Search results for: anionic ring opening polymerization

Authors: Mohammad R. Aghakashkooli, Milutin G. Jovanovic

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The brushless doubly-fed reluctance generator (BDFRG) is an emerging, medium-speed alternative to a conventional wound rotor slip-ring doubly-fed induction generator (DFIG) in wind energy conversion systems (WECS). It can provide competitive overall performance and similar low failure rates of a typically 30% rated back-to-back power electronics converter in 2:1 speed ranges but with the following important reliability and cost advantages over DFIG: the maintenance-free operation afforded by its brushless structure, 50% synchronous speed with the same number of rotor poles (allowing the use of a more compact, and more efficient two-stage gearbox instead of a vulnerable three-stage one), and superior grid integration properties including simpler protection for the low voltage ride through compliance of the fractional converter due to the comparatively higher leakage inductances and lower fault currents. Vector controlled pulse-width-modulated converters generally feature a much lower total harmonic distortion relative to hysteresis counterparts with variable switching rates and as such have been a predominant choice for BDFRG (and DFIG) wind turbines. Eliminating a shaft position sensor, which is often required for control implementation in this case, would be desirable to address the associated reliability issues. This fact has largely motivated the recent growing research of sensorless methods and developments of various rotor position and/or speed estimation techniques for this purpose. The main limitation of all the observer-based control approaches for grid-connected wind power applications of the BDFRG reported in the open literature is the requirement for pre-commissioning procedures and prior knowledge of the machine inductances, which are usually difficult to accurately identify by off-line testing. A model reference adaptive system (MRAS) based sensor-less vector control scheme to be presented will overcome this shortcoming. The true machine parameter independence of the proposed field-oriented algorithm, offering robust, inherently decoupled real and reactive power control of the grid-connected winding, is achieved by on-line estimation of the inductance ratio, the underlying rotor angular velocity and position MRAS observer being reliant upon. Such an observer configuration will be more practical to implement and clearly preferable to the existing machine parameter dependent solutions, and especially bearing in mind that with very little modifications it can be adapted for commercial DFIGs with immediately obvious further industrial benefits and prospects of this work. The excellent encoder-less controller performance with maximum power point tracking in the base speed region will be demonstrated by realistic simulation studies using large-scale BDFRG design data and verified by experimental results on a small laboratory prototype of the WECS emulation facility.

Keywords: brushless doubly fed reluctance generator, model reference adaptive system, sensorless vector control, wind energy conversion

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Authors: Eleonora Carloni, Michela Arnaboldi

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In academia, the investigation of the relationship between cultural heritage and corporations is ubiquitous in several fields of studies. In practice corporations are more and more integrating arts and cultural heritage in their strategies for disparate benefits, such as: to foster customer’s purchase intention with authentic and aesthetic experiences, to improve their reputation towards local communities, and to motivate employees with creative thinking. There are diverse forms under which corporations set these artistic interventions, from sponsorships to arts-based training centers for employees, but scholars agree that the maximum expression of this cultural trend are corporate museums, growing in number and relevance. Corporate museums are museum-like settings, hosting artworks of corporations’ history and interests. In academia they have been ascribed as strategic asset and they have been associated with diverse uses for corporations’ benefits, from place for preservation of cultural heritage, to tools for public relations and cultural flagship stores. Previous studies have thus extensively but fragmentally studied the diverse benefits of corporate museum opening to corporations, with a lack of comprehensive approach and a digression on how to evaluate and report corporate museum’s performances. Stepping forward, the present study aims to investigate: 1) what are the key performance measures corporate museums need to report to the associated corporations; 2) how are the key performance measures reported to the concerned corporations. This direction of study is not only suggested as future direction in academia but it has solid basis in practice, aiming to answer to the need of corporate museums’ directors to account for corporate museum’s activities to the concerned corporation. Coherently, at an empirical level the study relies on action research method, whose distinctive feature is to develop practical knowledge through a participatory process. This paper indeed relies on the experience of a collaborative project between the researchers and a set of corporate museums in Italy, aimed at co-developing a performance measurement system. The project involved two steps: a first step, in which researchers derived the potential performance measures from literature along with exploratory interviews; a second step, in which researchers supported the pool of corporate museums’ directors in co-developing a set of key performance indicators for reporting. Preliminary empirical findings show that while scholars insist on corporate museums’ capability to develop networking relations, directors insist on the role of museums as internal supplier of knowledge for innovation goals. Moreover, directors stress museums’ cultural mission and outcomes as potential benefits for corporation, by remarking to include both cultural and business measures in the final tool. In addition, they give relevant attention to the wording used in humanistic terms while struggling to express all measures in economic terms. The paper aims to contribute to corporate museums’ and more broadly to arts-based initiatives’ literature in two directions. Firstly, it elaborates key performance measures with related indicators to report on cultural initiatives for corporations. Secondly, it provides evidence of challenges and practices to handle reporting on these initiatives, because of tensions arising from the co-existence of diverse perspectives, namely arts and business worlds.

