Search results for: variable elastic foundation

Authors: Arefeh Arabaninezhad, Ali Fakher

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Since the deterministic analysis methods fail to take system uncertainties into account, probabilistic and non-probabilistic methods are suggested. Geotechnical analyses are used to determine the stress and deformation caused by construction; accordingly, many input variables which depend on ground behavior are required for geotechnical analyses. The Random Set approach is an applicable reliability analysis method when comprehensive sources of information are not available. Using Random Set method, with relatively small number of simulations compared to fully probabilistic methods, smooth extremes on system responses are obtained. Therefore random set approach has been proposed for reliability analysis in geotechnical problems. In the present study, the application of random set method in reliability analysis of deep excavations is investigated through three deep excavation projects which were monitored during the excavating process. A finite element code is utilized for numerical modeling. Two expected ranges, from different sources of information, are established for each input variable, and a specific probability assignment is defined for each range. To determine the most influential input variables and subsequently reducing the number of required finite element calculations, sensitivity analysis is carried out. Input data for finite element model are obtained by combining the upper and lower bounds of the input variables. The relevant probability share of each finite element calculation is determined considering the probability assigned to input variables present in these combinations. Horizontal displacement of the top point of excavation is considered as the main response of the system. The result of reliability analysis for each intended deep excavation is presented by constructing the Belief and Plausibility distribution function (i.e. lower and upper bounds) of system response obtained from deterministic finite element calculations. To evaluate the quality of input variables as well as applied reliability analysis method, the range of displacements extracted from models has been compared to the in situ measurements and good agreement is observed. The comparison also showed that Random Set Finite Element Method applies to estimate the horizontal displacement of the top point of deep excavation. Finally, the probability of failure or unsatisfactory performance of the system is evaluated by comparing the threshold displacement with reliability analysis results.

Keywords: deep excavation, random set finite element method, reliability analysis, uncertainty

Procedia PDF Downloads 265

Authors: Eva Filová, Jana Daňková, Věra Sovková, Matej Daniel

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Titanium alloys are biocompatible metals that are widely used in clinical practice as load bearing implants. The chemical modification may influence cell adhesion, proliferation, and differentiation as well as stiffness of the material. The aim of the study was to evaluate the adhesion, growth and differentiation of pig mesenchymal stem cells on the novel beta titanium alloy Ti36Nb6Ta compared to standard medical titanium alloy Ti6Al4V. Discs of Ti36Nb6Ta and Ti6Al4V alloy were sterilized by ethanol, put in 48-well plates, and seeded by pig mesenchymal stem cells at the density of 60×103/cm2 and cultured in Minimum essential medium (Sigma) supplemented with 10% fetal bovine serum and penicillin/streptomycin. Cell viability was evaluated using MTS assay (CellTiter 96® AQueous One Solution Cell Proliferation Assay;Promega), cell proliferation using Quant-iT™ ds DNA Assay Kit (Life Technologies). Cells were stained immunohistochemically using monoclonal antibody beta-actin, and secondary antibody conjugated with AlexaFluor®488 and subsequently the spread area of cells was measured. Cell differentiation was evaluated by alkaline phosphatase assay using p-nitrophenyl phosphate (pNPP) as a substrate; the reaction was stopped by NaOH, and the absorbance was measured at 405 nm. Osteocalcin, specific bone marker was stained immunohistochemically and subsequently visualized using confocal microscopy; the fluorescence intensity was analyzed and quantified. Moreover, gene expression of osteogenic markers osteocalcin and type I collagen was evaluated by real-time reverse transcription-PCR (qRT-PCR). For statistical evaluation, One-way ANOVA followed by Student-Newman-Keuls Method was used. For qRT-PCR, the nonparametric Kruskal-Wallis Test and Dunn's Multiple Comparison Test were used. The absorbance in MTS assay was significantly higher on titanium alloy Ti6Al4V compared to beta titanium alloy Ti36Nb6Ta on days 7 and 14. Mesenchymal stem cells were well spread on both alloys, but no difference in spread area was found. No differences in alkaline phosphatase assay, fluorescence intensity of osteocalcin as well as the expression of type I collagen, and osteocalcin genes were observed. Higher expression of type I collagen compared to osteocalcin was observed for cells on both alloys. Both beta titanium alloy Ti36Nb6Ta and titanium alloy Ti6Al4V Ti36Nb6Ta supported mesenchymal stem cellsˈ adhesion, proliferation and osteogenic differentiation. Novel beta titanium alloys Ti36Nb6Ta is a promising material for bone implantation. The project was supported by the Czech Science Foundation: grant No. 16-14758S, the Grant Agency of the Charles University, grant No. 1246314 and by the Ministry of Education, Youth and Sports NPU I: LO1309.

Keywords: beta titanium, cell growth, mesenchymal stem cells, titanium alloy, implant

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Authors: Abbas Ahmadi, Bijan Raie, Mohammad Reza Neyshabouri, Mohammad Ali Ghorbani, Farrokh Asadzadeh

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In recent years, vast areas of Urmia Lake in Dasht-e-Tabriz has dried up leading to saline sediments exposure on the surface lake coastal areas being highly susceptible to wind erosion. This study was conducted to investigate wind erosion and its relevance to soil physicochemical properties and also modeling of wind erodibility (WE) using artificial intelligence techniques. For this purpose, 96 soil samples were collected from 0-5 cm depth in 414000 hectares using stratified random sampling method. To measure the WE, all samples (<8 mm) were exposed to 5 different wind velocities (9.5, 11, 12.5, 14.1 and 15 m s-1 at the height of 20 cm) in wind tunnel and its relationship with soil physicochemical properties was evaluated. According to the results, WE varied within the range of 76.69-9.98 (g m-2 min-1)/(m s-1) with a mean of 10.21 and coefficient of variation of 94.5% showing a relatively high variation in the studied area. WE was significantly (P<0.01) affected by soil physical properties, including mean weight diameter, erodible fraction (secondary particles smaller than 0.85 mm) and percentage of the secondary particle size classes 2-4.75, 1.7-2 and 0.1-0.25 mm. Results showed that the mean weight diameter, erodible fraction and percentage of size class 0.1-0.25 mm demonstrated stronger relationship with WE (coefficients of determination were 0.69, 0.67 and 0.68, respectively). This study also compared efficiency of multiple linear regression (MLR), gene expression programming (GEP), artificial neural network (MLP), artificial neural network based on genetic algorithm (MLP-GA) and artificial neural network based on whale optimization algorithm (MLP-WOA) in predicting of soil wind erodibility in Dasht-e-Tabriz. Among 32 measured soil variable, percentages of fine sand, size classes of 1.7-2.0 and 0.1-0.25 mm (secondary particles) and organic carbon were selected as the model inputs by step-wise regression. Findings showed MLP-WOA as the most powerful artificial intelligence techniques (R2=0.87, NSE=0.87, ME=0.11 and RMSE=2.9) to predict soil wind erodibility in the study area; followed by MLP-GA, MLP, GEP and MLR and the difference between these methods were significant according to the MGN test. Based on the above finding MLP-WOA may be used as a promising method to predict soil wind erodibility in the study area.

