploy them in the field. Convolutional Neural Networks are a class of deep learning networks inspired by the biological processes in the visual cortex. A neural net is modeled after the human brain. It consists of millions of densely connected processing nodes. It is a form of machine learning where the neural net learns to recognize vehicles through training - which is called Deep Learning. The well-trained algorithm overcomes most of the issues faced by other detection methods and provides nearly 100% traffic data accuracy. Through this continuous learning-based method, we can constantly update traffic patterns, generate an unlimited number of timing plans and thus improve vehicle flow. Convolutional Neural Networks not only outperform other detection algorithms but also, in cases such as classifying objects into fine-grained categories, outperform humans. Safety is of primary importance to traffic professionals, but they don't have the studies or data to support their decisions. Currently, one-third of transportation agencies do not collect pedestrian and bike data. We will discuss how the use of Artificial Intelligence for data collection can help reduce pedestrian fatalities and enhance the safety of all vulnerable road users. Moreover, it provides traffic engineers with tools that allow them to unleash their potential, instead of dealing with constant complaints, a snapshot of limited handpicked data, dealing with multiple systems requiring additional work for adaptation. The methodologies used and proposed in the research contain a camera model identification method based on deep Convolutional Neural Networks. The proposed application was evaluated on our data sets acquired through a variety of daily real-world road conditions and compared with the performance of the commonly used methods requiring data collection by counting, evaluating, and adapting it, and running it through well-established algorithms, and then deploying it to the field. This work explores themes such as how technologies powered by Artificial Intelligence can benefit your community and how to translate the complex and often overwhelming benefits into a language accessible to elected officials, community leaders, and the public. Exploring such topics empowers citizens with insider knowledge about the potential of better traffic technology to save lives and improve communities. The synergies that Artificial Intelligence brings to traffic signal control and data collection are unsurpassed.

Keywords: artificial intelligence, convolutional neural networks, data collection, signal control, traffic signal

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Authors: Serhat Tüzün, Tufan Demirel

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Decision Support Systems (DSS) have been investigated by researchers and technologists for more than 35 years. This paper analyses the developments in the architecture and software of these systems, provides a systematic analysis for different Web-based DSS approaches and Intelligent Decision-making Technologies (IDT), with the suggestion for future studies. Decision Support Systems literature begins with building model-oriented DSS in the late 1960s, theory developments in the 1970s, and the implementation of financial planning systems and Group DSS in the early and mid-80s. Then it documents the origins of Executive Information Systems, online analytic processing (OLAP) and Business Intelligence. The implementation of Web-based DSS occurred in the mid-1990s. With the beginning of the new millennia, intelligence is the main focus on DSS studies. Web-based technologies are having a major impact on design, development and implementation processes for all types of DSS. Web technologies are being utilized for the development of DSS tools by leading developers of decision support technologies. Major companies are encouraging its customers to port their DSS applications, such as data mining, customer relationship management (CRM) and OLAP systems, to a web-based environment. Similarly, real-time data fed from manufacturing plants are now helping floor managers make decisions regarding production adjustment to ensure that high-quality products are produced and delivered. Web-based DSS are being employed by organizations as decision aids for employees as well as customers. A common usage of Web-based DSS has been to assist customers configure product and service according to their needs. These systems allow individual customers to design their own products by choosing from a menu of attributes, components, prices and delivery options. The Intelligent Decision-making Technologies (IDT) domain is a fast growing area of research that integrates various aspects of computer science and information systems. This includes intelligent systems, intelligent technology, intelligent agents, artificial intelligence, fuzzy logic, neural networks, machine learning, knowledge discovery, computational intelligence, data science, big data analytics, inference engines, recommender systems or engines, and a variety of related disciplines. Innovative applications that emerge using IDT often have a significant impact on decision-making processes in government, industry, business, and academia in general. This is particularly pronounced in finance, accounting, healthcare, computer networks, real-time safety monitoring and crisis response systems. Similarly, IDT is commonly used in military decision-making systems, security, marketing, stock market prediction, and robotics. Even though lots of research studies have been conducted on Decision Support Systems, a systematic analysis on the subject is still missing. Because of this necessity, this paper has been prepared to search recent articles about the DSS. The literature has been deeply reviewed and by classifying previous studies according to their preferences, taxonomy for DSS has been prepared. With the aid of the taxonomic review and the recent developments over the subject, this study aims to analyze the future trends in decision support systems.