Keywords: arts-based initiative, corporate museum, hybrid organization, performance measurement

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Authors: Istvan Csarnovics, Attila Bonyar, Miklos Veres, Laszlo Himics, Attila Csik, Judit Kaman, Julia Burunkova, Geza Szanto, Laszlo Balazs, Sandor Kokenyesi

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In this work, the performance of gold nanoparticles were investigated for stimulation of photosensitive materials for photonic applications. It was widely used for surface plasmon resonance experiments, not in the last place because of the manifestation of optical resonances in the visible spectral region. The localized surface plasmon resonance is rather easily observed in nanometer-sized metallic structures and widely used for measurements, sensing, in semiconductor devices and even in optical data storage. Firstly, gold nanoparticles on silica glass substrate satisfy the conditions for surface plasmon resonance in the green-red spectral range, where the chalcogenide glasses have the highest sensitivity. The gold nanostructures influence and enhance the optical, structural and volume changes and promote the exciton generation in gold nanoparticles/chalcogenide layer structure. The experimental results support the importance of localized electric fields in the photo-induced transformation of chalcogenide glasses as well as suggest new approaches to improve the performance of these optical recording media. Results may be utilized for direct, micrometre- or submicron size geometrical and optical pattern formation and used also for further development of the explanations of these effects in chalcogenide glasses. Besides of that, gold nanoparticles could be added to the organic light-sensitive material. The acrylate-based materials are frequently used for optical, holographic recording of optoelectronic elements due to photo-stimulated structural transformations. The holographic recording process and photo-polymerization effect could be enhanced by the localized plasmon field of the created gold nanostructures. Finally, gold nanoparticles widely used for electrochemical and optical sensor applications. Although these NPs can be synthesized in several ways, perhaps one of the simplest methods is the thermal annealing of pre-deposited thin films on glass or silicon surfaces. With this method, the parameters of the annealing process (time, temperature) and the pre-deposited thin film thickness influence and define the resulting size and distribution of the NPs on the surface. Localized surface plasmon resonance (LSPR) is a very sensitive optical phenomenon and can be utilized for a large variety of sensing purposes (chemical sensors, gas sensors, biosensors, etc.). Surface-enhanced Raman spectroscopy (SERS) is an analytical method which can significantly increase the yield of Raman scattering of target molecules adsorbed on the surface of metallic nanoparticles. The sensitivity of LSPR and SERS based devices is strongly depending on the used material and also on the size and geometry of the metallic nanoparticles. By controlling these parameters the plasmon absorption band can be tuned and the sensitivity can be optimized. The technological parameters of the generated gold nanoparticles were investigated and influence on the SERS and on the LSPR sensitivity was established. The LSPR sensitivity were simulated for gold nanocubes and nanospheres with MNPBEM Matlab toolbox. It was found that the enhancement factor (which characterize the increase in the peak shift for multi-particle arrangements compared to single-particle models) depends on the size of the nanoparticles and on the distance between the particles. This work was supported by GINOP- 2.3.2-15-2016-00041 project, which is co-financed by the European Union and European Social Fund. Istvan Csarnovics is grateful for the support through the New National Excellence Program of the Ministry of Human Capacities, supported by the ÚNKP-17-4 Attila Bonyár and Miklós Veres are grateful for the support of the János Bolyai Research Scholarship of the Hungarian Academy of Sciences.

Keywords: light sensitive nanocomposites, metallic nanoparticles, photonic application, plasmonic nanostructures

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Authors: L. R. Valencia Pérez, J. M. Peña Aguilar, A. Lamadrid Álvarez, A. Pastrana Palma, H. F. Valencia Pérez, M. Vivanco Vargas

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This work proposes a Cooperation-Competitive (Coopetitive) approach that allows coordinated work among the Secretary of Public Education (SEP), the Autonomous University of Querétaro (UAQ) and government funds from National Council for Science and Technology (CONACYT) or some other international organizations. To work on an overall knowledge transfer strategy with e-learning over the Cloud, where experts in junior high and high school education, working in multidisciplinary teams, perform analysis, evaluation, design, production, validation and knowledge transfer at large scale using a Cloud Computing platform. Allowing teachers and students to have all the information required to ensure a homologated nationally knowledge of topics such as mathematics, statistics, chemistry, history, ethics, civism, etc. This work will start with a pilot test in Spanish and initially in two regional dialects Otomí and Náhuatl. Otomí has more than 285,000 speaking indigenes in Queretaro and Mexico´s central region. Náhuatl is number one indigenous dialect spoken in Mexico with more than 1,550,000 indigenes. The phase one of the project takes into account negotiations with indigenous tribes from different regions, and the Information and Communication technologies to deliver the knowledge to the indigenous schools in their native dialect. The methodology includes the following main milestones: Identification of the indigenous areas where Otomí and Náhuatl are the spoken dialects, research with the SEP the location of actual indigenous schools, analysis and inventory or current schools conditions, negotiation with tribe chiefs, analysis of the technological communication requirements to reach the indigenous communities, identification and inventory of local teachers technology knowledge, selection of a pilot topic, analysis of actual student competence with traditional education system, identification of local translators, design of the e-learning platform, design of the multimedia resources and storage strategy for “Cloud Computing”, translation of the topic to both dialects, Indigenous teachers training, pilot test, course release, project follow up, analysis of student requirements for the new technological platform, definition of a new and improved proposal with greater reach in topics and regions. Importance of phase one of the project is multiple, it includes the proposal of a working technological scheme, focusing in the cultural impact in Mexico so that indigenous tribes can improve their knowledge about new forms of crop improvement, home storage technologies, proven home remedies for common diseases, ways of preparing foods containing major nutrients, disclose strengths and weaknesses of each region, communicating through cloud computing platforms offering regional products and opening communication spaces for inter-indigenous cultural exchange.

