Search results for: increase work readiness

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: Irmak Karaduman, Tugba Corlu, Sezin Galioglu, Burcu Akata, M. Ali Yildirim, Aytunç Ateş, Selim Acar

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Breath analysis represents a promising non-invasive, fast and cost-effective alternative to well-established diagnostic and monitoring techniques such as blood analysis, endoscopy, ultrasonic and tomographic monitoring. Portable, non-invasive, and low-cost breath analysis devices are becoming increasingly desirable for monitoring different diseases, especially asthma. Beacuse of this, NO gas sensing at low concentrations has attracted progressive attention for clinical analysis in asthma. Recently, nanomaterials based sensors are considered to be a promising clinical and laboratory diagnostic tool, because its large surface–to–volume ratio, controllable structure, easily tailored chemical and physical properties, which bring high sensitivity, fast dynamic processand even the increasing specificity. Among various nanomaterials, semiconducting metal oxides are extensively studied gas-sensing materials and are potential sensing elements for breathanalyzer due to their high sensitivity, simple design, low cost and good stability.The sensitivities of metal oxide semiconductor gas sensors can be enhanced by adding noble metals. Doping contents, distribution, and size of metallic or metal oxide catalysts are key parameters for enhancing gas selectivity as well as sensitivity. By manufacturing doping MOS structures, it is possible to develop more efficient sensor sensing layers. Zeolites are perhaps the most widely employed group of silicon-based nanoporous solids. Their well-defined pores of sub nanometric size have earned them the name of molecular sieves, meaning that operation in the size exclusion regime is possible by selecting, among over 170 structures available, the zeolite whose pores allow the pass of the desired molecule, while keeping larger molecules outside.In fact it is selective adsorption, rather than molecular sieving, the mechanism that explains most of the successful gas separations achieved with zeolite membranes. In view of their molecular sieving and selective adsorption properties, it is not surprising that zeolites have found use in a number of works dealing with gas sensing devices. In this study, the Cu doped ZnO nanostructure film was produced by SILAR method and investigated the NO gas sensing properties. To obtain the selectivity of the sample, the gases including CO,NH3,H2 and CH4 were detected to compare with NO. The maximum response is obtained at 85 C for 20 ppb NO gas. The sensor shows high response to NO gas. However, acceptable responses are calculated for CO and NH3 gases. Therefore, there are no responses obtain for H2 and CH4 gases. Enhanced to selectivity, Cu doped ZnO nanostructure film was coated with zeolite A thin film. It is found that the sample possess an acceptable response towards NO hardly respond to CO, NH3, H2 and CH4 at room temperature. This difference in the response can be expressed in terms of differences in the molecular structure, the dipole moment, strength of the electrostatic interaction and the dielectric constant. The as-synthesized thin film is considered to be one of the extremely promising candidate materials in electronic nose applications. This work is supported by The Scientific and Technological Research Council of Turkey (TUBİTAK) under Project No, 115M658 and Gazi University Scientific Research Fund under project no 05/2016-21.

Keywords: Cu doped ZnO, electrical characterization, gas sensing, zeolite

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Authors: George Charkoftakis, Panagiotis Liosatos, Nicolas-Alexander Tatlas, Dimitrios Goustouridis, Stelios M. Potirakis

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E-maintenance is a relatively new concept, generally referring to maintenance management by monitoring assets over the Internet. One of the key links in the chain of an e-maintenance system is data acquisition and transmission. Specifically for the case of a fleet of heavy-duty vehicles, where the main challenge is the diversity of the vehicles and vehicle-embedded self-diagnostic/reporting technologies, the design of the data acquisition and transmission unit is a demanding task. This clear if one takes into account that a heavy-vehicles fleet assortment may range from vehicles with only a limited number of analog sensors monitored by dashboard light indicators and gauges to vehicles with plethora of sensors monitored by a vehicle computer producing digital reporting. The present work proposes an adaptable internet of things (IoT) sensor node that is capable of addressing this challenge. The proposed sensor node architecture is based on the increasingly popular single-board computer – expansion boards approach. In the proposed solution, the expansion boards undertake the tasks of position identification by means of a global navigation satellite system (GNSS), cellular connectivity by means of 3G/long-term evolution (LTE) modem, connectivity to on-board diagnostics (OBD), and connectivity to analog and digital sensors by means of a novel design of expansion board. Specifically, the later provides eight analog plus three digital sensor channels, as well as one on-board temperature / relative humidity sensor. The specific device offers a number of adaptability features based on appropriate zero-ohm resistor placement and appropriate value selection for limited number of passive components. For example, although in the standard configuration four voltage analog channels with constant voltage sources for the power supply of the corresponding sensors are available, up to two of these voltage channels can be converted to provide power to the connected sensors by means of corresponding constant current source circuits, whereas all parameters of analog sensor power supply and matching circuits are fully configurable offering the advantage of covering a wide variety of industrial sensors. Note that a key feature of the proposed sensor node, ensuring the reliable operation of the connected sensors, is the appropriate supply of external power to the connected sensors and their proper matching to the IoT sensor node. In standard mode, the IoT sensor node communicates to the data center through 3G/LTE, transmitting all digital/digitized sensor data, IoT device identity, and position. Moreover, the proposed IoT sensor node offers WiFi connectivity to mobile devices (smartphones, tablets) equipped with an appropriate application for the manual registration of vehicle- and driver-specific information, and these data are also forwarded to the data center. All control and communication tasks of the IoT sensor node are performed by dedicated firmware. It is programmed with a high-level language (Python) on top of a modern operating system (Linux). Acknowledgment: This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH—CREATE—INNOVATE (project code: T1EDK- 01359, IntelligentLogger).

