Search results for: cohesion metrics

Authors: Henrry Vicente Rojas Asuero, Holger Manuel Benavides Muñoz

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Approximately 80% of the energy consumed worldwide is generated from fossil sources, which are responsible for the emission of a large volume of greenhouse gases. For this reason, the global trend, at present, is the widespread use of energy produced from renewable sources. This seeks safety and diversification of energy supply, based on social cohesion, economic feasibility and environmental protection. In this scenario, small hydropower systems (P ≤ 10MW) stand out due to their high efficiency, economic competitiveness and low environmental impact. Small hydropower systems, along with wind and solar energy, are expected to represent a significant percentage of the world's energy matrix in the near term. Among the various technologies present in the state of the art, relating to small hydropower systems, is the Gravitational Water Vortex Power Plant, a recent technology that excels because of its versatility of operation, since it can operate with jumps in the range of 0.70 m-2.00 m and flow rates from 1 m3/s to 20 m3/s. Its operating system is based on the utilization of the energy of rotation contained within a large water vortex artificially induced. This paper presents the study and experimental design of an optimal hydraulic structure with the capacity to induce the artificial formation of a gravitational water vortex trough a system of easy application and high efficiency, able to operate in conditions of very low head and minimum flow. The proposed structure consists of a channel, with variable base, vortex inductor, tangential flow generator, coupled to a circular tank with a conical transition bottom hole. In the laboratory test, the angular velocity of the water vortex was related to the geometric characteristics of the inductor channel, as well as the influence of the conical transition bottom hole on the physical characteristics of the water vortex. The results show angular velocity values of greater magnitude as a function of depth, in addition the presence of the conical transition in the bottom hole of the circular tank improves the water vortex formation conditions while increasing the angular velocity values. Thus, the proposed system is a sustainable solution for the energy supply of rural areas near to watercourses.

Keywords: experimental model, gravitational water vortex power plant, renewable energy, small hydropower

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Authors: Gayani Ranawake, Kate Wilson

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Underrepresentation of women in academia, particularly in science, has been discussed by many scholars for decades. The causes of this underrepresentation are debated to this day. Publication is an important aspect of success in academia, and publication and citation rates are significant metrics in performance review, promotion, and employment. It has been established that men’s and women’s language use in general, both spoken and written, is different. However, no one, to our knowledge, has looked at whether men’s and women’s writing in science is different. If there are significant differences in the writing of men and women, then these differences may affect women’s ability to succeed in science. This study is part of a larger project to explore whether differences can be recognized in the academic science writing of men and women. Mono authored articles from high ranking physics, biology and psychology journals by men and women authors were compared in terms of readability statistics. In particular, the abstract and introduction sections were compared, as these are the first sections encountered by a reviewer, and so may have an important effect on their impression of the work. The Flesch Reading Ease, the percentage of passive sentences and the Flesch-Kincaid Reading Grade Level were calculated for each section of each article, along with counts of numbers of sentences, words per sentence and sentences per paragraph. Significance of differences was tested using the Behrens statistic. It was found that for both physics and biology papers there were no significant differences in the complexity or verbosity of the writing of men and women authors. However, there was a significant difference between the two disciplines, with physics articles being generally more readable (higher readability score) while also more passive (higher number of passive sentences). In contrast, the psychology articles showed a difference between men and women authors which may be significant. The average readability for introductions in women’s articles was 28 which was higher than for men’s articles, which was 19 (higher values indicate more readable). Women’s articles in psychology also had a greater proportion of passive sentences. It can be concluded that, at least in the more traditional sciences, men and women have adopted similar ways of writing, and that disciplinary differences are greater than gender differences. This may not be the case in psychology, which many consider to be more closely aligned with the humanities. Whether the lack of differences is because women have adapted to a masculine way of writing, or whether the genre itself is gender neutral needs further investigation.

Keywords: academic writing, gender differences, readability, science

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Authors: D. Falliano, G. Ricciardi, E. Gugliandolo

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Foamed concrete belongs to the category of lightweight concrete. It is characterized by a density which is generally ranging from 200 to 2000 kg/m³ and typically comprises cement, water, preformed foam, fine sand and eventually fine particles such as fly ash or silica fume. The foam component mixed with the cement paste give rise to the development of a system of air-voids in the cementitious matrix. The peculiar characteristics of foamed concrete elements are summarized in the following aspects: 1) lightness which allows reducing the dimensions of the resisting frame structure and is advantageous in the scope of refurbishment or seismic retrofitting in seismically vulnerable areas; 2) thermal insulating properties, especially in the case of low densities; 3) the good resistance against fire as compared to ordinary concrete; 4) the improved workability; 5) cost-effectiveness due to the usage of rather simple constituting elements that are easily available locally. Classic foamed concrete cannot be extruded, as the dimensional stability is not permitted in the green state and this severely limits the possibility of industrializing them through a simple and cost-effective process, characterized by flexibility and high production capacity. In fact, viscosity enhancing agents (VEA) used to extrude traditional concrete, in the case of foamed concrete cause the collapsing of air bubbles, so that it is impossible to extrude a lightweight product. These requirements have suggested the study of a particular additive that modifies the rheology of foamed concrete fresh paste by increasing cohesion and viscosity and, at the same time, stabilizes the bubbles into the cementitious matrix, in order to allow the dimensional stability in the green state and, consequently, the extrusion of a lightweight product. There are plans to submit the additive’s formulation to patent. In addition to the general benefits of using the extrusion process, extrudable foamed concrete allow other limits to be exceeded: elimination of formworks, expanded application spectrum, due to the possibility of extrusion in a range varying between 200 and 2000 kg/m³, which allows the prefabrication of both structural and non-structural constructive elements. Besides, this contribution aims to present the significant differences regarding extrudable and classic foamed concrete fresh properties in terms of slump. Plastic air content, plastic density, hardened density and compressive strength have been also evaluated. The outcomes show that there are no substantial differences between extrudable and classic foamed concrete compression resistances.

Keywords: compressive strength, extrusion, foamed concrete, fresh properties, plastic air content, slump.

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Authors: Isabel Lopez-Oliva, Akshay Paropkari, Shweta Saraswat, Stefan Serban, Paola de Pablo, Karim Raza, Andrew Filer, Iain Chapple, Thomas Dietrich, Melissa Grant, Purnima Kumar

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Objective: We aimed to explicate the role of the subgingival microbiome in the causal link between rheumatoid arthritis (RA) and periodontitis (PD). Methods: Subjects with/without RA and with/without PD were randomized for treatment with scaling and root planing (SRP) or oral hygiene instructions. Subgingival biofilm, gingival crevicular fluid, and serum were collected at baseline and at 3- and 6-months post-operatively. Correlations were generated between 72 million 16S rDNA sequences, immuno-inflammatory mediators, circulating antibodies to oral microbial antigens, serum inflammatory molecules, and clinical metrics of RA. The dynamics of inter-microbial and host-microbial interactions were modeled using differential network analysis. Results: RA superseded periodontitis as a determinant of microbial composition, and DAS28 score superseded the severity of periodontitis as a driver of microbial assemblages (p=0.001, ANOSIM). RA subjects evidenced higher serum anti-PPAD (p=0.0013), anti-Pg-enolase (p=0.0031), anti-RPP3, anti- Pg-OMP and anti- Pi-OMP (p=0.001) antibodies than non-RA controls (with and without periodontitis). Following SRP, bacterial networks anchored by IL-1b, IL-4, IL-6, IL-10, IL-13, MIP-1b, and PDGF-b underwent ≥5-fold higher rewiring; and serum antibodies to microbial antigens decreased significantly. Conclusions: Our data suggest a circular relationship between RA and PD, beginning with an RA-influenced dysbiosis within the healthy subgingival microbiome that leads to exaggerated local inflammation in periodontitis and circulating antibodies to periodontal pathogens and positive correlation between severity of periodontitis and RA activity. Periodontal therapy restores host-microbial homeostasis, reduces local inflammation, and decreases circulating microbial antigens. Our data highlights the importance of integrating periodontal care into the management of RA patients.

