Search results for: mixed spin Heisenberg model
Commenced in January 2007
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Paper Count: 19239

Search results for: mixed spin Heisenberg model

219 Stakeholder Mapping and Requirements Identification for Improving Traceability in the Halal Food Supply Chain

Authors: Laila A. H. F. Dashti, Tom Jackson, Andrew West, Lisa Jackson

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Traceability systems are important in the agri-food and halal food sectors for monitoring ingredient movements, tracking sources, and ensuring food integrity. However, designing a traceability system for the halal food supply chain is challenging due to diverse stakeholder requirements and complex needs. Existing literature on stakeholder mapping and identifying requirements for halal food supply chains is limited. To address this gap, a pilot study was conducted to identify the objectives, requirements, and recommendations of stakeholders in the Kuwaiti halal food industry. The study collected data through semi-structured interviews with an international halal food manufacturer based in Kuwait. The aim was to gain a deep understanding of stakeholders' objectives, requirements, processes, and concerns related to the design of a traceability system in the country's halal food sector. Traceability systems are being developed and tested in the agri-food and halal food sectors due to their ability to monitor ingredient movements, track sources, and detect potential issues related to food integrity. Designing a traceability system for the halal food supply chain poses significant challenges due to diverse stakeholder requirements and the complexity of their needs (including varying food ingredients, different sources, destinations, supplier processes, certifications, etc.). Achieving a halal food traceability solution tailored to stakeholders' requirements within the supply chain necessitates prior knowledge of these needs. Although attempts have been made to address design-related issues in traceability systems, literature on stakeholder mapping and identification of requirements specific to halal food supply chains is scarce. Thus, this pilot study aims to identify the objectives, requirements, and recommendations of stakeholders in the halal food industry. The paper presents insights gained from the pilot study, which utilized semi-structured interviews to collect data from a Kuwait-based international halal food manufacturer. The objective was to gain an in-depth understanding of stakeholders' objectives, requirements, processes, and concerns pertaining to the design of a traceability system in Kuwait's halal food sector. The stakeholder mapping results revealed that government entities, food manufacturers, retailers, and suppliers are key stakeholders in Kuwait's halal food supply chain. Lessons learned from this pilot study regarding requirement capture for traceability systems include the need to streamline communication, focus on communication at each level of the supply chain, leverage innovative technologies to enhance process structuring and operations and reduce halal certification costs. The findings also emphasized the limitations of existing traceability solutions, such as limited cooperation and collaboration among stakeholders, high costs of implementing traceability systems without government support, lack of clarity regarding product routes, and disrupted communication channels between stakeholders. These findings contribute to a broader research program aimed at developing a stakeholder requirements framework that utilizes "business process modelling" to establish a unified model for traceable stakeholder requirements.

Keywords: supply chain, traceability system, halal food, stakeholders’ requirements

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218 Drivers of Global Great Power Assertiveness: Russia and Its Involvement in the Global South

Authors: Elina Vroblevska, Toms Ratfelders

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This paper examines the impact of international status-seeking aspirations on great power behavior within the international system. In particular, we seek to test the assumption advanced by the proponents of the Social Identity Theory (SIT) that the inability to achieve social mobilization through joining perceived higher-status social groups (of states) leads great powers to adopt the approach of social competition in which they aim to equal or outdo the dominant group in the area on which its claim to superior status rests. Since the dissolution of the Soviet Union, Russia has struggled to be accepted as a great power by the group of Western states that had created the dominant international system order, while the Soviet states were isolated. While the 1990s and the beginning of the 21st century can be characterized by striving to integrate into the existing order, the second decade has seen a rather sharp turn towards creating a new power center for Russia through the realization of ideas of multipolarity rivalry and uniqueness of the state itself. Increasingly, we have seen the Kremlin striving to collaborate and mobilize groups of states that fall outside of the categories of democracy, multiculturalism, and international order, the way that is perceived by the dominant group, which can be described as the West. Instead, Russia builds its own narrative where it creates an alternative understanding of these values, differentiating from the higher-status social group. The Global South, from a Russian perspective, is the group of states that can still be swayed to create an alternative power center in the international system - one where Russia can assert its status as a great power. This is based on a number of reasons, the most important being that the global north is already highly institutionalized in terms of economy (the EU) and defense (NATO), leaving no room for Russia but to integrate within the existing framework. Second, the difference in values and their interpretation - Russia has been adamant, for the last twenty years, on basing its moral code on traditional values like religion, the heterosexual family model, and moral superiority, which contradict the overall secularism of the Global North. And last, the striking difference in understanding of state governance models - with Russia becoming more autocratic over the course of the last 20 years, it has deliberately created distance between itself and democratic states, entering a “gray area” of alternative understanding of democracy which is more relatable to the global South countries. Using computational text analysis of the excerpts of Vladimir Putin’s speeches delivered from 2000-2022 regarding the areas that fall outside the immediate area of interest of Russia (the Global South), we identify 80 topics that relate to the particular component of the great power status - interest to use force globally. These topics are compared across four temporal frames that capture the periods of more and less permissible Western social boundaries. We find that there exists a negative association between such permissiveness and Putin’s emphasis on the “use of force” topics. This lends further support to the Social Identity Theory and contributes to broadening its applicability to explaining the questions related to great power assertiveness in areas outside of their primary focus regions.

Keywords: Russia, Global South, great power, identity

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217 Interactions between Sodium Aerosols and Fission Products: A Theoretical Chemistry and Experimental Approach

Authors: Ankita Jadon, Sidi Souvi, Nathalie Girault, Denis Petitprez

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Safety requirements for Generation IV nuclear reactor designs, especially the new generation sodium-cooled fast reactors (SFR) require a risk-informed approach to model severe accidents (SA) and their consequences in case of outside release. In SFRs, aerosols are produced during a core disruptive accident when primary system sodium is ejected into the containment and burn in contact with the air; producing sodium aerosols. One of the key aspects of safety evaluation is the in-containment sodium aerosol behavior and their interaction with fission products. The study of the effects of sodium fires is essential for safety evaluation as the fire can both thermally damage the containment vessel and cause an overpressurization risk. Besides, during the fire, airborne fission product first dissolved in the primary sodium can be aerosolized or, as it can be the case for fission products, released under the gaseous form. The objective of this work is to study the interactions between sodium aerosols and fission products (Iodine, toxic and volatile, being the primary concern). Sodium fires resulting from an SA would produce aerosols consisting of sodium peroxides, hydroxides, carbonates, and bicarbonates. In addition to being toxic (in oxide form), this aerosol will then become radioactive. If such aerosols are leaked into the environment, they can pose a danger to the ecosystem. Depending on the chemical affinity of these chemical forms with fission products, the radiological consequences of an SA leading to containment leak tightness loss will also be affected. This work is split into two phases. Firstly, a method to theoretically understand the kinetics and thermodynamics of the heterogeneous reaction between sodium aerosols and fission products: I2 and HI are proposed. Ab-initio, density functional theory (DFT) calculations using Vienna ab-initio simulation package are carried out to develop an understanding of the surfaces of sodium carbonate (Na2CO3) aerosols and hence provide insight on its affinity towards iodine species. A comprehensive study of I2 and HI adsorption, as well as bicarbonate formation on the calculated lowest energy surface of Na2CO3, was performed which provided adsorption energies and description of the optimized configuration of adsorbate on the stable surface. Secondly, the heterogeneous reaction between (I2)g and Na2CO3 aerosols were investigated experimentally. To study this, (I2)g was generated by heating a permeation tube containing solid I2, and, passing it through a reaction chamber containing Na2CO3 aerosol deposit. The concentration of iodine was then measured at the exit of the reaction chamber. Preliminary observations indicate that there is an effective uptake of (I2)g on Na2CO3 surface, as suggested by our theoretical chemistry calculations. This work is the first step in addressing the gaps in knowledge of in-containment and atmospheric source term which are essential aspects of safety evaluation of SFR SA. In particular, this study is aimed to determine and characterize the radiological and chemical source term. These results will then provide useful insights for the developments of new models to be implemented in integrated computer simulation tool to analyze and evaluate SFR safety designs.

Keywords: iodine adsorption, sodium aerosols, sodium cooled reactor, DFT calculations, sodium carbonate

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216 Hygrothermal Interactions and Energy Consumption in Cold Climate Hospitals: Integrating Numerical Analysis and Case Studies to Investigate and Analyze the Impact of Air Leakage and Vapor Retarding

Authors: Amir E. Amirzadeh, Richard K. Strand

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Moisture-induced problems are a significant concern for building owners, architects, construction managers, and building engineers, as they can have substantial impacts on building enclosures' durability and performance. Computational analyses, such as hygrothermal and thermal analysis, can provide valuable information and demonstrate the expected relative performance of building enclosure systems but are not grounded in absolute certainty. This paper evaluates the hygrothermal performance of common enclosure systems in hospitals in cold climates. The study aims to investigate the impact of exterior wall systems on hospitals, focusing on factors such as durability, construction deficiencies, and energy performance. The study primarily examines the impact of air leakage and vapor retarding layers relative to energy consumption. While these factors have been studied in residential and commercial buildings, there is a lack of information on their impact on hospitals in a holistic context. The study integrates various research studies and professional experience in hospital building design to achieve its objective. The methodology involves surveying and observing exterior wall assemblies, reviewing common exterior wall assemblies and details used in hospital construction, performing simulations and numerical analyses of various variables, validating the model and mechanism using available data from industry and academia, visualizing the outcomes of the analysis, and developing a mechanism to demonstrate the relative performance of exterior wall systems for hospitals under specific conditions. The data sources include case studies from real-world projects and peer-reviewed articles, industry standards, and practices. This research intends to integrate and analyze the in-situ and as-designed performance and durability of building enclosure assemblies with numerical analysis. The study's primary objective is to provide a clear and precise roadmap to better visualize and comprehend the correlation between the durability and performance of common exterior wall systems used in the construction of hospitals and the energy consumption of these buildings under certain static and dynamic conditions. As the construction of new hospitals and renovation of existing ones have grown over the last few years, it is crucial to understand the effect of poor detailing or construction deficiencies on building enclosure systems' performance and durability in healthcare buildings. This study aims to assist stakeholders involved in hospital design, construction, and maintenance in selecting durable and high-performing wall systems. It highlights the importance of early design evaluation, regular quality control during the construction of hospitals, and understanding the potential impacts of improper and inconsistent maintenance and operation practices on occupants, owner, building enclosure systems, and Heating, Ventilation, and Air Conditioning (HVAC) systems, even if they are designed to meet the project requirements.