Keywords: Mexicans indigenous tribes, education, knowledge transfer, cloud computing, otomi, Náhuatl, language

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Authors: Ye Xue, Zhenhua Deng

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Objectives: Facial soft tissue thickness (FSTT) data could be obtained from CT scans by measuring the face-to-skull distances at sparsely distributed anatomical landmarks by manually located on face and skull. However, automated measurement using 3D facial and skull models by dense points using open-source software has become a viable option due to the development of computed assisted imaging technologies. By utilizing dense FSTT information, it becomes feasible to generate plausible automated facial approximations. Therefore, establishing a comprehensive and detailed, densely calculated FSTT database is crucial in enhancing the accuracy of facial approximation. Materials and methods: This study utilized head CT scans from 250 Chinese adults of Han ethnicity, with 170 participants originally born and residing in northern China and 80 participants in southern China. The age of the participants ranged from 14 to 82 years, and all samples were divided into five non-overlapping age groups. Additionally, samples were also divided into three categories based on BMI information. The 3D Slicer software was utilized to segment bone and soft tissue based on different Hounsfield Unit (HU) thresholds, and surface models of the face and skull were reconstructed for all samples from CT data. Following procedures were performed unsing MeshLab, including converting the face models into hollowed cropped surface models amd automatically measuring the Hausdorff Distance (referred to as FSTT) between the skull and face models. Hausdorff point clouds were colorized based on depth value and exported as PLY files. A histogram of the depth distributions could be view and subdivided into smaller increments. All PLY files were visualized of Hausdorff distance value of each vertex. Basic descriptive statistics (i.e., mean, maximum, minimum and standard deviation etc.) and distribution of FSTT were analysis considering the sex, age, BMI and birthplace. Statistical methods employed included Multiple Regression Analysis, ANOVA, principal component analysis (PCA). Results: The distribution of FSTT is mainly influenced by BMI and sex, as further supported by the results of the PCA analysis. Additionally, FSTT values exceeding 30mm were found to be more sensitive to sex. Birthplace-related differences were observed in regions such as the forehead, orbital, mandibular, and zygoma. Specifically, there are distribution variances in the depth range of 20-30mm, particularly in the mandibular region. Northern males exhibit thinner FSTT in the frontal region of the forehead compared to southern males, while females shows fewer distribution differences between the northern and southern, except for the zygoma region. The observed distribution variance in the orbital region could be attributed to differences in orbital size and shape. Discussion: This study provides a database of Chinese individuals distribution of FSTT and suggested opening source tool shows fine function for FSTT measurement. By incorporating birthplace as an influential factor in the distribution of FSTT, a greater level of detail can be achieved in facial approximation.

Keywords: forensic anthropology, forensic imaging, cranial facial reconstruction, facial soft tissue thickness, CT, open-source tool

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Authors: Elena Iacob, Marie-Louise Ionescu, Elena Ionescu, Carmen Elena Tebrencu, Oana Teodora Ciuperca