Keywords: rheumatoid arthritis, periodontal, subgingival, DNA sequence analysis, oral microbiome

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Authors: Nzereogu Stella Kosi, Igwe Ogbonnaya, Emeh Chukwuebuka Odinaka

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A comparative analysis of the expansion rate and soil erodibility of some gullies in Nnewi and Nnobi both of Nanka Formation were studied. The study involved an integration of field observations, geotechnical analysis, slope stability analysis, multivariate statistical analysis, gully expansion rate analysis, and determination of the soil erodibility factor (K) from Revised Universal Soil Loss Equation (RUSLE). Fifteen representative gullies were studied extensively, and results reveal that the geotechnical properties of the soil, topography, vegetation cover, rainfall intensity, and the anthropogenic activities in the study area were major factors propagating and influencing the erodibility of the soils. The specific gravity of the soils ranged from 2.45-2.66 and 2.54-2.78 for Nnewi and Nnobi, respectively. Grain size distribution analysis revealed that the soils are composed of gravel (5.77-17.67%), sand (79.90-91.01%), and fines (2.36-4.05%) for Nnewi and gravel (7.01-13.65%), sand (82.47-88.67%), and fines (3.78-5.02%) for Nnobi. The soils are moderately permeable with values ranging from 2.92 x 10-5 - 6.80 x 10-4 m/sec and 2.35 x 10-6 - 3.84 x 10⁻⁴m/sec for Nnewi and Nnobi respectively. All have low cohesion values ranging from 1–5kPa and 2-5kPa and internal friction angle ranging from 29-38° and 30-34° for Nnewi and Nnobi, respectively, which suggests that the soils have low shear strength and are susceptible to shear failure. Furthermore, the compaction test revealed that the soils were loose and easily erodible with values of maximum dry density (MDD) and optimum moisture content (OMC) ranging from 1.82-2.11g/cm³ and 8.20-17.81% for Nnewi and 1.98-2.13g/cm³ and 6.00-17.80% respectively. The plasticity index (PI) of the fines showed that they are nonplastic to low plastic soils and highly liquefiable with values ranging from 0-10% and 0-9% for Nnewi and Nnobi, respectively. Multivariate statistical analyses were used to establish relationship among the determined parameters. Slope stability analysis gave factor of safety (FoS) values in the range of 0.50-0.76 and 0.82-0.95 for saturated condition and 0.73-0.98 and 0.87-1.04 for unsaturated condition for both Nnewi and Nnobi, respectively indicating that the slopes are generally unstable to critically stable. The erosion expansion rate analysis for a fifteen-year period (2005-2020) revealed an average longitudinal expansion rate of 36.05m/yr, 10.76m/yr, and 183m/yr for Nnewi, Nnobi, and Nanka type gullies, respectively. The soil erodibility factor (K) are 8.57x10⁻² and 1.62x10-4 for Nnewi and Nnobi, respectively, indicating that the soils in Nnewi have higher erodibility potentials than those of Nnobi. From the study, both the Nnewi and Nnobi areas are highly prone to erosion. However, based on the relatively lower fine content of the soil, relatively lower topography, steeper slope angle, and sparsely vegetated terrain in Nnewi, soil erodibility and gully intensity are more profound in Nnewi than Nnobi.

Keywords: soil erodibility, gully expansion, nnewi-nnobi, slope stability, factor of safety

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Authors: Daniel Faraj, Arabella Raupach, Charlotte Hespe, Helen Wilcox, Kristie-Lee Anning

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Aim: International child sponsorship programs comprise a considerable proportion of global aid accessible to the general population. Team Philippines (TP), a healthcare and welfare initiative run in association with the University of Notre Dame Sydney since 2013, leads a holistic sponsorship program for thirty children from Calauan, Philippines. To date, empirical research has not been performed on the overall success and impact of the TP child sponsorship program. As such, this study aims to evaluate its effectiveness in improving pediatric outcomes. Methods: Study cohorts comprised thirty sponsored and twenty-nine age- and gender-matched non-sponsored children. Data were extracted from the TP Medical Director database and lifestyle questionnaires for July-November 2019. Outcome measures included anthropometry, markers of medical health, dental health, exercise, and diet. Statistical analyses were performed in SPSS. Results: Sponsorship resulted in fewer medical diagnoses and prescription medications, superior dental health, and improved diet. Further, sponsored children may show a clinically significant trend toward improved physical health. Sponsorship did not affect growth and development metrics or levels of physical activity. Conclusions: The TP child sponsorship program significantly impacts positive pediatric health outcomes in the Calauan community. The strength of the program lies in its holistic, sustainable, and community-based model, which is enabled by effective international child sponsorship. This study further supports the relationship between supporting early livelihood and improved health in the pediatric population.

Keywords: child health, public health, health status disparities, healthcare disparities, social determinants of health, morbidity, community health services, culturally competent care, medically underserved areas, population health management, Philippines

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Authors: Heeba A. Gurku

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Introduction: Cone Beam CT(CBCT) images play an integral part in proper patient positioning in cancer patients undergoing radiation therapy treatment. But these images are low in quality. The purpose of this study is to generate high-quality synthetic CT images from CBCT using generative models. Material and Methods: This study utilized two datasets from The Cancer Imaging Archive (TCIA) 1) Lung cancer dataset of 20 patients (with full view CBCT images) and 2) Pancreatic cancer dataset of 40 patients (only 27 patients having limited view images were included in the study). Cycle Generative Adversarial Networks (GAN) and its variant Attention Guided Generative Adversarial Networks (AGGAN) models were used to generate the synthetic CTs. Models were evaluated by visual evaluation and on four metrics, Structural Similarity Index Measure (SSIM), Peak Signal Noise Ratio (PSNR) Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), to compare the synthetic CT and original CT images. Results: For pancreatic dataset with limited view CBCT images, our study showed that in Cycle GAN model, MAE, RMSE, PSNR improved from 12.57to 8.49, 20.94 to 15.29 and 21.85 to 24.63, respectively but structural similarity only marginally increased from 0.78 to 0.79. Similar, results were achieved with AGGAN with no improvement over Cycle GAN. However, for lung dataset with full view CBCT images Cycle GAN was able to reduce MAE significantly from 89.44 to 15.11 and AGGAN was able to reduce it to 19.77. Similarly, RMSE was also decreased from 92.68 to 23.50 in Cycle GAN and to 29.02 in AGGAN. SSIM and PSNR also improved significantly from 0.17 to 0.59 and from 8.81 to 21.06 in Cycle GAN respectively while in AGGAN SSIM increased to 0.52 and PSNR increased to 19.31. In both datasets, GAN models were able to reduce artifacts, reduce noise, have better resolution, and better contrast enhancement. Conclusion and Recommendation: Both Cycle GAN and AGGAN were significantly able to reduce MAE, RMSE and PSNR in both datasets. However, full view lung dataset showed more improvement in SSIM and image quality than limited view pancreatic dataset.