Keywords: hygrothermal analysis, building enclosure, hospitals, energy efficiency, optimization and visualization, uncertainty and decision making

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215 Taking the Good with the Bad: Psychological Well-Being and Social Integration in Russian-Speaking Immigrants in Montreal

Authors: Momoka Sunohara, Ashley J. Lemieux, Esther Yakobov, Andrew G. Ryder, Tomas Jurcik

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Immigration brings changes in many aspects of an individual's life, from social support dynamics, to housing and language, as well as difficulties with regards to discrimination, trauma, and loss. Past research has mostly emphasized individual differences in mental health and has neglected the impact of social-ecological context, such as acculturation and ethnic density. Purpose: The present study aimed to assess the relationship between variables associated with social integration such as perceived ethnic density and ways of coping, as well as psychological adjustment in a rapidly growing non-visible minority group of immigrants in Canada. Data: A small subset of an archival data from our previously published study was reanalyzed with additional variables. Data included information from 269 Russian-Speaking immigrants in Montreal, Canada. Method: Canonical correlation analysis (CCA) investigated the relationship between two sets of variables. SAS PROC CANCORR was used to conduct CCA on a set of social integration variables, including ethnic density, discrimination, social support, family functioning, and acculturation, and a set of psychological well-being variables, including distress, depression, self-esteem, and life satisfaction. In addition, canonical redundancy analysis was performed to calculate the proportion of variances of original variables explained by their own canonical variates. Results: Significance tests using Rao’s F statistics indicated that the first two canonical correlations (i.e., r1 = 0.64, r2 = 0.40) were statistically significant (p-value < 0.0001). Additionally, canonical redundancy analysis showed that the first two well-being canonical variates explained separately 62.9% and 12.8% variances of the standardized well-being variables, whereas the first two social integration canonical variates explained separately 14.7% and 16.7% variances of the standardized social integration variables. These results support the selection of the first two canonical correlations. Then, we interpreted the derived canonical variates based on their canonical structure (i.e., correlations with original variables). Two observations can be concluded. First, individuals who have adequate social support, and who, as a family, cope by acquiring social support, mobilizing others and reframing are more likely to have better self-esteem, greater life satisfaction and experience less feelings of depression or distress. Second, individuals who feel discriminated yet rate higher on a mainstream acculturation scale, and who, as a family, cope by acquiring social support, mobilizing others and using spirituality, while using less passive strategies are more likely to have better life satisfaction but also higher degree of depression. Implications: This model may serve to explain the complex interactions that exist between social and emotional adjustment and aid in facilitating the integration of individuals immigrating into new communities. The same group may experience greater depression but paradoxically improved life satisfaction associated with their coping process. Such findings need to be placed in the context of Russian cultural values. For instance, some Russian-speakers may value the expression of negative emotions with significant others during the integration process; this in turn may make negative emotions more salient, but also facilitate a greater sense of family and community connection, as well as life satisfaction.

Keywords: acculturation, ethnic density, mental health, Russian-speaking

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214 Upon Poly(2-Hydroxyethyl Methacrylate-Co-3, 9-Divinyl-2, 4, 8, 10-Tetraoxaspiro (5.5) Undecane) as Polymer Matrix Ensuring Intramolecular Strategies for Further Coupling Applications

Authors: Aurica P. Chiriac, Vera Balan, Mihai Asandulesa, Elena Butnaru, Nita Tudorachi, Elena Stoleru, Loredana E. Nita, Iordana Neamtu, Alina Diaconu, Liliana Mititelu-Tartau

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The interest for studying ‘smart’ materials is entirely justified and in this context were realized investigations on poly(2-hydroxyethylmethacrylate-co-3, 9-divinyl-2, 4, 8, 10-tetraoxaspiro (5.5) undecane), which is a macromolecular compound with sensibility at pH and temperature, gel formation capacity, binding properties, amphilicity, good oxidative and thermal stability. Physico-chemical characteristics in terms of the molecular weight, temperature-sensitive abilities and thermal stability, as well rheological, dielectric and spectroscopic properties were evaluated in correlation with further coupling capabilities. Differential scanning calorimetry investigation indicated Tg at 36.6 °C and a melting point at Tm=72.8°C, for the studied copolymer, and up to 200oC two exothermic processes (at 99.7°C and 148.8°C) were registered with losing weight of about 4 %, respective 19.27%, which indicate just processes of thermal decomposition (and not phenomena of thermal transition) owing to scission of the functional groups and breakage of the macromolecular chains. At the same time, the rheological studies (rotational tests) confirmed the non-Newtonian shear-thinning fluid behavior of the copolymer solution. The dielectric properties of the copolymer have been evaluated in order to investigate the relaxation processes and two relaxation processes under Tg value were registered and attributed to localized motions of polar groups from side chain macromolecules, or parts of them, without disturbing the main chains. According to literature and confirmed as well by our investigations, β-relaxation is assigned with the rotation of the ester side group and the γ-relaxation corresponds to the rotation of hydroxy- methyl side groups. The fluorescence spectroscopy confirmed the copolymer structure, the spiroacetal moiety getting an axial conformation, more stable, with lower energy, able for specific interactions with molecules from environment, phenomena underlined by different shapes of the emission spectra of the copolymer. Also, the copolymer was used as template for indomethacin incorporation as model drug, and the biocompatible character of the complex was confirmed. The release behavior of the bioactive compound was dependent by the copolymer matrix composition, the increasing of 3, 9-divinyl-2, 4, 8, 10-tetraoxaspiro (5.5) undecane comonomer amount attenuating the drug release. At the same time, the in vivo studies did not show significant differences of leucocyte formula elements, GOT, GPT and LDH levels, nor immune parameters (OC, PC, and BC) between control mice group and groups treated just with copolymer samples, with or without drug, data attesting the biocompatibility of the polymer samples. The investigation of the physico-chemical characteristics of poly(2-hydrxyethyl methacrylate-co-3, 9-divinyl-2, 4, 8, 10-tetraoxaspiro (5.5) undecane) in terms of temperature-sensitive abilities, rheological and dielectrical properties, are bringing useful information for further specific use of this polymeric compound.

Keywords: bioapplications, dielectric and spectroscopic properties, dual sensitivity at pH and temperature, smart materials

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213 Fully Autonomous Vertical Farm to Increase Crop Production

Authors: Simone Cinquemani, Lorenzo Mantovani, Aleksander Dabek

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New technologies in agriculture are opening new challenges and new opportunities. Among these, certainly, robotics, vision, and artificial intelligence are the ones that will make a significant leap, compared to traditional agricultural techniques, possible. In particular, the indoor farming sector will be the one that will benefit the most from these solutions. Vertical farming is a new field of research where mechanical engineering can bring knowledge and know-how to transform a highly labor-based business into a fully autonomous system. The aim of the research is to develop a multi-purpose, modular, and perfectly integrated platform for crop production in indoor vertical farming. Activities will be based both on hardware development such as automatic tools to perform different activities on soil and plants, as well as research to introduce an extensive use of monitoring techniques based on machine learning algorithms. This paper presents the preliminary results of a research project of a vertical farm living lab designed to (i) develop and test vertical farming cultivation practices, (ii) introduce a very high degree of mechanization and automation that makes all processes replicable, fully measurable, standardized and automated, (iii) develop a coordinated control and management environment for autonomous multiplatform or tele-operated robots in environments with the aim of carrying out complex tasks in the presence of environmental and cultivation constraints, (iv) integrate AI-based algorithms as decision support system to improve quality production. The coordinated management of multiplatform systems still presents innumerable challenges that require a strongly multidisciplinary approach right from the design, development, and implementation phases. The methodology is based on (i) the development of models capable of describing the dynamics of the various platforms and their interactions, (ii) the integrated design of mechatronic systems able to respond to the needs of the context and to exploit the strength characteristics highlighted by the models, (iii) implementation and experimental tests performed to test the real effectiveness of the systems created, evaluate any weaknesses so as to proceed with a targeted development. To these aims, a fully automated laboratory for growing plants in vertical farming has been developed and tested. The living lab makes extensive use of sensors to determine the overall state of the structure, crops, and systems used. The possibility of having specific measurements for each element involved in the cultivation process makes it possible to evaluate the effects of each variable of interest and allows for the creation of a robust model of the system as a whole. The automation of the laboratory is completed with the use of robots to carry out all the necessary operations, from sowing to handling to harvesting. These systems work synergistically thanks to the knowledge of detailed models developed based on the information collected, which allows for deepening the knowledge of these types of crops and guarantees the possibility of tracing every action performed on each single plant. To this end, artificial intelligence algorithms have been developed to allow synergistic operation of all systems.