Keywords: wind erosion, erodible fraction, gene expression programming, artificial neural network

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Authors: Ashneel Ajay Singh, Naoki Suzuki, Kazumi Sakuramoto,

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The North Pacific albacore (Thunnus alalunga) is a temperate tuna species distributed in the North Pacific which is of significant economic importance to the Pacific Island Nations and Territories. Despite its importance, the stock dynamics and ecological characteristics of albacore still, have gaps in knowledge. The stock-recruitment relationship of the North Pacific stock of albacore tuna was investigated for different density-dependent effects and a regime shift in the stock characteristics in response to changes in environmental and climatic conditions. Linear regression analysis for recruit per spawning biomass (RPS) and recruitment (R) against the female spawning stock biomass (SSB) were significant for the presence of different density-dependent effects and positive for a regime shift in the stock time series. Application of Deming regression to RPS against SSB with the assumption for the presence of observation and process errors in both the dependent and independent variables confirmed the results of simple regression. However, R against SSB results disagreed given variance level of < 3 and agreed with linear regression results given the assumption of variance ≥ 3. Assuming the presence of different density-dependent effects in the albacore tuna time series, environmental and climatic condition variables were compared with R, RPS, and SSB. The significant relationship of R, RPS and SSB were determined with the sea surface temperature (SST), Pacific Decadal Oscillation (PDO) and multivariate El Niño Southern Oscillation (ENSO) with SST being the principal variable exhibiting significantly similar trend with R and RPS. Recruitment is significantly influenced by the dynamics of the SSB as well as environmental conditions which demonstrates that the stock-recruitment relationship is multidimensional. Further investigation of the North Pacific albacore tuna age-class and structure is necessary for further support the results presented here. It is important for fishery managers and decision makers to be vigilant of regime shifts in environmental conditions relating to albacore tuna as it may possibly cause regime shifts in the albacore R and RPS which should be taken into account to effectively and sustainability formulate harvesting plans and management of the species in the North Pacific oceanic region.

Keywords: Albacore tuna, Thunnus alalunga, recruitment, spawning stock biomass, recruits per spawning biomass, sea surface temperature, pacific decadal oscillation, El Niño southern oscillation, density-dependent effects, regime shift

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Authors: Marco Sewald

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Comparing present to past the numbers of Americans expatriating U. S. citizenship have risen. Even though these numbers are small compared to the immigrants, U. S. citizens expatriations have historically been much lower, making the uptick worrisome. In addition, the published lists and numbers from the U.S. government seems incomplete, with many not counted. Different branches of the U. S. government report different numbers and no one seems to know exactly how big the real number is, even though the IRS and the FBI both track and/or publish numbers of Americans who renounce. Since there is no single explanation, anecdotal evidence suggests this uptick is caused by global tax law and increased compliance burdens imposed by the U.S. lawmakers on U.S. citizens abroad. Within a research project the question arose about the reasons why a constant growing number of U.S. citizens are expatriating – the answers are believed helping to explain the underlying governmental policy rational, leading to such activities. While it is impossible to locate former U.S. citizens to conduct a survey on the reasons and the U.S. government is not commenting on the reasons given within the process of expatriation, the chosen methodology is Structural Equation Modeling (SEM), in the first step by re-using current surveys conducted by different researchers within the population of U. S. citizens residing abroad during the last years. Surveys questioning the personal situation in the context of tax, compliance, citizenship and likelihood to repatriate to the U. S. In general SEM allows: (1) Representing, estimating and validating a theoretical model with linear (unidirectional or not) relationships. (2) Modeling causal relationships between multiple predictors (exogenous) and multiple dependent variables (endogenous). (3) Including unobservable latent variables. (4) Modeling measurement error: the degree to which observable variables describe latent variables. Moreover SEM seems very appealing since the results can be represented either by matrix equations or graphically. Results: the observed variables (items) of the construct are caused by various latent variables. The given surveys delivered a high correlation and it is therefore impossible to identify the distinct effect of each indicator on the latent variable – which was one desired result. Since every SEM comprises two parts: (1) measurement model (outer model) and (2) structural model (inner model), it seems necessary to extend the given data by conducting additional research and surveys to validate the outer model to gain the desired results.

Keywords: expatriation of U. S. citizens, SEM, structural equation modeling, validating

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Authors: Ran Goldblatt, Nicholas Jones, Jennifer Mannix, Brad Bottoms

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Accurate, complete, and up-to-date geospatial information is the foundation of successful disaster management. When the 2010 Haiti Earthquake struck, accurate and timely information on the distribution of critical infrastructure was essential for the disaster response community for effective search and rescue operations. Existing geospatial datasets such as Google Maps did not have comprehensive coverage of these features. In the days following the earthquake, many organizations released high-resolution satellite imagery, catalyzing a worldwide effort to map Haiti and support the recovery operations. Of these organizations, OpenStreetMap (OSM), a collaborative project to create a free editable map of the world, used the imagery to support volunteers to digitize roads, buildings, and other features, creating the most detailed map of Haiti in existence in just a few weeks. However, large portions of the island are still not fully covered by OSM. There is an increasing need for a tool to automatically identify which areas in Haiti, as well as in other countries vulnerable to disasters, that are not fully mapped. The objective of this project is to leverage different types of remote sensing measurements, together with machine learning approaches, in order to identify geographical areas where OSM coverage of building footprints is incomplete. Several remote sensing measures and derived products were assessed as potential predictors of OSM building footprints coverage, including: intensity of light emitted at night (based on VIIRS measurements), spectral indices derived from Sentinel-2 satellite (normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), soil-adjusted vegetation index (SAVI), urban index (UI)), surface texture (based on Sentinel-1 SAR measurements)), elevation and slope. Additional remote sensing derived products, such as Hansen Global Forest Change, DLR`s Global Urban Footprint (GUF), and World Settlement Footprint (WSF), were also evaluated as predictors, as well as OSM street and road network (including junctions). Using a supervised classification with a random forest classifier resulted in the prediction of 89% of the variation of OSM building footprint area in a given cell. These predictions allowed for the identification of cells that are predicted to be covered but are actually not mapped yet. With these results, this methodology could be adapted to any location to assist with preparing for future disastrous events and assure that essential geospatial information is available to support the response and recovery efforts during and following major disasters.

Keywords: disaster management, Haiti, machine learning, OpenStreetMap, remote sensing

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Authors: Georgi Y. Georgiev, Matthew Brouillet

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This research applies the power of agent-based modeling to a pivotal question at the intersection of biology, computer science, physics, and complex systems theory about the self-organization processes in open, complex, non-equilibrium thermodynamic systems. Central to this investigation is the principle of Maximum Entropy Production (MEP). This principle suggests that such systems evolve toward states that optimize entropy production, leading to the formation of structured environments. It is hypothesized that guided by the least action principle, open thermodynamic systems identify and follow the shortest paths to transmit energy and matter, resulting in maximal entropy production, internal structure formation, and a decrease in internal entropy. Concurrently, it is predicted that there will be an increase in system information as more information is required to describe the developing structure. To test this, an agent-based model is developed simulating an ant colony's formation of a path between a food source and its nest. Utilizing the Netlogo software for modeling and Python for data analysis and visualization, self-organization is quantified by calculating the decrease in system entropy based on the potential states and distribution of the ants within the simulated environment. External entropy production is also evaluated for information increase and efficiency improvements in the system's action. Simulations demonstrated that the system begins at maximal entropy, which decreases as the ants form paths over time. A range of system behaviors contingent upon the number of ants are observed. Notably, no path formation occurred with fewer than five ants, whereas clear paths were established by 200 ants, and saturation of path formation and entropy state was reached at populations exceeding 1000 ants. This analytical approach identified the inflection point marking the transition from disorder to order and computed the slope at this point. Combined with extrapolation to the final path entropy, these parameters yield important insights into the eventual entropy state of the system and the timeframe for its establishment, enabling the estimation of the self-organization rate. This study provides a novel perspective on the exploration of self-organization in thermodynamic systems, establishing a correlation between internal entropy decrease rate and external entropy production rate. Moreover, it presents a flexible framework for assessing the impact of external factors like changes in world size, path obstacles, and friction. Overall, this research offers a robust, replicable model for studying self-organization processes in any open thermodynamic system. As such, it provides a foundation for further in-depth exploration of the complex behaviors of these systems and contributes to the development of more efficient self-organizing systems across various scientific fields.