Keywords: CT images, CBCT images, cycle GAN, AGGAN

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Authors: Cassandra A. Skinner, Linda R. Chamberlain

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The nonprofit and public sectors are increasingly turning to Geographic Information Systems for data visualizations which can better inform programmatic and policy decisions. Additionally, the private and nonprofit sectors are turning to systems mapping to better understand the ecosystems within which they operate. This study explores the potential which combining these data visualization methods—a method which is called geographic systems mapping—to create an exhaustive and comprehensive understanding of a social problem’s ecosystem may have in social innovation efforts. Researchers with Grand Valley State University collaborated with Talent 2025 of West Michigan to conduct a mixed-methods research study to paint a comprehensive picture of the workforce development ecosystem in West Michigan. Using semi-structured interviewing, observation, secondary research, and quantitative analysis, data were compiled on workforce development organizations’ locations, programming, metrics for success, partnerships, funding sources, and service language. To best visualize and disseminate the data, a geographic system map was created which identifies programmatic, operational, and geographic gaps in workforce development services of West Michigan. By combining geographic and systems mapping methods, the geographic system map provides insight into the cross-sector relationships, collaboration, and competition which exists among and between workforce development organizations. These insights identify opportunities for and constraints around cross-sectoral social innovation in the West Michigan workforce development ecosystem. This paper will discuss the process utilized to prepare the geographic systems map, explain the results and outcomes, and demonstrate how geographic systems mapping illuminated the needs of the community and opportunities for social innovation. As complicated social problems like unemployment often require cross-sectoral and multi-stakeholder solutions, there is potential for geographic systems mapping to be a tool which informs, enables, and inspires these solutions.

Keywords: cross-sector collaboration, data visualization, geographic systems mapping, social innovation, workforce development

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Authors: Maciej Szelag

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The discovery of the carbon nanotubes (CNT), has led to a breakthrough in the material engineering. The CNT is characterized by very large surface area, very high Young's modulus (about 2 TPa), unmatched durability, high tensile strength (about 50 GPa) and bending strength. Their diameter usually oscillates in the range from 1 to 100 nm, and the length from 10 nm to 10-2 m. The relatively new approach is the CNT’s application in the concrete technology. The biggest problem in the use of the CNT to cement composites is their uneven dispersion and low adhesion to the cement paste. Putting the nanotubes alone into the cement matrix does not produce any effect because they tend to agglomerate, due to their large surface area. Most often, the CNT is used as an aqueous suspension in the presence of a surfactant that has previously been sonicated. The paper presents the results of investigations of the basic physical properties (apparent density, shrinkage) and mechanical properties (compression and tensile strength) of cement paste with the addition of the multiwall carbon nanotubes (MWCNT). The studies were carried out on four series of specimens (made of two different Portland Cement). Within each series, samples were made with three w/c ratios – 0.4, 0.5, 0.6 (water/cement). Two series were an unmodified cement matrix. In the remaining two series, the MWCNT was added in amount of 0.1% by cement’s weight. The MWCNT was used as an aqueous dispersion in the presence of a surfactant – SDS – sodium dodecyl sulfate (C₁₂H₂₅OSO₂ONa). So prepared aqueous solution was sonicated for 30 minutes. Then the MWCNT aqueous dispersion and cement were mixed using a mechanical stirrer. The parameters were tested after 28 days of maturation. Additionally, the change of these parameters was determined after samples temperature loading at 250°C for 4 hours (thermal shock). Measurement of the apparent density indicated that cement paste with the MWCNT addition was about 30% lighter than conventional cement matrix. This is due to the fact that the use of the MWCNT water dispersion in the presence of surfactant in the form of SDS resulted in the formation of air pores, which were trapped in the volume of the material. SDS as an anionic surfactant exhibits characteristics specific to blowing agents – gaseous and foaming substances. Because of the increased porosity of the cement paste with the MWCNT, they have obtained lower compressive and tensile strengths compared to the cement paste without additive. It has been observed, however, that the smallest decreases in the compressive and tensile strength after exposure to the elevated temperature achieved samples with the MWCNT. The MWCNT (well dispersed in the cement matrix) can form bridges between hydrates in a nanoscale of the material’s structure. Thus, this may result in an increase in the coherent cohesion of the cement material subjected to a thermal shock. The obtained material could be used for the production of an aerated concrete or using lightweight aggregates for the production of a lightweight concrete.

Keywords: cement paste, elevated temperature, mechanical parameters, multiwall carbon nanotubes, physical parameters, SDS

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Authors: Sadao Araki, Daisuke Gondo, Satoshi Imasaka, Hideki Yamamoto

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The separation of organic compounds from aqueous solutions is a key technology for recycling valuable organic compounds and for the treatment of wastewater. The wastewater from chemical plants often contains organic compounds such as ethyl acetate (EA), methylethyl ketone (MEK) and isopropyl alcohol (IPA). In this study, we prepared hydrophobic silica membranes by a sol-gel method. We used phenyltrimethoxysilane (PhTMS), ethyltrimethoxysilan (ETMS), Propyltrimethoxysilane (PrTMS), N-butyltrimethoxysilane (BTMS), N-Hexyltrimethoxysilane (HTMS) as silica sources to introduce each functional groups on the membrane surface. Cetyltrimethyl ammonium bromide (CTAB) was used as a molecular template to create suitable pore that enable the permeation of organic compounds. These membranes with five different functional groups were characterized by SEM, FT-IR, and permporometry. Thicknesses and pore diameters of silica layer for all membrane were about 1.0 μm and about 1 nm, respectively. In other words, functional groups had an insignificant effect on the membrane thicknesses and the formation of the pore by CTAB. We confirmed the effect of functional groups on the flux and separation factor for ethyl acetate (EA), methyl ethyl ketone, acetone and 1-butanol (1-BtOH) /water mixtures. All membranes showed a high flux for ethyl acetate compared with other compounds. In particular, the hydrophobic silica membrane prepared by using BTMS showed 0.75 kg m-2 h-1 of flux for EA. For all membranes, the fluxes of organic compounds showed the large values in the order corresponding to EA > MEK > acetone > 1-BtOH. On the other hand, carbon chain length of functional groups among ETMS, PrTMS, BTMS, PrTMS and HTMS did not have a major effect on the organic flux. Although we confirmed the relationship between organic fluxes and organic molecular diameters or fugacity of organic compounds, these factors had a low correlation with organic fluxes. It is considered that these factors affect the diffusivity. Generally, permeation through membranes is based on the diffusivity and solubility. Therefore, it is deemed that organic fluxes through these hydrophobic membranes are strongly influenced by solubility. We tried to estimate the organic fluxes by Hansen solubility parameter (HSP). HSP, which is based on the cohesion energy per molar volume and is composed of dispersion forces (δd), intermolecular dipole interactions (δp), and hydrogen-bonding interactions (δh), has recently attracted attention as a means for evaluating the resolution and aggregation behavior. Evaluation of solubility for two substances can be represented by using the Ra [(MPa)1/2] value, meaning the distance of HSPs for both of substances. A smaller Ra value means a higher solubility for each substance. On the other hand, it can be estimated that the substances with large Ra value show low solubility. We established the correlation equation, which was based on Ra, of organic flux at low concentrations of organic compounds and at 295-325 K.