Keywords: automation, vertical farming, robot, artificial intelligence, vision, control

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212 Clinical Presentation and Immune Response to Intramammary Infection of Holstein-Friesian Heifers with Isolates from Two Staphylococcus aureus Lineages

Authors: Dagmara A. Niedziela, Mark P. Murphy, Orla M. Keane, Finola C. Leonard

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Staphylococcus aureus is the most frequent cause of clinical and subclinical bovine mastitis in Ireland. Mastitis caused by S. aureus is often chronic and tends to recur after antibiotic treatment. This may be due to several virulence factors, including attributes that enable the bacterium to internalize into bovine mammary epithelial cells, where it may evade antibiotic treatment, or evade the host immune response. Four bovine-adapted lineages (CC71, CC97, CC151 and ST136) were identified among a collection of Irish S. aureus mastitis isolates. Genotypic variation of mastitis-causing strains may contribute to different presentations of the disease, including differences in milk somatic cell count (SCC), the main method of mastitis detection. The objective of this study was to investigate the influence of bacterial strain and lineage on host immune response, by employing cell culture methods in vitro as well as an in vivo infection model. Twelve bovine adapted S. aureus strains were examined for internalization into bovine mammary epithelial cells (bMEC) and their ability to induce an immune response from bMEC (using qPCR and ELISA). In vitro studies found differences in a variety of virulence traits between the lineages. Strains from lineages CC97 and CC71 internalized more efficiently into bovine mammary epithelial cells (bMEC) than CC151 and ST136. CC97 strains also induced immune genes in bMEC more strongly than strains from the other 3 lineages. One strain each of CC151 and CC97 that differed in their ability to cause an immune response in bMEC were selected on the basis of the above in vitro experiments. Fourteen first-lactation Holstein-Friesian cows were purchased from 2 farms on the basis of low SCC (less than 50 000 cells/ml) and infection free status. Seven cows were infected with 1.73 x 102 c.f.u. of the CC97 strain (Group 1) and another seven with 5.83 x 102 c.f.u. of the CC151 strain (Group 2). The contralateral quarter of each cow was inoculated with PBS (vehicle). Clinical signs of infection (temperature, milk and udder appearance, milk yield) were monitored for 30 days. Blood and milk samples were taken to determine bacterial counts in milk, SCC, white blood cell populations and cytokines. Differences in disease presentation in vivo between groups were observed, with two animals from Group 2 developing clinical mastitis and requiring antibiotic treatment, while one animal from Group 1 did not develop an infection for the duration of the study. Fever (temperature > 39.5⁰C) was observed in 3 animals from Group 2 and in none from Group 1. Significant differences in SCC and bacterial load between groups were observed in the initial stages of infection (week 1). Data is also being collected on cytokines and chemokines secreted during the course of infection. The results of this study suggest that a strain from lineage CC151 may cause more severe clinical mastitis, while a strain from lineage CC97 may cause mild, subclinical mastitis. Diversity between strains of S. aureus may therefore influence the clinical presentation of mastitis, which in turn may influence disease detection and treatment needs.

Keywords: Bovine mastitis, host immune response, host-pathogen interactions, Staphylococcus aureus

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211 Characteristics of Plasma Synthetic Jet Actuator in Repetitive Working Mode

Authors: Haohua Zong, Marios Kotsonis

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Plasma synthetic jet actuator (PSJA) is a new concept of zero net mass flow actuator which utilizes pulsed arc/spark discharge to rapidly pressurize gas in a small cavity under constant-volume conditions. The unique combination of high exit jet velocity (>400 m/s) and high actuation frequency (>5 kHz) provides a promising solution for high-speed high-Reynolds-number flow control. This paper focuses on the performance of PSJA in repetitive working mode which is more relevant to future flow control applications. A two-electrodes PSJA (cavity volume: 424 mm3, orifice diameter: 2 mm) together with a capacitive discharge circuit (discharge energy: 50 mJ-110 mJ) is designed to enable repetitive operation. Time-Resolved Particle Imaging Velocimetry (TR-PIV) system working at 10 kHz is exploited to investigate the influence of discharge frequency on performance of PSJA. In total, seven cases are tested, covering a wide range of discharge frequencies (20 Hz-560 Hz). The pertinent flow features (shock wave, vortex ring and jet) remain the same for single shot mode and repetitive working mode. Shock wave is issued prior to jet eruption. Two distinct vortex rings are formed in one cycle. The first one is produced by the starting jet whereas the second one is related with the shock wave reflection in cavity. A sudden pressure rise is induced at the throat inlet by the reflection of primary shock wave, promoting the shedding of second vortex ring. In one cycle, jet exit velocity first increases sharply, then decreases almost linearly. Afterwards, an alternate occurrence of multiple jet stages and refresh stages is observed. By monitoring the dynamic evolution of exit velocity in one cycle, some integral performance parameters of PSJA can be deduced. As frequency increases, the jet intensity in steady phase decreases monotonically. In the investigated frequency range, jet duration time drops from 250 µs to 210 µs and peak jet velocity decreases from 53 m/s to approximately 39 m/s. The jet impulse and the expelled gas mass (0.69 µN∙s and 0.027 mg at 20 Hz) decline by 48% and 40%, respectively. However, the electro-mechanical efficiency of PSJA defined by the ratio of jet mechanical energy to capacitor energy doesn’t show significant difference (o(0.01%)). Fourier transformation of the temporal exit velocity signal indicates two dominant frequencies. One corresponds to the discharge frequency, while the other accounts for the alternation frequency of jet stage and refresh stage in one cycle. The alternation period (300 µs approximately) is independent of discharge frequency, and possibly determined intrinsically by the actuator geometry. A simple analytical model is established to interpret the alternation of jet stage and refresh stage. Results show that the dynamic response of exit velocity to a small-scale disturbance (jump in cavity pressure) can be treated as a second-order under-damping system. Oscillation frequency of the exit velocity, namely alternation frequency, is positively proportional to exit area, but inversely proportional to cavity volume and throat length. Theoretical value of alternation period (305 µs) agrees well with the experimental value.

Keywords: plasma, synthetic jet, actuator, frequency effect

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210 Genome-Wide Analysis Identifies Locus Associated with Parathyroid Hormone Levels

Authors: Antonela Matana, Dubravka Brdar, Vesela Torlak, Marijana Popovic, Ivana Gunjaca, Ozren Polasek, Vesna Boraska Perica, Maja Barbalic, Ante Punda, Caroline Hayward, Tatijana Zemunik

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Parathyroid hormone (PTH) plays a critical role in the regulation of bone mineral metabolism and calcium homeostasis. Higher PTH levels are associated with heart failure, hypertension, coronary artery disease, cardiovascular mortality and poorer bone health. A twin study estimated that 60% of the variation in PTH concentrations is genetically determined. Only one GWAS of PTH concentration has been reported to date. Identified loci explained 4.5% of the variance in circulating PTH, suggesting that additional genetic variants remain undiscovered. Therefore, the aim of this study was to identify novel genetic variants associated with PTH levels in a general population. We have performed a GWAS meta-analysis on 2596 individuals originating from three Croatian cohorts: City of Split and the Islands of Korčula and Vis, within a large-scale project of “10,001 Dalmatians”. A total of 7 411 206 variants, imputed using the 1000 Genomes reference panel, with minor allele frequency ≥ 1% and Rsq ≥ 0.5 were analyzed for the association. GWAS within each data set was performed under an additive model, controlling for age, gender and relatedness. Meta-analysis was conducted using the inverse-variance fixed-effects method. Furthermore, to identify sex-specific effects, we have conducted GWAS meta-analyses analyzing males and females separately. In addition, we have performed biological pathway analysis. Four SNPs, representing one locus, reached genome-wide significance. The most significant SNP was rs11099476 on chromosome 4 (P=1.15x10-8), which explained 1.14 % of the variance in PTH. The SNP is located near the protein-coding gene RASGEF1B. Additionally, we detected suggestive association with SNPs, rs77178854 located on chromosome 2 in the DPP10 gene (P=2.46x10-7) and rs481121 located on chromosome 1 (P=3.58x10-7) near the GRIK1 gene. One of the top hits detected in the main meta-analysis, intron variant rs77178854 located within DPP10 gene, reached genome-wide significance in females (P=2.21x10-9). No single locus was identified in the meta-analysis in males. Fifteen biological pathways were functionally enriched at a P<0.01, including muscle contraction, ion homeostasis and cardiac conduction as the most significant pathways. RASGEF1B is the guanine nucleotide exchange factor, known to be associated with height, bone density, and hip. DPP10 encodes a membrane protein that is a member of the serine proteases family, which binds specific voltage-gated potassium channels and alters their expression and biophysical properties. In conclusion, we identified 2 novel loci associated with PTH levels in a general population, providing us with further insights into the genetics of this complex trait.

Keywords: general population, genome-wide association analysis, parathyroid hormone, single nucleotide polymorphisms.