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Infrared spectroscopy (FT-IR) is an advanced technique frequently used to authenticate both raw materials and final products using their specific fingerprints and to determine plant extracts biomarkers based on their functional groups. In recent years the market for Hypericum has grown rapidly and also has grown the cases of adultery/replacement, especially for Hypericum perforatum L.specie. Presence/absence of same biomarkers provides preliminary identification of Hypericum species in safe use in the manufacture of food supplements. The main objective of the work was to characterize the main biomarkers of Hypericum perforatum L. (St. John's wort) and identify this species in herbal food supplements after specific FT-IR fingerprint. An experimental program has been designed in order to test: (1) raw material (St. John's wort); (2)intermediate raw materials (St. John's wort dry extract ); (3) the finished products: tablets based on powders, on extracts, on powder and extract, hydroalcoholic solution from herbal mixture based on St. John's wort. The analyze using FTIR infrared spectroscopy were obtained raw materials, intermediates and finished products spectra, respectively absorption bands corresponding and similar with aliphatic and aromatic structures; examination was done individually and through comparison between Hypericum perforatum L. plant species and finished product The tests were done in correlation with phytochemical markers for authenticating the specie Hypericum perforatum L.: hyperoside, rutin, quercetin, isoquercetin, luteolin, apigenin, hypericin, hyperforin, chlorogenic acid. Samples were analyzed using a Shimatzu FTIR spectrometer and the infrared spectrum of each sample was recorded in the MIR region, from 4000 to 1000 cm-1 and then the fingerprint region was selected for data analysis. The following functional groups were identified -stretching vibrations suggests existing groups in the compounds of interest (flavones–rutin, hyperoside, polyphenolcarboxilic acids - chlorogenic acid, naphtodianthrones- hypericin): oxidril groups (OH) free alcohol type: rutin, hyperoside, chlorogenic acid; C = O bond from structures with free carbonyl groups of aldehyde, ketone, carboxylic, ester: hypericin; C = O structure with the free carbonyl of the aldehyde groups, ketone, carboxylic acid, esteric/C = O free bonds present in chlorogenic acid; C = C bonds of the aromatic ring (condensed aromatic hydrocarbons, heterocyclic compounds) present in all compounds of interest; OH phenolic groups: present in all compounds of interest, C-O-C groups from glycoside structures: rutin, hyperoside, chlorogenic acid. The experimental results show that: (I)The six fingerprint region analysis indicated the presence of specific functional groups: (1) 1000 - 1130 cm-1 (C-O–C of glycoside structures); (2) 1200-1380 cm-1 (carbonyl C-O or O-H phenolic); (3) 1400-1450 cm-1 (C=C aromatic); (4) 1600- 1730 cm-1 (C=O carbonyl); (5) 2850 - 2930 cm-1 (–CH3, -CH2-, =CH-); (6) 338-3920 cm-1 (OH free alcohol type); (II)Comparative FT-IR spectral analysis indicate the authenticity of the finished products ( tablets) in terms of Hypericum perforatum L. content; (III)The infrared spectroscopy is an adequate technique for identification and authentication of the medicinal herbs , intermediate raw material and in the food supplements less in the form of solutions where the results are not conclusive.

Keywords: Authentication, FT-IR fingerprint, Herbal supplements, Hypericum perforatum L.

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Authors: Alvaro Valera Sosa

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Background: In recent years, childhood overweight and obesity have become an increasing and challenging phenomenon in Berlin and Germany in general. The highest shares of childhood overweight in Berlin are district localities within the inner city ring with lowest socio-economic levels and the highest number of migration background populations. Most factors explaining overweight and obesity are linked to individual dispositions and nutrition balances. Among various strategies, to target drinking behaviors of children and adolescents has been proven to be effective. On the one hand, encouraging the intake of water – which does not contain energy and thus may support a healthy weight status – on the other hand, reducing the consumption of sugar-containing beverages – which are linked to weight gain and obesity. Anyhow, these preventive approaches have mostly developed into individual or educational interventions widely neglecting environmental modifications. Therefore, little is known on how urban physical environment patterns and features can act as influence factors for childhood overweight. Aiming the development of a physical environment intervention tackling children overweight, this study evaluated urban situations surrounding public playgrounds in Berlin where the issue is evident. It verified the presence and state of physical environmental conditions that can be conducive for children to engage physical activity and water intake. Methods: The study included public playgrounds for children from 0-12 y/o within district localities with the highest prevalence of childhood overweight, highest population density, and highest mixed uses. A systematic observation was realized to describe physical environment patterns and features that may affect children health behavior leading to overweight. Neighborhood walkability for all age groups was assessed using the Walkability for Health framework (TU-Berlin). Playground physical environment conditions were evaluated using Active Living Research assessment sheets. Finally, the food environment in the playground’s pedestrian catchment areas was reviewed focusing on: proximity to suppliers offering sugar-containing beverages, and physical access for 5 y/o children and up to drinking water following the Drinking Fountains and Public Health guidelines of the Pacific Institute. Findings: Out of 114 locations, only 7 had a child population over 3.000. Three with the lowest socio-economic index and highest percentage of migration background were selected. All three urban situations presented similar walkability: large trafficked avenues without buffer bordering at least one side of the playground, and important block to block disconnections for active travel. All three playgrounds rated equipment conditions from good to very good. None had water fountains at the reach of a 5 y/o. and all presented convenience stores and/or fast food outlets selling sugar-containing beverages nearby the perimeter. Conclusion: The three playground situations selected are representative of Berlin locations where most factors that influence children overweight are found. The results delivered urban and architectural design directives for an environmental intervention, used to study children health-related behavior. A post-intervention evaluation could prove associations between designed spaces and children overweight rate reduction creating a precedent in public health interventions and providing novel strategies for the health sector.

Keywords: children overweight, evaluation research, public playgrounds, urban design, urban health

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Authors: Lacramioara Ochiuz, Aurelia Vasile, Iulian Stoleriu, Cristina Ghiciuc, Maria Ignat

