Search results for: natural gas distribution network

Authors: Azza A. Ali, Toqa M. Elnahhas, Abeer I. Abd El-Fattah, Mona M. Kamal, Karema Abu-Elfotuh

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Background: Environmental pollution with the different aluminium (Al) containing compounds especially those in industrial waste water exposes people to higher than normal levels of Al that represents an environmental risk factor. Cosmetics, Al ware, and containers are also sources of Al besides some foods and food additives. In addition to its known neurotoxicity, Al affects other body structures like skeletal system, blood cells, liver and kidney. Accumulation of Al in kidney and liver induces nephrotoxicity and hepatotoxicity. Coenzyme Q10 (CoQ10) is a pseudo-vitamin substance primarily present in the mitochondria. It is a powerful antioxidant and acts as radical scavenger. Wheat grass is a natural product that contains carbohydrates, proteins, vitamins, minerals, enzymes and has antioxidant, anti-inflammatory, anticancer and cardiovascular protection activities. Cocoa is an excellent source of iron, potent antioxidants and can protect against many diseases. Vinpocetine is an antioxidant and anti inflammatory while zinc is an essential trace element involved in cell division and its deficiency is observed in many types of liver disease. Objective: To evaluate and compare the potency of different drugs (CoQ10, wheatgrass, cocoa, vinpocetine and zinc) against nephro- and hepato-toxicity induced by Al in rats. Methods: Rats were divided to seven groups and received daily for three weeks either saline for control group or AlCl3 (70 mg/kg, IP) for Al-toxicity model groups. Five groups of Al-toxicity model (treated groups) were orally received together with Al each of the following; CoQ10 (200mg/kg), wheat grass (100mg/kg), cocoa powder (24mg/kg), vinpocetine (20mg/kg) or zinc (32mg/kg). Biochemical changes in the serum level of Alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), lactate deshydrogenase (LDH) as well as total bilirubin, lipids, cholesterol, triglycerides, glucose, proteins, creatinine and urea were measured. Liver and kidney specimens from all groups were also collected for the assessment of hepatic and nephrotic level of inflammatory mediators (TNF-α, IL-6β, nuclear factor kappa B (NF-κB), Caspase-3, oxidative parameters (MDA, SOD, TAC, NO) and DNA fragmentation. Histopathological changes in liver and kidney were also evaluated. Results: Three weeks of AlCl3 (70 mg/kg, IP) exposure induced nephro- and hepato-toxicity in rats. Treatment by the all used drugs showed protection against hazards of AlCl3. The protective effects were indicated by the significant decrease in ALT, AST, ALP, LDH as well as total bilirubin, lipids, cholesterol, triglycerides, glucose, creatinine and urea levels which were increased by Al. Liver and kidney of the treated groups showed decrease in MDA, NO, TNF-α, IL-6β, NF-κB, caspase-3 and DNA fragmentation which were increased by Al, together with significant increase in total proteins, SOD and TAC which were decreased by Al. The protection against both nephro- and hepato-toxicity was more pronounced especially with CoQ10 and wheat grass than the other used drugs. Histopathological examinations confirmed the biochemical results of toxicity and of protection. Conclusion: Protection from nephrotoxicity, hepatotoxicity and the consequent degenerations induced by Al can be achieved by using different drugs as CoQ10, wheatgrass, cocoa, vinpocetine and zinc, but CoQ10 as well as wheat grass possesses the most superior protection.

Keywords: aluminum, nephrotoxicity, hepatotoxicity, coenzyme Q10, wheatgrass, cocoa, vinpocetine, zinc

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Authors: Glykeria A. Visvini, George Ν. Mathioudakis, Amaia Soto Beobide, George A. Voyiatzis

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Polymer nanocomposites are materials in which a polymer matrix is reinforced with nanoscale inclusions, such as nanoparticles, nanoplates, or nanofibers. These nanoscale inclusions can significantly enhance the mechanical, thermal, electrical, and other properties of the polymer matrix, making them attractive for a wide range of industrial applications. These properties can be tailored by adjusting the type and the concentration of the nanoinclusions, which provides a high degree of flexibility in their design and development. An important property that polymeric membranes can exhibit is water vapor permeability (WVP). This can be accomplished by various methods, including the incorporation of micro/nano-fillers into the polymer matrix. In this way, a micro/nano-pore network can be formed, allowing water vapor to permeate through the membrane. At the same time, the membrane can be stretched uni- or bi-axially, creating aligned or cross-linked micropores in the composite, respectively, which can also increase the WVP. Nowadays, in industry, stretched films reinforced with CaCO3 develop micro-porosity sufficient to give them breathability characteristics. Carbon-based nanomaterials, such as graphene oxide (GO), are tentatively expected to be able to effectively improve the WVP of corresponding composite polymer films. The presence in the GO structure of various functional oxidizing groups enhances its ability to attract and channel water molecules, exploiting the unique large surface area of graphene that allows the rapid transport of water molecules. Polypropylene (PP) is widely used in various industrial applications due to its desirable properties, including good chemical resistance, excellent thermal stability, low cost, and easy processability. The specific properties of PP are highly influenced by its crystalline behavior, which is determined by its processing conditions. The development of the β-crystalline phase in PP, in combination with stretching, is anticipating improving the microporosity of the polymer matrix, thereby enhancing its WVP. The aim of present study is to create breathable PP composite membranes using carbon-based nanomaterials, such as graphene oxide (GO), reduced graphene oxide (rGO), and graphene nanoplatelets (GNPs). Unlike traditional methods that rely on the drawing process to enhance the WVP of PP, this study intents to develop a low-cost approach using melt mixing with β-nucleating agents and carbon fillers to create highly breathable PP composite membranes. The study aims to investigate how the concentration of these additives affects the water vapor transport properties of the resulting PP films/membranes. The presence of β-nucleating agents and carbon fillers is expected to enhance β-phase growth in PP, while an alternation between β- and α-phase is expected to lead to improved microporosity and WVP. Our ambition is to develop highly breathable PP composite films with superior performance and at a lower cost compared to the benchmark. Acknowledgment: This research has been co‐financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call «Special Actions "AQUACULTURE"-"INDUSTRIAL MATERIALS"-"OPEN INNOVATION IN CULTURE"» (project code: Τ6YBP-00337)

Keywords: carbon based nanomaterials, nanocomposites, nucleating agent, polypropylene, water vapor permeability

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Authors: James Brown, Stella Kortekaas, Ian Finnie, George Zhang, Christine Devine, Neil Healy

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The use of GIS as an analysis tool for engineering decision making is now best practice in the offshore industry. GIS enables multidisciplinary data integration, analysis and visualisation which allows the presentation of large and intricate datasets in a simple map-interface accessible to all project stakeholders. Presenting integrated geoscience and geotechnical data in GIS enables decision makers to be well-informed. This paper is a successful case study of how GIS spatial analysis techniques were applied to help select the most favourable pipeline route. Routing a pipeline through any natural environment has numerous obstacles, whether they be topographical, geological, engineering or financial. Where the pipeline is subjected to external hydrostatic water pressure and is carrying pressurised hydrocarbons, the requirement to safely route the pipeline through hazardous terrain becomes absolutely paramount. This study illustrates how the application of modern, GIS-based pipeline routing techniques enabled the identification of a single most-favourable pipeline route crossing of a challenging seabed terrain. Conventional approaches to pipeline route determination focus on manual avoidance of primary constraints whilst endeavouring to minimise route length. Such an approach is qualitative, subjective and is liable to bias towards the discipline and expertise that is involved in the routing process. For very short routes traversing benign seabed topography in shallow water this approach may be sufficient, but for deepwater geohazardous sites, the need for an automated, multi-criteria, and quantitative approach is essential. This study combined multiple routing constraints using modern least-cost-routing algorithms deployed in GIS, hitherto unachievable with conventional approaches. The least-cost-routing procedure begins with the assignment of geocost across the study area. Geocost is defined as a numerical penalty score representing hazard posed by each routing constraint (e.g. slope angle, rugosity, vulnerability to debris flows) to the pipeline. All geocosted routing constraints are combined to generate a composite geocost map that is used to compute the least geocost route between two defined terminals. The analyses were applied to select the most favourable pipeline route for a potential gas development in deep water. The study area is geologically complex with a series of incised, potentially active, canyons carved into a steep escarpment, with evidence of extensive debris flows. A similar debris flow in the future could cause significant damage to a poorly-placed pipeline. Protruding inter-canyon spurs offer lower-gradient options for ascending an escarpment but the vulnerability of periodic failure of these spurs is not well understood. Close collaboration between geoscientists, pipeline engineers, geotechnical engineers and of course the gas export pipeline operator guided the analyses and assignment of geocosts. Shorter route length, less severe slope angles, and geohazard avoidance were the primary drivers in identifying the most favourable route.