Keywords: IoT sensor nodes, e-maintenance, single-board computers, sensor expansion boards, on-board diagnostics

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Authors: Jonas Volungevicius, Kristina Amaleviciute, Rimantas Vaisvalavicius, Alvyra Slepetiene, Darijus Veteikis

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Lithuanian territory is characterized by landscape with prevailing morain hills and clayey lowlands. The largest part of it has endured agrogenization of various degrees which was the cause of changes both in the structure of landscape and soil cover, transformations of soil profile and degradation of natural background soils. These changes influence negatively geoecological potential of landscape and soil and contribute to the weakening of the sustainability of agroecosystems. Research objective: to reveal the landscape agrogenization induced alterations of catenae and their appendant soil profiles in Lithuanian morain hills and clayey lowlands. Methods: Soil cover analysis and catenae charting was conducted using landscape profiling; soil morphology detected and soil type identified following WRB 2014. Granulometric composition of soil profiles was obtained by laser diffraction method (lazer diffractometer Mastersizer 2000). pH was measured in H2O extraction using potentiometric titration; SOC was determined by the Tyurin method modified by Nikitin, measuring with spectrometer Cary 50 (VARIAN) in 590 nm wavelength using glucose standards. Results: analysis showed that the decrease of forest vegetation and the other natural landscape components following the agrogenization of the research area influenced differently but significantly the structural alterations in soil cover and vertical soil profile. The research detected that due to landscape agrogenization, the suppression of zone-specific processes and the intensification of inter-zone processes determined by agrogenic factors take place in Lithuanian agroecosystems. In forested hills historically prevailing Retisols and Histosols territorial complex is transforming into the territorial complex of Regosols, Deluvial soils and drained Histosols. Processes taking place are simplification of vertical profile structure, intensive rejuvenation of profile, disappearance of the features of zone-specific soil-forming processes (podzolization, lessivage, gley formation). Erosion and deluvial processes manifest more intensively and weakly accumulating organic material more intensively spread in a vertical soil profile. The territorial soil complex of Gleyic Luvisols and Gleysols dominating in forested clayey lowlands subjected to agrogenization is transformed into the catena of drained Luvisols and pseudo Cambisols. The best expressed are their changes in moisture regime (morphological features of gley and stagnic properties are on decline) together with alterations of pH and distribution and intensity of accumulation of organic matter in profile. A specific horizon, antraquic, uncharacteristic to natural soil formation is appearing. Important to note that due to deep ploughing and other agrotechnical measures, the natural vertical differentiation of clay particles in a soil profile is destroyed which leads not only to alterations of physical qualities of soil, but also encumbers the identification of Luvisols by creating presumptions to misidentify them as Cambisols. The latter have never developed in these ecosystems under the present climatic conditions. Acknowledgements: This work was supported by the National Science Program: The effect of long-term, different-intensity management of resources on the soils of different genesis and on other components of the agro-ecosystems [grant number SIT-9/2015] funded by the Research Council of Lithuania.

Keywords: agroecosystems, landscape agrogenization, luvisols, retisols, transformation of soil profile

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Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

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Authors: Kavita Goel, Donald Winchester