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Topical administration of chemotherapeutic agents (eg. carmustine, bexarotene, mechlorethamine etc.) in local treatment of cutaneous T-cell lymphoma (CTCL) is accompanied by multiple side effects, such as contact hypersensitivity, pruritus, skin atrophy or even secondary malignancies. A known method of reducing the side effects of anticancer agent is the development of modified drug release systems using drug incapsulation in biocompatible nanoporous inorganic matrices, such as mesoporous MCM-41 silica. Mesoporous MCM-41 silica is characterized by large specific surface, high pore volume, uniform porosity, and stable dispersion in aqueous medium, excellent biocompatibility, in vivo biodegradability and capacity to be functionalized with different organic groups. Therefore, MCM-41 is an attractive candidate for a wide range of biomedical applications, such as controlled drug release, bone regeneration, protein immobilization, enzymes, etc. The main advantage of this material lies in its ability to host a large amount of the active substance in uniform pore system with adjustable size in a mesoscopic range. Silanol groups allow surface controlled functionalization leading to control of drug loading and release. This study shows (I) the amino-grafting optimization of mesoporous MCM-41 silica matrix by means of co-condensation during synthesis and post-synthesis using APTES (3-aminopropyltriethoxysilane); (ii) loading the therapeutic agent (carmustine) obtaining a modified drug release systems; (iii) determining the profile of in vitro carmustine release from these systems; (iv) assessment of carmustine release kinetics by fitting on four mathematical models. Obtained powders have been described in terms of structure, texture, morphology thermogravimetric analysis. The concentration of the therapeutic agent in the dissolution medium has been determined by HPLC method. In vitro dissolution tests have been done using cell Enhancer in a 12 hours interval. Analysis of carmustine release kinetics from mesoporous systems was made by fitting to zero-order model, first-order model Higuchi model and Korsmeyer-Peppas model, respectively. Results showed that both types of highly ordered mesoporous silica (amino grafted by co-condensation process or post-synthesis) are thermally stable in aqueous medium. In what regards the degree of loading and efficiency of loading with the therapeutic agent, there has been noticed an increase of around 10% in case of co-condensation method application. This result shows that direct co-condensation leads to even distribution of amino groups on the pore walls while in case of post-synthesis grafting many amino groups are concentrated near the pore opening and/or on external surface. In vitro dissolution tests showed an extended carmustine release (more than 86% m/m) both from systems based on silica functionalized directly by co-condensation and after synthesis. Assessment of carmustine release kinetics revealed a release through diffusion from all studied systems as a result of fitting to Higuchi model. The results of this study proved that amino-functionalized mesoporous silica may be used as a matrix for optimizing the anti-cancer topical therapy by loading carmustine and developing prolonged-release systems.

Keywords: carmustine, silica, controlled, release

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Authors: Nikola Toshikj, Michel Ramonda, Sylvain Catrouillet, Jean-Jacques Robin, Sebastien Blanquer

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Biodegradable and biocompatible block copolymers have risen as the golden materials in both medical and environmental applications. Moreover, if their architecture is of controlled manner, higher applications can be foreseen. In the meantime, organocatalytic ROP has been promoted as more rapid and immaculate route, compared to the traditional organometallic catalysis, towards efficient synthesis of block copolymer architectures. Therefore, herein we report novel organocatalytic pathway with guanidine molecules (TBD) for supported synthesis of trimethylene carbonate initiated by poly(caprolactone) as pre-polymer. Pristine PTMC-b-PCL-b-PTMC block copolymer structure, without any residual products and clear desired block proportions, was achieved under 1.5 hours at room temperature and verified by NMR spectroscopies and size-exclusion chromatography. Besides, when elaborating block copolymer films, further stability and amelioration of mechanical properties can be achieved via additional reticulation step of precedently methacrylated block copolymers. Subsequently, stimulated by the insufficient studies on the phase-separation/crystallinity relationship in these semi-crystalline block copolymer systems, their intrinsic thermal and morphology properties were investigated by differential scanning calorimetry and atomic force microscopy. Firstly, by DSC measurements, the block copolymers with χABN values superior to 20 presented two distinct glass transition temperatures, close to the ones of the respecting homopolymers, demonstrating an initial indication of a phase-separated system. In the interim, the existence of the crystalline phase was supported by the presence of melting temperature. As expected, the crystallinity driven phase-separated morphology predominated in the AFM analysis of the block copolymers. Neither crosslinking at melted state, hence creation of a dense polymer network, disturbed the crystallinity phenomena. However, the later revealed as sensible to rapid liquid nitrogen quenching directly from the melted state. Therefore, AFM analysis of liquid nitrogen quenched and crosslinked block copolymer films demonstrated a thermodynamically driven phase-separation clearly predominating over the originally crystalline one. These AFM films remained stable with their morphology unchanged even after 4 months at room temperature. However, as demonstrated by DSC analysis once rising the temperature above the melting temperature of the PCL block, neither the crosslinking nor the liquid nitrogen quenching shattered the semi-crystalline network, while the access to thermodynamical phase-separated structures was possible for temperatures under the poly (caprolactone) melting point. Precisely this coexistence of dual crosslinked/crystalline networks in the same copolymer structure allowed us to establish, for the first time, the shape-memory properties in such materials, as verified by thermomechanical analysis. Moreover, the response temperature to the material original shape depended on the block copolymer emplacement, hence PTMC or PCL as end-block. Therefore, it has been possible to reach a block copolymer with transition temperature around 40°C thus opening potential real-life medical applications. In conclusion, the initial study of phase-separation/crystallinity relationship in PTMC-b-PCL-b-PTMC block copolymers lead to the discovery of novel shape memory materials with superior properties, widely demanded in modern-life applications.

