Search results for: Wireless Sensor Network

Authors: Jihye Hwang, Eun Hwa Choi, Su Youn Baek, Bia Park, Gyeongmin Kim, Chorong Shin, Joon Ha Lee, Jae-Sam Hwang, Ui Wook Hwang

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White-spotted flower chafers are widely distributed in Asian countries and traditionally used for the treatment of chronic fatigue, blood circulation, and paralysis in the oriental medicine field. The evolution and development of insect wings and metamorphosis remain under-discovered subjects in arthropod evolutionary researches. Gene expression abundance analyses along with developmental stages based on the large-scale RNA-seq data are also still rarely done. Here we report the de novo assembly of a Protestia brevitarsis seulensis transcriptome along four different developmental stages (egg, larva, pupa, and adult) to explore its development and evolution of wings and metamorphosis. The de novo transcriptome assembly consists of 23,551 high-quality transcripts and is approximately 96.7% complete. Out of 8,545 transcripts, 5,183 correspond to the possible orthologs with Drosophila melanogaster. As a result, we could found 265 genes related to wing development and 19 genes related to metamorphosis. The comparison of transcript expression abundance with different developmental stages revealed developmental stage-specific transcripts especially working at the stage of wing development and metamorphosis of P. b. seulensis. This transcriptome quantification along the developmental stages may provide some meaningful clues to elucidate the genetic modulation mechanism of wing development and metamorphosis obtained during the insect evolution.

Keywords: white-spotted flower chafers, transcriptomics, RNA-seq, network biology, wing development, metamorphosis

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Authors: Praveena Nair Sivasankaran, Thomas Arthur Ward, Rubentheren Viyapuri

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Paper describes a methodology to fabricate a simplified dragonfly wing structure using balsa wood and red prepreg fibre glass. These simplified wing structures were created for use in Biomimetic Micro Air Vehicles (BMAV). Dragonfly wings are highly corrugated and possess complex vein structures. In order to mimic the wings function and retain its properties, a simplified version of the wing was designed. The simplified dragonfly wing structure was created using a method called spatial network analysis which utilizes Canny edge detection method. The vein structure of the wings were carved out in balsa wood and red prepreg fibre glass. Balsa wood and red prepreg fibre glass was chosen due to its ultra- lightweight property and hence, highly suitable to be used in our application. The fabricated structure was then immersed in a nanocomposite solution containing chitosan as a film matrix, reinforced with chitin nanowhiskers and tannic acid as a crosslinking agent. These materials closely mimic the membrane of a dragonfly wing. Finally, the wings were subjected to a bending test and comparisons were made with previous research for verification. The results had a margin of difference of about 3% and thus the structure was validated.

Keywords: dragonfly wings, simplified, Canny edge detection, balsa wood, red prepreg, chitin, chitosan, tannic acid

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Authors: Alvaro Aguinaga, Carlos Avila, Edgar Cando

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This article proposes a n-layer architecture, with a web client as a front-end, for the development of a virtual platform for process simulation on CNC machines. This Open-Source platform includes a CAD-CAM interface drawing primitives, and then used to furnish a CNC program that triggers a touch-screen virtual simulator. The objectives of this project are twofold. First one is an educational component that fosters new alternatives for the CAD-CAM/CNC learning process in undergrad and grade schools and technical and technological institutes emphasizing in the development of critical skills, discussion and collaborative work. The second objective puts together a research and technological component that will take the state of the art in CAD-CAM integration to a new level with the development of optimal algorithms and virtual platforms, on-line availability, that will pave the way for the long-term goal of this project, that is, to have a visible and active graduate school in Ecuador and a world wide Open-Innovation community in the area of CAD-CAM integration and operation of CNC machinery. The virtual platform, developed as a part of this study: (1) delivers improved training process of students, (2) creates a multidisciplinary team and a collaborative work space that will push the new generation of students to face future technological challenges, (3) implements industry standards for CAD/CAM, (4) presents a platform for the development of industrial applications. A protoype of this system was developed and implemented in a network of universities and technological institutes in Ecuador.

Keywords: CAD-CAM integration, virtual platforms, CNC machines, multi-layer based architecture

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Authors: Tayebeh Sahraeibelverdi, Ahmad Shirazi Hadi Veladi, Mazdak Radmalekshah

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Optical sensors became attractive due to preciseness, low power consumption, and intrinsic electromagnetic interference-free characteristic. Among the waveguide optical sensors, cavity-based ones attended for the high Q-factor. Micro ring resonators as a potential platform have been investigated for various applications as biosensors to pressure sensors thanks to their sensitive ring structure responding to any small change in the refractive index. Furthermore, these small micron size structures can come in an array, bringing the opportunity to have any of the resonance in a specific wavelength and be addressed in this way. Another exciting application is applying a strain to the ring and making them an optical strain gauge where the traditional ones are based on the piezoelectric material. Making them in arrays needs electrical wiring and about fifty times bigger in size. Any physical element that impacts the waveguide cross-section, Waveguide elastic-optic property change, or ring circumference can play a role. In comparison, ring size change has a larger effect than others. Here an engineered ring structure is investigated to study the strain effect on the ring resonance wavelength shift and its potential for more sensitive strain devices. At the same time, these devices can measure any strain by mounting on the surface of interest. The idea is to change the" O" shape ring to a "C" shape ring with a small opening starting from 2π/360 or one degree. We used the Mode solution of Lumbrical software to investigate the effect of changing the ring's opening and the shift induced by applied strain. The designed ring radius is a three Micron silicon on isolator ring which can be fabricated by standard complementary metal-oxide-semiconductor (CMOS) micromachining. The measured wavelength shifts from1-degree opening of the ring to a 6-degree opening have been investigated. Opening the ring for 1-degree affects the ring's quality factor from 3000 to 300, showing an order of magnitude Q-factor reduction. Assuming a strain making the ring-opening from 1 degree to 6 degrees, our simulation results showing negligible Q-factor reduction from 300 to 280. A ring resonator quality factor can reach up to 108 where an order of magnitude reduction is negligible. The resonance wavelength shift showed a blue shift and was obtained to be 1581, 1579,1578,1575nm for 1-, 2-, 4- and 6-degree ring-opening, respectively. This design can find the direction of the strain-induced by applying the opening on different parts of the ring. Moreover, by addressing the specified wavelength, we can precisely find the direction. We can open a significant opportunity to find cracks and any surface mechanical property very specifically and precisely. This idea can be implemented on polymer ring resonators while they can come with a flexible substrate and can be very sensitive to any strain making the two ends of the ring in the slit part come closer or further.