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In a world of information overload and work complexities, academics often struggle to create an online instructional environment enabling efficient and effective student learning. Research has established that students’ learning styles are different, some learn faster when taught using audio and visual methods. Attributes like prior knowledge and mental effort affect their learning. ‘Cognitive load theory’, opines learners have limited processing capacity. Cognitive load depends on the learner’s prior knowledge, the complexity of content and tasks, and instructional environment. Hence, the proper allocation of cognitive resources is critical for students’ learning. Consequently, a lecturer needs to understand the limits and strengths of the human learning processes, various learning styles of students, and accommodate these requirements while designing online assessments. As acknowledged in the cognitive load theory literature, visual and auditory explanations of worked examples potentially lead to a reduction of cognitive load (effort) and increased facilitation of learning when compared to conventional sequential text problem solving. This will help learner to utilize both subcomponents of their working memory. Instructional design changes were introduced at the case site for the delivery of the postgraduate business subjects. To make effective use of auditory and visual modalities, video recorded lectures, and key concept webinars were delivered to students. Videos were prepared to free up student limited working memory from irrelevant mental effort as all elements in a visual screening can be viewed simultaneously, processed quickly, and facilitates greater psychological processing efficiency. Most case study students in the postgraduate programs are adults, working full-time at higher management levels, and studying part-time. Their learning style and needs are different from other tertiary students. The purpose of the audio and visual interventions was to lower the students cognitive load and provide an online environment supportive to their efficient learning. These changes were expected to impact the student’s learning experience, their academic performance and retention favourably. This paper posits that these changes to instruction design facilitates students to integrate new knowledge into their long-term memory. A mixed methods case study methodology was used in this investigation. Primary data were collected from interviews and survey(s) of students and academics. Secondary data were collected from the organisation’s databases and reports. Some evidence was found that the academic performance of students does improve when new instructional design changes are introduced although not statistically significant. However, the overall grade distribution of student’s academic performance has changed and skewed higher which shows deeper understanding of the content. It was identified from feedback received from students that recorded webinars served as better learning aids than material with text alone, especially with more complex content. The recorded webinars on the subject content and assessments provides flexibility to students to access this material any time from repositories, many times, and this enhances students learning style. Visual and audio information enters student’s working memory more effectively. Also as each assessment included the application of the concepts, conceptual knowledge interacted with the pre-existing schema in the long-term memory and lowered student’s cognitive load.

Keywords: cognitive load theory, learning style, instructional environment, working memory

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Authors: Adewale Tolulope Irewale, Elias Emeka Elemike, Christian O. Dimkpa, Emeka Emmanuel Oguzie

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As the global population steadily approaches the 10billion mark, the world is currently faced with two major challenges among others – accessing sustainable and clean energy, and food security. Accessing cleaner and sustainable energy sources to drive global economy and technological advancement, and feeding the teeming human population require sustainable, innovative, and smart solutions. To solve the food production problem, producers have relied on fertilizers as a way of improving crop productivity. Commercial inorganic fertilizers, which is employed to boost agricultural food production, however, pose significant ecological sustainability and economic problems including soil and water pollution, reduced input efficiency, development of highly resistant weeds, micronutrient deficiency, soil degradation, and increased soil toxicity. These ecological and sustainability concerns have raised uncertainties about the continued effectiveness of conventional fertilizers. With the application of nanotechnology, plant biomass upcycling offers several advantages in greener energy production and sustainable agriculture through reduction of environmental pollution, increasing soil microbial activity, recycling carbon thereby reducing GHG emission, and so forth. This innovative technology has the potential for a circular economy and creating a sustainable agricultural practice. Nanomaterials have the potential to greatly enhance the quality and nutrient composition of organic biomass which in turn, allows for the conversion of biomass into nanofertilizers that are potentially more efficient. Water hyacinth plant harvested from an inland water at Warri, Delta State Nigeria were air-dried and milled into powder form. The dry biomass were used to prepare biochar at a pre-determined temperature in an oxygen deficient atmosphere. Physicochemical analysis of the resulting biochar was carried out to determine its porosity and general morphology using the Scanning Transmission Electron Microscopy (STEM). The functional groups (-COOH, -OH, -NH2, -CN, -C=O) were assessed using the Fourier Transform InfraRed Spectroscopy (FTIR) while the heavy metals (Cr, Cu, Fe, Pb, Mg, Mn) were analyzed using Inductively Coupled Plasma – Optical Emission Spectrometry (ICP-OES). Impregnation of the biochar with nanonutrients were achieved under varied conditions of pH, temperature, nanonutrient concentrations and resident time to achieve optimum adsorption. Adsorption and desorption studies were carried out on the resulting nanofertilizer to determine kinetics for the potential nutrients’ bio-availability to plants when used as green fertilizers. Water hyacinth (Eichhornia crassipes) which is an aggressively invasive aquatic plant known for its rapid growth and profusion is being examined in this research to harness its biomass as a sustainable feedstock to formulate functionalized nano-biochar fertilizers, offering various benefits including water hyacinth biomass upcycling, improved nutrient delivery to crops and aquatic ecosystem remediation. Altogether, this work aims to create output values in the three dimensions of environmental, economic, and social benefits.