Keywords: geocost, geohazard, pipeline route determination, pipeline route optimisation, spatial analysis

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Authors: Amber Dhoot, Tarush Gupta, Andrea Gurr, William Jenkins, Sandro Pietrunti, Alexis Tang

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Background: The COVID-19 pandemic has driven pharmacovigilance towards a new paradigm. Nowadays, more people than ever before are recognising and reporting adverse reactions from medications, treatments, and vaccines. In the modern era, with over 3.8 billion users, social media has become the most accessible medium for people to voice their opinions and so provides an opportunity to engage with more patient-centric and accessible pharmacovigilance. However, the pharmaceutical industry has been slow to incorporate social media into its modern pharmacovigilance strategy. This project aims to make social media a more effective tool in pharmacovigilance, and so reduce drug costs, improve drug safety and improve patient outcomes. This will be achieved by firstly uncovering and categorising the barriers facing the widespread adoption of social media in pharmacovigilance. Following this, the potential opportunities of social media will be explored. We will then propose realistic, practical recommendations to make social media a more effective tool for pharmacovigilance. Methodology: A comprehensive systematic literature review was conducted to produce a categorised summary of these barriers. This was followed by conducting 11 semi-structured interviews with pharmacovigilance experts to confirm the literature review findings whilst also exploring the unpublished and real-life challenges faced by those in the pharmaceutical industry. Finally, a survey of the general public (n = 112) ascertained public knowledge, perception, and opinion regarding the use of their social media data for pharmacovigilance purposes. This project stands out by offering perspectives from the public and pharmaceutical industry that fill the research gaps identified in the literature review. Results: Our results gave rise to several key analysis points. Firstly, inadequacies of current Natural Language Processing algorithms hinder effective pharmacovigilance data extraction from social media, and where data extraction is possible, there are significant questions over its quality. Social media also contains a variety of biases towards common drugs, mild adverse drug reactions, and the younger generation. Additionally, outdated regulations for social media pharmacovigilance do not align with new, modern General Data Protection Regulations (GDPR), creating ethical ambiguity about data privacy and level of access. This leads to an underlying mindset of avoidance within the pharmaceutical industry, as firms are disincentivised by the legal, financial, and reputational risks associated with breaking ambiguous regulations. Conclusion: Our project uncovered several barriers that prevent effective pharmacovigilance on social media. As such, social media should be used to complement traditional sources of pharmacovigilance rather than as a sole source of pharmacovigilance data. However, this project adds further value by proposing five practical recommendations that improve the effectiveness of social media pharmacovigilance. These include: prioritising health-orientated social media; improving technical capabilities through investment and strategic partnerships; setting clear regulatory guidelines using multi-stakeholder processes; creating an adverse drug reaction reporting interface inbuilt into social media platforms; and, finally, developing educational campaigns to raise awareness of the use of social media in pharmacovigilance. Implementation of these recommendations would speed up the efficient, ethical, and systematic adoption of social media in pharmacovigilance.

Keywords: adverse drug reaction, drug safety, pharmacovigilance, social media

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Authors: Dr Grace Scaplehorn, Mr Muhammad Adeel Akhtar, Dr Jane Gibson

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Background: Canoe Slalom entails the skilful navigation of a carbon composite canoe or kayak through a series of 18-25 hanging gates, strategically positioned along the course, either upstream or downstream, amidst currents of whitewater rapids in natural and man-made river settings. Athletes compete individually in timed trials, competing for the fastest course time, typically around 80 to 120 seconds. In the new discipline of Kayak Cross, descents of the course are initiated by groups of four athletes freefalling simultaneously from a starting platform situated 3m above the river. Kayak Cross athletes, in contrast to Canoe Slalom, can make physical contact with suspended gates without incurring time penalties and are required to perform a kayak roll half way down the course. The Canoe Slalom World Championships were held at Lee Valley Whitewater Centre, London, from 19th to 24th September 2023. The event comprised 299 international athletes competing for 10 World Championship titles in Canoe/Kayak Slalom events (Olympic Debut Munich 1972), and the new Kayak Cross discipline (Olympic Debut Paris 2024). The inaugural appearance of Kayak Cross at the World Championships occurred in 2017, in Pau, France. There is limited literature surrounding Kayak Cross and the incidence of athlete injuries compared to traditional Canoe Slalom, hence it was felt important to undertake this review to address the perception that the event is dangerous. Aim: The study aimed to quantify and collate data collected from athletes presenting to the event medical centre. Methods: Athletes’ details were collected at initial assessments from the start of the practice period (16th–18th September) and throughout the event. Demographics such as age, sex and nationality were recorded along with presenting complaints, treatment, medication administered and outcome. Specifically, injuries were then sub-classified into body regions. The data does not include athletes who sought medical attention from their own governing body’s medical team. Results: During the 8-day period, there were 11 individual presentations to the medical centre, 3.7% of the athlete population (n=299). The mean age was 23.9 years (n=7), 6 were male (n=10). The most common presentation was minor injury (n=9), with 6 being musculoskeletal and 3 comprising skin damage, followed by insect sting/allergy (n=1) and pain relief requests (n=1). Five presentations were event-related, all being musculoskeletal injuries; 2 shoulder/arm, 1 head/neck, 1 hand/wrist and 1 other (data was not recorded). Of these injuries, the only intervention was 2 cases of 400mg Ibuprofen, which was given to both shoulder/arm injuries. Four of the 11 presentations were pre-existing injuries, which had been exacerbated due to increased intensity of practice. Two patients were advised to return for review, with 100% compliance. There were no unplanned re-presentations, and no emergency transfers to secondary care. Both the Kayak Cross and Canoe Slalom competitions resulted in 1 new event-related athlete presentation each. Conclusion: The event resulted in a negligible incidence of presentations at the medical centre, for both Kayak Cross and Canoe Slalom. This data holds significance in informing risk assessments and medical protocols necessary for the organisation of canoe slalom events.

Keywords: canoe slalom, kayak cross, athlete injuries, event injuries

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Authors: A. Kolendo

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Pacific Islands are one of the most vulnerable areas to climate change. Sea level rise and accelerating storm surge continuously threaten the communities' habitats on low-lying atolls. With scientific predictions of encroaching tides on their land, the Islanders have been informed about the need for future relocation planning. However, some communities oppose such retreat strategies through the reasoning that comprehends current climatic changes through the lenses of the biblical ark of Noah. This parable states God's promise never to flood the Earth again and never deprive people of their land and habitats. Several interpretations of this parable emerged in Oceania, prompting either climate action or denial. Resistance to relocation planning expressed through Christian thoughts led religion to be perceived as a barrier to dialogue between the Islanders and scientists. Since climate change concerns natural processes, the attitudes towards environmental stewardship prompt the communities' responses to it; some Christian teachings indicate humanity's responsibility over the environment, whereas others ascertain the people's dominion, which prompts resistance and sometimes denial. With church denominations and their various environmental standpoints, competing responses to climate change emerged in Oceania. Before miss-ionization, traditional knowledge had guided the environmental sphere, influencing current Christian teachings. Each atoll characterizes a distinctive manner of traditional knowledge; however, the unique relationship with nature unites all islands. The interconnectedness between the land, sea and people indicates the integrity between the communities and their environments. Such a factor influences the comprehension of Noah's story in the context of climate change that threatens their habitats. Pacific Islanders experience climate change through the slow disappearance of their homelands. However, the Western world perceives it as a global issue that will affect the population in the long-term perspective. Therefore, the Islanders seek to comprehend this global phenomenon in a local context that reads climate change as the Great Deluge. Accordingly, the safety measures that this parable promotes compensate for the danger of climate change. The rainbow covenant gives hope in God's promise never to flood the Earth again. At the same time, Noah's survival relates to the Islanders' current situation. Since these communities have the lowest carbon emissions rate, their contribution to anthropogenic climate change is scarce. Therefore, the lack of environmental sin would contextualize them as contemporary Noah with the ultimate survival of sea level rise. This study aims to defy religion constituting a barrier through secondary data analysis from a risk compensation perspective. Instead, religion is portrayed as a source of knowledge that enables comprehension of the communities' situation. By demonstrating that the Pacific Islanders utilize Noah's story as a vessel for coping with the danger of climate change, the study argues that religion provides safety measures that compensate for the future projections of land's disappearance. The purpose is to build a bridge between religious communities and scientific bodies and ultimately bring an understanding of two diverse perspectives. By addressing the practical challenges of interdisciplinary research with faith-based systems, this study uplifts the voices of communities and portrays their experiences expressed through Christian thoughts.

Keywords: Christianity, climate change, existential threat, Pacific Islands, story of Noah

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Authors: M. Reza Hashemi, Chris Small, Scott Hayward

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The Northeast Coast of the US faces damaging effects of coastal flooding and winds due to Atlantic tropical and extratropical storms each year. Historically, several large storm events have produced substantial levels of damage to the region; most notably of which were the Great Atlantic Hurricane of 1938, Hurricane Carol, Hurricane Bob, and recently Hurricane Sandy (2012). The objective of this study was to develop an integrated modeling system that could be used as a forecasting/hindcasting tool to evaluate and communicate the risk coastal communities face from these coastal storms. This modeling system utilizes the ADvanced CIRCulation (ADCIRC) model for storm surge predictions and the Simulating Waves Nearshore (SWAN) model for the wave environment. These models were coupled, passing information to each other and computing over the same unstructured domain, allowing for the most accurate representation of the physical storm processes. The coupled SWAN-ADCIRC model was validated and has been set up to perform real-time forecast simulations (as well as hindcast). Modeled storm parameters were then passed to a coastal risk assessment tool. This tool, which is generic and universally applicable, generates spatial structural damage estimate maps on an individual structure basis for an area of interest. The required inputs for the coastal risk model included a detailed information about the individual structures, inundation levels, and wave heights for the selected region. Additionally, calculation of wind damage to structures was incorporated. The integrated coastal risk assessment system was then tested and applied to Charlestown, a small vulnerable coastal town along the southern shore of Rhode Island. The modeling system was applied to Hurricane Sandy and a synthetic storm. In both storm cases, effect of natural dunes on coastal risk was investigated. The resulting damage maps for the area (Charlestown) clearly showed that the dune eroded scenarios affected more structures, and increased the estimated damage. The system was also tested in forecast mode for a large Nor’Easters: Stella (March 2017). The results showed a good performance of the coupled model in forecast mode when compared to observations. Finally, a nearshore model XBeach was then nested within this regional grid (ADCIRC-SWAN) to simulate nearshore sediment transport processes and coastal erosion. Hurricane Irene (2011) was used to validate XBeach, on the basis of a unique beach profile dataset at the region. XBeach showed a relatively good performance, being able to estimate eroded volumes along the beach transects with a mean error of 16%. The validated model was then used to analyze the effectiveness of several erosion mitigation methods that were recommended in a recent study of coastal erosion in New England: beach nourishment, coastal bank (engineered core), and submerged breakwater as well as artificial surfing reef. It was shown that beach nourishment and coastal banks perform better to mitigate shoreline retreat and coastal erosion.