Keywords: optical ring resonator, strain gauge, strain sensor, surface mechanical property analysis

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Authors: Mariia Zhuldybina, Ahmed Moulay, Mirko Torres, Mike Rozel, Ngoc-Duc Trinh, Chloé Bois

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To reduce the global waste of perishable goods, a solution for monitoring and traceability of their environmental conditions is needed. Temperature is the most controllable environmental parameter determining the kinetics of physical, chemical, and microbial spoilage in food products. To store the time-temperature information, time-temperature indicator (TTI) is a promising solution. Printed electronics (PE) has shown a great potential to produce customized electronic devices using flexible substrates and inks with different functionalities. We propose to fabricate a hybrid printed TTI using environmentally friendly materials. The real-time TTI profile can be stored and transmitted to the smartphone via Near Field Communication (NFC). To ensure environmental performance, Canadian Green Electronics NSERC Network is developing green materials for the ink formulation with different functionalities. In terms of substrate, paper-based electronics has gained the great interest for utilization in a wide area of electronic systems because of their low costs in setup and methodology, as well as their eco-friendly fabrication technologies. The main objective is to deliver a prototype of TTI using small-scale printed techniques under typical printing conditions. All sub-components of the smart labels, including a memristor, a battery, an antenna compatible with NFC protocol, and a circuit compatible with integration performed by an offsite supplier will be fully printed with flexography or flat-bed screen printing.

Keywords: NFC, printed electronics, time-temperature indicator, hybrid electronics

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Authors: Helen Pushkarskaya, David Tolin, Lital Ruderman, Ariel Kirshenbaum, J. MacLaren Kelly, Christopher Pittenger, Ifat Levy

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Obsessive-Compulsive Disorder (OCD) produces profound morbidity. Difficulties with decision making and intolerance of uncertainty are prominent clinical features of OCD. The nature and etiology of these deficits are poorly understood. We used a well-validated choice task, grounded in behavioral economic theory, to investigate differences in valuation and value-based choice during decision making under uncertainty in 20 unmedicated participants with OCD and 20 matched healthy controls. Participants’ choices were used to assess individual decision-making characteristics. Compared to controls, individuals with OCD were less consistent in their choices and less able to identify options that were unambiguously preferable. These differences correlated with symptom severity. OCD participants did not differ from controls in how they valued uncertain options when outcome probabilities were known (risk) but were more likely than controls to avoid uncertain options when these probabilities were imprecisely specified (ambiguity). These results suggest that the underlying neural mechanisms of valuation and value-based choices during decision-making are abnormal in OCD. Individuals with OCD show elevated intolerance of uncertainty, but only when outcome probabilities are themselves uncertain. Future research focused on the neural valuation network, which is implicated in value-based computations, may provide new neurocognitive insights into the pathophysiology of OCD. Deficits in decision-making processes may represent a target for therapeutic intervention.

Keywords: obsessive compulsive disorder, decision-making, uncertainty intolerance, risk aversion, ambiguity aversion, valuation

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Authors: M. Bortolini, E. Ferrari, F. G. Galizia, C. Mora

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In the last decades, an increasing set of companies adopted lean philosophy to improve their productivity and efficiency promoting the so-called continuous improvement concept, reducing waste of time and cutting off no-value added activities. In parallel, increasing attention rises toward green practice and management through the spread of the green supply chain pattern, to minimise landfilled waste, drained wastewater and pollutant emissions. Starting from a review on contributions deepening lean and green principles applied to supply chain management, the most relevant drivers to measure the performance of industrial processes are pointed out. Specific attention is paid on the role of cost because it is of key importance and it crosses both lean and green principles. This analysis leads to figure out an original reference framework for integrating lean and green principles in designing and managing supply chains. The proposed framework supports the application, to the whole value chain or to parts of it, e.g. distribution network, assembly system, job-shop, storage system etc., of the lean-green integrated perspective. Evidences show that the combination of the lean and green practices lead to great results, higher than the sum of the performances from their separate application. Lean thinking has beneficial effects on green practices and, at the same time, methods allowing environmental savings generate positive effects on time reduction and process quality increase.