Keywords: hydrophobic, membrane, Hansen solubility parameter, functional group

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Authors: Hossam Ali-Hassan, Michael Bliemel

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This poster reflects upon our experiences using INNOV8, IBM’s Business Process Management (BPM) simulation game, in online MBA and undergraduate MIS classes over a period of 2 years. The game is designed to gives both business and information technology players a better understanding of how effective BPM impacts an entire business ecosystem. The game includes three different scenarios: Smarter Traffic, which is used to evaluate existing traffic patterns and re-route traffic based on incoming metrics; Smarter Customer Service where players develop more efficient ways to respond to customers in a call centre environment; and Smarter Supply Chains where players balance supply and demand and reduce environmental impact in a traditional supply chain model. We use the game as an experiential learning tool, where students have to act as managers making real time changes to business processes to meet changing business demands and environments. The students learn how information technology (IT) and information systems (IS) can be used to intelligently solve different problems and how computer simulations can be used to test different scenarios or models based on business decisions without having to actually make the potentially costly and/or disruptive changes to business processes. Moreover, when students play the three different scenarios, they quickly see how practical process improvements can help meet profitability, customer satisfaction and environmental goals while addressing real problems faced by municipalities and businesses today. After spending approximately two hours in the game, students reflect on their experience from it to apply several BPM principles that were presented in their textbook through the use of a structured set of assignment questions. For each final scenario students submit a screenshot of their solution followed by one paragraph explaining what criteria you were trying to optimize, and why they picked their input variables. In this poster we outline the course and the module’s learning objectives where we used the game to place this into context. We illustrate key features of the INNOV8 Simulation Game, and describe how we used them to reinforce theoretical concepts. The poster will also illustrate examples from the simulation, assignment, and learning outcomes.

Keywords: experiential learning, business process management, BPM, INNOV8, simulation, game

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Authors: Robert Cazar, Nathaly Maza

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Energy drinks and sports drinks are quite popular among young adults and teenagers worldwide. Some concerns regarding their health effects – particularly those of the energy drinks - have been raised based on scientific findings. Differentiating between these two types of drinks by means of their chemical properties seems to be an instructive task. Chemometrics provides the most appropriate strategy to do so. In this study, a discrimination analysis of the energy and sports drinks has been carried out applying chemometric methods. A set of eleven samples of available commercial brands of drinks – seven energy drinks and four sports drinks – were collected. Each sample was characterized by eight chemical variables (carbohydrates, energy, sugar, sodium, pH, degrees Brix, density, and citric acid). The data set was standardized and examined by exploratory chemometric techniques such as clustering and principal component analysis. As a preliminary step, a variable selection was carried out by inspecting the variable correlation matrix. It was detected that some variables are redundant, so they can be safely removed, leaving only five variables that are sufficient for this analysis. They are sugar, sodium, pH, density, and citric acid. Then, a hierarchical clustering `employing the average – linkage criterion and using the Euclidian distance metrics was performed. It perfectly separates the two types of drinks since the resultant dendogram, cut at the 25% similarity level, assorts the samples in two well defined groups, one of them containing the energy drinks and the other one the sports drinks. Further assurance of the complete discrimination is provided by the principal component analysis. The projection of the data set on the first two principal components – which retain the 71% of the data information – permits to visualize the distribution of the samples in the two groups identified in the clustering stage. Since the first principal component is the discriminating one, the inspection of its loadings consents to characterize such groups. The energy drinks group possesses medium to high values of density, citric acid, and sugar. The sports drinks group, on the other hand, exhibits low values of those variables. In conclusion, the application of chemometric methods on a data set that features some chemical properties of a number of energy and sports drinks provides an accurate, dependable way to discriminate between these two types of beverages.

Keywords: chemometrics, clustering, energy drinks, principal component analysis, sports drinks

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Authors: Lukas Vierus, Thomas Schuster

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A general framework is examined for dynamic tensor field tomography within an inhomogeneous medium characterized by refraction and absorption, treated as an inverse source problem concerning the associated transport equation. Guided by Fermat’s principle, the Riemannian metric within the specified domain is determined by the medium's refractive index. While considerable literature exists on the inverse problem of reconstructing a tensor field from its longitudinal ray transform within a static Euclidean environment, limited inversion formulas and algorithms are available for general Riemannian metrics and time-varying tensor fields. It is established that tensor field tomography, akin to an inverse source problem for a transport equation, persists in dynamic scenarios. Framing dynamic tensor tomography as an inverse source problem embodies a comprehensive perspective within this domain. Ensuring well-defined forward mappings necessitates establishing existence and uniqueness for the underlying transport equations. However, the bilinear forms of the associated weak formulations fail to meet the coercivity condition. Consequently, recourse to viscosity solutions is taken, demonstrating their unique existence within suitable Sobolev spaces (in the static case) and Sobolev-Bochner spaces (in the dynamic case), under a specific assumption restricting variations in the refractive index. Notably, the adjoint problem can also be reformulated as a transport equation, with analogous results regarding uniqueness. Analytical solutions are expressed as integrals over geodesics, facilitating more efficient evaluation of forward and adjoint operators compared to solving partial differential equations. Certainly, here's the revised sentence in English: Numerical experiments are conducted using a Nesterov-accelerated Landweber method, encompassing various fields, absorption coefficients, and refractive indices, thereby illustrating the enhanced reconstruction achieved through this holistic modeling approach.

Keywords: attenuated refractive dynamic ray transform of tensor fields, geodesics, transport equation, viscosity solutions

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Authors: David Edgar

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To understand how the brain’s subconscious and conscious functions, we must conquer the physics of Unity, which leads to duality’s algorithm. Where the subconscious (bottom-up) and conscious (top-down) processes function together to produce and consume intelligence, we use terms like ‘time is relative,’ but we really do understand the meaning. In the brain, there are different processes and, therefore, different observers. These different processes experience time at different rates. A sensory system such as the eyes cycles measurement around 33 milliseconds, the conscious process of the frontal lobe cycles at 300 milliseconds, and the subconscious process of the thalamus cycle at 5 milliseconds. Three different observers experience time differently. To bridge observers, the thalamus, which is the fastest of the processes, maintains a synchronous state and entangles the different components of the brain’s physical process. The entanglements form a synchronous cohesion between the brain components allowing them to share the same state and execute in the same measurement cycle. The thalamus uses the shared state to control the firing sequence of the brain’s linear subconscious process. Sharing state also allows the brain to cheat on the amount of sensory data that must be exchanged between components. Only unpredictable motion is transferred through the synchronous state because predictable motion already exists in the shared framework. The brain’s synchronous subconscious process is entirely based on energy conservation, where prediction regulates energy usage. So, the eyes every 33 milliseconds dump their sensory data into the thalamus every day. The thalamus is going to perform a motion measurement to identify the unpredictable motion in the sensory data. Here is the trick. The thalamus conducts its measurement based on the original observation time of the sensory system (33 ms), not its own process time (5 ms). This creates a data payload of synchronous motion that preserves the original sensory observation. Basically, a frozen moment in time (Flat 4D). The single moment in time can then be processed through the single state maintained by the synchronous process. Other processes, such as consciousness (300 ms), can interface with the synchronous state to generate awareness of that moment. Now, synchronous data traveling through a separate faster synchronous process creates a theoretical time tunnel where observation time is tunneled through the synchronous process and is reproduced on the other side in the original time-relativity. The synchronous process eliminates time dilation by simply removing itself from the equation so that its own process time does not alter the experience. To the original observer, the measurement appears to be instantaneous, but in the thalamus, a linear subconscious process generating sensory perception and thought production is being executed. It is all just occurring in the time available because other observation times are slower than thalamic measurement time. For life to exist in the physical universe requires a linear measurement process, it just hides by operating at a faster time relativity. What’s interesting is time dilation is not the problem; it’s the solution. Einstein said there was no universal time.