Keywords: complexity, self-organization, agent based modelling, efficiency

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Authors: Naeem Ullah, Menglan Duan, Mac Darlington Uche Onuoha

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The lowering of subsea equipment into the deep waters is a challenging job due to the harsh offshore environment. Many researchers have introduced various installation systems to deploy the payload safely into the deep oceans. In general practice, dual floating vessels are not employed owing to the prevalent safety risks and hazards caused by ever-increasing dynamical effects sourced by mutual interaction between the bodies. However, while keeping in the view of the optimal grounds, such as economical one, the Y-method, the two conventional tugboats supporting the equipment by the two independent strands connected to a tri-plate above the equipment, has been employed to study multibody dynamics of the dual barge lifting operations. In this study, the two tugboats and the suspended payload (Y-method) are deployed for the lowering of subsea equipment into the deep waters as a multibody dynamic system. The two-wire ropes are used for the lifting and installation operation by this Y-method installation system. 6-dof (degree of freedom) for each body are considered to establish coupled 18-dof multibody model by embedding technique or velocity transformation technique. The fundamental and prompt advantage of this technique is that the constraint forces can be eliminated directly, and no extra computational effort is required for the elimination of the constraint forces. The inertial frame of reference is taken at the surface of the water as the time-independent frame of reference, and the floating frames of reference are introduced in each body as the time-dependent frames of reference in order to formulate the velocity transformation matrix. The local transformation of the generalized coordinates to the inertial frame of reference is executed by applying the Euler Angle approach. The spherical joints are articulated amongst the multibody as the kinematic joints. The hydrodynamic force, the two-strand forces, the hydrostatic force, and the mooring forces are taken into consideration as the external forces. The radiation force of the hydrodynamic force is obtained by employing the Cummins equation. The wave exciting part of the hydrodynamic force is obtained by using force response amplitude operators (RAOs) that are obtained by the commercial solver ‘OpenFOAM’. The strand force is obtained by considering the wire rope as an elastic spring. The nonlinear hydrostatic force is obtained by the pressure integration technique at each time step of the wave movement. The mooring forces are evaluated by using Faltinsen analytical approach. ‘The Runge Kutta Method’ of Fourth-Order is employed to evaluate the coupled equations of motion obtained for 18-dof multibody model. The results are correlated with the simulated Orcaflex Model. Moreover, the results from Orcaflex Model are compared with the MOSES Model from previous studies. The MBDS of single barge lifting operation from the former studies are compared with the MBDS of the established dual barge lifting operation. The dynamics of the dual barge lifting operation are found larger in magnitude as compared to the single barge lifting operation. It is noticed that the traction at the top connection point of the cable decreases with the increase in the length, and it becomes almost constant after passing through the splash zone.

Keywords: dual barge lifting operation, Y-method, multibody dynamics, shipbuilding, installation of subsea equipment, shipbuilding

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Authors: Francesca Nardi, Kashish Aneja, Katherine Ginsbach

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The COVID-19 pandemic has demonstrated both a need for evidence-based and rights-based public health policy and how challenging it can be to make effective decisions with limited information, evidence, and data. The O’Neill Institute, in conjunction with several partners, has been working since the beginning of the pandemic to collect, analyze, and distribute critical data on public health policies enacted in response to COVID-19 around the world in the COVID-19 Law Lab. Well-designed laws and policies can help build strong health systems, implement necessary measures to combat viral transmission, enforce actions that promote public health and safety for everyone, and on the individual level have a direct impact on health outcomes. Poorly designed laws and policies, on the other hand, can fail to achieve the intended results and/or obstruct the realization of fundamental human rights, further disease spread, or cause unintended collateral harms. When done properly, laws can provide the foundation that brings clarity to complexity, embrace nuance, and identifies gaps of uncertainty. However, laws can also shape the societal factors that make disease possible. Law is inseparable from the rest of society, and COVID-19 has exposed just how much laws and policies intersects all facets of society. In the COVID-19 context, evidence-based and well-informed law and policy decisions—made at the right time and in the right place—can and have meant the difference between life or death for many. Having a solid evidentiary base of legal information can promote the understanding of what works well and where, and it can drive resources and action to where they are needed most. We know that legal mechanisms can enable nations to reduce inequities and prepare for emerging threats, like novel pathogens that result in deadly disease outbreaks or antibiotic resistance. The collection and analysis of data on these legal mechanisms is a critical step towards ensuring that legal interventions and legal landscapes are effectively incorporated into more traditional kinds of health science data analyses. The COVID-19 Law Labs see a unique opportunity to collect and analyze this kind of non-traditional data to inform policy using laws and policies from across the globe and across diseases. This global view is critical to assessing the efficacy of policies in a wide range of cultural, economic, and demographic circumstances. The COVID-19 Law Lab is not just a collection of legal texts relating to COVID-19; it is a dataset of concise and actionable legal information that can be used by health researchers, social scientists, academics, human rights advocates, law and policymakers, government decision-makers, and others for cross-disciplinary quantitative and qualitative analysis to identify best practices from this outbreak, and previous ones, to be better prepared for potential future public health events.

Keywords: public health law, surveillance, policy, legal, data

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Authors: Coriolano Salvini, Ambra Giovannelli

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The use of renewable energy sources for electric power production leads to reduced CO2 emissions and contributes to improving the domestic energy security. On the other hand, the intermittency and unpredictability of their availability poses relevant problems in fulfilling safely and in a cost efficient way the load demand along the time. Significant benefits in terms of “grid system applications”, “end-use applications” and “renewable applications” can be achieved by introducing energy storage systems. Among the currently available solutions, CAES (Compressed Air Energy Storage) shows favorable features. Small-medium size plants equipped with artificial air reservoirs can constitute an interesting option to get efficient and cost-effective distributed energy storage systems. The present paper is addressed to the design and off-design analysis of the compression system of small size CAES plants suited to absorb electric power in the range of hundreds of kilowatt. The system of interest is constituted by an intercooled (in case aftercooled) multi-stage reciprocating compressor and a man-made reservoir obtained by connecting large diameter steel pipe sections. A specific methodology for the system preliminary sizing and off-design modeling has been developed. Since during the charging phase the electric power absorbed along the time has to change according to the peculiar CAES requirements and the pressure ratio increases continuously during the filling of the reservoir, the compressor has to work at variable mass flow rate. In order to ensure an appropriately wide range of operations, particular attention has been paid to the selection of the most suitable compressor capacity control device. Given the capacity regulation margin of the compressor and the actual level of charge of the reservoir, the proposed approach allows the instant-by-instant evaluation of minimum and maximum electric power absorbable from the grid. The developed tool gives useful information to appropriately size the compression system and to manage it in the most effective way. Various cases characterized by different system requirements are analysed. Results are given and widely discussed.

Keywords: artificial air storage reservoir, compressed air energy storage (CAES), compressor design, compression system management.

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Authors: Samuele Ghignoli, Valentina de Lorenzi, Gianmarco Ferri, Stefano Luin, Francesco Cardarelli

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Insulin and glucagon are the two essential hormones for maintaining proper blood glucose homeostasis, which is disrupted in Diabetes. A constantly growing research interest has been focused on the study of the subcellular structures involved in hormone secretion, namely insulin- and glucagon-containing granules, and on the mechanisms regulating their behaviour. Yet, while several successful attempts were reported describing the dynamic properties of insulin granules, little is known about their counterparts in α cells, the glucagon-containing granules. To fill this gap, we used αTC1 clone 9 cells as a model of α cells and ZIGIR as a fluorescent Zinc chelator for granule labelling. We started by using spatiotemporal fluorescence correlation spectroscopy in the form of imaging-derived mean square displacement (iMSD) analysis. This afforded quantitative information on the average dynamical and structural properties of glucagon granules having insulin granules as a benchmark. Interestingly, the iMSD sensitivity to average granule size allowed us to confirm that glucagon granules are smaller than insulin ones (~1.4 folds, further validated by STORM imaging). To investigate possible heterogeneities in granule dynamic properties, we moved from correlation spectroscopy to single particle tracking (SPT). We developed a MATLAB script to localize and track single granules with high spatial resolution. This enabled us to classify the glucagon granules, based on their dynamic properties, as ‘blocked’ (i.e., trajectories corresponding to immobile granules), ‘confined/diffusive’ (i.e., trajectories corresponding to slowly moving granules in a defined region of the cell), or ‘drifted’ (i.e., trajectories corresponding to fast-moving granules). In cell-culturing control conditions, results show this average distribution: 32.9 ± 9.3% blocked, 59.6 ± 9.3% conf/diff, and 7.4 ± 3.2% drifted. This benchmarking provided us with a foundation for investigating selected experimental conditions of interest, such as the glucagon-granule relationship with the cytoskeleton. For instance, if Nocodazole (10 μM) is used for microtubule depolymerization, the percentage of drifted motion collapses to 3.5 ± 1.7% while immobile granules increase to 56.0 ± 10.7% (remaining 40.4 ± 10.2% of conf/diff). This result confirms the clear link between glucagon-granule motion and cytoskeleton structures, a first step towards understanding the intracellular behaviour of this subcellular compartment. The information collected might now serve to support future investigations on glucagon granules in physiology and disease. Acknowledgment: This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 866127, project CAPTUR3D).