Keywords: decision support systems, intelligent decision-making, systematic analysis, taxonomic review

Procedia PDF Downloads 271

Authors: Jara Kaye S. Villanueva, M. Rosario Concepcion O. Ang

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For the past few years, Philippines has depended most of its energy source on oil, coal, and fossil fuel. According to the Department of Energy (DOE), the dominance of coal in the energy mix will continue until the year 2020. The expanding energy needs in the country have led to increasing efforts to promote and develop renewable energy. This research is a part of the government initiative in preparation for renewable energy development and expansion in the country. The Philippine Renewable Energy Resource Mapping from Light Detection and Ranging (LiDAR) Surveys is a three-year government project which aims to assess and quantify the renewable energy potential of the country and to put them into usable maps. This study focuses on the site suitability analysis of the four renewable energy sources – biomass (coconut, corn, rice, and sugarcane), hydro, solar, and wind energy. The site assessment is a key component in determining and assessing the most suitable locations for the construction of renewable energy power plants. This method maximizes the use of both the technical methods in resource assessment, as well as taking into account the environmental, social, and accessibility aspect in identifying potential sites by utilizing and integrating two different methods: the Multi-Criteria Decision Analysis (MCDA) method and Geographic Information System (GIS) tools. For the MCDA, Analytical Hierarchy Processing (AHP) is employed to determine the parameters needed for the suitability analysis. To structure these site suitability parameters, various experts from different fields were consulted – scientists, policy makers, environmentalists, and industrialists. The need to have a well-represented group of people to consult with is relevant to avoid bias in the output parameter of hierarchy levels and weight matrices. AHP pairwise matrix computation is utilized to derive weights per level out of the expert’s gathered feedback. Whereas from the threshold values derived from related literature, international studies, and government laws, the output values were then consulted with energy specialists from the DOE. Geospatial analysis using GIS tools translate this decision support outputs into visual maps. Particularly, this study uses Euclidean distance to compute for the distance values of each parameter, Fuzzy Membership algorithm which normalizes the output from the Euclidean Distance, and the Weighted Overlay tool for the aggregation of the layers. Using the Natural Breaks algorithm, the suitability ratings of each of the map are classified into 5 discrete categories of suitability index: (1) not suitable (2) least suitable, (3) suitable, (4) moderately suitable, and (5) highly suitable. In this method, the classes are grouped based on the best groups similar values wherein each subdivision are set from the rest based on the big difference in boundary values. Results show that in the entire Philippine area of responsibility, biomass has the highest suitability rating with rice as the most suitable at 75.76% suitability percentage, whereas wind has the least suitability percentage with score 10.28%. Solar and Hydro fall in the middle of the two, with suitability values 28.77% and 21.27%.

Keywords: site suitability, biomass energy, hydro energy, solar energy, wind energy, GIS