Keywords: environmental sustainability, green supply chain, integrated framework, lean thinking, supply chain management

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Authors: Melina Kopke, Jelle Van Dijk

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Persons with cognitive disabilities, such as Autism Spectrum Disorder (ASD) are often dependent on some form of professional support. Recent transformations in Dutch healthcare have spurred institutions to apply new, empowering methods and tools to enable their clients to cope (more) independently in daily life. Assistive Technologies (ATs) seem promising as empowering tools. While ATs can, functionally speaking, help people to perform certain activities without human assistance, we hold that, from a design-theoretical perspective, such technologies often fail to empower in a deeper sense. Most technologies serve either to prescribe or to monitor users’ actions, which in some sense objectifies them, rather than strengthening their agency. This paper proposes that theories of embodied interaction could help formulating a design vision in which interactive assistive devices augment, rather than replace, human agency and thereby add to a persons’ empowerment in daily life settings. It aims to close the gap between empowerment theory and the opportunities provided by assistive technologies, by showing how embodiment and empowerment theory can be applied in practice in the design of new, interactive assistive devices. Taking a Research-through-Design approach, we conducted a case study of designing to support independently living people with ASD with structuring daily activities. In three iterations we interlaced design action, active involvement and prototype evaluations with future end-users and healthcare professionals, and theoretical reflection. Our co-design sessions revealed the issue of handling daily activities being multidimensional. Not having the ability to self-manage one’s daily life has immense consequences on one’s self-image, and also has major effects on the relationship with professional caregivers. Over the course of the project relevant theoretical principles of both embodiment and empowerment theory together with user-insights, informed our design decisions. This resulted in a system of wireless light units that users can program as a reminder for tasks, but also to record and reflect on their actions. The iterative process helped to gradually refine and reframe our growing understanding of what it concretely means for a technology to empower a person in daily life. Drawing on the case study insights we propose a set of concrete design principles that together form what we call the embodied empowerment design framework. The framework includes four main principles: Enabling ‘reflection-in-action’; making information ‘publicly available’ in order to enable co-reflection and social coupling; enabling the implementation of shared reflections into an ‘endurable-external feedback loop’ embedded in the persons familiar ’lifeworld’; and nudging situated actions with self-created action-affordances. In essence, the framework aims for the self-development of a suitable routine, or ‘situated practice’, by building on a growing shared insight of what works for the person. The framework, we propose, may serve as a starting point for AT designers to create truly empowering interactive products. In a set of follow-up projects involving the participation of persons with ASD, Intellectual Disabilities, Dementia and Acquired Brain Injury, the framework will be applied, evaluated and further refined.

Keywords: assistive technology, design, embodiment, empowerment

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Authors: Pitigalage Chamath Chandira Peiris

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A widely researched domain in the field of image processing in recent times has been single image super-resolution, which tries to restore a high-resolution image from a single low-resolution image. Many more single image super-resolution efforts have been completed utilizing equally traditional and deep learning methodologies, as well as a variety of other methodologies. Deep learning-based super-resolution methods, in particular, have received significant interest. As of now, the most advanced image restoration approaches are based on convolutional neural networks; nevertheless, only a few efforts have been performed using Transformers, which have demonstrated excellent performance on high-level vision tasks. The effectiveness of CNN-based algorithms in image super-resolution has been impressive. However, these methods cannot completely capture the non-local features of the data. Enhancer is a simple yet powerful Transformer-based approach for enhancing the resolution of images. A method for single image super-resolution was developed in this study, which utilized an efficient and effective transformer design. This proposed architecture makes use of a locally enhanced window transformer block to alleviate the enormous computational load associated with non-overlapping window-based self-attention. Additionally, it incorporates depth-wise convolution in the feed-forward network to enhance its ability to capture local context. This study is assessed by comparing the results obtained for popular datasets to those obtained by other techniques in the domain.

Keywords: single image super resolution, computer vision, vision transformers, image restoration

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Authors: Ana Neves

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The European Union’s multi-level constitutionalism is grounded in an intricate network of vertical and horizontal legal relationships among different levels and types of public authorities. In a very significant way since the 2008 crisis, evolving institutional arrangements and institutional dynamics in the European Union have been progressively impacting Member States and the terms under which national public authorities are organised, interact and exercise their powers. This impact occurs in both macro and micro dimensions. Several examples are relevant here, such as the involvement of national Parliaments in the activities of the European Union, the enhanced integration of public administrations, the side effects of the Council framework decision on the European Arrest Warrant, the European Union Justice Scoreboard, the protection of whistle-blowers regulation, the enhanced cooperation on the establishment of the European Public Prosecutor’s Office, the regime for the protection of the Union budget and the European Rule of Law Mechanism. A common trend or denominator underlies the deepening of institutional interdependence and the increased interactions between the European Union, Member States, and public authorities at different levels. This seems to be conditionality as a general principle. The European multi-level constitutionalism must be considered in the light of this conditionality principle, which does not “imply a relationship of command and obedience”. Nevertheless, it might be more effective or be a very compelling principle. It is as if the extension of the shared rule is being accompanied by a contrapuntal dialogue. The different public authorities at various levels are being called to rethink and readjust themselves within a broader and more plural framework concerning understanding the limitation of power.

Keywords: european union -, multi-level hierarchy, conditionality, separation of powers

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Authors: Nicola Rubino

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This paper presents an analysis of a group of commodity exporting countries' nominal exchange rate movements in relationship to the US dollar. Using a series of Unrestricted Self-exciting Threshold Autoregressive models (SETAR), we model and evaluate sixteen national CPI price differentials relative to the US dollar CPI. Out-of-sample forecast accuracy is evaluated through calculation of mean absolute error measures on the basis of two-hundred and fifty-three months rolling window forecasts and extended to three additional models, namely a logistic smooth transition regression (LSTAR), an additive non linear autoregressive model (AAR) and a simple linear Neural Network model (NNET). Our preliminary results confirm presence of some form of TAR non linearity in the majority of the countries analyzed, with a relatively higher goodness of fit, with respect to the linear AR(1) benchmark, in five countries out of sixteen considered. Although no model appears to statistically prevail over the other, our final out-of-sample forecast exercise shows that SETAR models tend to have quite poor relative forecasting performance, especially when compared to alternative non-linear specifications. Finally, by analyzing the implied half-lives of the > coefficients, our results confirms the presence, in the spirit of arbitrage band adjustment, of band convergence with an inner unit root behaviour in five of the sixteen countries analyzed.