Keywords: biochar-based nanofertilizers, eichhornia crassipes, greener agriculture, sustainable ecosystem, water hyacinth

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Authors: L. Calcagni, A. Battisti, M. Hensel, D. S. Hensel

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Since the beginning of the 21st century, we have seen a dynamic growth of water-based (WB) architecture, mainly due to the increasing threat of floods caused by sea level rise and heavy rains, all correlated with climate change. At the same time, the shortage of land available for urban development also led architects, engineers, and policymakers to reclaim the seabed or to build floating structures. Furthermore, the drive to produce energy from renewable resources has expanded the sector of offshore research, mining, and energy industry which seeks new types of WB structures. In light of these considerations, the time is ripe to consider floating architecture as a full-fledged building typology. Currently, there is no universally recognized academic definition of a floating building. Research on floating architecture lacks a proper, commonly shared vocabulary and typology distinction. Moreover, there is no global international legal framework for urban development on water, and there is no structured performance based building design (PBBD) approach for floating architecture in most countries, let alone national regulatory systems. Thus, first of all, the research intends to overcome the semantic and typological issues through the conceptualization of floating architecture, laying the proto-ontological conditions for floating development, and secondly to identify the parameters to be considered in the definition of a specific PBBD framework, setting the scene for national planning strategies. The theoretical overview and re-semanticization process involve the attribution of a new meaning to the term floating architecture. This terminological work of semantic redetermination is carried out through a systematic literature review and involves quantitative and historical research as well as logical argumentation methods. As it is expected that floating urban development is most likely to take place as an extension of coastal areas, the needs and design criteria are definitely more similar to those of the urban environment than to those of the offshore industry. Therefore, the identification and categorization of parameters –looking towards the potential formation of a PBBD framework for floating development– takes the urban and architectural guidelines and regulations as the starting point, taking the missing aspects, such as hydrodynamics (i.e. stability and buoyancy) from the offshore and shipping regulatory frameworks. This study is carried out through an evidence-based assessment of regulatory systems that are effective in different countries around the world, addressing on-land and on-water architecture as well as offshore and shipping industries. It involves evidence-based research and logical argumentation methods. Overall, inhabiting water is proposed not only as a viable response to the problem of rising sea levels, thus as a resilient frontier for urban development, but also as a response to energy insecurity, clean water, and food shortages, environmental concerns, and urbanization, in line with Blue Economy principles and the Agenda 2030. This review shows how floating architecture is to all intents and purposes, an urban adaptation measure and a solution towards self-sufficiency and energy-saving objectives. Moreover, the adopted methodology is, to all extents, open to further improvements and integrations, thus not rigid and already completely determined. Along with new designs and functions that will come into play in the practice field, eventually, life on water will seem no more unusual than life on land, especially by virtue of the multiple advantages it provides not only to users but also to the environment.

Keywords: adaptation measures, building typology, floating architecture, performance based building design, rising sea levels

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Authors: Areti Okalidou, Paul D. Hatzigiannakoglou, Aikaterini Vatou, George Kyriafinis

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Young children are nowadays adept at using technology. Hence, computer-based auditory training programs (CBATPs) have become increasingly popular in aural rehabilitation for children with hearing loss and/or with cochlear implants (CI). Yet, their clinical utility for prognostic, diagnostic, and monitoring purposes has not been explored. The purposes of the study were: a) to develop an updated version of the auditory rehabilitation tool for Greek-speaking children with cochlear implants, b) to develop a database for behavioral responses, and c) to compare accuracy rates and reaction times in children differing in hearing status and other medical and demographic characteristics, in order to assess the tool’s clinical utility in prognosis, diagnosis, and progress monitoring. The updated version of the auditory rehabilitation tool was developed on a tablet, retaining the User-Centered Design approach and the elements of the Virtual Reality (VR) serious game. The visual stimuli were farm animals acting in simple game scenarios designed to trigger children’s responses to animal sounds, names, and relevant sentences. Based on an extended version of Erber’s auditory development model, the VR game consisted of six stages, i.e., sound detection, sound discrimination, word discrimination, identification, comprehension of words in a carrier phrase, and comprehension of sentences. A familiarization stage (learning) was set prior to the game. Children’s tactile responses were recorded as correct, false, or impulsive, following a child-dependent set up of a valid delay time after stimulus offset for valid responses. Reaction times were also recorded, and the database was in Εxcel format. The tablet version of the auditory rehabilitation tool was piloted in 22 preschool children with Νormal Ηearing (ΝΗ), which led to improvements. The study took place in clinical settings or at children’s homes. Fifteen children with CI, aged 5;7-12;3 years with post-implantation 0;11-5;1 years used the auditory rehabilitation tool. Eight children with CI were monolingual, two were bilingual and five had additional disabilities. The control groups consisted of 13 children with ΝΗ, aged 2;6-9;11 years. A comparison of both accuracy rates, as percent correct, and reaction times (in sec) was made at each stage, across hearing status, age, and also, within the CI group, based on presence of additional disability and bilingualism. Both monolingual Greek-speaking children with CI with no additional disabilities and hearing peers showed high accuracy rates at all stages, with performances falling above the 3rd quartile. However, children with normal hearing scored higher than the children with CI, especially in the detection and word discrimination tasks. The reaction time differences between the two groups decreased in language-based tasks. Results for children with CI with additional disability or bilingualism varied. Finally, older children scored higher than younger ones in both groups (CI, NH), but larger differences occurred in children with CI. The interactions between familiarization of the software, age, hearing status and demographic characteristics are discussed. Overall, the VR game is a promising tool for tracking the development of auditory skills, as it provides multi-level longitudinal empirical data. Acknowledgment: This work is part of a project that has received funding from the Research Committee of the University of Macedonia under the Basic Research 2020-21 funding programme.