Keywords: neural synchronization, natural intelligence, 99.95% IoT data transmission savings, artificial subconscious intelligence (ASI)

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Authors: David Gottlieb, Jason Yoder

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The feeling of loneliness is not uncommon in modern society, and yet, there is a fundamental lack of understanding in its origins and purpose in nature. One interpretation of loneliness is that it is a subjective experience that punishes a lack of social behavior, and thus its emergence in human evolution is seemingly tied to the survival of early human tribes. Still, a common counterintuitive response to loneliness is a state of hypervigilance, resulting in social withdrawal, which may appear maladaptive to modern society. So far, no computational model of loneliness’ effect during evolution yet exists; however, agent-based models (ABM) can be used to investigate social behavior, and applying evolution to agents’ behaviors can demonstrate selective advantages for particular behaviors. We propose an ABM where each agent contains four social behaviors, and one goal-seeking behavior, letting evolution select the best behavioral patterns for resource allocation. In our paper, we use an algorithm similar to the boid model to guide the behavior of agents, but expand the set of rules that govern their behavior. While we use cohesion, separation, and alignment for simple social movement, our expanded model adds goal-oriented behavior, which is inspired by particle swarm optimization, such that agents move relative to their personal best position. Since agents are given the ability to form connections by interacting with each other, our final behavior guides agent movement toward its social connections. Finally, we introduce a mechanism to represent a state of loneliness, which engages when an agent's perceived social involvement does not meet its expected social involvement. This enables us to investigate a minimal model of loneliness, and using evolution we attempt to elucidate its value in human survival. Agents are placed in an environment in which they must acquire resources, as their fitness is based on the total resource collected. With these rules in place, we are able to run evolution under various conditions, including resource-rich environments, and when disease is present. Our simulations indicate that there is strong selection pressure for social behavior under circumstances where there is a clear discrepancy between initial resource locations, and against social behavior when disease is present, mirroring hypervigilance. This not only provides an explanation for the emergence of loneliness, but also reflects the diversity of response to loneliness in the real world. In addition, there is evidence of a richness of social behavior when loneliness was present. By introducing just two resource locations, we observed a divergence in social motivation after agents became lonely, where one agent learned to move to the other, who was in a better resource position. The results and ongoing work from this project show that it is possible to glean insight into the evolutionary advantages of even simple mechanisms of loneliness. The model we developed has produced unexpected results and has led to more questions, such as the impact loneliness would have at a larger scale, or the effect of creating a set of rules governing interaction beyond adjacency.

Keywords: agent-based, behavior, evolution, loneliness, social

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Authors: Selim M. Khan

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Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.

Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America

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Authors: A. Raj Kumar, S. Bilaloglu

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Stroke is a leading cause of adult disability worldwide. We depend on our hands for our activities of daily living(ADL). Although many patients regain the ability to walk, they continue to experience long-term hand motor impairments. As the number of individuals with young stroke is increasing, there is a critical need for effective approaches for rehabilitation of hand function post-stroke. Motor relearning for dexterity requires task-specific kinesthetic, tactile and visual feedback. However, when a stroke results in both sensory and motor impairment, it becomes difficult to ascertain when and what type of sensory substitutions can facilitate motor relearning. In an ideal situation, real-time task-specific data on the ability to learn and data-driven feedback to assist such learning will greatly assist rehabilitation for dexterity. We have found that kinesthetic and tactile information from the unaffected hand can assist patients re-learn the use of optimal fingertip forces during a grasp and lift task. Measurement of fingertip grip force (GF), load forces (LF), their corresponding rates (GFR and LFR), and other metrics can be used to gauge the impairment level and progress during learning. Currently ATI mini force-torque sensors are used in research settings to measure and compute the LF, GF, and their rates while grasping objects of different weights and textures. Use of the ATI sensor is cost prohibitive for deployment in clinical or at-home rehabilitation. A cost effective mechatronic device is developed to quantify GF, LF, and their rates for stroke rehabilitation purposes using off-the-shelf components such as load cells, flexi-force sensors, and an Arduino UNO microcontroller. A salient feature of the device is its integration with an interactive gaming environment to render a highly engaging user experience. This paper elaborates the integration of kinesthetic and tactile sensing through computation of LF, GF and their corresponding rates in real time, information processing, and interactive interfacing through augmented reality for visual feedback.

Keywords: feedback, gaming, kinesthetic, rehabilitation, tactile

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Authors: Kyra Kannen, Sonja D. Roelen, Sebastian Schnieder, Jarek Krajewski, Steffen Holsteg, André Karger, Johanna Askeridis, Celina Slawik, Philip Mildner, Jens Piesk, Ruslan David, Holger Kürten, Benjamin Oster, Robert Malzan, Mike Ludemann

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Virtual Reality (VR) is increasingly recognized for its potential in transforming mental disorder treatment, offering advantages such as cost-effectiveness, time efficiency, accessibility, reduced stigma, and scalability. While the application of VR in the context of anxiety disorders has been extensively evaluated and demonstrated to be effective, the utilization of VR as a therapeutic treatment for depression remains under-investigated. Our goal is to pioneer immersive VR therapy modules for treating major depression, alongside a web-based system for home use. We develop a modular digital therapy platform grounded in psychodynamic therapy interventions which addresses stress reduction, exploration of social situations and relationship support, social skill training, avoidance behavior analysis, and psychoeducation. In addition, an automated depression monitoring system, based on acoustic voice analysis, is implemented in the form of a speech-based diary to track the affective state of the user and depression severity. The use of immersive VR facilitates patient immersion into complex and realistic interpersonal interactions with high emotional engagement, which may contribute to positive treatment acceptance and satisfaction. In a proof-of-concept study, 45 depressed patients were assigned to VR or web-platform modules, evaluating user experience, usability and additional metrics including depression severity, mindfulness, interpersonal problems, and treatment satisfaction. The findings provide valuable insights into the effectiveness and user-friendliness of VR and web modules for depression therapy and contribute to the refinement of more tailored digital interventions to improve mental health.