Keywords: glucagon granules, single particle tracking, correlation spectroscopy, ZIGIR

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Authors: Jeremy Johnson, Craig Nitschke, Luke Kelly

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Fire regimes, climate and topographic gradients interact to influence ecosystem structure and function across fire-prone, montane landscapes worldwide. Biota have developed a range of adaptations to historic fire regime thresholds, which allow them to persist in these environments. In south-eastern Australia, a signal of fire regime changes is emerging across these landscapes, and anthropogenic climate change is likely to be one of the main drivers of an increase in burnt area and more frequent wildfire over the last 25 years. This shift has the potential to modify vegetation structure and composition at broad scales, which may lead to landscape patterns to which biota are not adapted, increasing the likelihood of local extirpation of some mammal species. This study aimed to address concerns related to the influence of abrupt changes in fire regimes on mammal populations in montane landscapes. It first examined the impact of climate, topography, and vegetation on fire patterns and then explored the consequences of these changes on mammal populations and their habitats. Field studies were undertaken across diverse vegetation, fire severity and fire frequency gradients, utilising camera trapping and passive acoustic monitoring methodologies and the collection of fine-scale vegetation data. Results show that drought is a primary contributor to fire regime shifts at the landscape scale, while topographic factors have a variable influence on wildfire occurrence at finer scales. Frequent, high severity wildfire influenced forest structure and composition at broad spatial scales, and at fine scales, it reduced occurrence of hollow-bearing trees and promoted coarse woody debris. Mammals responded differently to shifts in forest structure and composition depending on their habitat requirements. This study highlights the complex interplay between fire regimes, environmental gradients, and biotic adaptations across temporal and spatial scales. It emphasizes the importance of understanding complex interactions to effectively manage fire-prone ecosystems in the face of climate change.

Keywords: fire, ecology, biodiversity, landscape ecology

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Authors: Joachim F. Sartor

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According to German guidelines, external natural catchments are greater sub-catchments without significant portions of impervious areas, which possess a surface drainage system and empty in a sewer network. Basically, such catchments should be disconnected from sewer networks, particularly from combined systems. If this is not possible due to local conditions, their flow hydrographs have to be considered at the design of sewer systems, because the impact may be significant. Since there is a lack of sufficient measurements of storm-runoff events for such catchments and hence verified simulation methods to analyze their design flows, German standards give only general advices and demands special considerations in such cases. Compared to urban sub-catchments, external natural catchments exhibit greatly different flow characteristics. With increasing area size their hydrological behavior approximates that of rural catchments, e.g. sub-surface flow may prevail and lag times are comparable long. There are few observed peak flow values and simple (mostly empirical) approaches that are offered by literature for Central Europe. Most of them are at least helpful to crosscheck results that are achieved by simulation lacking calibration. Using storm-runoff data from five monitored rural watersheds in the west of Germany with catchment areas between 0.33 and 1.07 km2 , the author investigated by multiple event simulation three different approaches to determine the rainfall excess. These are the modified SCS variable run-off coefficient methods by Lutz and Zaiß as well as the soil moisture model by Ostrowski. Selection criteria for storm events from continuous precipitation data were taken from recommendations of M 165 and the runoff concentration method (parallel cascades of linear reservoirs) from a DWA working report to which the author had contributed. In general, the two run-off coefficient methods showed results that are of sufficient accuracy for most practical purposes. The soil moisture model showed no significant better results, at least not to such a degree that it would justify the additional data collection that its parameter determination requires. Particularly typical convective summer events after long dry periods, that are often decisive for sewer networks (not so much for rivers), showed discrepancies between simulated and measured flow hydrographs.

Keywords: external natural catchments, sewer network design, storm-runoff modelling, urban drainage

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Authors: Matej Komanec, Jan Bohata, Stanislav Zvanovec, Tomas Nemecek, Jan Broucek, Josef Beran

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With the exponential growth of social networks, video streaming and increasing demands on data rates, the number of newly built data centers rises proportionately. The data centers, however, have to adjust to the rapidly increased amount of data that has to be processed. For this purpose, multi-mode (MM) fiber based infrastructures are often employed. It stems from the fact, the connections in data centers are typically realized within a short distance, and the application of MM fibers and components considerably reduces costs. On the other hand, the usage of MM components brings specific requirements for installation service conditions. Moreover, it has to be taken into account that MM fiber components have a higher production tolerance for parameters like core and cladding diameters, eccentricity, etc. Due to the high demands for the reliability of data center components, the determination of properly excited optical field inside the MM fiber core belongs to the key parameters while designing such an MM optical system architecture. Appropriately excited mode field of the MM fiber provides optimal power budget in connections, leads to the decrease of insertion losses (IL) and achieves effective modal bandwidth (EMB). The main parameter, in this case, is the encircled flux (EF), which should be properly defined for variable optical sources and consequent different mode-field distribution. In this paper, we present detailed investigation and measurements of the mode field distribution for short MM links purposed in particular for data centers with the emphasis on reliability and safety. These measurements are essential for large MM network design. The various scenarios, containing different fibers and connectors, were tested in terms of IL and mode-field distribution to reveal potential challenges. Furthermore, we focused on estimation of particular defects and errors, which can realistically occur like eccentricity, connector shifting or dust, were simulated and measured, and their dependence to EF statistics and functionality of data center infrastructure was evaluated. The experimental tests were performed at two wavelengths, commonly used in MM networks, of 850 nm and 1310 nm to verify EF statistics. Finally, we provide recommendations for data center systems and networks, using OM3 and OM4 MM fiber connections.

Keywords: optical fiber, multi-mode, data centers, encircled flux

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Authors: John-Nelson Ekumah, Selorm Yao-Say Solomon Adade, Mingming Zhong, Yufan Sun, Qiufang Liang, Muhammad Safiullah Virk, Xorlali Nunekpeku, Nana Adwoa Nkuma Johnson, Bridget Ama Kwadzokpui, Xiaofeng Ren

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Enhancing starch gel strength and stability is crucial. However, traditional gel property assessment methods are destructive, time-consuming, and resource-intensive. Thus, understanding ethanol treatment effects on kudzu starch gel strength and developing a rapid, nondestructive gel strength assessment method is essential for optimizing the treatment process and ensuring product quality consistency. This study investigated the effects of different ethanol concentrations on the microstructure of kudzu starch gels using a comprehensive microstructural analysis. We also developed a nondestructive method for predicting gel strength and classifying treatment levels using near-infrared (NIR) spectroscopy, and advanced data analytics. Scanning electron microscopy revealed progressive network densification and pore collapse with increasing ethanol concentration, correlating with enhanced mechanical properties. NIR spectroscopy, combined with various variable selection methods (CARS, GA, and UVE) and modeling algorithms (PLS, SVM, and ELM), was employed to develop predictive models for gel strength. The UVE-SVM model demonstrated exceptional performance, with the highest R² values (Rc = 0.9786, Rp = 0.9688) and lowest error rates (RMSEC = 6.1340, RMSEP = 6.0283). Pattern recognition algorithms (PCA, LDA, and KNN) successfully classified gels based on ethanol treatment levels, achieving near-perfect accuracy. This integrated approach provided a multiscale perspective on ethanol-induced starch gel modification, from molecular interactions to macroscopic properties. Our findings demonstrate the potential of NIR spectroscopy, coupled with advanced data analysis, as a powerful tool for rapid, nondestructive quality assessment in starch gel production. This study contributes significantly to the understanding of starch modification processes and opens new avenues for research and industrial applications in food science, pharmaceuticals, and biomaterials.