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209 Catalytic Decomposition of Formic Acid into H₂/CO₂ Gas: A Distinct Approach

Authors: Ayman Hijazi, Witold Kwapinski, J. J. Leahy

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Finding a sustainable alternative energy to fossil fuel is an urgent need as various environmental challenges in the world arise. Therefore, formic acid (FA) decomposition has been an attractive field that lies at the center of the biomass platform, comprising a potential pool of hydrogen energy that stands as a distinct energy vector. Liquid FA features considerable volumetric energy density of 6.4 MJ/L and a specific energy density of 5.3 MJ/Kg that qualifies it in the prime seat as an energy source for transportation infrastructure. Additionally, the increasing research interest in FA decomposition is driven by the need for in-situ H₂ production, which plays a key role in the hydrogenation reactions of biomass into higher-value components. It is reported elsewhere in the literature that catalytic decomposition of FA is usually performed in poorly designed setups using simple glassware under magnetic stirring, thus demanding further energy investment to retain the used catalyst. Our work suggests an approach that integrates designing a distinct catalyst featuring magnetic properties with a robust setup that minimizes experimental & measurement discrepancies. One of the most prominent active species for the dehydrogenation/hydrogenation of biomass compounds is palladium. Accordingly, we investigate the potential of engrafting palladium metal onto functionalized magnetic nanoparticles as a heterogeneous catalyst to favor the production of CO-free H₂ gas from FA. Using an ordinary magnet to collect the spent catalyst renders core-shell magnetic nanoparticles as the backbone of the process. Catalytic experiments were performed in a jacketed batch reactor equipped with an overhead stirrer under an inert medium. Through a distinct approach, FA is charged into the reactor via a high-pressure positive displacement pump at steady-state conditions. The produced gas (H₂+CO₂) was measured by connecting the gas outlet to a measuring system based on the amount of the displaced water. The uniqueness of this work lies in designing a very responsive catalyst, pumping a consistent amount of FA into a sealed reactor running at steady-state mild temperatures, and continuous gas measurement, along with collecting the used catalyst without the need for centrifugation. Catalyst characterization using TEM, XRD, SEM, and CHN elemental analyzer provided us with details of catalyst preparation and facilitated new venues to alter the nanostructure of the catalyst framework. Consequently, the introduction of amine groups has led to appreciable improvements in terms of dispersion of the doped metals and eventually attaining nearly complete conversion (100%) of FA after 7 hours. The relative importance of the process parameters such as temperature (35-85°C), stirring speed (150-450rpm), catalyst loading (50-200mgr.), and Pd doping ratio (0.75-1.80wt.%) on gas yield was assessed by a Taguchi design-of-experiment based model. Experimental results showed that operating at a lower temperature range (35-50°C) yielded more gas, while the catalyst loading and Pd doping wt.% were found to be the most significant factors with P-values 0.026 & 0.031, respectively.

Keywords: formic acid decomposition, green catalysis, hydrogen, mesoporous silica, process optimization, nanoparticles

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208 Implementing Urban Rainwater Harvesting Systems: Between Policy and Practice

Authors: Natàlia Garcia Soler, Timothy Moss

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Despite the multiple benefits of sustainable urban drainage, as demonstrated in numerous case studies across the world, urban rainwater harvesting techniques are generally restricted to isolated model projects. The leap from niche to mainstream has, in most cities, proved an elusive goal. Why policies promoting rainwater harvesting are limited in their widespread implementation has seldom been subjected to systematic analysis. Much of the literature on the policy, planning and institutional contexts of these techniques focus either on their potential benefits or on project design, but very rarely on a critical-constructive analysis of past experiences of implementation. Moreover, the vast majority of these contributions are restricted to single-case studies. There is a dearth of knowledge with respect to, firstly, policy implementation processes and, secondly, multi-case analysis. Insights from both, the authors argue, are essential to inform more effective rainwater harvesting in cities in the future. This paper presents preliminary findings from a research project on rainwater harvesting in cities from a social science perspective that is funded by the Swedish Research Foundation (Formas). This project – UrbanRain – is examining the challenges and opportunities of mainstreaming rainwater harvesting in three European cities. The paper addresses two research questions: firstly, what lessons can be learned on suitable policy incentives and planning instruments for rainwater harvesting from a meta-analysis of the relevant international literature and, secondly, how far these lessons are reflected in a study of past and ongoing rainwater harvesting projects in a European forerunner city. This two-tier approach frames the structure of the paper. We present, first, the results of the literature analysis on policy and planning issues of urban rainwater harvesting. Here, we analyze quantitatively and qualitatively the literature of the past 15 years on this topic in terms of thematic focus, issues addressed and key findings and draw conclusions on research gaps, highlighting the need for more studies on implementation factors, actor interests, institutional adaptation and multi-level governance. In a second step we focus in on the experiences of rainwater harvesting in Berlin and present the results of a mapping exercise on a wide variety of projects implemented there over the last 30 years. Here, we develop a typology to characterize the rainwater harvesting projects in terms of policy issues (what problems and goals are targeted), project design (which kind of solutions are envisaged), project implementation (how and when they were implemented), location (whether they are in new or existing urban developments) and actors (which stakeholders are involved and how), paying particular attention to the shifting institutional framework in Berlin. Mapping and categorizing these projects is based on a combination of document analysis and expert interviews. The paper concludes by synthesizing the findings, identifying how far the goals, governance structures and instruments applied in the Berlin projects studied reflect the findings emerging from the meta-analysis of the international literature on policy and planning issues of rainwater harvesting and what implications these findings have for mainstreaming such techniques in future practice.

Keywords: institutional framework, planning, policy, project implementation, urban rainwater management

Procedia PDF Downloads 287
207 Designing Next Generation Platforms for Recombinant Protein Production by Genome Engineering of Escherichia coli

Authors: Priyanka Jain, Ashish K. Sharma, Esha Shukla, K. J. Mukherjee

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We propose a paradigm shift in our approach to design improved platforms for recombinant protein production, by addressing system level issues rather than the individual steps associated with recombinant protein synthesis like transcription, translation, etc. We demonstrate that by controlling and modulating the cellular stress response (CSR), which is responsible for feedback control of protein synthesis, we can generate hyper-producing strains. We did transcriptomic profiling of post-induction cultures, expressing different types of protein, to analyze the nature of this cellular stress response. We found significant down-regulation of substrate utilization, translation, and energy metabolism genes due to generation CSR inside the host cell. However, transcription profiling has also shown that many genes are up-regulated post induction and their role in modulating the CSR is unclear. We hypothesized that these up-regulated genes trigger signaling pathways, generating the CSR and concomitantly reduce the recombinant protein yield. To test this hypothesis, we knocked out the up-regulated genes, which did not have any downstream regulatees, and analyzed their impact on cellular health and recombinant protein expression. Two model proteins i.e., GFP and L-Asparaginase were chosen for this analysis. We observed a significant improvement in expression levels, with some knock-outs showing more than 7-fold higher expression compared to control. The 10 best single knock-outs were chosen to make 45 combinations of all possible double knock-outs. A further increase in expression was observed in some of these double knock- outs with GFP levels being highest in a double knock-out ΔyhbC + ΔelaA. However, for L-Asparaginase which is a secretory protein, the best results were obtained using a combination of ΔelaA+ΔcysW knock-outs. We then tested all the knock outs for their ability to enhance the expression of a 'difficult-to-express' protein. The Rubella virus E1 protein was chosen and tagged with sfGFP at the C-terminal using a linker peptide for easy online monitoring of expression of this fusion protein. Interestingly, the highest increase in Rubella-sGFP levels was obtained in the same double knock-out ΔelaA + ΔcysW (5.6 fold increase in expression yield compared to the control) which gave the highest expression for L-Asparaginase. However, for sfGFP alone, the ΔyhbC+ΔmarR knock-out gave the highest level of expression. These results indicate that there is a fair degree of commonality in the nature of the CSR generated by the induction of different proteins. Transcriptomic profiling of the double knock out showed that many genes associated with the translational machinery and energy biosynthesis did not get down-regulated post induction, unlike the control where these genes were significantly down-regulated. This confirmed our hypothesis of these genes playing an important role in the generation of the CSR and allowed us to design a strategy for making better expression hosts by simply knocking out key genes. This strategy is radically superior to the previous approach of individually up-regulating critical genes since it blocks the mounting of the CSR thus preventing the down-regulation of a very large number of genes responsible for sustaining the flux through the recombinant protein production pathway.

Keywords: cellular stress response, GFP, knock-outs, up-regulated genes

Procedia PDF Downloads 227
206 Artificial Intelligence for Traffic Signal Control and Data Collection

Authors: Reggie Chandra

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

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

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205 Web-Based Decision Support Systems and Intelligent Decision-Making: A Systematic Analysis

Authors: Serhat Tüzün, Tufan Demirel

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

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

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204 Urban Slum Communities Engage in the Fight Against TB in Karnataka, South India

Authors: N. Rambabu, H. Gururaj, Reynold Washington, Oommen George

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Motivation: Under the USAID Strengthening Health Outcomes through Private Sector (SHOPS-TB) initiative, Karnataka Health Promotion Trust (KHPT) with technical support of Abt associates is implementing a TB prevention and care model in Karnataka State, South India. KHPT is the interface agency between the public and private sectors, and providers and the target community facilitating early TB case detection and enhancing treatment compliance through private health care providers (pHCP) engagement in RNTCP. The project coverage is 0.84 million urban poor from 663 slums in 12 districts of Karnataka. Problem Statement: India with the highest burden of global TB (26%) and two million cases annually, accounts for approximately one fifth of the global incidence. WHO estimates 300,000 people die from TB annually in India. India expanded the coverage of Directly Observed Treatment, Short-course chemotherapy (DOTS) to the entire country as early as 2006. However, the performance of RNTCP has not been uniform across states. While the national annual new smear-positive (NSP) case notification rate is 53, it is much lower at 47 in Karnataka. A third of TB patients in India reside in urban slums. Approach: Under SHOPS, KHPT actively engages with communities through key opinion leaders and community structures. Interpersonal communication, by Outreach workers through house-to-house visits and at aggregation points, is the primary method used for communication about TB and its management and to increase demand for sputum examination and DOTS. pHCP are mapped, trained and mentored by KHPT. ORWs also provide patient and family counseling on TB treatment, side effects and adherence, screen close contacts of index patients especially children under 6 years of age and screen co-morbidities including HIV, diabetes and malnutrition and risk factors including alcoholism, tobacco use, occupational hazards making appropriate accompanied or documented referrals. A treatment ‘buddy’ system for the patients involving close friends or family members, ICT-based support, DOTS Prerana (inspiration) groups of TB patients, family members and community, DOTS Mitra (friend) helpline services are also used for care and support services. Results: The intervention educated 39988 slum dwellers, referred 1731 chest symptomatics, tested 1061 patients and initiated 248 patients on anti-TB treatment within three months of intervention through continuous community engagement. Conclusions: The intervention’s potential to increase access to preferred health care providers, reduce patient and health system delays in diagnosis and initiation of treatment, improve health seeking behaviour and enhance compliance of pHCPs to standard treatment protocols is being monitored. Initial results are promising.