Keywords: virtual reality therapy, digital health, depression, psychotherapy

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Authors: Elif Berna Var

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Cultural, physical, socio-economic, or politic changes occurred in urban areas might be resulted in the decaying period which may cause social problems. As a solution to that, urban renewal projects have been used in European countries since World War II whereas they have gained importance in Turkey after the 1980s. The first attempts were mostly related to physical or economic aspects which caused negative effects on social pattern later. Thus, social concerns have also started to include in renewal processes in developed countries. This integrative approach combining social, physical, and economic aspects promotes creating more sustainable neighbourhoods for both current and future generations. However, it is still a new subject for developing countries like Turkey. Concentrating on Trabzon-Turkey, this study highlights the importance of socially sustainable urban renewal processes especially in historical neighbourhoods where protecting the urban identity of the area is vital, as well as social structure, to create sustainable environments. Being in the historic city centre and having remarkable traditional houses, Ortahisar is an important image for Trabzon. Because of the fact that architectural and historical pattern of the area is still visible but need rehabilitations, it is preferred to use 'urban rehabilitation' as a way of urban renewal method for this study. A project is developed by the local government to create a secondary city centre and a new landmark for the city. But it is still ambiguous if this project can provide social sustainability of area which is one of the concerns of the research. In the study, it is suggested that social sustainability of an area can be achieved by several factors. In order to determine the factors affecting the social sustainability of an urban rehabilitation project, previous studies have been analysed and some common features are attempted to define. To achieve this, firstly, several analyses are conducted to find out social structure of Ortahisar. Secondly, structured interviews are implemented to 150 local people which aims to measure satisfaction level, awareness, the expectation of them, and to learn their demographical background in detail. Those data are used to define the critical factors for a more socially sustainable neighbourhood in Ortahisar. Later, the priority of those factors is asked to 50 experts and 150 local people to compare their attitudes and to find common criterias. According to the results, it can be said that social sustainability of Ortahisar neighbourhood can be improved by considering various factors like quality of urban areas, demographical factors, public participation, social cohesion and harmony, proprietorial factors, facilities of education and employment. In the end, several suggestions are made for Ortahisar case to promote more socially sustainable urban neighbourhood. As a pilot study highlighting the importance of social sustainability, it is hoped that this attempt might be the contributory effect on achieving more socially sustainable urban rehabilitation projects in Turkey.

Keywords: urban rehabilitation, social sustainability, Trabzon, Turkey

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Authors: Carmen Georgeta Dumitrache

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Measurements of terrestrial science aims to study the totality of operations and computing, which are carried out for the purposes of representation on the plan or map of the land surface in a specific cartographic projection and topographic scale. With the development of society, the metrics have evolved, and they land, being dependent on the achievement of a goal-bound utility of economic activity and of a scientific purpose related to determining the form and dimensions of the Earth. For measurements in the field, data processing and proper representation on drawings and maps of planimetry and landform of the land, using topographic and geodesic instruments, calculation and graphical reporting, which requires a knowledge of theoretical and practical concepts from different areas of science and technology. In order to use properly in practice, topographical and geodetic instruments designed to measure precise angles and distances are required knowledge of geometric optics, precision mechanics, the strength of materials, and more. For processing, the results from field measurements are necessary for calculation methods, based on notions of geometry, trigonometry, algebra, mathematical analysis and computer science. To be able to illustrate topographic measurements was established for the lifting of property located near the locality of Gircov, Romania. We determine this total surface of the plan (T30), parcel/plot, but also in the field trace the coordinates of a parcel. The purpose of the removal of the planimetric consisted of: the exact determination of the bounding surface; analytical calculation of the surface; comparing the surface determined with the one registered in the documents produced; drawing up a plan of location and delineation with closeness and distance contour, as well as highlighting the parcels comprising this property; drawing up a plan of location and delineation with closeness and distance contour for a parcel from Dave; in the field trace outline of plot points from the previous point. The ultimate goal of this work was to determine and represent the surface, but also to tear off a plot of the surface total, while respecting the first surface condition imposed by the Act of the beneficiary's property.

Keywords: topography, surface, coordinate, modeling

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Authors: Julien Benomar

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The World Bank report published in April 2023 called “Migrants, Refugees and Society” allows us to first distinguish migrants in search of economic opportunities and refugees that flee a situation of danger and choose their destination based on their immediate need for safety. Amongst those two categories, the report distinguished people having professional skills adapted to the labor market of the host country and those who have not. Out of that distinction of four categories, we choose to focus our research on refugees that do not have professional skills adapted to the labor market of the host country. Given that refugees generally have no recourse to public assistance schemes and cannot count on the support of their entourage or support network, we propose to examine the extent to which external assistance, such as international humanitarian action, is likely to accompany refugees' transition to financial empowerment through entrepreneurship. To this end, we propose to carry out a case study structured in three stages: (i) an exchange with a Non-Governmental Organisation (NGO) active in supporting refugee populations from Congo and Burundi to Rwanda, enabling us to (i.i) define together a financial empowerment income, and (i. ii) learn about the content of the support measures taken for the beneficiaries of the humanitarian project; (ii) monitor the population of 118 beneficiaries, including 73 refugees and 45 Rwandans (reference population); (iii) conduct a participatory analysis to identify the level of performance of the project and areas for improvement. The case study thus involved the staff of an international NGO active in helping refugees from Rwanda since 2015 and the staff of a Luxembourg NGO that has been funding this economic aid project through entrepreneurship since 2021. The case study thus involved the staff of an international NGO active in helping refugees from Rwanda since 2015 and the staff of a Luxembourg NGO, which has been funding this economic aid through an entrepreneurship project since 2021, and took place over a 48-day period between April and May 2023. The main results are of two types: (i) the need to associate indicators for monitoring the impact of the project on the indirect beneficiaries of the project (refugee community) and (ii) the identification of success factors making it possible to bring concrete and relevant responses to the constraints encountered. The first result thus made it possible to identify the following indicators: Indicator of community potential ((jobs, training or mentoring) promoted by the activity of the entrepreneur), Indicator of social contribution (tax paid by the entrepreneur), Indicator of resilience (savings and loan capacity generated, and finally impact on social cohesion. The second result made it possible to identify that among the 7 success factors tested, the sector of activity chosen and the level of experience in the sector of the future activity are those that stand out the most clearly.

Keywords: entrepreuneurship, refugees, financial empowerment, international aid

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Authors: Ahmedou Moulaye Idriss, Tfeil Yahya, Tamas Ungi, Gabor Fichtinger

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Image-guided therapy (IGT) plays a crucial role in minimally invasive procedures for liver interventions. Accurate segmentation of the liver and precise needle placement is essential for successful interventions such as needle aspiration. In this study, we propose a deep learning-based liver 3D slicer designed to enhance segmentation accuracy and facilitate needle aspiration procedures. The developed 3D slicer leverages state-of-the-art convolutional neural networks (CNNs) for automatic liver segmentation in medical images. The CNN model is trained on a diverse dataset of liver images obtained from various imaging modalities, including computed tomography (CT) and magnetic resonance imaging (MRI). The trained model demonstrates robust performance in accurately delineating liver boundaries, even in cases with anatomical variations and pathological conditions. Furthermore, the 3D slicer integrates advanced image registration techniques to ensure accurate alignment of preoperative images with real-time interventional imaging. This alignment enhances the precision of needle placement during aspiration procedures, minimizing the risk of complications and improving overall intervention outcomes. To validate the efficacy of the proposed deep learning-based 3D slicer, a comprehensive evaluation is conducted using a dataset of clinical cases. Quantitative metrics, including the Dice similarity coefficient and Hausdorff distance, are employed to assess the accuracy of liver segmentation. Additionally, the performance of the 3D slicer in guiding needle aspiration procedures is evaluated through simulated and clinical interventions. Preliminary results demonstrate the effectiveness of the developed 3D slicer in achieving accurate liver segmentation and guiding needle aspiration procedures with high precision. The integration of deep learning techniques into the IGT workflow shows great promise for enhancing the efficiency and safety of liver interventions, ultimately contributing to improved patient outcomes.