Keywords: biodegradable block copolymers, organocatalytic ROP, self-assembly, shape-memory

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Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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Authors: Carolyn Hatch, Laurent Simon

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Urban mobility and the transportation industry are undergoing a transformation, shifting from an auto production-consumption model that has dominated since the early 20th century towards new forms of personal and shared multi-modality [1]. This is shaped by key forces such as climate change, which has induced a shift in production and consumption patterns and efforts to decarbonize and improve transport services through, for instance, the integration of vehicle automation, electrification and mobility sharing [2]. Advanced innovation practices and platforms for experimentation and validation of new mobility products and services that are increasingly complex and multi-stakeholder-oriented are shaping this new world of mobility. Transportation hubs – such as airports - are emblematic of these disruptive forces playing out in the mobility industry. Airports are emerging as the core of innovation ecosystems on and around contemporary mobility issues, and increasingly recognized as complex public/private nodes operating in many societal dimensions [3,4]. These include urban development, sustainability transitions, digital experimentation, customer experience, infrastructure development and data exploitation (for instance, airports generate massive and often untapped data flows, with significant potential for use, commercialization and social benefit). Yet airport innovation practices have not been well documented in the innovation literature. This paper addresses this gap by proposing a model of airport innovation that aims to equip airport stakeholders to respond to these new and complex innovation needs in practice. The methodology involves: 1 – a literature review bringing together key research and theory on airport innovation management, open innovation and innovation ecosystems in order to evaluate airport practices through an innovation lens; 2 – an international benchmarking of leading airports and their innovation practices, including such examples as Aéroports de Paris, Schipol in Amsterdam, Changi in Singapore, and others; and 3 – semi-structured interviews with airport managers on key aspects of organizational practice, facilitated through a close partnership with the Airport Council International (ACI), a major stakeholder in this research project. Preliminary results find that the most successful airports are those that have shifted to a multi-stakeholder, platform ecosystem model of innovation. The recent entrance of new actors in airports (Google, Amazon, Accor, Vinci, Airbnb and others) have forced the opening of organizational boundaries to share and exchange knowledge with a broader set of ecosystem players. This has also led to new forms of governance and intermediation by airport actors to connect complex, highly distributed knowledge, along with new kinds of inter-organizational collaboration, co-creation and collective ideation processes. Leading airports in the case study have demonstrated a unique capacity to force traditionally siloed activities to “think together”, “explore together” and “act together”, to share data, contribute expertise and pioneer new governance approaches and collaborative practices. In so doing, they have successfully integrated these many disruptive change pathways and forced their implementation and coordination towards innovative mobility outcomes, with positive societal, environmental and economic impacts. This research has implications for: 1 - innovation theory, 2 - urban and transport policy, and 3 - organizational practice - within the mobility industry and across the economy.

Keywords: airport management, ecosystem, innovation, mobility, platform, transport hubs

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Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Damith Tennakoon, Mojgan Jadidi, Seyedreza Razavialavi

Abstract:

With recent advancements of automation in robotics, from self-driving cars to autonomous 4-legged quadrupeds, one industry that has been stagnant is the construction industry. The methodologies used in a modern-day construction site consist of arduous physical labor and the use of heavy machinery, which has not changed over the past few decades. The dangers of a modern-day construction site affect the health and safety of the workers due to performing tasks such as lifting and moving heavy objects and having to maintain unhealthy posture to complete repetitive tasks such as painting, installing drywall, and laying bricks. Further, training for heavy machinery is costly and requires a lot of time due to their complex control inputs. The main focus of this research is using immersive wearable technology and robotic arms to perform the complex and intricate skills of modern-day construction workers while alleviating the physical labor requirements to perform their day-to-day tasks. The methodology consists of mounting a stereo vision camera, the ZED Mini by Stereolabs, onto the end effector of an industrial grade robotic arm, streaming the video feed into the Virtual Reality (VR) Meta Quest 2 (Quest 2) head-mounted display (HMD). Due to the nature of stereo vision, and the similar field-of-views between the stereo camera and the Quest 2, human-vision can be replicated on the HMD. The main advantage this type of camera provides over a traditional monocular camera is it gives the user wearing the HMD a sense of the depth of the camera scene, specifically, a first-person view of the robotic arm’s end effector. Utilizing the built-in cameras of the Quest 2 HMD, open-source hand-tracking libraries from OpenXR can be implemented to track the user’s hands in real-time. A mixed-reality (XR) Unity application can be developed to localize the operator's physical hand motions with the end-effector of the robotic arm. Implementing gesture controls will enable the user to move the robotic arm and control its end-effector by moving the operator’s arm and providing gesture inputs from a distant location. Given that the end effector of the robotic arm is a gripper tool, gripping and opening the operator’s hand will translate to the gripper of the robot arm grabbing or releasing an object. This human-robot interaction approach provides many benefits within the construction industry. First, the operator’s safety will be increased substantially as they can be away from the site-location while still being able perform complex tasks such as moving heavy objects from place to place or performing repetitive tasks such as painting walls and laying bricks. The immersive interface enables precision robotic arm control and requires minimal training and knowledge of robotic arm manipulation, which lowers the cost for operator training. This human-robot interface can be extended to many applications, such as handling nuclear accident/waste cleanup, underwater repairs, deep space missions, and manufacturing and fabrication within factories. Further, the robotic arm can be mounted onto existing mobile robots to provide access to hazardous environments, including power plants, burning buildings, and high-altitude repair sites.