Keywords: ADCIRC, coastal flooding, storm surge, coastal risk assessment, living shorelines

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Authors: Priyanka Mokashi, Aparna Khanna, Nancy Pandita

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Diabetes mellitus is a chronic metabolic disorder which will be the 7th leading cause of death by 2030. The current line of treatment for the diabetes mellitus is oral antidiabetic drugs (biguanides, sulfonylureas, meglitinides, thiazolidinediones and alpha-glycosidase inhibitors) and insulin therapy depending upon the type 1 or type 2 diabetes mellitus. But, these treatments have their disadvantages, ranging from the developing of resistance to the drugs and adverse effects caused by them. Alternative to these synthetic agents, natural products provides a new insight for the development of more efficient and safe drugs due to their therapeutic values. Enicostema littorale blume (A. Raynal) is a traditional Indian plant belongs to the Gentianaceae family. It is widely distributed in Asia, Africa, and South America. There are few reports on Swrtiamarin, major component of this plant for its antidiabetic activity. However, the antidiabetic activity of flavonoids from E. littorale and their mechanism of action have not yet been elucidated. Flavonoids have a positive relationship with disease prevention and can act on various molecular targets and regulate different signaling pathways in pancreatic β-cells, adipocytes, hepatocytes and skeletal myofibers. They may exert beneficial effects in diabetes by (i) improving hyperglycemia through regulation of glucose metabolism in hepatocytes; (ii) enhancing insulin secretion and reducing apoptosis and promoting proliferation of pancreatic β-cells; (iii) increasing glucose uptake in hepatocytes, skeletal muscle and white adipose tissue (iv) reducing insulin resistance, inflammation and oxidative stress. Therefore, we have isolated four flavonoid rich fractions, Fraction A (FA), Fraction B (FB), Fraction C (FC), Fraction D (FD) from crude alcoholic hot (AH) extract from E. littorale, identified by LC/MS. Total eight flavonoids were identified on the basis of fragmentation pattern. Flavonoid FA showed the presence of swertisin, isovitexin, and saponarin; FB showed genkwanin, quercetin, isovitexin, FC showed apigenin, swertisin, quercetin, 5-O-glucosylswertisin and 5-O-glucosylisoswertisin whereas FD showed the presence of swertisin. Further, these fractions were assessed for their antidiabetic activity on stimulating glucose uptake in insulin-resistant HepG2 cell line model (IR/HepG2). The results showed that FD containing C-glycoside Swertisin has significantly increased the glucose uptake rate of IR/HepG2 cells at the concentration of 10 µg/ml as compared to positive control Metformin (0.5mM) which was determined by glucose oxidase- peroxidase method. It has been reported that enhancement of glucose uptake of cells occurs due the translocation of Glut4 vesicles to cell membrane through IR/IRS1/AKT pathway. Therefore, we have studied expressions of three genes IRS1, AKT and Glut4 by real-time PCR to evaluate whether they follow the same pathway or not. It was seen that the glucose uptake rate has increased in FD treated IR/HepG2 cells due to the activation of insulin receptor substrate-1 (IRS1) followed by protein kinase B (AKT) through phosphoinositide 3-kinase (PI3K) leading to translocation of Glut 4 vesicles to cell membrane, thereby enhancing glucose uptake and insulin sensitivity of insulin resistant HepG2 cells. Hence, the up-regulation indicated the mechanism of action through which FD (Swertisin) acts as antidiabetic candidate in the treatment of type 2 diabetes mellitus.

Keywords: E. littorale, glucose transporter, glucose uptake rate, insulin resistance

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Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Prem K. Mony, Bharadwaj Amrutur, Prashanth Thankachan, Swarnarekha Bhat, Suman Rao, Maryann Washington, Annamma Thomas, N. Sheela, Hiteshwar Rao, Sumi Antony

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The disease burden among mothers and newborns is caused mostly by a handful of avoidable conditions occurring around the time of childbirth and within the first month following delivery. Real-time monitoring of vital parameters of mothers and neonates offers a potential opportunity to impact access as well as the quality of care in vulnerable populations. We describe the design, development and testing of an innovative wearable device for remote biomonitoring (RBM) of body temperatures in mothers and neonates in a hospital in southern India. The architecture consists of: [1] a low-cost, wearable sensor tag; [2] a gateway device for ‘real-time’ communication link; [3] piggy-backing on a commercial GSM communication network; and [4] an algorithm-based data analytics system. Requirements for the device were: long battery-life upto 28 days (with sampling frequency 5/hr); robustness; IP 68 hermetic sealing; and human-centric design. We undertook pre-clinical laboratory testing followed by clinical trial phases I & IIa for evaluation of safety and efficacy in the following sequence: seven healthy adult volunteers; 18 healthy mothers; and three sets of babies – 3 healthy babies; 10 stable babies in the Neonatal Intensive Care Unit (NICU) and 1 baby with hypoxic ischaemic encephalopathy (HIE). The 3-coin thickness, pebble-design sensor weighing about 8 gms was secured onto the abdomen for the baby and over the upper arm for adults. In the laboratory setting, the response-time of the sensor device to attain thermal equilibrium with the surroundings was 4 minutes vis-a-vis 3 minutes observed with a precision-grade digital thermometer used as a reference standard. The accuracy was ±0.1°C of the reference standard within the temperature range of 25-40°C. The adult volunteers, aged 20 to 45 years, contributed a total of 345 hours of readings over a 7-day period and the postnatal mothers provided a total of 403 paired readings. The mean skin temperatures measured in the adults by the sensor were about 2°C lower than the axillary temperature readings (sensor =34.1 vs digital = 36.1); this difference was statistically significant (t-test=13.8; p<0.001). The healthy neonates provided a total of 39 paired readings; the mean difference in temperature was 0.13°C (sensor =36.9 vs digital = 36.7; p=0.2). The neonates in the NICU provided a total of 130 paired readings. Their mean skin temperature measured by the sensor was 0.6°C lower than that measured by the radiant warmer probe (sensor =35.9 vs warmer probe = 36.5; p < 0.001). The neonate with HIE provided a total of 25 paired readings with the mean sensor reading being not different from the radian warmer probe reading (sensor =33.5 vs warmer probe = 33.5; p=0.8). No major adverse events were noted in both the adults and neonates; four adult volunteers reported mild sweating under the device/arm band and one volunteer developed mild skin allergy. This proof-of-concept study shows that real-time monitoring of temperatures is technically feasible and that this innovation appears to be promising in terms of both safety and accuracy (with appropriate calibration) for improved maternal and neonatal health.

Keywords: public health, remote biomonitoring, temperature surveillance, wearable sensors, mothers and newborns

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Authors: Judy M. Obliosca, Olivia Vest, Sandra Poulos, Kelsi Smith, Tammy Ferguson, Abigail Powers Lott, Alicia K. Smith, Yang Xu, Christopher K. Tison

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Post-Traumatic Stress Disorder (PTSD) is a mental health problem that people may develop after experiencing traumatic events such as combat, natural disasters, and major emotional challenges. Tragically, the number of military personnel with PTSD correlates directly with the number of veterans who attempt suicide, with the highest rate in the Army. Research has shown epigenetic risks in those who are prone to several psychiatric dysfunctions, particularly PTSD. Once initiated in response to trauma, epigenetic alterations in particular, the DNA methylation in the form of 5-methylcytosine (5mC) alters chromatin structure and represses gene expression. Current methods to detect DNA methylation, such as bisulfite-based genomic sequencing techniques, are laborious and have massive analysis workflow while still having high error rates. A faster and simpler detection method of high sensitivity and precision would be useful in a clinical setting to confirm potential PTSD etiologies, prevent other psychiatric disorders, and improve military health. A nano-enhanced Surface Plasmon Resonance imaging (SPRi)-based assay that simultaneously detects site-specific 5mC base (termed as PTSD base) in methylated genes related to PTSD is being developed. The arrays on a sensing chip were first constructed for parallel detection of PTSD bases using synthetic and genomic DNA (gDNA) samples. For the gDNA sample extracted from the whole blood of a PTSD patient, the sample was first digested using specific restriction enzymes, and fragments were denatured to obtain single-stranded methylated target genes (ssDNA). The resulting mixture of ssDNA was then injected into the assay platform, where targets were captured by specific DNA aptamer probes previously immobilized on the surface of a sensing chip. The PTSD bases in targets were detected by anti-5-methylcytosine antibody (anti-5mC), and the resulting signals were then enhanced by the universal nanoenhancer. Preliminary results showed successful detection of a PTSD base in a gDNA sample. Brighter spot images and higher delta values (control-subtracted reflectivity signal) relative to those of the control were observed. We also implemented the in-house surface activation system for detection and developed SPRi disposable chips. Multiplexed PTSD base detection of target methylated genes in blood DNA from PTSD patients of severity conditions (asymptomatic and severe) was conducted. This diagnostic capability being developed is a platform technology, and upon successful implementation for PTSD, it could be reconfigured for the study of a wide variety of neurological disorders such as traumatic brain injury, Alzheimer’s disease, schizophrenia, and Huntington's disease and can be extended to the analyses of other sample matrices such as urine and saliva.