Keywords: DOTS, KHPT, health outcomes, public and private sector

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203 Development of a Psychometric Testing Instrument Using Algorithms and Combinatorics to Yield Coupled Parameters and Multiple Geometric Arrays in Large Information Grids

Authors: Laith F. Gulli, Nicole M. Mallory

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The undertaking to develop a psychometric instrument is monumental. Understanding the relationship between variables and events is important in structural and exploratory design of psychometric instruments. Considering this, we describe a method used to group, pair and combine multiple Philosophical Assumption statements that assisted in development of a 13 item psychometric screening instrument. We abbreviated our Philosophical Assumptions (PA)s and added parameters, which were then condensed and mathematically modeled in a specific process. This model produced clusters of combinatorics which was utilized in design and development for 1) information retrieval and categorization 2) item development and 3) estimation of interactions among variables and likelihood of events. The psychometric screening instrument measured Knowledge, Assessment (education) and Beliefs (KAB) of New Addictions Research (NAR), which we called KABNAR. We obtained an overall internal consistency for the seven Likert belief items as measured by Cronbach’s α of .81 in the final study of 40 Clinicians, calculated by SPSS 14.0.1 for Windows. We constructed the instrument to begin with demographic items (degree/addictions certifications) for identification of target populations that practiced within Outpatient Substance Abuse Counseling (OSAC) settings. We then devised education items, beliefs items (seven items) and a modifiable “barrier from learning” item that consisted of six “choose any” choices. We also conceptualized a close relationship between identifying various degrees and certifications held by Outpatient Substance Abuse Therapists (OSAT) (the demographics domain) and all aspects of their education related to EB-NAR (past and present education and desired future training). We placed a descriptive (PA)1tx in both demographic and education domains to trace relationships of therapist education within these two domains. The two perceptions domains B1/b1 and B2/b2 represented different but interrelated perceptions from the therapist perspective. The belief items measured therapist perceptions concerning EB-NAR and therapist perceptions using EB-NAR during the beginning of outpatient addictions counseling. The (PA)s were written in simple words and descriptively accurate and concise. We then devised a list of parameters and appropriately matched them to each PA and devised descriptive parametric (PA)s in a domain categorized information grid. Descriptive parametric (PA)s were reduced to simple mathematical symbols. This made it easy to utilize parametric (PA)s into algorithms, combinatorics and clusters to develop larger information grids. By using matching combinatorics we took paired demographic and education domains with a subscript of 1 and matched them to the column with each B domain with subscript 1. Our algorithmic matching formed larger information grids with organized clusters in columns and rows. We repeated the process using different demographic, education and belief domains and devised multiple information grids with different parametric clusters and geometric arrays. We found benefit combining clusters by different geometric arrays, which enabled us to trace parametric variables and concepts. We were able to understand potential differences between dependent and independent variables and trace relationships of maximum likelihoods.

Keywords: psychometric, parametric, domains, grids, therapists

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202 PARP1 Links Transcription of a Subset of RBL2-Dependent Genes with Cell Cycle Progression

Authors: Ewelina Wisnik, Zsolt Regdon, Kinga Chmielewska, Laszlo Virag, Agnieszka Robaszkiewicz

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Apart from protecting genome, PARP1 has been documented to regulate many intracellular processes inter alia gene transcription by physically interacting with chromatin bound proteins and by their ADP-ribosylation. Our recent findings indicate that expression of PARP1 decreases during the differentiation of human CD34+ hematopoietic stem cells to monocytes as a consequence of differentiation-associated cell growth arrest and formation of E2F4-RBL2-HDAC1-SWI/SNF repressive complex at the promoter of this gene. Since the RBL2 complexes repress genes in a E2F-dependent manner and are widespread in the genome in G0 arrested cells, we asked (a) if RBL2 directly contributes to defining monocyte phenotype and function by targeting gene promoters and (b) if RBL2 controls gene transcription indirectly by repressing PARP1. For identification of genes controlled by RBL2 and/or PARP1,we used primer libraries for surface receptors and TLR signaling mediators, genes were silenced by siRNA or shRNA, analysis of gene promoter occupation by selected proteins was carried out by ChIP-qPCR, while statistical analysis in GraphPad Prism 5 and STATISTICA, ChIP-Seq data were analysed in Galaxy 2.5.0.0. On the list of 28 genes regulated by RBL2, we identified only four solely repressed by RBL2-E2F4-HDAC1-BRM complex. Surprisingly, 24 out of 28 emerged genes controlled by RBL2 were co-regulated by PARP1 in six different manners. In one mode of RBL2/PARP1 co-operation, represented by MAP2K6 and MAPK3, PARP1 was found to associate with gene promoters upon RBL2 silencing, which was previously shown to restore PARP1 expression in monocytes. PARP1 effect on gene transcription was observed only in the presence of active EP300, which acetylated gene promoters and activated transcription. Further analysis revealed that PARP1 binding to MA2K6 and MAPK3 promoters enabled recruitment of EP300 in monocytes, while in proliferating cancer cell lines, which actively transcribe PARP1, this protein maintained EP300 at the promoters of MA2K6 and MAPK3. Genome-wide analysis revealed a similar distribution of PARP1 and EP300 around transcription start sites and the co-occupancy of some gene promoters by PARP1 and EP300 in cancer cells. Here, we described a new RBL2/PARP1/EP300 axis which controls gene transcription regardless of the cell type. In this model cell, cycle-dependent transcription of PARP1 regulates expression of some genes repressed by RBL2 upon cell cycle limitation. Thus, RBL2 may indirectly regulate transcription of some genes by controlling the expression of EP300-recruiting PARP1. Acknowledgement: This work was financed by Polish National Science Centre grants nr DEC-2013/11/D/NZ2/00033 and DEC-2015/19/N/NZ2/01735. L.V. is funded by the National Research, Development and Innovation Office grants GINOP-2.3.2-15-2016-00020 TUMORDNS, GINOP-2.3.2-15-2016-00048-STAYALIVE and OTKA K112336. AR is supported by Polish Ministry of Science and Higher Education 776/STYP/11/2016.

Keywords: retinoblastoma transcriptional co-repressor like 2 (RBL2), poly(ADP-ribose) polymerase 1 (PARP1), E1A binding protein p300 (EP300), monocytes

Procedia PDF Downloads 209
201 Songwriting in the Postdigital Age: Using TikTok and Instagram as Online Informal Learning Technologies

Authors: Matthias Haenisch, Marc Godau, Julia Barreiro, Dominik Maxelon

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In times of ubiquitous digitalization and the increasing entanglement of humans and technologies in musical practices in the 21st century, it is to be asked, how popular musicians learn in the (post)digital Age. Against the backdrop of the increasing interest in transferring informal learning practices into formal settings of music education the interdisciplinary research association »MusCoDA – Musical Communities in the (Post)Digital Age« (University of Erfurt/University of Applied Sciences Clara Hoffbauer Potsdam, funded by the German Ministry of Education and Research, pursues the goal to derive an empirical model of collective songwriting practices from the study of informal lelearningf songwriters and bands that can be translated into pedagogical concepts for music education in schools. Drawing on concepts from Community of Musical Practice and Actor Network Theory, lelearnings considered not only as social practice and as participation in online and offline communities, but also as an effect of heterogeneous networks composed of human and non-human actors. Learning is not seen as an individual, cognitive process, but as the formation and transformation of actor networks, i.e., as a practice of assembling and mediating humans and technologies. Based on video stimulated recall interviews and videography of online and offline activities, songwriting practices are followed from the initial idea to different forms of performance and distribution. The data evaluation combines coding and mapping methods of Grounded Theory Methodology and Situational Analysis. This results in network maps in which both the temporality of creative practices and the material and spatial relations of human and technological actors are reconstructed. In addition, positional analyses document the power relations between the participants that structure the learning process of the field. In the area of online informal lelearninginitial key research findings reveal a transformation of the learning subject through the specific technological affordances of TikTok and Instagram and the accompanying changes in the learning practices of the corresponding online communities. Learning is explicitly shaped by the material agency of online tools and features and the social practices entangled with these technologies. Thus, any human online community member can be invited to directly intervene in creative decisions that contribute to the further compositional and structural development of songs. At the same time, participants can provide each other with intimate insights into songwriting processes in progress and have the opportunity to perform together with strangers and idols. Online Lelearnings characterized by an increase in social proximity, distribution of creative agency and informational exchange between participants. While it seems obvious that traditional notions not only of lelearningut also of the learning subject cannot be maintained, the question arises, how exactly the observed informal learning practices and the subject that emerges from the use of social media as online learning technologies can be transferred into contexts of formal learning

Keywords: informal learning, postdigitality, songwriting, actor-network theory, community of musical practice, social media, TikTok, Instagram, apps

Procedia PDF Downloads 126
200 Varieties of Capitalism and Small Business CSR: A Comparative Overview