Keywords: transition regression model, real exchange rate, nonlinearities, price differentials, PPP, commodity points

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Authors: Po-Fang Hsu, Chiching Wei

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In this paper, we present a novel neural graph matching approach applied to document comparison. Document comparison is a common task in the legal and financial industries. In some cases, the most important differences may be the addition or omission of words, sentences, clauses, or paragraphs. However, it is a challenging task without recording or tracing the whole edited process. Under many temporal uncertainties, we explore the potentiality of our approach to proximate the accurate comparison to make sure which element blocks have a relation of edition with others. In the beginning, we apply a document layout analysis that combines traditional and modern technics to segment layouts in blocks of various types appropriately. Then we transform this issue into a problem of layout graph matching with textual awareness. Regarding graph matching, it is a long-studied problem with a broad range of applications. However, different from previous works focusing on visual images or structural layout, we also bring textual features into our model for adapting this domain. Specifically, based on the electronic document, we introduce an encoder to deal with the visual presentation decoding from PDF. Additionally, because the modifications can cause the inconsistency of document layout analysis between modified documents and the blocks can be merged and split, Sinkhorn divergence is adopted in our neural graph approach, which tries to overcome both these issues with many-to-many block matching. We demonstrate this on two categories of layouts, as follows., legal agreement and scientific articles, collected from our real-case datasets.

Keywords: document comparison, graph matching, graph neural network, modification similarity, multi-modal

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Authors: Ahmed Hosny, Haroon Elshaikh, Gaber Hassib, Yassin Ali

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The Moho discontinuity undulations beneath the southern part of Egypt have been defined using the seismic waves generated by tele earthquakes. These earthquakes have been recorded by the Aswan seismic network, which consists of 10 seismic stations established around the lake of Nasser. An additional seismic station was located towards the east of the Lake of Nasser by about ~ 150 km. Receiver functions and H-k stacking methods were used for obtaining the depths of Moho discontinuity and the Vp/Vs ratios beneath each seismic station. Our results revealed that, the depths of Moho discontinuity beneath the stations located around the Lake of Nasser range from 36 to 39 km, with an average value of 37.5 km. These results are consistent with the previous works done on the same area. The obtained Vp/Vs ratios for the crust of this area were ranged from 1.73 to 1.86, with an average value of 1.79. While beneath the station located towards the east, the Moho discontinuity was detected at a shallowest depth of 27 km and the Vp/Vs ratio was 1.82. The difference in the Moho depths beneath the stations located around the Lake of Nasser and the station located to the east revealed the boundary position between the Saharan Metacraton to the west and the Nubian-Arabian Shield to the east. This structural boundary delineates the position of the old collision of the Oceanic crust of the Nubian-Arabian Shield to the east with the Continental crust of the Saharan Metacraton to the west.

Keywords: Moho undulations, south of Egypt, seismic waves, earthquakes

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Authors: Jeevan Jyoti, Bhanu Pratap Singh, S. R. Dhakate

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In the present study, multiwalled carbon nanotubes (MWCNTs) and reduced graphene oxide (RGO) were synthesized by chemical vapor deposition and Improved Hummer’s method, respectively and their composite with acrylonitrile butadiene styrene (ABS) were prepared by twin screw co rotating extrusion technique. The electromagnetic interference (EMI) shielding effectiveness of graphene oxide carbon nanotube (GCNTs) hybrid composites was investigated and the results were compared with EMI shielding of carbon nanotube (CNTs) and reduced graphene oxide (RGO) in the frequency range of 12.4-18 GHz (Ku-band). The experimental results indicate that the EMI shielding effectiveness of these composites is achieved up to –21 dB for 10 wt. % loading of GCNT loading. The mechanism of improvement in EMI shielding effectiveness is discussed by resolving their contribution in absorption and reflection loss. The main reason for such a high improved shielding effectiveness has been attributed to the significant improvement in the electrical conductivity of the composites. The electrical conductivity of these GCNT/ABS composites was increased from 10-13 S/cm to 10-7 S/cm showing the improvement of the 6 order of the magnitude. Scanning electron microscopic (SEM) and high resolution transmission electron microscopic (HRTEM) studies showed that the GCNTs were uniformly dispersed in the ABS polymer matrix. GCNTs form a network throughout the polymer matrix and promote the reinforcement.

Keywords: ABS, EMI shielding, multiwalled carbon nanotubes, reduced graphene oxide, graphene, oxide-carbon nanotube (GCNTs), twin screw extruder, multiwall carbon nanotube, electrical conductivity

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Authors: Alireza Ansariyar, Safieh Laaly

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Over the last decades, the vehicle industry has shown increased interest in integrating autonomous, connected, and electrical technologies in vehicle design with the primary hope of improving mobility and road safety while reducing transportation’s environmental impact. Using the State of Maryland (M.D.) in the United States as a pilot study, this research investigates CAVs’ fuel consumption and air pollutants (C.O., PM, and NOx) and utilizes meaningful linear regression models to predict CAV’s environmental effects. Maryland transportation network was simulated in VISUM software, and data on a set of variables were collected through a comprehensive survey. The number of pollutants and fuel consumption were obtained for the time interval 2010 to 2021 from the macro simulation. Eventually, four linear regression models were proposed to predict the amount of C.O., NOx, PM pollutants, and fuel consumption in the future. The results highlighted that CAVs’ pollutants and fuel consumption have a significant correlation with the income, age, and race of the CAV customers. Furthermore, the reliability of four statistical models was compared with the reliability of macro simulation model outputs in the year 2030. The error of three pollutants and fuel consumption was obtained at less than 9% by statistical models in SPSS. This study is expected to assist researchers and policymakers with planning decisions to reduce CAV environmental impacts in M.D.