Keywords: epigenetic assay, DNA methylation, PTSD, whole blood, multiplexing

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Authors: Utkarsh A. Mishra, Ankit Bansal

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At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

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Authors: Sofia Quaglia, Carmine Di Martino, Brendan Tierney

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Artificial Intelligence (A.I.) constitutes various aspects of modern life, from the Machine Learning algorithms predicting the stocks on Wall streets to the killing of belligerents and innocents alike on the battlefield. Moreover, the end goal is to create autonomous A.I.; this means that the presence of humans in the decision-making process will be absent. The question comes naturally: when an A.I. does something wrong when its behavior is harmful to the community and its actions go against the law, which is to be held responsible? This research’s subject matter in A.I. and Robot Ethics focuses mainly on Robot Rights and its ultimate objective is to answer the questions: (i) What is the function of rights? (ii) Who is a right holder, what is personhood and the requirements needed to be a moral agent (therefore, accountable for responsibility)? (iii) Can an A.I. be a moral agent? (ontological requirements) and finally (iv) if it ought to be one (ethical implications). With the direction to answer this question, this research project was done via a collaboration between the School of Computer Science in the Technical University of Dublin that oversaw the technical aspects of this work, as well as the Department of Philosophy in the University of Milan, who supervised the philosophical framework and argumentation of the project. Firstly, it was found that all rights are positive and based on consensus; they change with time based on circumstances. Their function is to protect the social fabric and avoid dangerous situations. The same goes for the requirements considered necessary to be a moral agent: those are not absolute; in fact, they are constantly redesigned. Hence, the next logical step was to identify what requirements are regarded as fundamental in real-world judicial systems, comparing them to that of ones used in philosophy. Autonomy, free will, intentionality, consciousness and responsibility were identified as the requirements to be considered a moral agent. The work went on to build a symmetrical system between personhood and A.I. to enable the emergence of the ontological differences between the two. Each requirement is introduced, explained in the most relevant theories of contemporary philosophy, and observed in its manifestation in A.I. Finally, after completing the philosophical and technical analysis, conclusions were drawn. As underlined in the research questions, there are two issues regarding the assignment of moral agency to artificial agent: the first being that all the ontological requirements must be present and secondly being present or not, whether an A.I. ought to be considered as an artificial moral agent. From an ontological point of view, it is very hard to prove that an A.I. could be autonomous, free, intentional, conscious, and responsible. The philosophical accounts are often very theoretical and inconclusive, making it difficult to fully detect these requirements on an experimental level of demonstration. However, from an ethical point of view it makes sense to consider some A.I. as artificial moral agents, hence responsible for their own actions. When considering artificial agents as responsible, there can be applied already existing norms in our judicial system such as removing them from society, and re-educating them, in order to re-introduced them to society. This is in line with how the highest profile correctional facilities ought to work. Noticeably, this is a provisional conclusion and research must continue further. Nevertheless, the strength of the presented argument lies in its immediate applicability to real world scenarios. To refer to the aforementioned incidents, involving the murderer of innocents, when this thesis is applied it is possible to hold an A.I. accountable and responsible for its actions. This infers removing it from society by virtue of its un-usability, re-programming it and, only when properly functioning, re-introducing it successfully

Keywords: artificial agency, correctional system, ethics, natural agency, responsibility

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Authors: E. Locatelli, I. Monaco, R. C. Martin, Y. Li, R. Pini, M. Chiariello, M. Comes Franchini

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Despite the many advantages of application of nanomaterials in the field of nanomedicine, increasing concerns have been expressed on their potential adverse effects on human health. There is urgency for novel green strategies toward novel materials with enhanced biocompatibility using safe reagents. Photothermal ablation therapy, which exploits localized heat increase of a few degrees to kill cancer cells, has appeared recently as a non-invasive and highly efficient therapy against various cancer types; anyway new agents able to generate hyperthermia when irradiated are needed and must have precise biocompatibility in order to avoid damage to healthy tissues and prevent toxicity. Recently, there has been increasing interest in magnesium as a biomaterial: it is the fourth most abundant cation in the human body, and it is essential for human metabolism. However magnesium nanoparticles (Mg NPs) have had limited diffusion due to the high reduction potential of magnesium cations, which makes NPs synthesis challenging. Herein, we report the synthesis of Mg NPs and their surface functionalization for the obtainment of a stable and biocompatible nanomaterial suitable for photothermal ablation therapy against cancer. We synthesized the Mg crystals by reducing MgCl2 with metallic lithium and exploiting naphthalene as an electron carrier: the lithium–naphthalene complex acts as the real reducing agent. Firstly, the nanocrystal particles were coated with the ligand 12-ethoxy ester dodecanehydroxamic acid, and then entrapped into water-dispersible polymeric micelles (PMs) made of the FDA-approved PLGA-b-PEG-COOH copolymer using the oil-in-water emulsion technique. Lately, we developed a more straightforward methodology by introducing chitosan, a highly biocompatible natural product, at the beginning of the process, simultaneously using lithium–naphthalene complex, thus having a one-pot procedure for the formation and surface modification of MgNPs. The obtained MgNPs were purified and fully characterized, showing diameters in the range of 50-300 nm. Notably, when coated with chitosan the particles remained stable as dry powder for more than 10 months. We proved the possibility of generating a temperature rise of a few to several degrees once MgNPs were illuminated using a 810 nm diode laser operating in continuous wave mode: the temperature rise resulted significant (0-15 °C) and concentration dependent. We then investigated potential cytotoxicity of the MgNPs: we used HN13 epithelial cells, derived from a head and neck squamous cell carcinoma and the hepa1-6 cell line, derived from hepatocellular carcinoma and very low toxicity was observed for both nanosystems. Finally, in vivo photothermal therapy was performed on xenograft hepa1-6 tumor bearing mice: the animals were treated with MgNPs coated with chitosan and showed no sign of suffering after the injection. After 12 hours the tumor was exposed to near-infrared laser light. The results clearly showed an extensive damage to tumor tissue after only 2 minutes of laser irradiation at 3Wcm-1, while no damage was reported when the tumor was treated with the laser and saline alone in control group. Despite the lower photothermal efficiency of Mg with respect to Au NPs, we consider MgNPs a promising, safe and green candidate for future clinical translations.

Keywords: chitosan, magnesium nanoparticles, nanomedicine, photothermal therapy

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Authors: Dmitry Yu. Korulkin, Raissa A. Muzychkina

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Bioactive substances of plant origin can be one of the advanced means of solution to the issue of combined therapy to inflammation. The main advantages of medical plants are softness and width of their therapeutic effect on an organism, the absence of side effects and complications even if the used continuously, high tolerability by patients. Moreover, medial plants are often the only and (or) cost-effective sources of natural biologically active substances and medicines. Along with other biologically active groups of chemical compounds, essential oils with wide range of pharmacological effects became very ingrained in medical practice. Essential oil was obtained by the method hydrodistillation air-dry aerial part of Polygonum L. plants using Clevenger apparatus. Qualitative composition of essential oils was analyzed by chromatography-mass-spectrometry method using Agilent 6890N apparatus. The qualitative analysis is based on the comparison of retention time and full mass-spectra with respective data on components of reference oils and pure compounds, if there were any, and with the data of libraries of mass-spectra Wiley 7th edition and NIST 02. The main components of essential oil are for: Polygonum amphibium L. - γ-terpinene, borneol, piperitol, 1,8-cyneole, α-pinene, linalool, terpinolene and sabinene; Polygonum minus Huds. Fl. Angl. – linalool, terpinolene, camphene, borneol, 1,8-cyneole, α-pinene, 4-terpineol and 1-octen-3-ol; Polygonum alpinum All. – camphene, sabinene, 1-octen-3-ol, 4-carene, p- and o-cymol, γ-terpinene, borneol, -terpineol; Polygonum persicaria L. - α-pinene, sabinene, -terpinene, 4-carene, 1,8-cyneole, borneol, 4-terpineol. Antibacterial activity was researched relating to strains of gram-positive bacteria Staphylococcus aureus, Bacillus subtilis, Streptococcus agalacticae, relating to gram-negative strain Escherichia coli and to yeast fungus Сandida albicans using agar diffusion method. The medicines of comparison were gentamicin for bacteria and nystatin for yeast fungus Сandida albicans. It has been shown that Polygonum L. essential oils has moderate antibacterial effect to gram-positive microorganisms and weak antifungal activity to Candida albicans yeast fungus. At the second stage of our researches wound healing properties of ointment form of 3% essential oil was researched on the model of flat dermal wounds. To assess the influence of essential oil on healing processes the model of flat dermal wound. The speed of wound healing on rats of different groups was judged based on assessment the area of a wound from time to time. During research of wound healing properties disturbance of integral in neither group: general condition and behavior of animals, food intake, and excretion. Wound healing action of 3% ointment on base of Polygonum L. essential oil and polyethyleneglycol is comparable with the action of reference substances. As more favorable healing dynamics was observed in the experimental group than in control group, the tested ointment can be deemed more promising for further detailed study as wound healing means.