Keywords: construction automation, human-robot interaction, hand-tracking, mixed reality

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Authors: Jia H. Wong, Jingli Zhang, Habsah Mohamad, Iswatun H. Abdullah Ripain, Muhammad Bilal, Amelia J. Lloyd, Abdul A. Mohamed Yusoff, Jafri M. Abdullah

Abstract:

Epilepsy is one of the most common neurological diseases affecting more than 50 million of people worldwide. Epilepsy is a state of recurrent, spontaneous seizures with multiple syndromes and symptoms of different causes of brain dysfunction, prognosis, and treatments; characterized by transient, occasional and stereotyped interruptions of behavior whereby the excitatory-inhibitory activities within the central nervous system (CNS) are thrown out of balance due to various kinds of interferences. The goal of antiepileptic treatment is to enable patients to be free from seizures or to achieve control of seizures through surgical treatment and/or pharmacotherapy. Pharmacotherapy through AED plays an important role especially in countries with epilepsy treatment gap due to costs and availability of health facilities, skills and resources, yet there are about one-third of the people with epilepsy have drug-resistant seizures. Hence, this poses considerable challenges to the healthcare system and the effort in providing cost-effective treatment as well as the search for alternatives to treatment and management of epilepsy. Enhancement of γ-aminobutyric acid (GABA)-mediated inhibitory neurotransmission is one of the key mechanisms of actions of antiepileptic drugs. GABA type > a receptors (GABAAR) are ligand-gated ion channels that mediate rapid inhibitory neurotransmission upon the binding of GABA with a heteropentameric structure forming a central pore that is permeable to the influx of chloride ions in its activated state. The major isoform of GABAA receptors consists of two α1, two β2, and one γ2 subunit. It is the most abundantly expressed combinations in the brain and the most commonly researched through Xenopus laevis oocytes. With the advancing studies on ethnomedicine and traditional treatments using medicinal plants, increasing evidence reveal that spice and herb plants with medicinal properties play an important role in the treatment of ailments within communities across different cultures. Capsaicin is the primary natural capsaicinoid in hot peppers of plant genus Capsicum, consist of an aromatic ring, an amide linkage and a hydrophobic side chain. The study showed that capsaicins conferred neuroprotection in status epilepticus mouse models through anti-ictogenic, hypothermic, antioxidative, anti-inflammatory, and anti-apoptotic actions in a dose-dependent manner. In this study, five capsaicin derivatives were tested for their ability to increase the GABA-induced chloride current on α1β2γ2S of GABAAR expressed on Xenopus laevis oocytes using the method of two-microelectrode voltage clamp. Two of the capsaicin derivatives, IS5 (N-(4-hydroxy-3-methoxybenzyl)-3-methylbutyramide) and IS10 (N-(4-hydroxy-3-methoxybenzyl)-decanamide) at a concentration of 30µM were able to significantly increase the GABA-induced chloride current with p=0.002 and p=0.026 respectively. This study were able to show the enhancement effect of two capsaicin derivatives with moderate length of hydrocarbon chain on this receptor subtype, revealing the promising inhibitory activity of capsaicin derivatives through enhancement of GABA-induced chloride current and further investigations should be carried out to verify its antiepileptic effects in animal models.

Keywords: α1β2γ2 GABAA receptors, α1β2γ2S, antiepileptic, capsaicin derivatives, two-microelectrode voltage clamp, Xenopus laevis oocytes

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Authors: Leila Noori, Rosario Barone, Francesca Rappa, Antonella Marino Gammazza, Alessandra Maria Vitale, Giuseppe Donato Mangano, Giusy Sentiero, Filippo Macaluso, Kathryn H. Myburgh, Francesco Cappello, Federica Scalia

Abstract:

The neuromuscular system controls, directs, and allows movement of the body through the action of neural circuits, which include motor neurons, sensory neurons, and skeletal muscle fibers. Protein homeostasis of the involved cytotypes appears crucial to maintain the correct and prolonged functions of the neuromuscular system, and both neuronal cells and skeletal muscle fibers express significant quantities of protein chaperones, the molecular machinery responsible to maintain the protein turnover. Genetic mutations or defective post-translational modifications of molecular chaperones (i.e., genetic or acquired chaperonopathies) may lead to neuromuscular disorders called as neurochaperonopathies. The limited knowledge of the effects of the defective chaperones on skeletal muscle fibers and neurons impedes the progression of therapeutic approaches. A distinct genetic variation of CCT5 gene encoding for the subunit 5 of the chaperonin CCT (Chaperonin Containing TCP1; also known as TRiC, TCP1 Ring Complex) was recently described associated with severe distal motor neuropathy by our team. In this study, we investigated the histopathological abnormalities of the skeletal muscle biopsy of the pediatric patient affected by the mutation Leu224Val in the CCT5 subunit. We provide molecular and structural features of the diseased skeletal muscle tissue that we believe may be useful to identify undiagnosed cases of this rare genetic disorder. We investigated the histological abnormalities of the affected tissue via hematoxylin and eosin staining. Then we used immunofluorescence and qPCR techniques to explore the expression and distribution of CCT5 in diseased and healthy skeletal muscle tissue. Immunofluorescence and immunohistochemistry assays were performed to study the sarcomeric and structural proteins of skeletal muscle, including actin, myosin, tubulin, troponin-T, telethonin, and titin. We performed Western blot to examine the protein expression of CCT5 and some heat shock proteins, Hsp90, Hsp60, Hsp27, and α-B crystallin, along with the main client proteins of the CCT5, actin, and tubulin. Our findings revealed muscular atrophy, abnormal morphology, and different sizes of muscle fibers in affected tissue. The swollen nuclei and wide interfiber spaces were seen. Expression of CCT5 had been decreased and showed a different distribution pattern in the affected tissue. Altered expression, distribution, and bandage pattern were detected by confocal microscopy for the interested muscular proteins in tissue from the patient compared to the healthy control. Protein levels of the studied Hsps normally located at the Z-disk were reduced. Western blot results showed increased levels of the actin and tubulin proteins in the diseased skeletal muscle biopsy compared to healthy tissue. Chaperones must be expressed at high levels in skeletal muscle to counteract various stressors such as mechanical, oxidative, and thermal crises; therefore, it seems relevant that defects of molecular chaperones may result in damaged skeletal muscle fibers. So far, several chaperones or cochaperones involved in neuromuscular disorders have been defined. Our study shows that alteration of the CCT5 subunit is associated with the damaged structure of skeletal muscle fibers and alterations of chaperone system components and paves the way to explore possible alternative substrates of chaperonin CCT. However, further studies are underway to investigate the CCT mechanisms of action to design applicable therapeutic strategies.

Keywords: molecular chaperones, neurochaperonopathy, neuromuscular system, protein homeostasis

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Authors: Chiu-Yin Leung

Abstract:

This research investigates a complex assemblage among indigenous identities, socio-political organization and national apparatus in the border landscape of post-colonial Hong Kong. This former British colony had designated a transient mode of governance in its New Territories and particularly the northernmost borderland in 1951-2012. With a discriminated system of land provisions for the indigenous villagers, the place has been inherited with distinctive village-based culture, historic monuments and agrarian practices until its sovereignty return into the People’s Republic of China. In its latest development imperatives by the national strategic planning, the frontier area of Hong Kong has been identified as a strategy site for regional economic integration in South China, with cross-border projects of innovation and technology zones, mega-transport infrastructure and inter-jurisdictional arrangement. Contemporary literature theorizes borders as the material and discursive production of territoriality, which manifest in state apparatus and the daily lives of its citizens and condense in the contested articulations of power, security and citizenship. Drawing on the concept of assemblage, this paper attempts to tract how the border regime and infrastructure in Hong Kong as a city are deeply ingrained in the everyday lived spaces of the local communities but also the changing urban and regional strategies across different longitudinal moments. Through an intensive ethnographic fieldwork among the borderland villages since 2008 and the extensive analysis of colonial archives, new development plans and spatial planning frameworks, the author navigates the genealogy of the border landscape in Ta Kwu Ling frontier area and its implications as the milieu for new state space, covering heterogeneous fields particularly in indigenous rights, heritage preservation, rural sustainability and regional economy. Empirical evidence suggests an apparent bias towards indigenous power and colonial representation in classifying landscape values and conserving historical monuments. Squatter and farm tenants are often deprived of property rights, statutory participation and livelihood option in the planning process. The postcolonial bureaucracies have great difficulties in mobilizing resources to catch up with the swift, political-first approach of the mainland counterparts. Meanwhile, the cultural heritage, lineage network and memory landscape are not protected altogether with any holistic view or collaborative effort across the border. The enactment of land resumption and compensation scheme is furthermore disturbed by lineage-based customary law, technocratic bureaucracy, intra-community conflicts and multi-scalar political mobilization. As many traces of colonial misfortune and tyranny have been whitewashed without proper management, the author argues that postcolonial justice is yet reconciled in this fragmented border landscape. The assemblage of border in mainstream representation has tended to oversimplify local struggles as a collective mist and setup a wider production of schizophrenia experiences in the discussion of further economic integration among Hong Kong and other mainland cities in the Pearl River Delta Region. The research is expected to shed new light on the theorizing of border regions and postcolonialism beyond Eurocentric perspectives. In reassembling the borderland experiences with other arrays in state governance, village organization and indigenous identities, the author also suggests an alternative epistemology in reconciling socio-spatial differences and opening up imaginaries for positive interventions.

Keywords: heritage conservation, indigenous communities, post-colonial borderland, regional development, rural sustainability

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Authors: Ali Kazemi

Abstract:

Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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