Keywords: deep learning, liver segmentation, 3D slicer, image guided therapy, needle aspiration

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Authors: Omojokun Gabriel Aju

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Communication network is a process of exchanging data between two or more devices via some forms of transmission medium using communication protocols. The data could be in form of text, images, audio, video or numbers which can be grouped into FTP, Email, HTTP, VOIP or Video applications. The effectiveness of such data exchange will be proved if they are accurately delivered within specified time. While some senders will not really mind when the data is actually received by the receiving device, inasmuch as it is acknowledged to have been received by the receiver. The time a data takes to get to a receiver could be very important to another sender, as any delay could cause serious problem or even in some cases rendered the data useless. The validity or invalidity of a data after delay will therefore definitely depend on the type of data (information). It is therefore imperative for the network device (such as router) to be able to differentiate among the packets which are time sensitive and those that are not, when they are passing through the same network. So, here is where the queuing disciplines comes to play, to handle network resources when such network is designed to service widely varying types of traffics and manage the available resources according to the configured policies. Therefore, as part of the resources allocation mechanisms, a router within the network must implement some queuing discipline that governs how packets (data) are buffered while waiting to be transmitted. The implementation of the queuing discipline will regulate how the packets are buffered while waiting to be transmitted. In achieving this, various queuing disciplines are being used to control the transmission of these packets, by determining which of the packets get the highest priority, less priority and which packets are dropped. The queuing discipline will therefore control the packets latency by determining how long a packet can wait to be transmitted or dropped. The common queuing disciplines are first-in-first-out queuing, Priority queuing and Weighted-fair queuing (FIFO, PQ and WFQ). This paper critically evaluates and analyse through the use of Optimized Network Evaluation Tool (OPNET) Modeller, Version 14.5 the effects of three queuing disciplines (FIFO, PQ and WFQ) on the performance of 5 different applications (FTP, HTTP, E-Mail, Voice and Video) within specified parameters using packets sent, packets received and transmission delay as performance metrics. The paper finally suggests some ways in which networks can be designed to provide better transmission performance while using these queuing disciplines.

Keywords: applications, first-in-first-out queuing (FIFO), optimised network evaluation tool (OPNET), packets, priority queuing (PQ), queuing discipline, weighted-fair queuing (WFQ)

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Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

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In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

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Authors: Clinton Adas

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Antibiotic resistance has been identified by the World Health Organisation as a real possibility for the 21st Century. While many factors contribute to this, one of the more significant is industrial animal farming and its effect on the food chain and environment. Livestock consumes a significant portion of antibiotics sold globally, and these are used to make animals grow faster for profit purposes, to prevent illness caused by inhumane living conditions, and to treat disease when it breaks out. Many of these antibiotics provide little benefit to animals, and most are the same as those used by humans - including those deemed critical to human health that should therefore be used sparingly. Antibiotic resistance contributes to growing numbers of illnesses and death in humans, and the excess usage of these medications results in waste that enters the environment and is harmful to many ecological processes. This combination of antimicrobial resistance and environmental degradation furthermore harms the economic well-being and prospects of many. Using an interdisciplinary approach including medical, environmental, economic, and legal studies, the paper evaluates the dynamic between animal welfare and commerce and argues that while animal welfare is not of great concern to many, this approach is ultimately harming human welfare too. It is, however, proposed that both could be addressed under a One Health and Welfare approach, as we cannot continue to ignore the linkages between animals, the environment, and people. The evaluation of industrial animal farming is therefore considered through three aspects – the environmental impact, which is measured by pollution that causes environmental degradation; the human impact, which is measured by the rise of illnesses from pollution and antibiotics resistance; and the economic impact, which is measured through costs to the health care system and the financial implications of industrial farming on the economic well-being of many. These three aspects are considered in light of the Sustainable Development Goals that provide additional tangible metrics to evidence the negative impacts. While the research addresses the welfare of farmed animals, there is potential for these principles to be extrapolated into other contexts, including wildlife and habitat protection. It must be noted that while the question of animal rights in industrial animal farming is acknowledged and of importance, this is a separate matter that is not addressed here.

Keywords: animal and human welfare, industrial animal farming, one health and welfare, sustainable development goals

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Authors: Sinem Tas

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This research paper attempts to study the perspective of personal experience in relation to spatial dynamics and artistic outcomes within the realm of cultural identity. This article serves as a partial analysis within a broader PhD investigation that focuses on the cultural dynamics and political structures behind cultural identity through an autoethnography of narrative while presenting its correlation with artistic creation in the context of space and people. Focusing on the artistic/creative practice project AUTRUI, the primary goal is to analyse and understand the influence of personal experiences and culturally constructed identity as an artist in resulting in the compositional modality of the last image considering self-reflective experience. Referencing the works of Joyce Davidson and Christine Milligan - the scholars who emphasise the importance of emotion and spatial experience in geographical studies contribute to this work as they highlight the significance of emotion across various spatial scales in their work Embodying Emotion Sensing Space: Introducing Emotional Geographies (2004). Their perspective suggests that understanding emotions within different spatial contexts is crucial for comprehending human experiences and interactions with space. Incorporating the insights of scholars like Yi-Fu Tuan, particularly his seminal work Space and Place: The Perspective of Experience (1979), is important for creating an in-depth frame of geographical experience. Tuan's humanistic perspective on space and place provides a valuable theoretical framework for understanding the interplay between personal experiences and spatial contexts. A substantial contextualisation of the geopolitics of Turkey - the implications for national identity and cohesion - will be addressed by drawing an outline of the political and geographical frame as a methodological strategy to understand the dynamics behind this research. Besides the bibliographical reading, the methods used to study this relation are participatory observation, memory work along with memoir analysis, personal interviews, and discussion of photographs and news. The utilisation of the self as data requires the analysis of the written sources with personal engagement. By delving into written sources such as written communications or diaries as well as memoirs, the research gains a firsthand perspective, enriching the analytical depth of the study. Furthermore, the examination of photography and news articles serves as a valuable means of contextualising experiences from a journalist's background within specific geographical settings. The inclusion of interviews with close family members access provides firsthand perspectives and intimate insights rooted in shared experiences within similar geographical contexts, offering complementary insights and diversified viewpoints, enhancing the comprehensiveness of the investigation.