Keywords: antibacterial, antifungal, bioactive substances, essential oils, isolation, Polygonum L.

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Authors: Sarah M. Schoellhammer, Stephen Gibb

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Bureaucracy, in particular, its core element, a formal and stable hierarchy of authority, is proving less and less appropriate under the conditions of today’s knowledge economy. Centralization and formalization were consistently found to hinder innovation, undermining cross-functional collaboration, personal responsibility, and flexibility. With its focus on systematical planning, controlling and monitoring the development of new or improved solutions for customers, even innovation management as a discipline is to a significant extent based on a mechanistic understanding of organizations. The most important drivers of innovation, human creativity, and initiative, however, can be more hindered than supported by central elements of classic innovation management, such as predefined innovation strategies, rigid stage gate processes, and decisions made in management gate meetings. Heterarchy, as an alternative network form of organization, is essentially characterized by its dynamic influence structures, whereby the biggest influence is allocated by the collective to the persons perceived the most competent in a certain issue. Theoretical arguments that the non-hierarchical concept better supports innovation than bureaucracy have been supported by empirical research. These prior studies either focus on the structure and general functioning of non-hierarchical organizations or on their innovativeness, that means innovation as an outcome. Complementing classic innovation management approaches, this work aims to shed light on how innovations are initiated and realized in heterarchies in order to identify alternative solutions practiced under conditions of the post-bureaucratic organization. Through an initial individual case study, which is part of a multiple-case project, the innovation practices of an innovative and highly heterarchical medium-sized company in the German fire engineering industry are investigated. In a pragmatic mixed methods approach media resonance, company documents, and workspace architecture are analyzed, in addition to qualitative interviews with the CEO and employees of the case company, as well as a quantitative survey aiming to characterize the company along five scaled dimensions of a heterarchy spectrum. The analysis reveals some similarities and striking differences to approaches suggested by classic innovation management. The studied heterarchy has no predefined innovation strategy guiding new product and service development. Instead, strategic direction is provided by the CEO, described as visionary and creative. Procedures for innovation are hardly formalized, with new product ideas being evaluated on the basis of gut feeling and flexible, rather general criteria. Employees still being hesitant to take responsibility and make decisions, hierarchical influence is still prominent. Described as open-minded and collaborative, culture and leadership were found largely congruent with definitions of innovation culture. Overall, innovation efforts at the case company tend to be coordinated more through cultural than through formal organizational mechanisms. To better enable innovation in mainstream organizations, responsible practitioners are recommended not to limit changes to reducing the central elements of the bureaucratic organization, formalization, and centralization. The freedoms this entails need to be sustained through cultural coordination mechanisms, with personal initiative and responsibility by employees as well as common innovation-supportive norms and values. These allow to integrate diverse competencies, opinions, and activities and, thus, to guide innovation efforts.

Keywords: bureaucracy, heterarchy, innovation management, values

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Authors: Zbigniew Czyz, Ksenia Siadkowska, Krzysztof Skiba, Karol Scislowski

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Today’s progress in the rotorcraft is mostly associated with an optimization of aircraft performance achieved by active and passive modifications of main rotor assemblies and a tail propeller. The key task is to improve their performance, improve the hover quality factor for rotors but not change in specific fuel consumption. One of the tasks to improve the helicopter is an active optimization of the main rotor providing for flight stages, i.e., an ascend, flight, a descend. An active interference with the airflow around the rotor blade section can significantly change characteristics of the aerodynamic airfoil. The efficiency of actuator systems modifying aerodynamic coefficients in the current solutions is relatively high and significantly affects the increase in strength. The solution to actively change aerodynamic characteristics assumes a periodic change of geometric features of blades depending on flight stages. Changing geometric parameters of blade warping enables an optimization of main rotor performance depending on helicopter flight stages. Structurally, an adaptation of shape memory alloys does not significantly affect rotor blade fatigue strength, which contributes to reduce costs associated with an adaptation of the system to the existing blades, and gains from a better performance can easily amortize such a modification and improve profitability of such a structure. In order to obtain quantitative and qualitative data to solve this research problem, a number of numerical analyses have been necessary. The main problem is a selection of design parameters of the main rotor and a preliminary optimization of its performance to improve the hover quality factor for rotors. This design concept assumes a three-bladed main rotor with a chord of 0.07 m and radius R = 1 m. The value of rotor speed is a calculated parameter of an optimization function. To specify the initial distribution of geometric warping, a special software has been created that uses a numerical method of a blade element which respects dynamic design features such as fluctuations of a blade in its joints. A number of performance analyses as a function of rotor speed, forward speed, and altitude have been performed. The calculations were carried out for the full model assembly. This approach makes it possible to observe the behavior of components and their mutual interaction resulting from the forces. The key element of each rotor is the shaft, hub and pins holding the joints and blade yokes. These components are exposed to the highest loads. As a result of the analysis, the safety factor was determined at the level of k > 1.5, which gives grounds to obtain certification for the strength of the structure. The construction of the joint rotor has numerous moving elements in its structure. Despite the high safety factor, the places with the highest stresses, where the signs of wear and tear may appear, have been indicated. The numerical analysis carried out showed that the most loaded element is the pin connecting the modular bearing of the blade yoke with the element of the horizontal oscillation joint. The stresses in this element result in a safety factor of k=1.7. The other analysed rotor components have a safety factor of more than 2 and in the case of the shaft, this factor is more than 3. However, it must be remembered that the structure is as strong as the weakest cell is. Designed rotor for unmanned aerial vehicles adapted to work with blades with intelligent materials in its structure meets the requirements for certification testing. Acknowledgement: This work has been financed by the Polish National Centre for Research and Development under the LIDER program, Grant Agreement No. LIDER/45/0177/L-9/17/NCBR/2018.

Keywords: main rotor, rotorcraft aerodynamics, shape memory alloy, materials, unmanned helicopter

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Authors: Soni T. L.

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Sustainable environmental stress is a major concern which needs immediate attention. This paper is an attempt to present participatory action research for sustainable agriculture. Being first and best culture, agriculture protects and improves the natural environment, the social and economic conditions of people, and safeguards the health and welfare of all groups. During course of time agriculture turned to agribusiness, then the values are not safeguarded. Moreover, in today’s busy life many are not taking efforts to take part in agriculture production. Then children are not getting the opportunity to understand agriculture and farming practices. So student initiatives are vital to make them aware. Here the programmes structured by the researcher come under the auspicious of National Service Scheme, a student-centered educational programme, organized by Ministry of Youth Affairs, Government of India. The twin objectives of the study are to examine the role of student initiatives for sustainable agriculture and the role of participatory action research in student initiatives. SWOT analysis is made to study strengths, weaknesses, threats and opportunities. The Methodology adopted is Participatory Action Research. The method is participatory in a sense there is collaboration through participation. The method is action, there is lab land experiences which is real. The method is research that there is documented lessons and creation of new knowledge. Plan of action cover measures adopted and strategies taken i.e., bhavana – kalpana – yojana – sadhana. Through the team effort, the team was successful in converting more than 10 hectares of barren land into cultivable land within and outside the campus. Team efforts of students saved a huge amount of labour cost and produced a huge quantity of organic output and the team was also successful in creating 1000 rain pits in the premises of College for rainwater harvesting. The findings include conveyance of the Message: Food Production is superior to Food donation. Moreover, the study fostered good work ethic and social responsibility among students. Students undertake innovative programmes underlying social and environmental issues and participants got increased opportunities to interact with local and less privileged and acquired increased awareness about real-life experiences which make them confident to interact with people and it resulted in the strengthening of social capital- cooperation, team spirit, social commitment among students. Participants promoted sustainable domestic efforts and ultimately environmental protection is ensured. Finally, there is recognition to the team, institution and the researcher at the university level, state level and at the national level. The learned lessons are, if the approach is good, the response is good and success generates success. Participatory action research is empowering experience for practitioners, focusing the combined time, energy and creativity of a committed group we should lead so many programmes which makes the institution centre of excellence. Authorities should take necessary steps for the Inclusion of community development activities in the curriculum. Action research is problem, client and action centered. So, we must adapt and adopt, coordinates and correlates measures which preserve and conserve the environment.