Keywords: connected and autonomous vehicles, statistical model, environmental effects, pollutants and fuel consumption, VISUM, linear regression models

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Authors: Siti Khadijah Che Osmi, Mohammed Ahmad Syed

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Underground structures are crucial components which required detailed analysis and design. Tunnels, for instance, are massively constructed as transportation infrastructures and utilities network especially in urban environments. Considering their prime importance to the economy and public safety that cannot be compromised, thus any instability to these tunnels will be highly detrimental to their performance. Recent experience suggests that tunnels become vulnerable during earthquakes and blast scenarios. However, a very limited amount of studies has been carried out to study and understanding the dynamic response and performance of underground tunnels under those unpredictable extreme hazards. In view of the importance of enhancing the resilience of these structures, the overall aims of the study are to evaluate probabilistic future performance of shallow tunnels subjected to seismic and blast loads by developing detailed fragility analysis. Critical non-linear time history numerical analyses using sophisticated finite element software Midas GTS NX have been presented about the current methods of analysis, taking into consideration of structural typology, ground motion and explosive characteristics, effect of soil conditions and other associated uncertainties on the tunnel integrity which may ultimately lead to the catastrophic failure of the structures. The proposed fragility curves for both extreme loadings are discussed and compared which provide significant information the performance of the tunnel under extreme hazards which may beneficial for future risk assessment and loss estimation.

Keywords: fragility analysis, seismic loads, shallow tunnels, blast loads

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Authors: Balimu Mwiya, Mundia Muya, Chabota Kaliba, Peter Mukalula

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Factors affecting construction unit cost vary depending on a country’s political, economic, social and technological inclinations. Factors affecting construction costs have been studied from various perspectives. Analysis of cost factors requires an appreciation of a country’s practices. Identified cost factors provide an indication of a country’s construction economic strata. The purpose of this paper is to identify the essential factors that affect unit cost estimation and their breakdown using artificial neural networks. Twenty-five (25) identified cost factors in road construction were subjected to a questionnaire survey and employing SPSS factor analysis the factors were reduced to eight. The 8 factors were analysed using the neural network (NN) to determine the proportionate breakdown of the cost factors in a given construction unit rate. NN predicted that political environment accounted 44% of the unit rate followed by contractor capacity at 22% and financial delays, project feasibility, overhead and profit each at 11%. Project location, material availability and corruption perception index had minimal impact on the unit cost from the training data provided. Quantified cost factors can be incorporated in unit cost estimation models (UCEM) to produce more accurate estimates. This can create improvements in the cost estimation of infrastructure projects and establish a benchmark standard to assist the process of alignment of work practises and training of new staff, permitting the on-going development of best practises in cost estimation to become more effective.

Keywords: construction cost factors, neural networks, roadworks, Zambian construction industry

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Authors: Jenny Radeva, Anke-Gundula Roth, Christian Goebbert, Robert Niestroj-Pahl, Lars Daehne, Axel Wolfram, Juergen Wiese

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The technological advantages of ceramic filtration elements were combined with polyelectrolyte films in the development process of hybrid membrane for the elimination of pharmaceuticals from Aquarius solutions. Previously extruded alumina ceramic membranes were coated with nanosized polyelectrolyte films using Layer-by-Layer technology. The polyelectrolyte chains form a network with nano-pores on the ceramic surface and promote the retention of small molecules like pharmaceuticals and microplastics, which cannot be eliminated using standard ultrafiltration methods. Additionally, the polyelectrolyte coat contributes with its adjustable (based on application) Zeta Potential for repulsion of contaminant molecules with opposite charges. Properties like permeability, bubble point, pore size distribution and Zeta Potential of ceramic and hybrid membranes were characterized using various laboratory and pilot tests and compared with each other. The most significant role for the membrane characterization played the filtration behavior investigation, during which retention against widely used pharmaceuticals like Diclofenac, Ibuprofen and Sulfamethoxazol was subjected to series of filtration tests. The presented study offers a new perspective on nanosized molecules removal from aqueous solutions and shows the importance of combined techniques application for the elimination of pharmaceutical contaminants from drinking water.

Keywords: water treatment, hybrid membranes, layer-by-layer coating, filtration, polyelectrolytes

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Authors: Smaran Manchala

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Homomorphic Encryption (HE) enables computations on encrypted data without requiring decryption, mitigating data vulnerability during processing. Usable Fully Homomorphic Encryption (FHE) could revolutionize secure data operations across cloud computing, AI training, and healthcare, providing both privacy and functionality, however, the computational inefficiency of schemes like Cheon-Kim-Kim-Song (CKKS) hinders their widespread practical use. This study focuses on optimizing CKKS for faster matrix operations through the implementation of vector computation parallelization and GPU acceleration. The variable effects of vector parallelization on GPUs were explored, recognizing that while parallelization typically accelerates operations, it could introduce overhead that results in slower runtimes, especially in smaller, less computationally demanding operations. To assess performance, two neural network models, MLPN and CNN—were tested on the MNIST dataset using both ARM and x86-64 architectures, with CNN chosen for its higher computational demands. Each test was repeated 1,000 times, and outliers were removed via Z-score analysis to measure the effect of vector parallelization on CKKS performance. Model accuracy was also evaluated under CKKS encryption to ensure optimizations did not compromise results. According to the results of the trail runs, applying vector parallelization had a 2.63X efficiency increase overall with a 1.83X performance increase for x86-64 over ARM architecture. Overall, these results suggest that the application of vector parallelization in tandem with GPU acceleration significantly improves the efficiency of CKKS even while accounting for vector parallelization overhead, providing impact in future zero trust operations.