Authors: Stéphanie Looser, Walter Wehrmeyer

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Given the limited research on Small and Mediumsized Enterprises’ (SMEs) contribution to Corporate Social Responsibility (CSR) and even scarcer research on Swiss SMEs, this paper helps to fill these gaps by enabling the identification of supranational SME parameters and to make a contribution to the evolving field of these topics. Thus, the paper investigates the current state of SME practices in Switzerland and across 15 other countries. Combining the degree to which SMEs demonstrate an explicit (or business case) approach or see CSR as an implicit moral activity with the assessment of their attributes for “variety of capitalism” defines the framework of this comparative analysis. According to previous studies, liberal market economies, e.g. in the United States (US) or United Kingdom (UK), are aligned with extrinsic CSR, while coordinated market systems (in Central European or Asian countries) evolve implicit CSR agendas. To outline Swiss small business CSR patterns in particular, 40 SME owner-managers were interviewed. The transcribed interviews were coded utilising MAXQDA for qualitative content analysis. A secondary data analysis of results from different countries (i.e., Australia, Austria, Chile, Cameroon, Catalonia (notably a part of Spain that seeks autonomy), China, Finland, Germany, Hong Kong (a special administrative region of China), Italy, Netherlands, Singapore, Spain, Taiwan, UK, US) lays groundwork for this comparative study on small business CSR. Applying the same coding categories (in MAXQDA) for the interview analysis as well as for the secondary data research while following grounded theory rules to refine and keep track of ideas generated testable hypotheses and comparative power on implicit (and the lower likelihood of explicit) CSR in SMEs retrospectively. The paper identifies Swiss small business CSR as deep, profound, “soul”, and an implicit part of the day-to-day business. Similar to most Central European, Mediterranean, Nordic, and Asian countries, explicit CSR is still very rare in Swiss SMEs. Astonishingly, also UK and US SMEs follow this pattern in spite of their strong and distinct liberal market economies. Though other findings show that nationality matters this research concludes that SME culture and its informal CSR agenda are strongly formative and superseding even forces of market economies, nationally cultural patterns, and language. In a world of “big business”, explicit “business case” CSR, and the mantra that “CSR must pay”, this study points to a distinctly implicit small business CSR model built on trust, physical closeness, and virtues that is largely detached from the bottom line. This pattern holds for different cultural contexts and it is concluded that SME culture is stronger than nationality leading to a supra-national, monolithic SME CSR approach. Hence, classifications of countries by their market system or capitalism, as found in the comparative capitalism literature, do not match the CSR practices in SMEs as they do not mirror the peculiarities of their business. This raises questions on the universality and generalisability of management concepts.

Keywords: CSR, comparative study, cultures of capitalism, small, medium-sized enterprises

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199 Hydrodynamic Characterisation of a Hydraulic Flume with Sheared Flow

Authors: Daniel Rowe, Christopher R. Vogel, Richard H. J. Willden

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The University of Oxford’s recirculating water flume is a combined wave and current test tank with a 1 m depth, 1.1 m width, and 10 m long working section, and is capable of flow speeds up to 1 ms−1 . This study documents the hydrodynamic characteristics of the facility in preparation for experimental testing of horizontal axis tidal stream turbine models. The turbine to be tested has a rotor diameter of 0.6 m and is a modified version of one of two model-scale turbines tested in previous experimental campaigns. An Acoustic Doppler Velocimeter (ADV) was used to measure the flow at high temporal resolution at various locations throughout the flume, enabling the spatial uniformity and turbulence flow parameters to be investigated. The mean velocity profiles exhibited high levels of spatial uniformity at the design speed of the flume, 0.6 ms−1 , with variations in the three-dimensional velocity components on the order of ±1% at the 95% confidence level, along with a modest streamwise acceleration through the measurement domain, a target 5 m working section of the flume. A high degree of uniformity was also apparent for the turbulence intensity, with values ranging between 1-2% across the intended swept area of the turbine rotor. The integral scales of turbulence exhibited a far higher degree of variation throughout the water column, particularly in the streamwise and vertical scales. This behaviour is believed to be due to the high signal noise content leading to decorrelation in the sampling records. To achieve more realistic levels of vertical velocity shear in the flume, a simple procedure to practically generate target vertical shear profiles in open-channel flows is described. Here, the authors arranged a series of non-uniformly spaced parallel bars placed across the width of the flume and normal to the onset flow. By adjusting the resistance grading across the height of the working section, the downstream profiles could be modified accordingly, characterised by changes in the velocity profile power law exponent, 1/n. Considering the significant temporal variation in a tidal channel, the choice of the exponent denominator, n = 6 and n = 9, effectively provides an achievable range around the much-cited value of n = 7 observed at many tidal sites. The resulting flow profiles, which we intend to use in future turbine tests, have been characterised in detail. The results indicate non-uniform vertical shear across the survey area and reveal substantial corner flows, arising from the differential shear between the target vertical and cross-stream shear profiles throughout the measurement domain. In vertically sheared flow, the rotor-equivalent turbulence intensity ranges between 3.0-3.8% throughout the measurement domain for both bar arrangements, while the streamwise integral length scale grows from a characteristic dimension on the order of the bar width, similar to the flow downstream of a turbulence-generating grid. The experimental tests are well-defined and repeatable and serve as a reference for other researchers who wish to undertake similar investigations.

Keywords: acoustic doppler Velocimeter, experimental hydrodynamics, open-channel flow, shear profiles, tidal stream turbines

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198 Calculation of Pressure-Varying Langmuir and Brunauer-Emmett-Teller Isotherm Adsorption Parameters

Authors: Trevor C. Brown, David J. Miron

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Gas-solid physical adsorption methods are central to the characterization and optimization of the effective surface area, pore size and porosity for applications such as heterogeneous catalysis, and gas separation and storage. Properties such as adsorption uptake, capacity, equilibrium constants and Gibbs free energy are dependent on the composition and structure of both the gas and the adsorbent. However, challenges remain, in accurately calculating these properties from experimental data. Gas adsorption experiments involve measuring the amounts of gas adsorbed over a range of pressures under isothermal conditions. Various constant-parameter models, such as Langmuir and Brunauer-Emmett-Teller (BET) theories are used to provide information on adsorbate and adsorbent properties from the isotherm data. These models typically do not provide accurate interpretations across the full range of pressures and temperatures. The Langmuir adsorption isotherm is a simple approximation for modelling equilibrium adsorption data and has been effective in estimating surface areas and catalytic rate laws, particularly for high surface area solids. The Langmuir isotherm assumes the systematic filling of identical adsorption sites to a monolayer coverage. The BET model is based on the Langmuir isotherm and allows for the formation of multiple layers. These additional layers do not interact with the first layer and the energetics are equal to the adsorbate as a bulk liquid. This BET method is widely used to measure the specific surface area of materials. Both Langmuir and BET models assume that the affinity of the gas for all adsorption sites are identical and so the calculated adsorbent uptake at the monolayer and equilibrium constant are independent of coverage and pressure. Accurate representations of adsorption data have been achieved by extending the Langmuir and BET models to include pressure-varying uptake capacities and equilibrium constants. These parameters are determined using a novel regression technique called flexible least squares for time-varying linear regression. For isothermal adsorption the adsorption parameters are assumed to vary slowly and smoothly with increasing pressure. The flexible least squares for pressure-varying linear regression (FLS-PVLR) approach assumes two distinct types of discrepancy terms, dynamic and measurement for all parameters in the linear equation used to simulate the data. Dynamic terms account for pressure variation in successive parameter vectors, and measurement terms account for differences between observed and theoretically predicted outcomes via linear regression. The resultant pressure-varying parameters are optimized by minimizing both dynamic and measurement residual squared errors. Validation of this methodology has been achieved by simulating adsorption data for n-butane and isobutane on activated carbon at 298 K, 323 K and 348 K and for nitrogen on mesoporous alumina at 77 K with pressure-varying Langmuir and BET adsorption parameters (equilibrium constants and uptake capacities). This modeling provides information on the adsorbent (accessible surface area and micropore volume), adsorbate (molecular areas and volumes) and thermodynamic (Gibbs free energies) variations of the adsorption sites.

Keywords: Langmuir adsorption isotherm, BET adsorption isotherm, pressure-varying adsorption parameters, adsorbate and adsorbent properties and energetics

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197 Characterizing the Spatially Distributed Differences in the Operational Performance of Solar Power Plants Considering Input Volatility: Evidence from China

Authors: Bai-Chen Xie, Xian-Peng Chen

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China has become the world's largest energy producer and consumer, and its development of renewable energy is of great significance to global energy governance and the fight against climate change. The rapid growth of solar power in China could help achieve its ambitious carbon peak and carbon neutrality targets early. However, the non-technical costs of solar power in China are much higher than at international levels, meaning that inefficiencies are rooted in poor management and improper policy design and that efficiency distortions have become a serious challenge to the sustainable development of the renewable energy industry. Unlike fossil energy generation technologies, the output of solar power is closely related to the volatile solar resource, and the spatial unevenness of solar resource distribution leads to potential efficiency spatial distribution differences. It is necessary to develop an efficiency evaluation method that considers the volatility of solar resources and explores the mechanism of the influence of natural geography and social environment on the spatially varying characteristics of efficiency distribution to uncover the root causes of managing inefficiencies. The study sets solar resources as stochastic inputs, introduces a chance-constrained data envelopment analysis model combined with the directional distance function, and measures the solar resource utilization efficiency of 222 solar power plants in representative photovoltaic bases in northwestern China. By the meta-frontier analysis, we measured the characteristics of different power plant clusters and compared the differences among groups, discussed the mechanism of environmental factors influencing inefficiencies, and performed statistical tests through the system generalized method of moments. Rational localization of power plants is a systematic project that requires careful consideration of the full utilization of solar resources, low transmission costs, and power consumption guarantee. Suitable temperature, precipitation, and wind speed can improve the working performance of photovoltaic modules, reasonable terrain inclination can reduce land cost, and the proximity to cities strongly guarantees the consumption of electricity. The density of electricity demand and high-tech industries is more important than resource abundance because they trigger the clustering of power plants to result in a good demonstration and competitive effect. To ensure renewable energy consumption, increased support for rural grids and encouraging direct trading between generators and neighboring users will provide solutions. The study will provide proposals for improving the full life-cycle operational activities of solar power plants in China to reduce high non-technical costs and improve competitiveness against fossil energy sources.