Keywords: art, autoethnography, place and space, Turkey

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Authors: Sairi Satari

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Introduction: Six-sigma is a metric that quantifies the performance of processes as a rate of Defects-Per-Million Opportunities. Sigma methodology can be applied in chemical pathology laboratory for evaluating process performance with evidence for process improvement in quality assurance program. In the laboratory, these methods have been used to improve the timeliness of troubleshooting, reduce the cost and frequency of quality control and minimize pre and post-analytical errors. Aim: The aim of this study is to evaluate the sigma values of the Cobas 8000 analyzer based on the minimum requirement of the specification. Methodology: Twenty-one analytes were chosen in this study. The analytes were alanine aminotransferase (ALT), albumin, alkaline phosphatase (ALP), Amylase, aspartate transaminase (AST), total bilirubin, calcium, chloride, cholesterol, HDL-cholesterol, creatinine, creatinine kinase, glucose, lactate dehydrogenase (LDH), magnesium, potassium, protein, sodium, triglyceride, uric acid and urea. Total error was obtained from Clinical Laboratory Improvement Amendments (CLIA). The Bias was calculated from end cycle report of Royal College of Pathologists of Australasia (RCPA) cycle from July to December 2016 and coefficient variation (CV) from six-month internal quality control (IQC). The sigma was calculated based on the formula :Sigma = (Total Error - Bias) / CV. The analytical performance was evaluated based on the sigma, sigma > 6 is world class, sigma > 5 is excellent, sigma > 4 is good and sigma < 4 is satisfactory and sigma < 3 is poor performance. Results: Based on the calculation, we found that, 96% are world class (ALT, albumin, ALP, amylase, AST, total bilirubin, cholesterol, HDL-cholesterol, creatinine, creatinine kinase, glucose, LDH, magnesium, potassium, triglyceride and uric acid. 14% are excellent (calcium, protein and urea), and 10% ( chloride and sodium) require more frequent IQC performed per day. Conclusion: Based on this study, we found that IQC should be performed frequently for only Chloride and Sodium to ensure accurate and reliable analysis for patient management.

Keywords: sigma matrics, analytical performance, total error, bias

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Authors: Keigo Nishitani, Kohei Mizuta Mizuta, Kazuyoshi Kurita, Yukinori Taniguchi

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To establish mass production process of Ti capsule which has Fe powder inside as magnetic hyperthermia implant, we assumed that Ti thin sheet can be drawn into a φ1.0 mm die hole through the medium of Fe Powder and becomes outer shell of capsule. This study discusses mechanism of powder assisted deep drawing process by both of numerical simulation and experiment. Ti thin sheet blank was placed on die, and was covered by Fe powder layer without pressurizing. Then upper punch was indented on the Fe powder layer, and the blank can be drawn into die cavity as pressurized powder particles were extruded into die cavity from behind of the drawn blank. Distinct Element Method (DEM) has been used to demonstrate the process. To identify bonding parameters on Fe particles which are cohesion, tensile bond stress and inter particle friction angle, axial and diametrical compression failure test of Fe powder compact was conducted. Several density ratios of powder compacts in range of 0.70 - 0.85 were investigated and relationship between mean stress and equivalent stress was calculated with consideration of critical state line which rules failure criterion in consolidation of Fe powder. Since variation of bonding parameters with density ratio has been experimentally identified, and good agreement has been recognized between several failure tests and its simulation, demonstration of powder assisted sheet forming by using DEM becomes applicable. Results of simulation indicated that indent/drawing length of Ti thin sheet is promoted by smaller Fe particle size, larger indent punch diameter, lower friction coefficient between die surface and Ti sheet and certain degrees of die inlet taper angle. In the deep drawing test, we have made die-set with φ2.4 mm punch and φ1.0 mm die bore diameter. Pure Ti sheet with 100 μm thickness, annealed at 650 deg. C has been tested. After indentation, indented/drawn capsule has been observed by microscope, and its length was measured to discuss the feasibility of this capsulation process. Longer drawing length exists on progressive loading pass comparing with the case of single stroke loading. It is expected that progressive loading has an advantage of which extrusion of powder particle into die cavity with Ti sheet is promoted since powder particle layer can be rebuilt while the punch is withdrawn from the layer in each loading steps. This capsulation phenomenon is qualitatively demonstrated by DEM simulation. Finally, we have fabricated Ti capsule which has Fe powder inside for magnetic hyperthermia cancer care treatment. It is concluded that suggested method is possible to use the manufacturing of Ti capsule implant for magnetic hyperthermia cancer care.

Keywords: metal powder compaction, metal forming, distinct element method, cancer care, magnetic hyperthermia

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Authors: Andres Manuel Garcia Lamparte, Rocio Losada Iglesias, Marcos BoullóN Magan, David Miranda Barros

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The biodiversity strategy of the European Union for 2030, mentions climate change as one of the key factors for biodiversity loss and considers green infrastructure as one of the solutions to this problem. In this line, the European Commission has developed a green infrastructure strategy which commits members states to consider green infrastructure in their territorial planning. This green infrastructure is aimed at granting the provision of a wide number of ecosystem services to support biodiversity and human well-being by countering the effects of climate change. Yet, there are not too many tools available to delimit green infrastructure. The available ones consider the potential of the territory to provide ecosystem services. However, these methods usually aggregate several maps of ecosystem services potential without considering possible trade-offs. This can lead to excluding areas with a high potential for providing ecosystem services which have many trade-offs with other ecosystem services. In order to tackle this problem, a methodology is proposed to consider ecosystem services trade-offs in the objective function of a simulated annealing algorithm aimed at delimiting green infrastructure multifunctional buffer areas. To this end, the provision potential maps of the regulating ecosystem services considered to delimit the multifunctional buffer areas are clustered in groups, so that ecosystem services that create trade-offs are excluded in each group. The normalized provision potential maps of the ecosystem services in each group are added to obtain a potential map per group which is normalized again. Then the potential maps for each group are combined in a raster map that shows the highest provision potential value in each cell. The combined map is then used in the objective function of the simulated annealing algorithm. The algorithm is run both using the proposed methodology and considering the ecosystem services individually. The results are analyzed with spatial statistics and landscape metrics to check the number of ecosystem services that the delimited areas produce, as well as their regularity and compactness. It has been observed that the proposed methodology increases the number of ecosystem services produced by delimited areas, improving their multifunctionality and increasing their effectiveness in preventing climate change impacts.

Keywords: ecosystem services trade-offs, green infrastructure delineation, multifunctional buffer areas, climate change

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Authors: Scott R. Butler

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Ontario, Canada’s largest province, is in the midst of an interesting experiment in mandated asset management planning for local governments. At the beginning of 2021, Ontario’s 444 municipalities were responsible for the management of 302,864 lane kilometers of roads that have a replacement cost of $97.545 billion CDN. Roadways are by far the most complex, expensive, and extensive assets that a municipality is responsible for overseeing. Since adopting Ontario Regulation 588/47: Asset Management Planning for Municipal Infrastructure in 2017, the provincial government has established prescriptions for local road authorities regarding asset category and levels of service being provided. This provincial regulation further stipulates that asset data such as extent, condition, and life cycle costing are to be captured in manner compliant with qualitative descriptions and technical metrics. The Ontario Good Roads Association undertook an exercise to aggregate the road-related data contained within the 444 asset management plans that municipalities have filed with the provincial government. This analysis concluded that collectively Ontario municipal roadways have a $34.7 billion CDN in deferred maintenance. The ill-state of repair of Ontario municipal roads has lasting implications for province’s economic competitiveness and has garnered considerable political attention. Municipal efforts to address the maintenance backlog are stymied by the extremely limited fiscal parameters municipalities must operate within in Ontario. Further exacerbating the program are provincially designed programs that are ineffective, administratively burdensome, and not necessarily aligned with local priorities or strategies. This paper addresses how municipal asset management plans – and more specifically, the data contained in these plans – can be used to design innovative policy frameworks, flexible funding programs, and new levels of service that respond to these funding challenges, as well as emerging issues such as local economic development and climate change. To fully unlock the potential that Ontario Regulation 588/17 has imposed will require a resolute commitment to data standardization and horizontal collaboration between municipalities within regions.

Keywords: transportation, municipal asset management, subnational policy design, subnational funding program design

Procedia PDF Downloads 70