Keywords: CKKS scheme, runtime efficiency, fully homomorphic encryption (FHE), GPU acceleration, vector parallelization

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Authors: Yousuf Nasser Al Khamisi

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Purpose: This paper presents a Knowledge Transfer (KT) Framework in healthcare sectors by applying a systematic literature review process to the healthcare organizations domain to identify enablers and barriers of KT in Healthcare. Methods: The paper conducted a systematic literature search of peer-reviewed papers that described key elements of KT using four databases (Medline, Cinahl, Scopus, and Proquest) for a 10-year period (1/1/2008–16/10/2017). The results of the literature review were used to build a conceptual framework of KT in healthcare organizations. The author used a systematic review of the literature, as described by Barbara Kitchenham in Procedures for Performing Systematic Reviews. Findings: The paper highlighted the impacts of using Knowledge Management (KM) concept at a healthcare organization in controlling infectious diseases in hospitals, improving family medicine performance and enhancing quality improvement practices. Moreover, it found that good-coding performance is analytically linked with a knowledge sharing network structure rich in brokerage and hierarchy rather than in density. The unavailability or ignored of the latest evidence on more cost-effective or more efficient delivery approaches leads to increase the healthcare costs and may lead to unintended results. Originality: Search procedure produced 12,093 results, of which 3523 were general articles about KM and KT. The titles and abstracts of these articles had been screened to segregate what is related and what is not. 94 articles identified by the researchers for full-text assessment. The total number of eligible articles after removing un-related articles was 22 articles.

Keywords: healthcare organisation, knowledge management, knowledge transfer, KT framework

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Authors: Y. Mehdipour, S. Ebrahimi, A. Jahanpour, F. Seyedzaei, B. Sabayan, A. Karimi, H. Amirifard

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Ischemic stroke is one of the common reasons for disability and mortality. The fourth leading cause of death in the world and the third in some other sources. Only 1/3 of the patients with ischemic stroke fully recover, 1/3 of them end in permanent disability and 1/3 face death. Thus, the use of predictive models to predict stroke has a vital role in reducing the complications and costs related to this disease. Thus, the aim of this study was to specify the effective factors and predict ischemic stroke with the help of DM methods. The present study was a descriptive-analytic study. The population was 213 cases from among patients referring to Ali ibn Abi Talib (AS) Hospital in Zahedan. Data collection tool was a checklist with the validity and reliability confirmed. This study used DM algorithms of decision tree for modeling. Data analysis was performed using SPSS-19 and SPSS Modeler 14.2. The results of the comparison of algorithms showed that CHAID algorithm with 95.7% accuracy has the best performance. Moreover, based on the model created, factors such as anemia, diabetes mellitus, hyperlipidemia, transient ischemic attacks, coronary artery disease, and atherosclerosis are the most effective factors in stroke. Decision tree algorithms, especially CHAID algorithm, have acceptable precision and predictive ability to determine the factors affecting ischemic stroke. Thus, by creating predictive models through this algorithm, will play a significant role in decreasing the mortality and disability caused by ischemic stroke.

Keywords: data mining, ischemic stroke, decision tree, Bayesian network

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Authors: Tibor Ajtai, Noémi Utry, Máté Pintér, Tomi Smausz, Zoltán Kónya, Béla Hopp, Gábor Szabó, Zoltán Bozóki

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Characterization of spectral responses of light absorbing carbonaceous particulate matter (LAC) is of great importance in both modelling its climate effect and interpreting remote sensing measurement data. The residential or domestic combustion of coal is one of the dominant LAC constituent. According to some related assessments the residential coal burning account for roughly half of anthropogenic BC emitted from fossil fuel burning. Despite of its significance in climate the comprehensive investigation of optical properties of residential coal aerosol is really limited in the literature. There are many reason of that starting from the difficulties associated with the controlled burning conditions of the fuel, through the lack of detailed supplementary proximate and ultimate chemical analysis enforced, the interpretation of the measured optical data, ending with many analytical and methodological difficulties regarding the in-situ measurement of coal aerosol spectral responses. Since the gas matrix of ambient can significantly mask the physicochemical characteristics of the generated coal aerosol the accurate and controlled generation of residential coal particulates is one of the most actual issues in this research area. Most of the laboratory imitation of residential coal combustion is simply based on coal burning in stove with ambient air support allowing one to measure only the apparent spectral feature of the particulates. However, the recently introduced methodology based on a laser ablation of solid coal target opens up novel possibilities to model the real combustion procedure under well controlled laboratory conditions and makes the investigation of the inherent optical properties also possible. Most of the methodology for spectral characterization of LAC is based on transmission measurement made of filter accumulated aerosol or deduced indirectly from parallel measurements of scattering and extinction coefficient using free floating sampling. In the former one the accuracy while in the latter one the sensitivity are liming the applicability of this approaches. Although the scientific community are at the common platform that aerosol-phase PhotoAcoustic Spectroscopy (PAS) is the only method for precise and accurate determination of light absorption by LAC, the PAS based instrumentation for spectral characterization of absorption has only been recently introduced. In this study, the investigation of the inherent, spectral features of laser generated and chemically characterized residential coal aerosols are demonstrated. The experimental set-up and its characteristic for residential coal aerosol generation are introduced here. The optical absorption and the scattering coefficients as well as their wavelength dependency are determined by our state-of-the-art multi wavelength PAS instrument (4λ-PAS) and multi wavelength cosinus sensor (Aurora 3000). The quantified wavelength dependency (AAE and SAE) are deduced from the measured data. Finally, some correlation between the proximate and ultimate chemical as well as the measured or deduced optical parameters are also revealed.