Keywords: VR serious games, auditory rehabilitation, auditory training, children with cochlear implants

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Authors: Ho-Ting Wu, Kai-Wei Ke, Bo-Yu Huang, Liang-Lin Yan, Chun-Ting Lin

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With the advances in advanced technology, wireless sensor network (WSN) has become one of the most promising candidates to implement the wireless industrial internet of things (IIOT) architecture. However, the legacy IEEE 802.15.4 based WSN technology such as Zigbee system cannot meet the stringent QoS requirement of low powered, real-time, and highly reliable transmission imposed by the IIOT environment. Recently, the IEEE society developed IEEE 802.15.4e Time Slotted Channel Hopping (TSCH) access mode to serve this purpose. Furthermore, the IETF 6TiSCH working group has proposed standards to integrate IEEE 802.15.4e with IPv6 protocol smoothly to form a complete protocol stack for IIOT. In this work, we develop key network technologies for IEEE 802.15.4e based wireless IIoT architecture, focusing on practical design and system implementation. We realize the OpenWSN-based wireless IIOT system. The system architecture is divided into three main parts: web server, network manager, and sensor nodes. The web server provides user interface, allowing the user to view the status of sensor nodes and instruct sensor nodes to follow commands via user-friendly browser. The network manager is responsible for the establishment, maintenance, and management of scheduling and topology information. It executes centralized scheduling algorithm, sends the scheduling table to each node, as well as manages the sensing tasks of each device. Sensor nodes complete the assigned tasks and sends the sensed data. Furthermore, to prevent scheduling error due to packet loss, a schedule inspection mechanism is implemented to verify the correctness of the schedule table. In addition, when network topology changes, the system will act to generate a new schedule table based on the changed topology for ensuring the proper operation of the system. To enhance the system performance of such system, we further propose dynamic bandwidth allocation and distributed scheduling mechanisms. The developed distributed scheduling mechanism enables each individual sensor node to build, maintain and manage the dedicated link bandwidth with its parent and children nodes based on locally observed information by exchanging the Add/Delete commands via two processes. The first process, termed as the schedule initialization process, allows each sensor node pair to identify the available idle slots to allocate the basic dedicated transmission bandwidth. The second process, termed as the schedule adjustment process, enables each sensor node pair to adjust their allocated bandwidth dynamically according to the measured traffic loading. Such technology can sufficiently satisfy the dynamic bandwidth requirement in the frequently changing environments. Last but not least, we propose a packet retransmission scheme to enhance the system performance of the centralized scheduling algorithm when the packet delivery rate (PDR) is low. We propose a multi-frame retransmission mechanism to allow every single network node to resend each packet for at least the predefined number of times. The multi frame architecture is built according to the number of layers of the network topology. Performance results via simulation reveal that such retransmission scheme is able to provide sufficient high transmission reliability while maintaining low packet transmission latency. Therefore, the QoS requirement of IIoT can be achieved.

Keywords: IEEE 802.15.4e, industrial internet of things (IIOT), scheduling mechanisms, wireless sensor networks (WSN)

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Authors: Shuai Yuan, Minxia Shi, Xu Zhang, Jianzhi Yang, Kangqi Tian, Yuzheng Ma

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The precise measurement of muscle activities is essential for understanding the function of various body movements. This work aims to develop a muscle magnetic field signal detection system based on mathematical analysis. Medical research has underscored that early detection of muscle atrophy, coupled with lifestyle adjustments such as dietary control and increased exercise, can significantly enhance muscle-related diseases. Currently, surface electromyography (sEMG) is widely employed in research as an early predictor of muscle atrophy. Nonetheless, the primary limitation of using sEMG to forecast muscle strength is its inability to directly measure the signals generated by muscles. Challenges arise from potential skin-electrode contact issues due to perspiration, leading to inaccurate signals or even signal loss. Additionally, resistance and phase are significantly impacted by adipose layers. The recent emergence of optically pumped magnetometers introduces a fresh avenue for bio-magnetic field measurement techniques. These magnetometers possess high sensitivity and obviate the need for a cryogenic environment unlike superconducting quantum interference devices (SQUIDs). They detect muscle magnetic field signals in the range of tens to thousands of femtoteslas (fT). The utilization of magnetometers for capturing muscle magnetic field signals remains unaffected by issues of perspiration and adipose layers. Since their introduction, optically pumped atomic magnetometers have found extensive application in exploring the magnetic fields of organs such as cardiac and brain magnetism. The optimal operation of these magnetometers necessitates an environment with an ultra-weak magnetic field. To achieve such an environment, researchers usually utilize a combination of active magnetic compensation technology with passive magnetic shielding technology. Passive magnetic shielding technology uses a magnetic shielding device built with high permeability materials to attenuate the external magnetic field to a few nT. Compared with more layers, the coils that can generate a reverse magnetic field to precisely compensate for the residual magnetic fields are cheaper and more flexible. To attain even lower magnetic fields, compensation coils designed by Biot-Savart law are involved to generate a counteractive magnetic field to eliminate residual magnetic fields. By solving the magnetic field expression of discrete points in the target region, the parameters that determine the current density distribution on the plane can be obtained through the conventional target field method. The current density is obtained from the partial derivative of the stream function, which can be represented by the combination of trigonometric functions. Optimization algorithms in mathematics are introduced into coil design to obtain the optimal current density distribution. A one-dimensional linear regression analysis was performed on the collected data, obtaining a coefficient of determination R2 of 0.9349 with a p-value of 0. This statistical result indicates a stable relationship between the peak-to-peak value (PPV) of the muscle magnetic field signal and the magnitude of grip strength. This system is expected to be a widely used tool for healthcare professionals to gain deeper insights into the muscle health of their patients.