Procedia PDF Downloads 141

Authors: Heather Mroz

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Geothermal fluids can provide a nearly unlimited source of renewable energy but are often highly corrosive due to dissolved carbon dioxide (CO2), hydrogen sulphide (H2S), Ammonia (NH3) and chloride ions. The corrosive environment drives material selection for many components, including piping, heat exchangers and pressure vessels, to higher alloys of stainless steel, nickel-based alloys and titanium. The use of these alloys is cost-prohibitive and does not offer the pressure rating of carbon steel. One solution, explosion cladding, has been proven to reduce the capital cost of the geothermal equipment while retaining the mechanical and corrosion properties of both the base metal and the cladded surface metal. Explosion cladding is a solid-state welding process that uses precision explosions to bond two dissimilar metals while retaining the mechanical, electrical and corrosion properties. The process is commonly used to clad steel with a thin layer of corrosion-resistant alloy metal, such as stainless steel, brass, nickel, silver, titanium, or zirconium. Additionally, explosion welding can join a wider array of compatible and non-compatible metals with more than 260 metal combinations possible. The explosion weld is achieved in milliseconds; therefore, no bulk heating occurs, and the metals experience no dilution. By adhering to a strict set of manufacturing requirements, both the shear strength and tensile strength of the bond will exceed the strength of the weaker metal, ensuring the reliability of the bond. For over 50 years, explosion cladding has been used in the oil and gas and chemical processing industries and has provided significant economic benefit in reduced maintenance and lower capital costs over solid construction. The focus of this paper will be on the many benefits of the use of explosion clad in process equipment instead of more expensive solid alloy construction. The method of clad-plate production with explosion welding as well as the methods employed to ensure sound bonding of the metals. It will also include the origins of explosion cladding as well as recent technological developments. Traditionally explosion clad plate was formed into vessels, tube sheets and heads but recent advances include explosion welded piping. The final portion of the paper will give examples of the use of explosion-clad metals in geothermal energy recovery. The classes of materials used for geothermal brine will be discussed, including stainless steels, nickel alloys and titanium. These examples will include heat exchangers (tube sheets), high pressure and horizontal separators, standard pressure crystallizers, piping and well casings. It is important to educate engineers and designers on material options as they develop equipment for geothermal resources. Explosion cladding is a niche technology that can be successful in many situations, like geothermal energy recovery, where high temperature, high pressure and corrosive environments are typical. Applications for explosion clad metals include vessel and heat exchanger components as well as piping.

Keywords: clad metal, explosion welding, separator material, well casing material, piping material

Procedia PDF Downloads 148

Authors: Mohammadjavad Sotoudeheian, Navid Farahmandian

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Cardiac hypertrophy arises in response to persistent increases in hemodynamic loads. In comparison, diabetic cardiomyopathy is defined by an abnormal myocardial changes without other cardiac-related risk factors. Pathological cardiac hypertrophy and myocardial remodeling are hallmarks of cardiovascular diseases and are risk factors for heart failure. The transcription factor forkhead box class O (FOXOs) can protect heart tissue by hostile oxidative stress and stimulating apoptosis and autophagy. FOXO proteins, as sensitive elements and mediators in response to environmental changes, have been revealed to prevent and inverse cardiac hypertrophy. FOXOs are inhibited by insulin and are critical mediators of insulin action. Insulin deficiency and uncontrolled diabetes lead to a catabolic state. FOXO1 acts downstream of the insulin-dependent pathways, which are dysregulated in diabetes. It regulates cardiomyocyte hypertrophy downstream of IGF1R/PI3K/Akt activation, which are critical regulators of cardiac hypertrophy. The complex network of signaling pathways comprising insulin/IGF-1 signaling, AMPK, JNK, and Sirtuins regulate the development of cardiovascular dysfunction by modulating the activity of FOXOs. Insulin receptors and IGF1R act via the PI3k/Akt and the MAPK/ERK pathways. Activation of Akt in response to insulin or IGF-1 induces phosphorylation of FOXOs. Increased protein synthesis induced by activation of the IGF-I/Akt/mTOR signaling pathway leads to hypertrophy. This pathway and the myostatin/Smad pathway are potent negative muscle development regulators. In cardiac muscle, insulin receptor substrates (IRS)-1 or IRS-2 activates the Akt signaling pathway and inactivate FOXO1. Under metabolic stress, p38 MAPK promotes degradation of IRS-1 and IRS-2 in cardiac myocytes and activates FOXO1, leading to cardiomyopathy. Sirt1 and FOXO1 interaction play an essential role in starvation-induced autophagy in cardiac metabolism. Inhibition of Angiotensin-II induced cardiomyocyte hypertrophy is associated with reduced FOXO1 acetylation and activation of Sirt1. The NF-κB, ERK, and FOXOs are de-acetylated by SIRT1. De-acetylation of FOXO1 induces the expression of genes involved in autophagy and stimulates autophagy flux. Therefore, under metabolic stress, FOXO1 can cause diabetic cardiomyopathy. The overexpression of FOXO1 leads to decreased cardiomyocyte size and suppresses cardiac hypertrophy through inhibition of the calcineurin–NFAT pathway. Diabetes mellitus is associated with elevation of O-GlcNAcylation. Some of its binding partners regulate the substrate selectivity of O-GlcNAc transferase (OGT). O-GlcNAcylation of essential contractile proteins may inhibit protein-protein interactions, reduce calcium sensitivity, and modulate contractile function. Uridine diphosphate (UDP)-GlcNAc is the obligatory substrate of OGT, which catalyzes a reversible post-translational protein modification. The increase of O-GlcNAcylation is accompanied by impaired cardiac hypertrophy in diabetic hearts. Inhibition of O-GlcNAcylation blocks activation of ERK1/2 and hypertrophic growth. O-GlcNAc modification on NFAT is required for its translocation from the cytosol to the nucleus, where NFAT stimulates the transcription of various hypertrophic genes. Inhibition of O-GlcNAcylation dampens NFAT-induced cardiac hypertrophic growth. Transcriptional activity of FOXO1 is enriched by improved O-GlcNAcylation upon high glucose stimulation or OGT overexpression. In diabetic conditions, the modification of FOXO1 by O-GlcNAc is promoted in cardiac troponin I and myosin light chain 2. Therefore targeting O-GlcNAcylation represents a potential therapeutic option to prevent hypertrophy in the diabetic heart.