Keywords: absorption, scattering, residential coal, aerosol generation by laser ablation

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Authors: Kimmo J. Kurppa

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This paper describes the development of the buyer-supplier dyad concept over the years and proposes improvements, clarifications and extensions to the prevailing definitions published in 1970’s and 1980’s. This paper suggests a partition of the buyer-supplier dyad to concepts of Commercial Dyad (dyadic interaction in vertical relationships) and Innovative Dyad (dyadic interaction in horizontal relationship) since dyadic interaction takes place in two major types of contexts between industrial firms. Especially the context of joint product development in a dyadic relationship has not been adequately recognized being totally different from the interaction taking place in commercial buyer-supplier interaction. This paper provides therefore a solution to the existing gap in research by clarifying the descriptions and the context where dyadic interaction takes place between industrial firms. This paper also illustrates and explains how the firm’s organization and the interaction taking place inside it, is connected to the dyadic interaction structure between the firm and its partner firm. This theme has been discussed earlier but the phenomenon has not been adequately described and has not been illustrated in earlier research. This conceptual study has been interested in how the dyad concept of Industrial Marketing has been defined in the earlier research and how the definition could be improved. This conceptual paper has been constructed by using the systematic review methodology and proposes avenues for future research. The concept and existence of relationship and interaction between firm’s internal interaction network and external interaction between firm’s dyadic counterparts, need to be verified through empirical research.

Keywords: dyadic interaction, industrial dyad, buyer-supplier relationship, strategic reciprocity, experience, socially adjusted opportunism

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Authors: Houria Rezala, Jose Luis Valverde, Amaya Romero, Alessandra Molinari, Andrea Maldotti

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A pillared montmorillonite containing iron doped titania (Fe/Ti-PILC) has been prepared from a natural clay. This material has been characterized by X-ray diffraction, nitrogen adsorption, temperature programmed desorption of ammonia, inductively coupled plasma atomic emission spectroscopy, atomic absorption, and diffuse reflectance UV-VIS spectroscopy. The layer structure of Fe/Ti-PILC resulted to be ordered with an insertion of pillars, which caused a slight increase in the basal spacing of the clay. Its specific surface area was about three times larger than that of the parent Na-montmorillonite due principally to the creation of a remarkable microporous network. The doped material was a robust photocatalyst able to oxidize liquid alkyl aromatics to the corresponding carbonylic derivatives, using O2 as the oxidizing species, at mild pressure and temperature conditions. Accumulation of valuable carbonylic derivatives was possible since their over-oxidation to carbon dioxide was negligible. Fe/Ti-PILC was able to discriminate between toluene and cyclohexane in favor of the aromatic compound with an efficiency that is about three times higher than that of titanium pillared clays (Ti-PILC). It is likely that the addition of iron favored the formation of new acid sites able to interact with the aromatic substrate. Iron doping caused a significant TiO2 visible light-induced activity (wavelength > 400 nm) with only minor negative effects on its performance under UV-light irradiation (wavelength > 290 nm).

Keywords: alkyl aromatics oxidation, heterogeneous photocatalysis, iron doping, pillared clays

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Authors: Koutsopoulou Ioanna, Gkintoni Evgenia, Halkiopoulos Constantinos, Antonopoulou Hera

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Recent advances in Internet Computer Technology (ICT) and the ever-increasing use of technological equipment amongst adolescents and young adults along with unattended access to the internet and social media and uncontrolled use of smart phones and PCs have caused social problems like sexting to emerge. The main purpose of the present article is first to present an analytic theoretical framework of sexting as a recent social phenomenon based on studies that have been conducted the last decade or so; and second to investigate Greek students’ and also social network users, sexting perceptions and to record how often social media users exchange sexual messages and to retrace demographic variables predictors. Data from 1,000 students were collected and analyzed and all statistical analysis was done by the software package WEKA. The results indicate among others, that the use of data mining methods is an important tool to draw conclusions that could affect decision and policy making especially in the field and related social topics of educational psychology. To sum up, sexting lurks many risks for adolescents and young adults students in Greece and needs to be better addressed in relevance to the stakeholders as well as society in general. Furthermore, policy makers, legislation makers and authorities will have to take action to protect minors. Prevention strategies based on Greek cultural specificities are being proposed. This social problem has raised concerns in recent years and will most likely escalate concerns in global communities in the future.

Keywords: educational ethics, sexting, Greek sexters, sex education, data mining

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Authors: Maedeh Pourmajidian, Joseph R. McDermid

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Advanced High Strength Steels are revolutionizing both the steel and automotive industries due to their high specific strength and ability to absorb energy during crash events. This allows manufacturers to design vehicles with significantly increased fuel efficiency without compromising passenger safety. To maintain the structural integrity of the fabricated parts, they must be protected from corrosion damage through continuous hot-dip galvanizing process, which is challenging due to selective oxidation of Mn and Si on the surface of this AHSSs. The effects of process atmosphere oxygen partial pressure and small additions of Sn on the selective oxidation of a medium-Mn C-6Mn-2Si advanced high strength steel was investigated. Intercritical annealing heat treatments were carried out at 690˚C in an N2-5%H2 process atmosphere under dew points ranging from –50˚C to +5˚C. Surface oxide chemistries, morphologies, and thicknesses were determined at a variety of length scales by several techniques, including SEM, TEM+EELS, and XPS. TEM observations of the sample cross-sections revealed the transition to internal oxidation at the +5˚C dew point. EELS results suggested that the internal oxides network was composed of a multi-layer oxide structure with varying chemistry from oxide core towards the outer part. The combined effect of employing a known surface active element as a function of process atmosphere on the surface structure development and the possible impact on reactive wetting of the steel substrates by the continuous galvanizing zinc bath will be discussed.