Keywords: participatory action research, student initiatives, sustainable development, sustainability

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Authors: Chenyi Ma

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Background: The second costliest hurricane in U.S. history, Sandy landed in southern New Jersey on October 29, 2012, and struck the entire state with high winds and torrential rains. The disaster killed more than 100 people, left more than 8.5 million households without power, and damaged or destroyed more than 200,000 homes across the state. Immediately after the disaster, public policy support was provided in nine coastal counties that constituted 98% of the major and severely damaged housing units in NJ overall. The programs include Individuals and Households Assistance Program, Small Business Loan Program, National Flood Insurance Program, and the Federal Emergency Management Administration (FEMA) Public Assistance Grant Program. In the most severely affected counties, additional funding was provided through Community Development Block Grant: Reconstruction, Rehabilitation, Elevation, and Mitigation Program, and Homeowner Resettlement Program. How these policies individually and as a whole impacted housing recovery across communities with different socioeconomic and demographic profiles has not yet been studied, particularly in relation to damage levels. The concept of community social vulnerability has been widely used to explain many aspects of natural disasters. Nevertheless, how communities are vulnerable has been less fully examined. Community resilience has been conceptualized as a protective factor against negative impacts from disasters, however, how community resilience buffers the effects of vulnerability is not yet known. Because housing recovery is a dynamic social and economic process that varies according to context, this study examined the path from community vulnerability and resilience to housing recovery looking at both community characteristics and policy interventions. Sample/Methods: This retrospective longitudinal case study compared a literature-identified set of pre-disaster community characteristics, the effects of multiple public policy programs, and a set of time-variant community resilience indicators to changes in housing stock (operationally defined by percent of building permits to total occupied housing units/households) between 2010 and 2014, two years before and after Hurricane Sandy. The sample consisted of 51 municipalities in the nine counties in which between 4% and 58% of housing units suffered either major or severe damage. Structural equation modeling (SEM) was used to determine the path from vulnerability to the housing recovery, via multiple public programs, separately and as a whole, and via the community resilience indicators. The spatial analytical tool ArcGIS 10.2 was used to show the spatial relations between housing recovery patterns and community vulnerability and resilience. Findings: Holding damage levels constant, communities with higher proportions of Hispanic households had significantly lower levels of housing recovery while communities with households with an adult >age 65 had significantly higher levels of the housing recovery. The contrast was partly due to the different levels of total public support the two types of the community received. Further, while the public policy programs individually mediated the negative associations between African American and female-headed households and housing recovery, communities with larger proportions of African American, female-headed and Hispanic households were “vulnerable” to lower levels of housing recovery because they lacked sufficient public program support. Even so, higher employment rates and incomes buffered vulnerability to lower housing recovery. Because housing is the "wobbly pillar" of the welfare state, the housing needs of these particular groups should be more fully addressed by disaster policy.

Keywords: community social vulnerability, community resilience, hurricane, public policy

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Authors: Mukhtar Maigari

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The landscape of Higher Education (HE) institutions, especially following the CVID-19 pandemic, necessitates advanced approaches to manage Indoor Environmental Quality (IEQ) which is crucial for the comfort, health, and productivity of students and staff. This study investigates the application of Building Information Modelling (BIM) as a multifaceted tool for monitoring, assessing, and controlling IEQ in HE buildings aiming to bridge the gap between traditional management practices and the innovative capabilities of BIM. Central to the study is a comprehensive literature review, which lays the foundation by examining current knowledge and technological advancements in both IEQ and BIM. This review sets the stage for a deeper investigation into the practical application of BIM in IEQ management. The methodology consists of Post-Occupancy Evaluation (POE) which encompasses physical monitoring, questionnaire surveys, and interviews under the umbrella of case studies. The physical data collection focuses on vital IEQ parameters such as temperature, humidity, CO2 levels etc, conducted by using different equipment including dataloggers to ensure accurate data. Complementing this, questionnaire surveys gather perceptions and satisfaction levels from students, providing valuable insights into the subjective aspects of IEQ. The interview component, targeting facilities management teams, offers an in-depth perspective on IEQ management challenges and strategies. The research delves deeper into the development of a conceptual BIM-based framework, informed by the insight findings from case studies and empirical data. This framework is designed to demonstrate the critical functions necessary for effective IEQ monitoring, assessment, control and automation with real time data handling capabilities. This BIM-based framework leads to the developing and testing a BIM-based prototype tool. This prototype leverages on software such as Autodesk Revit with its visual programming tool i.e., Dynamo and an Arduino-based sensor network thereby allowing for real-time flow of IEQ data for monitoring, control and even automation. By harnessing the capabilities of BIM technology, the study presents a forward-thinking approach that aligns with current sustainability and wellness goals, particularly vital in the post-COVID-19 era. The integration of BIM in IEQ management promises not only to enhance the health, comfort, and energy efficiency of educational environments but also to transform them into more conducive spaces for teaching and learning. Furthermore, this research could influence the future of HE buildings by prompting universities and government bodies to revaluate and improve teaching and learning environments. It demonstrates how the synergy between IEQ and BIM can empower stakeholders to monitor IEQ conditions more effectively and make informed decisions in real-time. Moreover, the developed framework has broader applications as well; it can serve as a tool for other sustainability assessments, like energy analysis in HE buildings, leveraging measured data synchronized with the BIM model. In conclusion, this study bridges the gap between theoretical research and real-world application by practicalizing how advanced technologies like BIM can be effectively integrated to enhance environmental quality in educational institutions. It portrays the potential of integrating advanced technologies like BIM in the pursuit of improved environmental conditions in educational institutions.

Keywords: BIM, POE, IEQ, HE-buildings

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Authors: Ruth Shapira

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Introduction: The rapid urbanization of the last century confronts planners, regulatory bodies, developers and most of all the public with seemingly unsolved conflicts regarding values, capital, and wellbeing of the built and un-built urban space. There is an out of control change of scale of the urban form and of the rhythm of the urban life which has known no significant progress in the last 2-3 decades despite the on-growing urban population. It is the objective of this paper to analyze some of these fundamental issues through the case study of a relatively small town in the center of Israel (Kiryat-Ono, 36,000 inhabitants), unfold the deep structure of qualities versus disruptors, present some cure that we have developed to bridge over and humbly suggest a practice that may bring about a sustainable new urban environment based on timeless values of the past, an approach that can be generic for similar cases. Basic Methodologies:The object, the town of Kiryat Ono, shall be experimented upon in a series of four action processes: De-composition, Re-composition, the Centering process and, finally, Controlled Structural Disintegration. Each stage will be based on facts, analysis of previous multidisciplinary interventions on various layers – and the inevitable reaction of the OBJECT, leading to the conclusion based on innovative theoretical and practical methods that we have developed and that we believe are proper for the open ended network, setting the rules for the contemporary urban society to cluster by – thus – a new urban vocabulary based on the old structure of times passed. The Study: Kiryat Ono, was founded 70 years ago as an agricultural settlement and rapidly turned into an urban entity. In spite the massive intensification, the original DNA of the old small town was still deeply embedded, mostly in the quality of the public space and in the sense of clustered communities. In the past 20 years, the recent demand for housing has been addressed to on the national level with recent master plans and urban regeneration policies mostly encouraging individual economic initiatives. Unfortunately, due to the obsolete existing planning platform the present urban renewal is characterized by pressure of developers, a dramatic change in building scale and widespread disintegration of the existing urban and social tissue.Our office was commissioned to conceptualize two master plans for the two contradictory processes of Kiryat Ono’s future: intensification and conservation. Following a comprehensive investigation into the deep structures and qualities of the existing town, we developed a new vocabulary of conservation terms thus redefying the sense of PLACE. The main challenge was to create master plans that should offer a regulatory basis to the accelerated and sporadic development providing for the public good and preserving the characteristics of the place consisting of a tool box of design guidelines that will have the ability to reorganize space along the time axis in a sustainable way. In conclusion: The system of rules that we have developed can generate endless possible patterns making sure that at each implementation fragment an event is created, and a better place is revealed. It takes time and perseverance but it seems to be the way to provide a healthy and sustainable framework for the accelerated urbanization of our chaotic present.

Keywords: sustainable urban design, intensification, emergent urban patterns, sustainable housing, compact urban neighborhoods, sustainable regeneration, restoration, complexity, uncertainty, need for change, implications of legislation on local planning

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Authors: Dionyssia Lyra, Shoaib Ismail

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Salinization of natural resources constitutes a significant component of the degradation force that leads to depletion of productive lands and fresh water reserves. The global extent of salt-affected soils is approximately 7% of the earth’s land surface and is expanding. The problems of excessive salt accumulation are most widespread in coastal, arid and semi-arid regions, where agricultural production is substantially hindered. The use of crops that can withstand high saline conditions is extremely interesting in such a context. Salt-loving plants or else ‘halophytes’ thrive when grown in hostile saline conditions, where traditional crops cannot survive. Salicornia bigelovii, a halophytic crop with multiple uses (vegetable, forage, biofuel), has demonstrated remarkable adaptability to harsh climatic conditions prevailing in dry areas with great potential for its expansion. Since 2011, the International Center for Biosaline Agriculture (ICBA) with Masdar Institute (MI) and King Abdul Aziz University of Science & Technology (KAUST) to look into the potential for growing S. bigelovii under hot and dry conditions. Through the projects undertaken, 50 different S. bigelovii genotypes were assessed under high saline conditions. The overall goal was to select the best performing S. bigelovii populations in terms of seed and biomass production for future breeding. Specific objectives included: 1) evaluation of selected S. bigelovii genotypes for various agronomic and growth parameters under field conditions, 2) seed multiplication of S. bigelovii using saline groundwater and 3) acquisition of inbred lines for further breeding. Field trials were conducted for four consecutive years at ICBA headquarters. During the first year, one Salicornia population was evaluated for seed and biomass production at different salinity levels, fertilizer treatments and planting methods. All growth parameters and biomass productivity for the salicornia population showed better performance with optimal biomass production in terms of both salinity level and fertilizer application. During the second year, 46 Salicornia populations (obtained from KAUST and Masdar Institute) were evaluated for 24 growth parameters and treated with groundwater through drip irrigation. The plant material originated from wild collections. Six populations were also assessed for their growth performance under full-strength seawater. Salicornia populations were highly variable for all characteristics under study for both irrigation treatments, indicating that there is a large pool of genetic information available for breeding. Irrigation with the highest level of salinity had a negative impact on the agronomic performance. The maximum seed yield obtained was 2 t/ha at 20 dS/m (groundwater treatment) at 25 cm x 25 cm planting distance. The best performing Salicornia populations for fresh biomass and seed yield were selected for the following season. After continuous selection, the best performing salicornia will be adopted for scaling-up options. Taking into account the results of the production field trials, salicornia expansion will be targeted in coastal areas of the Arabian Peninsula. As a crop with high biofuel and forage potential, its cultivation can improve the livelihood of local farmers.