Keywords: solar power plants, environmental factors, data envelopment analysis, efficiency evaluation

Procedia PDF Downloads 90
196 Key Aroma Compounds as Predictors of Pineapple Sensory Quality

Authors: Jenson George, Thoa Nguyen, Garth Sanewski, Craig Hardner, Heather Eunice Smyth

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Pineapple (Ananas comosus), with its unique sweet flavour, is one of the most popular tropical, non-climacteric fruits consumed worldwide. It is also the third most important tropical fruit in world production. In Australia, 99% of the pineapple production is from the Queensland state due to the favourable subtropical climatic conditions. The flavourful fruit is known to contain around 500 volatile organic compounds (VOC) at varying concentrations and greatly contribute to the flavour quality of pineapple fruit by providing distinct aroma sensory properties that are sweet, fruity, tropical, pineapple-like, caramel-like, coconut-like, etc. The aroma of pineapple is one of the important factors attracting consumers and strengthening the marketplace. To better understand the aroma of Australian-grown pineapples, the matrix-matched Gas chromatography–mass spectrometry (GC-MS), Head Space - Solid-phase microextraction (HS-SPME), Stable-isotope dilution analysis (SIDA) method was developed and validated. The developed method represents a significant improvement over current methods with the incorporation of multiple external reference standards, multiple isotopes labeled internal standards, and a matching model system of pineapple fruit matrix. This method was employed to quantify 28 key aroma compounds in more than 200 genetically diverse pineapple varieties from a breeding program. The Australian pineapple cultivars varied in content and composition of free volatile compounds, which were predominantly comprised of esters, followed by terpenes, alcohols, aldehydes, and ketones. Using selected commercial cultivars grown in Australia, and by employing the sensorial analysis, the appearance (colour), aroma (intensity, sweet, vinegar/tang, tropical fruits, floral, coconut, green, metallic, vegetal, fresh, peppery, fermented, eggy/sulphurous) and texture (crunchiness, fibrousness, and juiciness) were obtained. Relationships between sensory descriptors and volatiles were explored by applying multivariate analysis (PCA) to the sensorial and chemical data. The key aroma compounds of pineapple exhibited a positive correlation with corresponding sensory properties. The sensory and volatile data were also used to explore genetic diversity in the breeding population. GWAS was employed to unravel the genetic control of the pineapple volatilome and its interplay with fruit sensory characteristics. This study enhances our understanding of pineapple aroma (flavour) compounds, their biosynthetic pathways and expands breeding option for pineapple cultivars. This research provides foundational knowledge to support breeding programs, post-harvest and target market studies, and efforts to optimise the flavour of commercial pineapple varieties and their parent lines to produce better tasting fruits for consumers.

Keywords: Ananas comosus, pineapple, flavour, volatile organic compounds, aroma, Gas chromatography–mass spectrometry (GC-MS), Head Space - Solid-phase microextraction (HS-SPME), Stable-isotope dilution analysis (SIDA).

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195 National Digital Soil Mapping Initiatives in Europe: A Review and Some Examples

Authors: Dominique Arrouays, Songchao Chen, Anne C. Richer-De-Forges

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Soils are at the crossing of many issues such as food and water security, sustainable energy, climate change mitigation and adaptation, biodiversity protection, human health and well-being. They deliver many ecosystem services that are essential to life on Earth. Therefore, there is a growing demand for soil information on a national and global scale. Unfortunately, many countries do not have detailed soil maps, and, when existing, these maps are generally based on more or less complex and often non-harmonized soil classifications. An estimate of their uncertainty is also often missing. Thus, there are not easy to understand and often not properly used by end-users. Therefore, there is an urgent need to provide end-users with spatially exhaustive grids of essential soil properties, together with an estimate of their uncertainty. One way to achieve this is digital soil mapping (DSM). The concept of DSM relies on the hypothesis that soils and their properties are not randomly distributed, but that they depend on the main soil-forming factors that are climate, organisms, relief, parent material, time (age), and position in space. All these forming factors can be approximated using several exhaustive spatial products such as climatic grids, remote sensing products or vegetation maps, digital elevation models, geological or lithological maps, spatial coordinates of soil information, etc. Thus, DSM generally relies on models calibrated with existing observed soil data (point observations or maps) and so-called “ancillary co-variates” that come from other available spatial products. Then the model is generalized on grids where soil parameters are unknown in order to predict them, and the prediction performances are validated using various methods. With the growing demand for soil information at a national and global scale and the increase of available spatial co-variates national and continental DSM initiatives are continuously increasing. This short review illustrates the main national and continental advances in Europe, the diversity of the approaches and the databases that are used, the validation techniques and the main scientific and other issues. Examples from several countries illustrate the variety of products that were delivered during the last ten years. The scientific production on this topic is continuously increasing and new models and approaches are developed at an incredible speed. Most of the digital soil mapping (DSM) products rely mainly on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs or for existing conventional maps. However, some scientific issues remain to be solved and also political and legal ones related, for instance, to data sharing and to different laws in different countries. Other issues related to communication to end-users and education, especially on the use of uncertainty. Overall, the progress is very important and the willingness of institutes and countries to join their efforts is increasing. Harmonization issues are still remaining, mainly due to differences in classifications or in laboratory standards between countries. However numerous initiatives are ongoing at the EU level and also at the global level. All these progress are scientifically stimulating and also promissing to provide tools to improve and monitor soil quality in countries, EU and at the global level.

Keywords: digital soil mapping, global soil mapping, national and European initiatives, global soil mapping products, mini-review

Procedia PDF Downloads 184
194 Centrality and Patent Impact: Coupled Network Analysis of Artificial Intelligence Patents Based on Co-Cited Scientific Papers

Authors: Xingyu Gao, Qiang Wu, Yuanyuan Liu, Yue Yang

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In the era of the knowledge economy, the relationship between scientific knowledge and patents has garnered significant attention. Understanding the intricate interplay between the foundations of science and technological innovation has emerged as a pivotal challenge for both researchers and policymakers. This study establishes a coupled network of artificial intelligence patents based on co-cited scientific papers. Leveraging centrality metrics from network analysis offers a fresh perspective on understanding the influence of information flow and knowledge sharing within the network on patent impact. The study initially obtained patent numbers for 446,890 granted US AI patents from the United States Patent and Trademark Office’s artificial intelligence patent database for the years 2002-2020. Subsequently, specific information regarding these patents was acquired using the Lens patent retrieval platform. Additionally, a search and deduplication process was performed on scientific non-patent references (SNPRs) using the Web of Science database, resulting in the selection of 184,603 patents that cited 37,467 unique SNPRs. Finally, this study constructs a coupled network comprising 59,379 artificial intelligence patents by utilizing scientific papers co-cited in patent backward citations. In this network, nodes represent patents, and if patents reference the same scientific papers, connections are established between them, serving as edges within the network. Nodes and edges collectively constitute the patent coupling network. Structural characteristics such as node degree centrality, betweenness centrality, and closeness centrality are employed to assess the scientific connections between patents, while citation count is utilized as a quantitative metric for patent influence. Finally, a negative binomial model is employed to test the nonlinear relationship between these network structural features and patent influence. The research findings indicate that network structural features such as node degree centrality, betweenness centrality, and closeness centrality exhibit inverted U-shaped relationships with patent influence. Specifically, as these centrality metrics increase, patent influence initially shows an upward trend, but once these features reach a certain threshold, patent influence starts to decline. This discovery suggests that moderate network centrality is beneficial for enhancing patent influence, while excessively high centrality may have a detrimental effect on patent influence. This finding offers crucial insights for policymakers, emphasizing the importance of encouraging moderate knowledge flow and sharing to promote innovation when formulating technology policies. It suggests that in certain situations, data sharing and integration can contribute to innovation. Consequently, policymakers can take measures to promote data-sharing policies, such as open data initiatives, to facilitate the flow of knowledge and the generation of innovation. Additionally, governments and relevant agencies can achieve broader knowledge dissemination by supporting collaborative research projects, adjusting intellectual property policies to enhance flexibility, or nurturing technology entrepreneurship ecosystems.