Keywords: 3G AHSS, hot-dip galvanizing, oxygen partial pressure, selective oxidation

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Authors: Lei Zhu, Nan Li

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Cold stamping has been widely applied in the automotive industry for the mass production of a great range of automotive panels. Predicting the springback to ensure the dimensional accuracy of the cold-stamped components is a critical step. The main approaches for the prediction and compensation of springback in cold stamping include running Finite Element (FE) simulations and conducting experiments, which require forming process expertise and can be time-consuming and expensive for the design of cold stamping tools. Machine learning technologies have been proven and successfully applied in learning complex system behaviours using presentative samples. These technologies exhibit the promising potential to be used as supporting design tools for metal forming technologies. This study, for the first time, presents a novel application of a Convolutional Neural Network (CNN) based surrogate model to predict the springback fields for variable U-shape cold bending geometries. A dataset is created based on the U-shape cold bending geometries and the corresponding FE simulations results. The dataset is then applied to train the CNN surrogate model. The result shows that the surrogate model can achieve near indistinguishable full-field predictions in real-time when compared with the FE simulation results. The application of CNN in efficient springback prediction can be adopted in industrial settings to aid both conceptual and final component designs for designers without having manufacturing knowledge.

Keywords: springback, cold stamping, convolutional neural networks, machine learning

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Authors: Aderonke Oluseun Akinwumi, Olusola A. Komolaf

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This paper gives information about the wide array of challenges facing both the electric utilities and consumers in the distribution system in developing countries, using Obafemi Awolowo University, Ile-Ife Nigeria as a case study. It also proffers cost-effective solution through remote monitoring, diagnostic and operation of distribution networks without compromising the system reliability. As utilities move from manned and unintelligent networks to completely unmanned smart grids, switching activities at substations and feeders will be managed and controlled remotely by dedicated systems hence this design. The Substation Remote Diagnostic and Operation Solution (sRDOs) would remotely monitor the load on Medium Voltage (MV) and Low Voltage (LV) feeders as well as distribution transformers and allow the utility disconnect non-paying customers with absolutely no extra resource deployment and without interrupting supply to paying customers. The aftermath of the implementation of this design improved the lifetime of key distribution infrastructure by automatically isolating feeders during overload conditions and more importantly erring consumers. This increased the ratio of revenue generated on electricity bills to total network load.

Keywords: electric utility, consumers, remote monitoring, diagnostic, system reliability, manned and unintelligent networks, unmanned smart grids, switching activities, medium voltage, low voltage, distribution transformer

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Authors: Muhammad Umair, Yasir Nawab, Khubab Shaker, Muhammad Maqsood, Adeel Zulfiqar, Danish Mahmood Baitab

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Fabric is a flexible woven material consisting of a network of natural or artificial fibers often referred to as thread or yarn. Today fabrics are produced by weaving, braiding, knitting, tufting and non-woven. Weaving is a method of fabric production in which warp and weft yarns are interlaced perpendicular to each other. There is infinite number of ways for the interlacing of warp and weft yarn. Each way produces a different fabric structure. The yarns parallel to the machine direction are called warp yarns and the yarns perpendicular to the machine direction are called weft or filling yarns. Air jet weaving is the modern method of weft insertion and considered as high speed loom. The twist loss in air jet during weft insertion affects the strength. The aim of this study was to investigate the effect of twist change in weft yarn during air-jet weft insertion. A total number of 8 samples were produced using 1/1 plain and 3/1 twill weave design with two fabric widths having same loom settings. Two different types of yarns like cotton and PC blend were used. The effect of material type, weave design and fabric width on twist change of weft yarn was measured and discussed. Twist change in the different types of weft yarn and weave design was measured and compared the twist change in the weft yarn with the yarn before weft yarn insertion and twist loss is measured. Wider fabric leads to higher twist loss in the yarn.

Keywords: air jet loom, twist per inch, twist loss, weft yarn

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Authors: Chaomeng Liu, Li Li, Xiao Wang, Li Ren, Qinge Zhang

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Late-life depression (LLD) is a prevalent mental disorder among the elderly, frequently accompanied by significant cognitive decline, and has emerged as a worldwide public health concern. Microglia, astrocytes, and peripheral immune cells play pivotal roles in regulating inflammatory responses within the central nervous system (CNS) across diverse cerebral disorders. This review commences with the clinical research findings and accentuates the recent advancements pertaining to microglia and astrocytes in the neuroinflammation process of LLD. The reciprocal communication network between the CNS and immune system is of paramount importance in the pathogenesis of depression and cognitive decline. Stress-induced downregulation of tight and gap junction proteins in the brain results in increased blood-brain barrier permeability and impaired astrocyte function. Concurrently, activated microglia release inflammatory mediators, initiating the kynurenine metabolic pathway and exacerbating the quinolinic acid/kynurenic acid imbalance. Moreover, the balance between Th17 and Treg cells is implicated in the preservation of immune homeostasis within the cerebral milieu of individuals suffering from LLD. The ultimate objective of this review is to present future strategies for the management and treatment of LLD, informed by the most recent advancements in research, with the aim of averting or postponing the onset of AD.

Keywords: neuroinflammation, late-life depression, microglia, astrocytes, central nervous system, blood-brain barrier, Kynurenine pathway

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