Keywords: kudzu starch gel, near-infrared spectroscopy, gel strength prediction, support vector machine, pattern recognition algorithms, ethanol treatment

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Authors: Bagireanu Astrid, Bros-Williamson Julio, Duncheva Mila, Currie John

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Digital Twins (DT) are an innovative concept of cyber-physical integration of data between an asset and its virtual replica. They have originated in established industries such as manufacturing and aviation and have garnered increasing attention as a potentially transformative technology within the built environment. With the potential to support decision-making, real-time simulations, forecasting abilities and managing operations, DT do not fall under a singular scope. This makes defining and leveraging the potential uses of DT a potential missed opportunity. Despite its recognised potential in established industries, literature on DT in the built environment remains limited. Inadequate attention has been given to the implementation of DT in construction projects, as opposed to its operational stage applications. Additionally, the absence of a standardised definition has resulted in inconsistent interpretations of DT in both industry and academia. There is a need to consolidate research to foster a unified understanding of the DT. Such consolidation is indispensable to ensure that future research is undertaken with a solid foundation. This paper aims to present a comprehensive systematic literature review on the role of DT in the built environment. To accomplish this objective, a review and thematic analysis was conducted, encompassing relevant papers from the last five years. The identified papers are categorised based on their specific areas of focus, and the content of these papers was translated into a through classification of DT. In characterising DT and the associated data processes identified, this systematic literature review has identified 6 DT opportunities specifically relevant to the built environment: Facilitating collaborative procurement methods, Supporting net-zero and decarbonization goals, Supporting Modern Methods of Construction (MMC) and off-site manufacturing (OSM), Providing increased transparency and stakeholders collaboration, Supporting complex decision making (real-time simulations and forecasting abilities) and Seamless integration with Internet of Things (IoT), data analytics and other DT. Finally, a discussion of each area of research is provided. A table of definitions of DT across the reviewed literature is provided, seeking to delineate the current state of DT implementation in the built environment context. Gaps in knowledge are identified, as well as research challenges and opportunities for further advancements in the implementation of DT within the built environment. This paper critically assesses the existing literature to identify the potential of DT applications, aiming to harness the transformative capabilities of data in the built environment. By fostering a unified comprehension of DT, this paper contributes to advancing the effective adoption and utilisation of this technology, accelerating progress towards the realisation of smart cities, decarbonisation, and other envisioned roles for DT in the construction domain.

Keywords: built environment, design, digital twins, literature review

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Authors: Rhoda N. Kayongo

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As behavior analysts in education continue to debate on how higher institutions can continue to benefit from their social and academic related programs, higher education is facing challenges in the area of character development. This is manifested in the percentages of college completion rates, teen pregnancies, drug abuse, sexual abuse, suicide, plagiarism, lack of academic integrity, and violence among their students. Attending college is a perceived opportunity to positively influence the actions and behaviors of the next generation of society; thus colleges and universities have to provide opportunities to develop students’ values and behaviors. Prior studies were mainly conducted in private institutions and more so in developed countries. However, with the complexity of the nature of student body currently due to the changing world, a multidimensional approach combining multiple factors that enhance character development outcomes is needed to suit the changing trends. The main purpose of this study was to identify opportunities in colleges and develop a model for predicting character development outcomes. A survey questionnaire composed of 7 scales including in-classroom interaction, out-of-classroom interaction, school climate, personal lifestyle, home environment, and peer influence as independent variables and character development outcomes as the dependent variable was administered to a total of five hundred and one students of 3rd and 4th year level in selected public colleges and universities in the Philippines and Rwanda. Using structural equation modelling, a predictive model explained 57% of the variance in character development outcomes. Findings from the results of the analysis showed that in-classroom interactions have a substantial direct influence on character development outcomes of the students (r = .75, p < .05). In addition, out-of-classroom interaction, school climate, and home environment contributed to students’ character development outcomes but in an indirect way. The study concluded that in the classroom are many opportunities for teachers to teach, model and integrate character development among their students. Thus, suggestions are made to public colleges and universities to deliberately boost and implement experiences that cultivate character within the classroom. These may contribute tremendously to the students' character development outcomes and hence render effective models of behaviour analysis in higher education.

Keywords: character development, tertiary institutions, predictive model, behavior analysis

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Authors: Mario Perez-Won, Roberto Lemus-Mondaca, Constanza Olivares-Rivera, Fernanda Marin-Monardez

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This research presents the simultaneous application of high hydrostatic pressure (HHP) and osmotic dehydration (DO) as a pretreatment to hot –air drying of jumbo squid (Dosidicus gigas) cubes. The drying time was reduced to 2 hours at 60ºC and 5 hours at 40°C as compared to the jumbo squid samples untreated. This one was due to osmotic pressure under high-pressure treatment where increased salt saturation what caused an increasing water loss. Thus, a more reduced time during convective drying was reached, and so water effective diffusion in drying would play an important role in this research. Different working conditions such as pressure (350-550 MPa), pressure time (5-10 min), salt concentration, NaCl (10 y 15%) and drying temperature (40-60ºC) were optimized according to kinetic parameters of each mathematical model. The models used for drying experimental curves were those corresponding to Weibull, Page and Logarithmic models, however, the latest one was the best fitted to the experimental data. The values for water effective diffusivity varied from 4.82 to 6.59x10-9 m2/s for the 16 curves (DO+HHP) whereas the control samples obtained a value of 1.76 and 5.16×10-9 m2/s, for 40 and 60°C, respectively. On the other hand, quality characteristics such as color, texture, non-enzymatic browning, water holding capacity (WHC) and rehydration capacity (RC) were assessed. The L* (lightness) color parameter increased, however, b * (yellowish) and a* (reddish) parameters decreased for the DO+HHP treated samples, indicating treatment prevents sample browning. The texture parameters such as hardness and elasticity decreased, but chewiness increased with treatment, which resulted in a product with a higher tenderness and less firmness compared to the untreated sample. Finally, WHC and RC values of the most treatments increased owing to a minor damage in tissue cellular compared to untreated samples. Therefore, a knowledge regarding to the drying kinetic as well as quality characteristics of dried jumbo squid samples subjected to a pretreatment of osmotic dehydration under high hydrostatic pressure is extremely important to an industrial level so that the drying process can be successful at different pretreatment conditions and/or variable processes.

Keywords: diffusion coefficient, drying process, high pressure, jumbo squid, modelling, quality aspects

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Authors: Liqin Zhang, Liang Yan

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This paper addresses the speed synchronization control problem for a network-based multi-motor system from the perspective of cluster consensus theory. Each motor is considered as a single agent connected through fixed and undirected network. This paper presents an improved control protocol from three aspects. First, for the purpose of improving both tracking and synchronization performance, this paper presents a distributed leader-following method. The improved control protocol takes the importance of each motor’s speed into consideration, and all motors are divided into different groups according to speed weights. Specifically, by using control parameters optimization, the synchronization error and tracking error can be regulated and decoupled to some extent. The simulation results demonstrate the effectiveness and superiority of the proposed strategy. In practical engineering, the simplified models are unrealistic, such as single-integrator and double-integrator. And previous algorithms require the acceleration information of the leader available to all followers if the leader has a varying velocity, which is also difficult to realize. Therefore, the method focuses on an observer-based variable structure algorithm for consensus tracking, which gets rid of the leader acceleration. The presented scheme optimizes synchronization performance, as well as provides satisfactory robustness. What’s more, the existing algorithms can obtain a stable synchronous system; however, the obtained stable system may encounter some disturbances that may destroy the synchronization. Focus on this challenging technological problem, a state-dependent-switching approach is introduced. In the presence of unmeasured angular speed and unknown failures, this paper investigates a distributed fault-tolerant consensus tracking algorithm for a group non-identical motors. The failures are modeled by nonlinear functions, and the sliding mode observer is designed to estimate the angular speed and nonlinear failures. The convergence and stability of the given multi-motor system are proved. Simulation results have shown that all followers asymptotically converge to a consistent state when one follower fails to follow the virtual leader during a large enough disturbance, which illustrates the good performance of synchronization control accuracy.