Keywords: muscle magnetic signal, magnetic shielding, compensation coils, trigonometric functions.

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Authors: Marija Mihajlovic Pereira

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Teaching and learning a musical instrument is challenging for both teachers and students. Teachers generally use diverse strategies to resolve students' particular issues in a one-to-one context. Considering individual sessions as a supportive educational context, the teacher can play a decisive role in stimulating and promoting self-regulated learning strategies, especially with beginning learners. The teachers who promote self-controlling behaviors, strategic monitoring, and regulation of actions toward goals could expect their students to practice more qualitatively and consciously. When encouraged to adopt self-regulation habits, students' could benefit from greater productivity on a longer path. Founded on Bary Zimmerman's cyclical model that comprehends three phases - forethought, performance, and self-reflection, this work aims to articulate self-regulated and music learning. Self-regulated learning appeals to the individual's attitude in planning, controlling, and reflecting on their performance. Furthermore, this study aimed to present an observation grid for perceiving teaching instructions that encourage students' controlling cognitive behaviors in light of the belief that conscious promotion of self-regulation may motivate strategic actions toward goals in musical performance. The participants, two teachers, and two students have been involved in the social inclusion project in Lisbon (Portugal). The author and one independent inter-observer analyzed six video-recorded string instrument lessons. The data correspond to three sessions per teacher lectured to one (different) student. Violin (f) and violoncello (m) teachers hold a Master's degree in music education and approximately five years of experience. In their second year of learning an instrument, students have acquired reasonable skills in musical reading, posture, and sound quality until then. The students also manifest positive learning behaviors, interest in learning a musical instrument, although their study habits are still inconsistent. According to the grid's four categories (parent codes), in-class rehearsal frames were coded using MaxQda software, version 20, according to the grid's four categories (parent codes): self-regulated learning, teaching verbalizations, teaching strategies, and students' in-class performance. As a result, selected rehearsal frames qualitatively describe teaching instructions that might promote students' body and hearing awareness, such as "close the eyes while playing" or "sing to internalize the pitch." Another analysis type, coding the short video events according to the observation grid's subcategories (child codes), made it possible to perceive the time teachers dedicate to specific verbal or non-verbal strategies. Furthermore, a coding overlay analysis indicated that teachers tend to stimulate. (i) Forethought – explain tasks, offer feedback and ensure that students identify a goal, (ii) Performance – teach study strategies and encourage students to sing and use vocal abilities to ensure inner audition, (iii) Self-reflection – frequent inquiring and encouraging the student to verbalize their perception of performance. Although developed in the context of individual string instrument lessons, this classroom observation grid brings together essential variables in a one-to-one lesson. It may find utility in a broader context of music education due to the possibility to organize, observe and evaluate teaching practices. Besides that, this study contributes to cognitive development by suggesting a practical approach to fostering self-regulated learning.

Keywords: music education, observation grid, self-regulated learning, string instruments, teaching practices

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Authors: Ankur Chaudhuri, Sibani Sen Chakraborty