Keywords: diabetes, cardiac hypertrophy, O-GlcNAcylation, FOXO1, Akt, PI3K, AMPK, insulin

Procedia PDF Downloads 103

Authors: Abdoulaye Maihatchi Ahamed, Zubin Arora, Benjamin Swobada, Jean-yves Lansot, Alexandre Chagnes

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Lithium-ion battery (LiB) is the technology of choice in the development of electric vehicles. But there are still many challenges, including the development of positive electrode materials exhibiting high cycle ability, high energy density, and low environmental impact. For this latter, LiBs must be manufactured in a circular approach by developing the appropriate strategies to reuse and recycle them. Presently, the recycling of LiBs is carried out by the pyrometallurgical route, but more and more processes implement or will implement the hydrometallurgical route or a combination of pyrometallurgical and hydrometallurgical operations. After producing the black mass by mineral processing, the hydrometallurgical process consists in leaching the black mass in order to uptake the metals contained in the cathodic material. Then, these metals are extracted selectively by liquid-liquid extraction, solid-liquid extraction, and/or precipitation stages. However, liquid-liquid extraction combined with precipitation/crystallization steps is the most implemented operation in the LiB recycling process to selectively extract copper, aluminum, cobalt, nickel, manganese, and lithium from the leaching solution and precipitate these metals as high-grade sulfate or carbonate salts. Liquid-liquid extraction consists in contacting an organic solvent and an aqueous feed solution containing several metals, including the targeted metal(s) to extract. The organic phase is non-miscible with the aqueous phase. It is composed of an extractant to extract the target metals and a diluent, which is usually aliphatic kerosene produced from the petroleum industry. Sometimes, a phase modifier is added in the formulation of the extraction solvent to avoid the third phase formation. The extraction properties of the diluent do not depend only on the chemical structure of the extractant, but it may also depend on the nature of the diluent. Indeed, the interactions between the diluent can influence more or less the interactions between extractant molecules besides the extractant-diluent interactions. Only a few studies in the literature addressed the influence of the diluent on the extraction properties, while many studies focused on the effect of the extractants. Recently, new low-carbon footprint aliphatic diluents were produced by catalytic dearomatisation and distillation of bio-based oil. This study aims at investigating the influence of the nature of the diluent on the extraction properties of three extractants towards cobalt, nickel, manganese, copper, aluminum, and lithium: Cyanex®272 for nickel-cobalt separation, DEHPA for manganese extraction, and Acorga M5640 for copper extraction. The diluents used in the formulation of the extraction solvents are (i) low-odor aliphatic kerosene produced from the petroleum industry (ELIXORE 180, ELIXORE 230, ELIXORE 205, and ISANE IP 175) and (ii) bio-sourced aliphatic diluents (DEV 2138, DEV 2139, DEV 1763, DEV 2160, DEV 2161 and DEV 2063). After discussing the effect of the diluents on the extraction properties, this conference will address the development of a low carbon footprint process based on the use of the best bio-sourced diluent for the production of high-grade cobalt sulfate, nickel sulfate, manganese sulfate, and lithium carbonate, as well as metal copper.

Keywords: diluent, hydrometallurgy, lithium-ion battery, recycling

Procedia PDF Downloads 74