Keywords: consensus control, distributed follow, fault-tolerant control, multi-motor system, speed synchronization

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Authors: Ekatereine Abashidze, Nino Nazarashvili, Dali Gaganidze, Oleg Gorgadze, Mariam Aznarashvili, Eter Gvritishvili

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Potato is one of the leading agricultural crops in Georgia. Georgia produces early and late potato varieties in almost all regions. Potato production is equal to 25,000 ha and its average yield is 20-25 t/ha. Among the plant pests that limit potato production and quality, the potato cyst nematodes (Globodera pallida (Stone) Behrens and Globodera rostochiensis (Wollenveber) Behrens) are harmful around the world. PCN is among the most difficult plant pests to control. Cysts protected by a durable wall can survive for over 30 years . Control of PCN (G. pallida and G. rostochiensis) is regulated by Council Directive 2007/33/EE C. There was no legislative regulation of these pests in Georgia before 2016. By Resolution #302 from July 1, 2016, developed within the action plan of the DCFTA (Deep and Comprehensive Free Trade Area) the Government of Georgia established control over potato cyst nematodes. The Agreement about the legal acts approximation to EU legislation concerns the approval of rules of PCN control and research of these pests. Taking into consideration the above mentioned, it is necessary to study PCN (G. pallida and G. rostochiensis) in the potato-growing areas of Georgia. The aim of this research is to conduct survey of potato cyst nematodes (Globodera rostochiensis and G. pallida) in two geographically distinct regions of Georgia - Samtskhe - Javakheti and Svanetii and to identify the species G. Rostochiensis and G. Pallida by the morphological - morphometric and molecular methods. Soil samples were taken in each village, in a zig-zag pattern on the potato fields of the private sector, using the Metlitsky method. Samples were taken also from infested potato plant roots. To extract nematode cysts from soil samples Fanwick can be used according to standard methods by EPPO. Cysts were measured under a stereoscopic microscope (Leica M50). Identification of the nematod species was carried out according to morphological and morphometric characteristics of the cysts and larvae using appropriate protocols EPPO. For molecular identification, a multiplex PCR test was performed by the universal ITS5 and cyst nematodes’ (G. pallida, G. rostochiensis) specific primers. To identify the species of potato cyst nematodes (PCN) in two regions (Samtskhe-Javakheti and Svaneti) were taken 200 samples, among them: 80 samples in Samtskhe-Javakheti region and 120 in Svaneti region. Cysts of Globiodera spp. were revealed in 50 samples obtained from Samtskhe-Javakheti and 80 samples from Svaneti regions. Morphological, morphometric and molecular analysis of two forms of PCN found in investigated regions of Georgia shows that one form of PCN belongs to G. rostoshiensi; the second form is the different species of Globodera sp.t is the subject of future research. Despite the different geographic locations, larvae and cysts of G. rostoshiensi were found in both regions. But cysts and larvae of G. pallida were not reported. Acknowledgement: The research has been supported by the Shota Rustaveli National Scientific Foundation of Georgia: Project # FR17_235.

Keywords: cyst nematode, globodera rostochiensis, globodera pallida, morphologic-morphometric measurement

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Authors: Idit Kalisher, Israel Luski

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One result of the growing dynamicity of labor markets in recent decades is a wider scope of employment mobility – i.e., transitions between employers, either within or between careers. Employment mobility decisions are primarily affected by the current employment status of the worker, which is reflected in wage and tenure. Using 34,328 observations from the National Longitudinal Survey of Youth 1979 (NLS79), which were derived from the USA population between 1990 and 2012, this paper aims to investigate the effects of wage and tenure over employment mobility choices, and additionally to examine the effects of other personal characteristics, individual labor market characteristics and macroeconomic factors. The estimation strategy was designed to address two challenges that arise from the combination of the model and the data: (a) endogeneity of the wage and the tenure in the choice equation; and (b) unobserved heterogeneity, as the data of this research is longitudinal. To address (a), estimation was performed using two-stage limited dependent variable procedure (2SLDV); and to address (b), the second stage was estimated using femlogit – an implementation of the multinomial logit model with fixed effects. Among workers who have experienced at least one turnover, the wage was found to have a main effect on career turnover likelihood of all workers, whereas the wage effect on job turnover likelihood was found to be dependent on individual characteristics. The wage was found to negatively affect the turnover likelihood and the effect was found to vary across wage level: high-wage workers were more affected compared to low-wage workers. Tenure was found to have a main positive effect on both turnover types’ likelihoods, though the effect was moderated by the wage. The findings also reveal that as their wage increases, women are more likely to turnover than men, and academically educated workers are more likely to turnover within careers. Minorities were found to be as likely as Caucasians to turnover post wage-increase, but less likely to turnover with each additional tenure year. The wage and the tenure effects were found to vary also between careers. The difference in attitude towards money, labor market opportunities and risk aversion could explain these findings. Additionally, the likelihood of a turnover was found to be affected by previous unemployment spells, age, and other labor market and personal characteristics. The results of this research could assist policymakers as well as business owners and employers. The former may be able to encourage women and older workers’ employment by considering the effects of gender and age on the probability of a turnover, and the latter may be able to assess their employees’ likelihood of a turnover by considering the effects of their personal characteristics.

Keywords: employment mobility, endogeneity, femlogit, turnover

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Mikhail V. Khachaturyan, Inga A. Koryagina, Eugenia V. Klicheva

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In modern conditions, scientific judgment of problems in developing mechanisms of value creation and risk management acquires special relevance. Formation of economic knowledge has resulted in the constant analysis of consumer behavior for all players from national and world markets. Effective mechanisms development of the demand analysis, crucial for consumer's characteristics of future production, and the risks connected with the development of this production are the main objectives of control systems in modern conditions. The modern period of economic development is characterized by a high level of globalization of business and rigidity of competition. At the same time, the considerable share of new products and services costs has a non-material intellectual nature. The most successful in Russia is the contemporary development of small innovative firms. Such firms, through their unique technologies and new approaches to process management, which form the basis of their intellectual capital, can show flexibility and succeed in the market. As a rule, such enterprises should have very variable structure excluding the tough scheme of submission and demanding essentially new incentives for inclusion of personnel in innovative activity. Realization of similar structures, as well as a new approach to management, can be constructed based on value-oriented management which is directed to gradual change of consciousness of personnel and formation from groups of adherents included in the solution of the general innovative tasks. At the same time, valuable changes can gradually capture not only innovative firm staff, but also the structure of its corporate partners. Introduction of new technologies is the significant factor contributing to the development of new valuable imperatives and acceleration of the changing values systems of the organization. It relates to the fact that new technologies change the internal environment of the organization in a way that the old system of values becomes inefficient in new conditions. Introduction of new technologies often demands change in the structure of employee’s interaction and training in their new principles of work. During the introduction of new technologies and the accompanying change in the value system, the structure of the management of the values of the organization is changing. This is due to the need to attract more staff to justify and consolidate the new value system and bring their view into the motivational potential of the new value system of the organization.