Keywords: centrality, patent coupling network, patent influence, social network analysis

Procedia PDF Downloads 54
193 Environmental Effect of Empty Nest Households in Germany: An Empirical Approach

Authors: Dominik Kowitzke

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Housing constructions have direct and indirect environmental impacts especially caused by soil sealing and gray energy consumption related to the use of construction materials. Accordingly, the German government introduced regulations limiting additional annual soil sealing. At the same time, in many regions like metropolitan areas the demand for further housing is high and of current concern in the media and politics. It is argued that meeting this demand by making better use of the existing housing supply is more sustainable than the construction of new housing units. In this context, targeting the phenomenon of so-called over the housing of empty nest households seems worthwhile to investigate for its potential to free living space and thus, reduce the need for new housing constructions and related environmental harm. Over housing occurs if no space adjustment takes place in household lifecycle stages when children move out from home and the space formerly created for the offspring is from then on under-utilized. Although in some cases the housing space consumption might actually meet households’ equilibrium preferences, frequently space-wise adjustments to the living situation doesn’t take place due to transaction or information costs, habit formation, or government intervention leading to increasing costs of relocations like real estate transfer taxes or tenant protection laws keeping tenure rents below the market price. Moreover, many detached houses are not long-term designed in a way that freed up space could be rent out. Findings of this research based on socio-economic survey data, indeed, show a significant difference between the living space of empty nest and a comparison group of households which never had children. The approach used to estimate the average difference in living space is a linear regression model regressing the response variable living space on a two-dimensional categorical variable distinguishing the two groups of household types and further controls. This difference is assumed to be the under-utilized space and is extrapolated to the total amount of empty nests in the population. Supporting this result, it is found that households that move, despite market frictions impairing the relocation, after children left their home tend to decrease the living space. In the next step, only for areas with tight housing markets in Germany and high construction activity, the total under-utilized space in empty nests is estimated. Under the assumption of full substitutability of housing space in empty nests and space in new dwellings in these locations, it is argued that in a perfect market with empty nest households consuming their equilibrium demand quantity of housing space, dwelling constructions in the amount of the excess consumption of living space could be saved. This, on the other hand, would prevent environmental harm quantified in carbon dioxide equivalence units related to average constructions of detached or multi-family houses. This study would thus provide information on the amount of under-utilized space inside dwellings which is missing in public data and further estimates the external effect of over housing in environmental terms.

Keywords: empty nests, environment, Germany, households, over housing

Procedia PDF Downloads 171
192 Planning Fore Stress II: Study on Resiliency of New Architectural Patterns in Urban Scale

Authors: Amir Shouri, Fereshteh Tabe

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Master planning and urban infrastructure’s thoughtful and sequential design strategies will play the major role in reducing the damages of natural disasters, war and or social/population related conflicts for cities. Defensive strategies have been revised during the history of mankind after having damages from natural depressions, war experiences and terrorist attacks on cities. Lessons learnt from Earthquakes, from 2 world war casualties in 20th century and terrorist activities of all times. Particularly, after Hurricane Sandy of New York in 2012 and September 11th attack on New York’s World Trade Centre (WTC) in 21st century, there have been series of serious collaborations between law making authorities, urban planners and architects and defence related organizations to firstly, getting prepared and/or prevent such activities and secondly, reduce the human loss and economic damages to minimum. This study will work on developing a model of planning for New York City, where its citizens will get minimum impacts in threat-full time with minimum economic damages to the city after the stress is passed. The main discussion in this proposal will focus on pre-hazard, hazard-time and post-hazard transformative policies and strategies that will reduce the “Life casualties” and will ease “Economic Recovery” in post-hazard conditions. This proposal is going to scrutinize that one of the key solutions in this path might be focusing on all overlaying possibilities on architectural platforms of three fundamental infrastructures, the transportation, the power related sources and defensive abilities on a dynamic-transformative framework that will provide maximum safety, high level of flexibility and fastest action-reaction opportunities in stressful periods of time. “Planning Fore Stress” is going to be done in an analytical, qualitative and quantitative work frame, where it will study cases from all over the world. Technology, Organic Design, Materiality, Urban forms, city politics and sustainability will be discussed in deferent cases in international scale. From the modern strategies of Copenhagen for living friendly with nature to traditional approaches of Indonesian old urban planning patterns, the “Iron Dome” of Israel to “Tunnels” in Gaza, from “Ultra-high-performance quartz-infused concrete” of Iran to peaceful and nature-friendly strategies of Switzerland, from “Urban Geopolitics” in cities, war and terrorism to “Design of Sustainable Cities” in the world, will all be studied with references and detailed look to analysis of each case in order to propose the most resourceful, practical and realistic solutions to questions on “New City Divisions”, “New City Planning and social activities” and “New Strategic Architecture for Safe Cities”. This study is a developed version of a proposal that was announced as winner at MoMA in 2013 in call for ideas for Rockaway after Sandy Hurricane took place.

Keywords: urban scale, city safety, natural disaster, war and terrorism, city divisions, architecture for safe cities

Procedia PDF Downloads 484
191 Assessing Brain Targeting Efficiency of Ionisable Lipid Nanoparticles Encapsulating Cas9 mRNA/gGFP Following Different Routes of Administration in Mice

Authors: Meiling Yu, Nadia Rouatbi, Khuloud T. Al-Jamal

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Background: Treatment of neurological disorders with modern medical and surgical approaches remains difficult. Gene therapy, allowing the delivery of genetic materials that encodes potential therapeutic molecules, represents an attractive option. The treatment of brain diseases with gene therapy requires the gene-editing tool to be delivered efficiently to the central nervous system. In this study, we explored the efficiency of different delivery routes, namely intravenous (i.v.), intra-cranial (i.c.), and intra-nasal (i.n.), to deliver stable nucleic acid-lipid particles (SNALPs) containing gene-editing tools namely Cas9 mRNA and sgRNA encoding for GFP as a reporter protein. We hypothesise that SNALPs can reach the brain and perform gene-editing to different extents depending on the administration route. Intranasal administration (i.n.) offers an attractive and non-invasive way to access the brain circumventing the blood–brain barrier. Successful delivery of gene-editing tools to the brain offers a great opportunity for therapeutic target validation and nucleic acids therapeutics delivery to improve treatment options for a range of neurodegenerative diseases. In this study, we utilised Rosa26-Cas9 knock-in mice, expressing GFP, to study brain distribution and gene-editing efficiency of SNALPs after i.v.; i.c. and i.n. routes of administration. Methods: Single guide RNA (sgRNA) against GFP has been designed and validated by in vitro nuclease assay. SNALPs were formulated and characterised using dynamic light scattering. The encapsulation efficiency of nucleic acids (NA) was measured by RiboGreen™ assay. SNALPs were incubated in serum to assess their ability to protect NA from degradation. Rosa26-Cas9 knock-in mice were i.v., i.n., or i.c. administered with SNALPs to test in vivo gene-editing (GFP knockout) efficiency. SNALPs were given as three doses of 0.64 mg/kg sgGFP following i.v. and i.n. or a single dose of 0.25 mg/kg sgGFP following i.c.. knockout efficiency was assessed after seven days using Sanger Sequencing and Inference of CRISPR Edits (ICE) analysis. In vivo, the biodistribution of DiR labelled SNALPs (SNALPs-DiR) was assessed at 24h post-administration using IVIS Lumina Series III. Results: Serum-stable SNALPs produced were 130-140 nm in diameter with ~90% nucleic acid loading efficiency. SNALPs could reach and stay in the brain for up to 24h following i.v.; i.n. and i.c. administration. Decreasing GFP expression (around 50% after i.v. and i.c. and 20% following i.n.) was confirmed by optical imaging. Despite the small number of mice used, ICE analysis confirmed GFP knockout in mice brains. Additional studies are currently taking place to increase mice numbers. Conclusion: Results confirmed efficient gene knockout achieved by SNALPs in Rosa26-Cas9 knock-in mice expressing GFP following different routes of administrations in the following order i.v.= i.c.> i.n. Each of the administration routes has its pros and cons. The next stages of the project involve assessing gene-editing efficiency in wild-type mice and replacing GFP as a model target with therapeutic target genes implicated in Motor Neuron Disease pathology.

Keywords: CRISPR, nanoparticles, brain diseases, administration routes

Procedia PDF Downloads 101
190 The Implantable MEMS Blood Pressure Sensor Model With Wireless Powering And Data Transmission

Authors: Vitaliy Petrov, Natalia Shusharina, Vitaliy Kasymov, Maksim Patrushev, Evgeny Bogdanov

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The leading worldwide death reasons are ischemic heart disease and other cardiovascular illnesses. Generally, the common symptom is high blood pressure. Long-time blood pressure control is very important for the prophylaxis, correct diagnosis and timely therapy. Non-invasive methods which are based on Korotkoff sounds are impossible to apply often and for a long time. Implantable devices can combine longtime monitoring with high accuracy of measurements. The main purpose of this work is to create a real-time monitoring system for decreasing the death rate from cardiovascular diseases. These days implantable electronic devices began to play an important role in medicine. Usually implantable devices consist of a transmitter, powering which could be wireless with a special made battery and measurement circuit. Common problems in making implantable devices are short lifetime of the battery, big size and biocompatibility. In these work, blood pressure measure will be the focus because it’s one of the main symptoms of cardiovascular diseases. Our device will consist of three parts: the implantable pressure sensor, external transmitter and automated workstation in a hospital. The Implantable part of pressure sensors could be based on piezoresistive or capacitive technologies. Both sensors have some advantages and some limitations. The Developed circuit is based on a small capacitive sensor which is made of the technology of microelectromechanical systems (MEMS). The Capacitive sensor can provide high sensitivity, low power consumption and minimum hysteresis compared to the piezoresistive sensor. For this device, it was selected the oscillator-based circuit where frequency depends from the capacitance of sensor hence from capacitance one can calculate pressure. The external device (transmitter) used for wireless charging and signal transmission. Some implant devices for these applications are passive, the external device sends radio wave signal on internal LC circuit device. The external device gets reflected the signal from the implant and from a change of frequency is possible to calculate changing of capacitance and then blood pressure. However, this method has some disadvantages, such as the patient position dependence and static using. Developed implantable device doesn’t have these disadvantages and sends blood pressure data to the external part in real-time. The external device continuously sends information about blood pressure to hospital cloud service for analysis by a physician. Doctor’s automated workstation at the hospital also acts as a dashboard, which displays actual medical data of patients (which require attention) and stores it in cloud service. Usually, critical heart conditions occur few hours before heart attack but the device is able to send an alarm signal to the hospital for an early action of medical service. The system was tested with wireless charging and data transmission. These results can be used for ASIC design for MEMS pressure sensor.

Keywords: MEMS sensor, RF power, wireless data, oscillator-based circuit

Procedia PDF Downloads 589