Keywords: biosaline agriculture, genotypes selection, halophytes, Salicornia bigelovii

Procedia PDF Downloads 386

Authors: Ildiko Fekete-Kertesz, Jade Chaker, Sylvain Berthelot, Viktoria Feigl, Monika Molnar, Lidia Favier

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There has been growing concern about emerging micropollutants in recent years, because of the possible environmental and health risk posed by these substances, which are released into the environment as a consequence of anthropogenic activities. Among them pharmaceuticals are currently not considered under water quality regulations; however, their potential effect on the environment have become more frequent in recent years. Due to the fact that these compounds can be detected in natural water matrices, it can be concluded, that the currently applied water treatment processes are not efficient enough for their effective elimination. To date, advanced oxidation processes (AOPs) are considered as highly competitive water treatment technologies for the removal of those organic micropollutants not treatable by conventional techniques due to their high chemical stability and/or low biodegradability. AOPs such as (photo)chemical oxidation and heterogeneous photocatalysis have proven their potential in degrading harmful organic compounds from aqueous matrices. However, some of these technologies generate reaction by-products, which can even be more toxic to aquatic organisms than the parent compounds. Thus, target compound removal does not necessarily result in the removal of toxicity. Therefore, to evaluate process efficiency the determination of the toxicity and ecotoxicity of the reaction intermediates is crucial to estimate the environmental risk of such techniques. In this context, the present study investigates the effectiveness of TiO2 assisted photodegradation for the removal of emerging water contaminants. Two drugs named losartan (used in high blood pressure medication) and levetiracetam (used to treat epilepsy) were considered in this work. The photocatalytic reactions were carried out with a commercial catalyst usually employed in photocatalysis. Moreover, the toxicity of the by-products generated during the process was assessed with various ecotoxicological methods applying aquatic test organisms from different trophic levels. A series of experiments were performed to evaluate the toxicity of untreated and treated solutions applying the Aliivibrio fischeri bioluminescence inhibition test, the Tetrahymena pyriformis proliferation inhibition test, the Daphnia magna lethality and immobilization tests and the Lemna minor growth inhibition test. The applied ecotoxicological methodology indicated sensitively the toxic effects of the treated and untreated water samples, hence the applied test battery is suitable for the ecotoxicological characterization of TiO2 based photocatalytic water treatment technologies and the indication of the formation of toxic by-products from the parent chemical compounds. Obtained results clearly showed that the TiO2 assisted photodegradation was more efficient in the elimination of losartan than levetiracetam. It was also observed that the treated levetiracetam solutions had more severe effect on the applied test organisms. A possible explanation would be the production of levetiracetam by-products, which are more toxic than the parent compound. The increased toxicity and the risk of formation of toxic metabolites represent one possible limitation to the implementation of photocatalytic treatment using TiO2 for the removal of losartan and levetiracetam. Our results proved that, the battery of ecotoxicity tests used in this work can be a promising investigation tool for the environmental risk assessment of photocatalytic processes.

Keywords: aquatic micropollutants, ecotoxicology, nano titanium dioxide, photocatalysis, water treatment

Procedia PDF Downloads 169

Authors: Nur A. Özdemir, Sude Erkin, Hatice K. Güney, Cemre S. Atılgan, Enes Huylu, Hüseyin Y. Altıntaş, Aysemin Top, Özak Durmuş

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Carbon emissions produced during a product’s life cycle, from extraction of raw materials up to waste disposal and market consumption activities are the major contributors to global warming. In the light of the science-based targets (SBT) leading the way to a zero-carbon economy for sustainable growth of the companies, carbon footprint reporting of the purchased goods has become critical for identifying hotspots and best practices for emission reduction opportunities. In line with Ford Otosan's corporate sustainability strategy, research was conducted to evaluate the carbon footprint of purchased products in accordance with Scope 3 of the Greenhouse Gas Protocol (GHG). The purpose of this paper is to develop a systematic and transparent methodology to calculate carbon footprint of the products produced by automotive OEMs (Original Equipment Manufacturers) within the context of automobile supply chain management. To begin with, primary material data were collected through IMDS (International Material Database System) corresponds to company’s three distinct types of vehicles including Light Commercial Vehicle (Courier), Medium Commercial Vehicle (Transit and Transit Custom), Heavy Commercial Vehicle (F-MAX). Obtained material data was classified as metals, plastics, liquids, electronics, and others to get insights about the overall material distribution of produced vehicles and matched to the SimaPro Ecoinvent 3 database which is one of the most extent versions for modelling material data related to the product life cycle. Product life cycle analysis was calculated within the framework of ISO 14040 – 14044 standards by addressing the requirements and procedures. A comprehensive literature review and cooperation with suppliers were undertaken to identify the production methods of parts used in vehicles and to find out the amount of scrap generated during part production. Cumulative weight and material information with related production process belonging the components were listed by multiplying with current sales figures. The results of the study show a key modelling on carbon footprint of products and processes based on a scientific approach to drive sustainable growth by setting straightforward, science-based emission reduction targets. Hence, this study targets to identify the hotspots and correspondingly provide broad ideas about our understanding of how to integrate carbon footprint estimates into our company's supply chain management by defining convenient actions in line with climate science. According to emission values arising from the production phase including raw material extraction and material processing for Ford OTOSAN vehicles subjected in this study, GHG emissions from the production of metals used for HCV, MCV and LCV account for more than half of the carbon footprint of the vehicle's production. Correspondingly, aluminum and steel have the largest share among all material types and achieving carbon neutrality in the steel and aluminum industry is of great significance to the world, which will also present an immense impact on the automobile industry. Strategic product sustainability plan which includes the use of secondary materials, conversion to green energy and low-energy process design is required to reduce emissions of steel, aluminum, and plastics due to the projected increase in total volume by 2030.

Keywords: automotive, carbon footprint, IMDS, scope 3, SimaPro, sustainability

Procedia PDF Downloads 86

Authors: Benjamin Thomas Greer, Grace Cotulla, Mandy Johnson

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Human trafficking is one of the fastest growing international crimes and human rights violations in the world. The United States Department of State (State Department) approximates some 800,000 to 900,000 people are annually trafficked across sovereign borders, with approximately 14,000 to 17,500 of these people coming into the United States. Today’s slavery is conducted by unscrupulous individuals who are often connected to organized criminal enterprises and transnational gangs, extracting huge monetary sums. According to the International Labour Organization (ILO), human traffickers collect approximately $32 billion worldwide annually. Surpassed only by narcotics dealing, trafficking of humans is tied with illegal arms sales as the second largest criminal industry in the world and is the fastest growing field in the 21st century. Perpetrators of this heinous crime abound. They are not limited to single or “sole practitioners” of human trafficking, but rather, often include Transnational Criminal Organizations (TCO), domestic street gangs, labor contractors, and otherwise seemingly ordinary citizens. Monetary gain is being elevated over territorial disputes and street gangs are increasingly operating in a collaborative effort with TCOs to further disguise their criminal activity; to utilizing their vast networks, in an attempt to avoid detection. Traffickers rely on a network of clandestine routes to sell their commodities with impunity. As law enforcement agencies seek to retard the expansion of transnational criminal organization’s entry into human trafficking, it is imperative that they develop reliable trafficking mapping of known exploitative routes. In a recent report given to the Mexican Congress, The Procuraduría General de la República (PGR) disclosed, from 2008 to 2010 they had identified at least 47 unique criminal networking routes used to traffic victims and that Mexico’s estimated domestic victims number between 800,000 adults and 20,000 children annually. Designing a reliable mapping system is a crucial step to effective law enforcement response and deploying a successful victim support system. Creating this mapping analytic is exceedingly difficult. Traffickers are constantly changing the way they traffic and exploit their victims. They swiftly adapt to local environmental factors and react remarkably well to market demands, exploiting limitations in the prevailing laws. This article will highlight how human trafficking has become one of the fastest growing and most high profile human rights violations in the world today; compile current efforts to map and illustrate trafficking routes; and will demonstrate how the proprietary analytical mapping analysis of point-source and destination-source mapping can help local law enforcement, governmental agencies and victim services providers effectively respond to the type and nature of trafficking to their specific geographical locale. Trafficking transcends state and international borders. It demands an effective and consistent cooperation between local, state, and federal authorities. Each region of the world has different impact factors which create distinct challenges for law enforcement and victim services. Our mapping system lays the groundwork for a targeted anti-trafficking response.