Keywords: value, risk, creation, problems, organization

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Authors: Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho

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In semiconductor manufacturing, virtual metrology (VM) refers to methods to predict properties of a wafer based on machine parameters and sensor data of the production equipment, without performing the (costly) physical measurement of the wafer properties (Wikipedia). Additional benefits include avoidance of human bias and identification of important factors affecting the quality of the process which allow improving the process quality in the future. It is however rare to find VM applied to other areas of manufacturing. In this work, we propose to use VM to copper clad laminate (CCL) manufacturing. CCL is a core element of a printed circuit board (PCB) which is used in smartphones, tablets, digital cameras, and laptop computers. The manufacturing of CCL consists of three processes: Treating, lay-up, and pressing. Treating, the most important process among the three, puts resin on glass cloth, heat up in a drying oven, then produces prepreg for lay-up process. In this process, three important quality factors are inspected: Treated weight (T/W), Minimum Viscosity (M/V), and Gel Time (G/T). They are manually inspected, incurring heavy cost in terms of time and money, which makes it a good candidate for VM application. We developed prediction models of the three quality factors T/W, M/V, and G/T, respectively, with process variables, raw material, and environment variables. The actual process data was obtained from a CCL manufacturer. A variety of variable selection methods and learning algorithms were employed to find the best prediction model. We obtained prediction models of M/V and G/T with a high enough accuracy. They also provided us with information on “important” predictor variables, some of which the process engineers had been already aware and the rest of which they had not. They were quite excited to find new insights that the model revealed and set out to do further analysis on them to gain process control implications. T/W did not turn out to be possible to predict with a reasonable accuracy with given factors. The very fact indicates that the factors currently monitored may not affect T/W, thus an effort has to be made to find other factors which are not currently monitored in order to understand the process better and improve the quality of it. In conclusion, VM application to CCL’s treating process was quite successful. The newly built quality prediction model allowed one to reduce the cost associated with actual metrology as well as reveal some insights on the factors affecting the important quality factors and on the level of our less than perfect understanding of the treating process.

Keywords: copper clad laminate, predictive modeling, quality control, virtual metrology

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Authors: Rayanne Branco Dos Santos Lima, Lorena Pinheiro Barbosa, Kamila Ferreira Lima, Victor Manuel Tegoma Ruiz, Monyka Brito Lima Dos Santos, Maria Wendiane Gueiros Gaspar, Luzia Camila Coelho Ferreira, Leandro Cardozo Dos Santos Brito, Deyse Maria Alves Rocha

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Introduction: The lack of regulation of the baby's sleep-wake pattern in the first years of life affects the health of thousands of women. Maternal sleep deprivation can trigger or aggravate psychosomatic problems such as depression, anxiety and stress that can directly influence maternal safety, with consequences for the baby's and mother's sleep. Such conditions can affect the family's quality of life and child development. Objective: To correlate maternal security with maternal state anxiety scores and the mother's and baby's total sleep time. Method: Cross-sectional study carried out with 96 mothers of babies aged 10 to 24 months, accompanied by nursing professionals linked to a Federal University in Northeast Brazil. Study variables were maternal security, maternal state anxiety scores, infant latency and sleep time, and total nocturnal sleep time of mother and infant. Maternal safety was calculated using a four-point Likert scale (1=not at all safe, 2=somewhat safe, 3=very safe, 4=completely safe). Maternal anxiety was measured by State-Trait Anxiety Inventory, state-anxiety subscale whose scores vary from 20 to 80 points, and the higher the score, the higher the anxiety levels. Scores below 33 are considered mild; from 33 to 49, moderate and above 49, high. As for the total nocturnal sleep time, values between 7-9 hours of sleep were considered adequate for mothers, and values between 9-12 hours for the baby, according to the guidelines of the National Sleep Foundation. For the sleep latency time, a time equal to or less than 20 min was considered adequate. It is noteworthy that the latency time and the time of night sleep of the mother and the baby were obtained by the mother's subjective report. To correlate the data, Spearman's correlation was used in the statistical package R version 3.6.3. Results: 96 women and babies participated, aged 22 to 38 years (mean 30.8) and 10 to 24 months (mean 14.7), respectively. The average of maternal security was 2.89 (unsafe); Mean maternal state anxiety scores were 43.75 (moderate anxiety). The babies' average sleep latency time was 39.6 min (>20 min). The mean sleep times of the mother and baby were, respectively, 6h and 42min and 8h and 19min, both less than the recommended nocturnal sleep time. Maternal security was positively correlated with maternal state anxiety scores (rh=266, p=0.009) and negatively correlated with infant sleep latency (rh= -0.30. P=0.003). Baby sleep time was positively correlated with maternal sleep time. (rh 0.46, p<0.001). Conclusion: The more secure the mothers considered themselves, the higher the anxiety scores and the shorter the baby's sleep latency. Also, the longer the baby sleeps, the longer the mother sleeps. Thus, interventions are needed to promote the quality and efficiency of sleep for both mother and baby.

Keywords: sleep, anxiety, infant, mother-child relations

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Authors: Soumi Banerjee

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In this research paper we will go deep into understanding Benedict Anderson’s definition of the nation as an imagined community and we will analyze why and how national identities were created through long and complex processes, and how there can exist strong emotional bonds between people within an imagined community, given the fact that these people have never known each other personally, but will still feel some form of imagined unity. Such identity construction on the part of an individual or within societies are always in some sense in a state of flux as imagined communities are ever changing, which provides us with the ontological foundation for reaching on this paper. This sort of identity crisis among individuals living in the Western world, who are in search for psychological comfort and security, illustrates a possible need for spatially dislocated, ontologically insecure and vulnerable individuals to have a secure identity. To create such an identity there has to be something to build upon, which could be achieved through what may be termed as ‘homesteading’. This could in short, and in my interpretation of Kinnvall and Nesbitt’s concept, be described as a search for security that involves a search for ‘home’, where home acts as a secure place, which one can build an identity around. The next half of the paper will then look into how populism and identity have played an increasingly important role in the political elections in the so-called western democracies of the world, using the U.S. as an example. Notions of ‘us and them’, the people and the elites will be looked into and analyzed through a social constructivist theoretical lens. Here we will analyze how such narratives about identity and the nation state affects people, their personality development and identity in different ways by studying the U.S. President Donald Trump’s speeches and analyze if and how he used different identity creating narratives for gaining political and popular support. The reason to choose narrative analysis as a method in this research paper is to use the narratives as a device to understand how the perceived notions of 'us and them' can initiate huge identity crisis with a community or a nation-state. This is a relevant subject as results and developments such as rising populist rightwing movements are being felt in a number of European states, with the so-called Brexit vote in the U.K. and the election of Donald Trump as president are two of the prime examples. This paper will then attempt to argue that these mechanisms are strengthened and gaining significance in situations when humans in an economic, social or ontologically vulnerable position, imagined or otherwise, in a general and broad meaning perceive themselves to be under pressure, and a sense of insecurity is rising. These insecurities and sense of being under threat have been on the rise in many of the Western states that are otherwise usually perceived to be some of the safest, democratically stable and prosperous states in the world, which makes it of interest to study what has changed, and help provide some part of the explanation as to how creating a ‘them’ in the discourse of national identity can cause massive security crisis.