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In human, glutaminyl cyclase activity is highly abundant in neuronal and secretory tissues and is preferentially restricted to hypothalamus and pituitary. The N-terminal modification of β-amyloids (Aβs) peptides by the generation of a pyro-glutamyl (pGlu) modified Aβs (pE-Aβs) is an important process in the initiation of the formation of neurotoxic plaques in Alzheimer’s disease (AD). This process is catalyzed by glutaminyl cyclase (QC). The expression of QC is characteristically up-regulated in the early stage of AD, and the hallmark of the inhibition of QC is the prevention of the formation of pE-Aβs and plaques. A computer-aided drug design (CADD) process was employed to give an idea for the designing of potentially active compounds to understand the inhibitory potency against human glutaminyl cyclase (QC). This work elaborates the ligand-based and structure-based pharmacophore exploration of glutaminyl cyclase (QC) by using the known inhibitors. Three dimensional (3D) quantitative structure-activity relationship (QSAR) methods were applied to 154 compounds with known IC50 values. All the inhibitors were divided into two sets, training-set, and test-sets. Generally, training-set was used to build the quantitative pharmacophore model based on the principle of structural diversity, whereas the test-set was employed to evaluate the predictive ability of the pharmacophore hypotheses. A chemical feature-based pharmacophore model was generated from the known 92 training-set compounds by HypoGen module implemented in Discovery Studio 2017 R2 software package. The best hypothesis was selected (Hypo1) based upon the highest correlation coefficient (0.8906), lowest total cost (463.72), and the lowest root mean square deviation (2.24Å) values. The highest correlation coefficient value indicates greater predictive activity of the hypothesis, whereas the lower root mean square deviation signifies a small deviation of experimental activity from the predicted one. The best pharmacophore model (Hypo1) of the candidate inhibitors predicted comprised four features: two hydrogen bond acceptor, one hydrogen bond donor, and one hydrophobic feature. The Hypo1 was validated by several parameters such as test set activity prediction, cost analysis, Fischer's randomization test, leave-one-out method, and heat map of ligand profiler. The predicted features were then used for virtual screening of potential compounds from NCI, ASINEX, Maybridge and Chembridge databases. More than seven million compounds were used for this purpose. The hit compounds were filtered by drug-likeness and pharmacokinetics properties. The selective hits were docked to the high-resolution three-dimensional structure of the target protein glutaminyl cyclase (PDB ID: 2AFU/2AFW) to filter these hits further. To validate the molecular docking results, the most active compound from the dataset was selected as a reference molecule. From the density functional theory (DFT) study, ten molecules were selected based on their highest HOMO (highest occupied molecular orbitals) energy and the lowest bandgap values. Molecular dynamics simulations with explicit solvation systems of the final ten hit compounds revealed that a large number of non-covalent interactions were formed with the binding site of the human glutaminyl cyclase. It was suggested that the hit compounds reported in this study could help in future designing of potent inhibitors as leads against human glutaminyl cyclase.

Keywords: glutaminyl cyclase, hit lead, pharmacophore model, simulation

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Authors: Daniele Lerede, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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The European Green Deal is the first internationally agreed set of measures to contrast climate change and environmental degradation. Besides the main target of reducing emissions by at least 55% by 2030, it sets the target of accompanying European countries through an energy transition to make the European Union into a modern, resource-efficient, and competitive net-zero emissions economy by 2050, decoupling growth from the use of resources and ensuring a fair adaptation of all social categories to the transformation process. While the general purpose to allow the realization of the purposes of the Green Deal already dates back to 2019, strategies and policies keep being developed coping with recent circumstances and achievements. However, general long-term measures like the Circular Economy Action Plan, the proposals to shift from fossil natural gas to renewable and low-carbon gases, in particular biomethane and hydrogen, and to end the sale of gasoline and diesel cars by 2035, will all have significant effects on energy supply and demand evolution across the next decades. The interactions between energy supply and demand over long-term time frames are usually assessed via energy system models to derive useful insights for policymaking and to address technological choices and research and development. TEMOA-Europe is a newly developed energy system optimization model instance based on the minimization of the total cost of the system under analysis, adopting a technologically integrated, detailed, and explicit formulation and considering the evolution of the system in partial equilibrium in competitive markets with perfect foresight. TEMOA-Europe is developed on the TEMOA platform, an open-source modeling framework totally implemented in Python, therefore ensuring third-party verification even on large and complex models. TEMOA-Europe is based on a single-region representation of the European Union and EFTA countries on a time scale between 2005 and 2100, relying on a set of assumptions for socio-economic developments based on projections by the International Energy Outlook and a large technological dataset including 7 sectors: the upstream and power sectors for the production of all energy commodities and the end-use sectors, including industry, transport, residential, commercial and agriculture. TEMOA-Europe also includes an updated hydrogen module considering its production, storage, transportation, and utilization. Besides, it can rely on a wide set of innovative technologies, ranging from nuclear fusion and electricity plants equipped with CCS in the power sector to electrolysis-based steel production processes and steel in the industrial sector – with a techno-economic characterization based on public literature – to produce insightful energy scenarios and especially to cope with the very long analyzed time scale. The aim of this work is to examine in detail the scheme of measures and policies for the realization of the purposes of the Green Deal and to transform them into a set of constraints and new socio-economic development pathways. Based on them, TEMOA-Europe will be used to produce and comparatively analyze scenarios to assess the consequences of Green Deal-related measures on the future evolution of the energy mix over the whole energy system in an economic optimization environment.