Keywords: human trafficking, mapping, routes, law enforcement intelligence

Procedia PDF Downloads 358

Authors: Syeda Fatima Manzelat

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The present study aims to study the groups of algal genera that are responsible for the biodeterioration, biodegradation, and biological pollution of the structures and features of the two historic parks of the UK. Different sites of Campbell Park and Great Linford Manor Park in Milton Keynes are selected to study the morphological, aesthetic, and physical effects of the algal growth. Specimens and swabs were collected mechanically from selected sites. Algal specimens are preserved in Lugol’s solution and labelled with standard information. Photomicrograph analysis of slides using taxonomic keys and visual observation identified algal species that are homogenously and non-homogenously mixed in the aerial, terrestrial, and aquatic habitats. A qualitative study revealed seven classes of Algae. Most of the algal genera isolated have proven records of potential biodegradation, discoloration, and biological pollution. Chlorophyceae was predominantly represented by eleven genera: Chlorella, Chlorococcum Cladophora, Coenochloris Cylindrocapsa, Microspora, Prasiola, Spirogyra, Trentepholia, Ulothrix and Zygnema. Charophyceae is represented by four genera: Cosmarium, Klebsormidium, Mesotaenium, and Mougeotia. Xanthophyceae with two genera, Tribonema and Vaucheria. Bacillariophyceae (Diatoms) are represented by six genera: Acnanthes, Bacillaria, Fragilaria, Gomphonema, Synedra, and Tabellaria, Dinophyceae with a Dinoflagellate. Rhodophyceae included Bangia and Batrachospermum, Cyanophyceae with five genera, Chroococcus, Gloeocapsa, Scytonema, Stigonema and Oscillatoria. The quantitative analysis by statistical method revealed that Chlorophyceae was the predominant class, with eleven genera isolated from different sites of the two parks. Coenochloris of Chlorophyceae was isolated from thirteen sites during the study, followed by Gloeocapsa of Cyanophyceae, which is isolated from 12 sites. These two algae impart varying shades of green colour on the surfaces on which they form biofilms. Prasiola, Vaucheria, and Trentepholia were isolated only from Great Linford Park. Trentepholia imparted a significant orange colour to the walls and trees of the sites. The compounds present in algae that are responsible for discoloration are the green pigment chlorophyll, orange pigment β-carotene, and yellow pigment quinone. Mesotaenium, Dinoflagellate, Gomphonema, Fragilaria, Tabellaria and two unidentified genera were isolated from Campbell Park only. Largest number of algal genera (25) were isolated from the canal of Campbell Park followed by (21) from the canal at Great Linford Manor Park. The Algae were found to grow on surfaces of walls, wooden fencings, metal sculptures, and railings. The Algae are reported to induce surface erosion, natural weathering, and cracking, leading to technical and mechanical instability and extensive damage to building materials. The algal biofilms secrete different organic acids, which are responsible for biosolubilization and biodeterioration of the building materials. The aquatic algal blooms isolated during the study release toxins which are responsible for allergy, skin rashes, vomiting, diarrhea, fever, muscle spasms, and lung and throat infections. The study identifies the places and locations at the historic sites which need to be paid attention. It provides an insight to the conservation strategies to overcome the negative impacts of bio colonization by algae. Prevention measures by different treatments need to be regularly monitored.

Keywords: algae, biodegradation, historic gardens, UK

Procedia PDF Downloads 34

Authors: Syeda Fatima Manzelat

Abstract:

The present study aims to study the groups of algal genera which are responsible for the biodeterioration, biodegradation and biological pollution of the structures and features of the two historic parks of UK. Different sites of Campbell Park and Great Linford Manor Park in Milton Keynes are selected to study morphological, aesthetic and physical effect of the algal growth. Specimens and swabs were collected mechanically from selected sites. Algal specimens are preserved in Lugol’s solution and labelled with standard information. Photomicrograph analysis of slides using taxonomic keys and visual observation identified algal species that are homogenously and non-homogenously mixed in the aerial, terrestrial and aquatic habitats. Qualitative study revealed seven classes of Algae. Most of the algal genera isolated are with proven records of potential biodegradation, discoloration and biological pollution. Chlorophyceae was predominant represented by eleven genera Chlorella, Chlorococcum Cladophora, Coenochloris Cylindrocapsa. Microspora, Prasiola, Spirogyra, Trentepholia, Ulothrix and Zygnema. Charophyceae is represented by four genera Cosmarium Klebsormidium, Mesotaenium and Mougeotia. Xanthophyceae with two genera Tribonema andVaucheria. Bacillariophyceae (Diatoms) represented by six genera Acnanthes, Bacillaria, Fragilaria, Gomphonema, Synedra and Tabellaria. Dinophyceae with a Dinoflagellate. Rhodophyceae included Bangia and Batrachospermum. Cyanophyceae with five genera, Chroococcus, Gloeocapsa, Scytonema, Stigonema and Oscillatoria. The quantitative analysis by statistical method revealed that Chlorophyceae was the predominant class with eleven genera isolated from different sites of the two parks. Coenochloris of Chlorophyceae was isolated from thirteen sites during the study followed by Gloeocapsa of Cyanophyceae which is isolated from 12 sites. These two algae impart varying shades of green colour on the surfaces on which they form biofilms. Prasiola, Vaucheria and Trentepholia were isolated only from Great Linford Park. Trentepholia imparted a significant orange colour to the walls and trees of the sites. The compounds present in algae that are responsible for discoloration are the green pigment chlorophyll, orange pigment β-carotene and yellow pigment quinone. Mesotaenium, Dinoflagellate, Gomphonema, Fragilaria, Tabellaria and 2 unidentified genera were isolated from Campbell Park only. Largest number of algal genera (25) were isolated from the canal of Campbell Park followed by (21) from the canal at Great Linford Manor Park. The Algae were found to grow on surfaces of walls, wooden fencings, metal sculptures and railing. The Algae are reported to induce surface erosion, natural weathering and cracking leading to technical and mechanical instability and extensive damage to building materials The algal biofilms secrete different organic acids which are responsible for bio solubilization and biodeterioration of the building materials. The aquatic algal blooms isolated during the study release toxins which are responsible for allergy, skin rashes, vomiting, diarrhoea, fever, muscle spasms, lung and throat infections The study identifies the places and locations at the historic sites which need to be paid attention. It provides an insight to the conservation strategies to overcome the negative impacts of bio colonization by algae. Prevention measures by different treatments need to be regularly monitored.

Keywords: algae, biodeterioration, historic gardens, UK

Procedia PDF Downloads 17

Authors: M. M. Hassani, S. Ammann, F. K. Wittel, P. Niemz, H. J. Herrmann

Abstract:

Application of engineered wood, especially in the form of glued-laminated timbers has increased significantly. Recent progress in plywood made of high strength and high stiffness hardwoods, like European beech, gives designers in general more freedom by increased dimensional stability and load-bearing capacity. However, the strong hygric dependence of basically all mechanical properties renders many innovative ideas futile. The tendency of hardwood for higher moisture sorption and swelling coefficients lead to significant residual stresses in glued-laminated configurations, cross-laminated patterns in particular. These stress fields cause initiation and evolution of cracks in the bond-lines resulting in: interfacial de-bonding, loss of structural integrity, and reduction of load-carrying capacity. Subsequently, delamination of glued-laminated timbers made of hardwood elements can be considered as the dominant failure mechanism in such composite elements. In addition, long-term creep and mechano-sorption under changing environmental conditions lead to loss of stiffness and can amplify delamination growth over the lifetime of a structure even after decades. In this study we investigate the delamination process of adhesively bonded hardwood (European beech) elements subjected to changing climatic conditions. To gain further insight into the long-term performance of adhesively bonded elements during the design phase of new products, the development and verification of an authentic moisture-dependent constitutive model for various species is of great significance. Since up to now, a comprehensive moisture-dependent rheological model comprising all possibly emerging deformation mechanisms was missing, a 3D orthotropic elasto-plastic, visco-elastic, mechano-sorptive material model for wood, with all material constants being defined as a function of moisture content, was developed. Apart from the solid wood adherends, adhesive layer also plays a crucial role in the generation and distribution of the interfacial stresses. Adhesive substance can be treated as a continuum layer constructed from finite elements, represented as a homogeneous and isotropic material. To obtain a realistic assessment on the mechanical performance of the adhesive layer and a detailed look at the interfacial stress distributions, a generic constitutive model including all potentially activated deformation modes, namely elastic, plastic, and visco-elastic creep was developed. We focused our studies on the three most common adhesive systems for structural timber engineering: one-component polyurethane adhesive (PUR), melamine-urea-formaldehyde (MUF), and phenol-resorcinol-formaldehyde (PRF). The corresponding numerical integration approaches, with additive decomposition of the total strain are implemented within the ABAQUS FEM environment by means of user subroutine UMAT. To predict the true stress state, we perform a history dependent sequential moisture-stress analysis using the developed material models for both wood substrate and adhesive layer. Prediction of the delamination process is founded on the fracture mechanical properties of the adhesive bond-line, measured under different levels of moisture content and application of the cohesive interface elements. Finally, we compare the numerical predictions with the experimental observations of de-bonding in glued-laminated samples under changing environmental conditions.

Keywords: engineered wood, adhesive, material model, FEM analysis, fracture mechanics, delamination

Procedia PDF Downloads 408

Authors: Hoora Beheshti Haradasht, Abooali Golzary

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Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

Procedia PDF Downloads 55