Keywords: identity crisis, migration, ontological security(in), nation-states

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Authors: Janaina Pereira, Barbara Gonzalez, Valentina Chitas, Teresa Molina

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Intro: The positive impact of opioid maintenance programs on the health of heroin addicts, and on public health in general, has been widely recognized, namely on the prevalence reduction of infectious diseases as HIV, and on the social reintegration of this population. Nevertheless, a part of patients in these programs cannot remain heroin abstinent, or has relapses, during the treatment. Method: Thus, this cross-sectional research aims at analyzing the relation between a set of psychological and psychosocial variables, which have been associated with the onset of heroin use, and assess if they are also associated with absence of abstinence in participants in an opioid maintenance program. A total of 62 patients, aged between 26 and 58 years old (M= 40.87, DP= 7.39) with a time in opioid maintenance program between 1 and 10 years (M= 5.42, DP= 3.05), 77.4% male and 22.6% female, participated in this research. To assess the criterion variable (heroin use) we used the mean value of positive results in urine tests during the participation in the program, weighted according to the number of months in program. The predictor variables were the coping strategies, the dispositional sensation seeking, and the existence of Posttraumatic stress disorder (PTSD). Results: The results showed that only 33.87% of the patients were totally abstinent of heroin use since the beginning of the program, and the absence of abstinence, as the number of positive heroin tests, was primarily predicted by less proactive coping, and secondarily by a higher level of sensation seeking. 16.13% of the sample fulfilled diagnosis criteria for PTSD, and 67.74 % had at least one traumatic experience throughout their lives. The total of PTSD symptoms had a positive correlation with the number of physical health problems, and with the lack of professional occupation. These results have several implications for the clinical practice in this field, and we suggest the promotion of proactive coping strategies should integrate these opioid maintenance programs, as they represent the tendency to face future events as challenges and opportunities, being positively related to positive results on several fields. The early identification of PTSD in the participants, before entering the opioid maintenance programs, would be important as it is related to negative features that hinder social reintegration, Finally, to identify individuals with a sensation seeking profile would be relevant, not only because they face a higher risk of relapse, but also because the therapeutical approaches should not ignore this dispositional feature in the alternatives they propose to the patients.

Keywords: opioid maintenance programs, proactive coping, PTSD, sensation seeking

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Authors: Mohiuddin Ahsanul Kabir Chowdhury, Ahmed Ehsanur Rahman, Nazia Binte Ali, Abdullah Nurus Salam Khan, Afrin Iqbal, Mohammad Mehedi Hasan, Salma Morium, Afsana Bhuiyan, Shams El Arifeen

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Violence against women has been treated as a global epidemic which is as fatal as any serious disease or accidents. Like many other low-income countries it is also common in Bangladesh. In spite of existence of a few documented evidences in some other countries, in Bangladesh, domestic violence against women (DVAW) is not considered as a factor for malnutrition in children yet. Hence, the aim of the study was to investigate the association between DVAW and the nutritional status of their under-5 children in the context of slum areas of Chittagong, Bangladesh. A Cross-sectional survey was conducted among 87 women of reproductive age having at least one child under-5 years of age and staying with husband for at least last 1 year in selected slums under Chittagong City Corporation area. Data collection tools were structured questionnaire for the study participants and mid-upper arm circumference (MUAC) to measure the nutritional status of the under-5 children. The data underwent descriptive and regression analysis. Out of 87 respondents, 50 (57.5%) reported to suffer from domestic violence by their husband during last one year. Physical violence was found to be significantly associated with age (p=0.02), age at marriage (p=0.043), wealth score (p=0.000), and with knowledge regarding law (p=0.017). According to the measurement of mid-upper arm circumference (MUAC) 21% children were suffering from severe acute malnutrition (SAM) and the same percentage of children were suffering from moderate acute malnutrition (MAM). However, unadjusted odds ratio suggested that there was negative association with domestic violence and nutritional status. But, the logistic regression confounding for other variable showed significant association with total family income (p=0.006), wealth score (p=0.031), age at marriage (p=0.029) and number of child (p=0.006). Domestic violence against women and under nutrition of the children, both are highly prevalent in Bangladesh. More extensive research should be performed to identify the factors contributing to the high prevalence of domestic violence and malnutrition in urban slums of Bangladesh. Household-based intervention is needed to limit this burning problem. In a nutshell, effective community participation, education and counseling are essential to create awareness among the community.

Keywords: Bangladesh, cross sectional survey, domestic violence against women, nutritional status, under-5 children, urban slums

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Authors: Jacqueline A. G. Sachett, Cláudia S. Nogueira, Diana C. P. Lima, Jessica T. S. Oliveira, Guilherme K. M. Salazar, Lílian K. Aguiar

Abstract:

The Polo Amazon Telehealth offers several tools for professionals working in Primary Health Care as a second formative opinion, teleconsulting and training between the different areas, whether medicine, dentistry, nursing, physiotherapy, among others. These activities have a monthly schedule of free access to the municipalities of Amazonas registered. With this premise, and in partnership with the University of the State of Amazonas (UEA), is promoting the practice of the triad; teaching-research-extension in order to collaborate with the enrichment and acquisition of knowledge through educational practices carried out through teleconferences. Therefore, nursing is to join efforts and inserts as a collaborator of this project running, contributing to the education and training of these professionals who are part of the health system in full Amazon. The aim of this study is to report the experience of academic of Amazonas State University nursing course, about the experience in the extension project underway in Polo Telemedicine Amazon. This was a descriptive study, the experience report type, about the experience of nursing academic UEA, by extension 'Telenursing: teleconsulting and second formative opinion for FHS professionals in the state of Amazonas' project, held in Polo Telemedicine Amazon, through an agreement with the UEA and funded by the Foundation of Amazonas Research from July / 2012 to July / 2016. Initially developed active search of members of the Family Health Strategy professionals, in order to provide training and training teams to use the virtual clinic, as well as the virtual environment is the focus of this tool design. The election period was an aggravating factor for the implementation of teleconsulting proposal, due to change of managers in each municipality, requiring the stoppage until they assume their positions. From this definition, we established the need for new training. The first video conference took place on 03.14.2013 for learning and training in the use of Virtual Learning Environment and Virtual Clinic, with the participation of municipalities of Novo Aripuanã, São Paulo de Olivença and Manacapuru. During the whole project was carried out literature about what is being done and produced at the national level about the subject. By the time the telenursing project has received twenty-five (25) consultancy requests. The consultants sent by nursing professionals, all have been answered to date. Faced with the lived experience, particularly in video conferencing, face to cause difficulties issues, such as the fluctuation in the number of participants in activities, difficulty of participants to reconcile the opening hours of the units with the schedule of video conferencing, transmission difficulties and changes schedule. It was concluded that the establishment of connection between the Telehealth points is one of the main factors for the implementation of Telenursing and that this feature is still new for nursing. However, effective training and updating, may provide to these professional category subsidies to quality health care in the Amazon.

Keywords: Amazon, teleconsulting, telehealth, telenursing

Procedia PDF Downloads 306

Authors: Lucksini Raveendran

Abstract:

Introduction: This mixed-methods study focuses on the experiences of ethnocultural youth and families in Canada, identifying key barriers and opportunities to inform service programming and policies that can better meet their mental health needs during the COVID-19 pandemic and beyond. Methods: Mental Health Commission of Canada's Headstrong initiative administered the youth survey (April – June 2020) and family survey (June – August 2020) with a total sample size of 137 and 481 respondents, respectively. Thematic analysis was conducted to identify key challenges faced, coping strategies used, and help-seeking behaviours. A similar approach was also applied to the family survey data, but instead, a representative sample was collated to analyze geographically variable and ethnically diverse subgroups. Results and analysis: Multiple challenges have impacted families, including increased feelings of loneliness and distress from border travel restrictions, especially among those navigating pregnancy alone or managing children with developmental needs, which is often understudied. Also, marginalized groups were disproportionately affected by inequitable access to communication technologies, further deepening the digital divide. Some reported living in congregated homes with regular conflicts, thus leading to increased anxiety and exposure to violence. For many families, urbanicity and ethnicity played a key role in how families reported coping with feelings of uncertainty while managing work commitments, navigating community resources, fulfilling care responsibilities, and homeschooling children of all ages. Despite these challenges, there was evidence of post-traumatic growth and building community resiliency. Conclusions and implications for policy, practice, or additional research: There is a need to foster opportunities to promote and sustain mental health, wellness, and resilience for families through social connections. Also, intersectionality must be embedded in the collection, analysis, and application of data to improve equitable access to evidence-based and recovery-oriented mental health supports among diverse families in Canada. Lastly, address future research on the long-term COVID-19 impacts of travel border restrictions on family wellness.

Keywords: mental health, youth mental health, family wellness, health equity

Procedia PDF Downloads 89