Keywords: European Green Deal, energy system optimization modeling, scenario analysis, TEMOA-Europe

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Authors: Chia-Jung Chen, Yu-Chi Hsu, June-Dong Lin, Kun-Chen Chan, Chieh-Tien Wang, Li-Ching Wu, Chung-Feng Liu

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With fast advances in healthcare technology, various total laboratory automation (TLA) processes have been proposed. However, adopting TLA needs quite high funding. This study explores an early adoption experience by Taiwan’s large-scale hospital group, the Chimei Hospital Group (CMG), which owns three branch hospitals (Yongkang, Liouying and Chiali, in order by service scale), based on the five stages of Everett Rogers’ Diffusion Decision Process. 1.Knowledge stage: Over the years, two weaknesses exists in laboratory department of CMG: 1) only a few examination categories (e.g., sugar testing and HbA1c) can now be completed and reported within a day during an outpatient clinical visit; 2) the Yongkang Hospital laboratory space is dispersed across three buildings, resulting in duplicated investment in analysis instruments and inconvenient artificial specimen transportation. Thus, the senior management of the department raised a crucial question, was it time to process the redesign of the laboratory department? 2.Persuasion stage: At the end of 2013, Yongkang Hospital’s new building and restructuring project created a great opportunity for the redesign of the laboratory department. However, not all laboratory colleagues had the consensus for change. Thus, the top managers arranged a series of benchmark visits to stimulate colleagues into being aware of and accepting TLA. Later, the director of the department proposed a formal report to the top management of CMG with the results of the benchmark visits, preliminary feasibility analysis, potential benefits and so on. 3.Decision stage: This TLA suggestion was well-supported by the top management of CMG and, finally, they made a decision to carry out the project with an instrument-leasing strategy. After the announcement of a request for proposal and several vendor briefings, CMG confirmed their laboratory automation architecture and finally completed the contracts. At the same time, a cross-department project team was formed and the laboratory department assigned a section leader to the National Taiwan University Hospital for one month of relevant training. 4.Implementation stage: During the implementation, the project team called for regular meetings to review the results of the operations and to offer an immediate response to the adjustment. The main project tasks included: 1) completion of the preparatory work for beginning the automation procedures; 2) ensuring information security and privacy protection; 3) formulating automated examination process protocols; 4) evaluating the performance of new instruments and the instrument connectivity; 5)ensuring good integration with hospital information systems (HIS)/laboratory information systems (LIS); and 6) ensuring continued compliance with ISO 15189 certification. 5.Confirmation stage: In short, the core process changes include: 1) cancellation of signature seals on the specimen tubes; 2) transfer of daily examination reports to a data warehouse; 3) routine pre-admission blood drawing and formal inpatient morning blood drawing can be incorporated into an automatically-prepared tube mechanism. The study summarizes below the continuous improvement orientations: (1) Flexible reference range set-up for new instruments in LIS. (2) Restructure of the specimen category. (3) Continuous review and improvements to the examination process. (4) Whether installing the tube (specimen) delivery tracks need further evaluation.

Keywords: innovation decision process, total laboratory automation, health care

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Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

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Authors: Eeva Wallenius-Nareneva, Tuula Toivanen-Labiad

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Background: Oral health promotion event was organised for forty Afghanistan, Iraqi and Bangladeshi underage asylum seekers in Finland. The invitation to arrange this coaching occasion was accepted in the Degree Programme in Oral Hygiene in Metropolia. The personnel in the reception center found the need to improve oral health among the youngsters. The purpose was to strengthen the health literacy of the boys in their oral self-care and to reduce dental fears. The Finnish studies, especially the terminology of oral health was integrated to coaching with the help of interpreters. Cooperative learning was applied. Methods: Oral health was interactively discussed in four study group sessions: 1. The importance of healthy eating habits; - Good and bad diets, - Regular meals, - Acid attack o Xylitol. 2. Oral diseases − connection to general health; - Aetiology of gingivitis, periodontitis and caries, - Harmfulness of smoking 3. Tools and techniques for oral self-care; - Brushing and inter dental cleaning. 4. Sharing earlier dental care experiences; - Cultural differences, - Dental fear, - Regular check-ups. Results: During coaching deficiencies appeared in brushing and inter dental cleaning techniques. Some boys were used to wash their mouth with salt justifying it by salt’s antiseptic properties. Many brushed their teeth by vertical movements. The boys took feedback positively when a demonstration with model jaws revealed the inefficiency of the technique. The advantages of fluoride tooth paste were advised. Dental care procedures were new and frightening for many boys. Finnish dental care system was clarified. The safety and indolence of the treatments and informed consent were highlighted. Video presentations and the dialog lowered substantially the threshold to visit dental clinic. The occasion gave the students means for meeting patients from different cultural and language backgrounds. The information hidden behind the oral health problems of the asylum seekers was valuable. Conclusions: Learning dental care practices used in different cultures is essential for dental professionals. The project was a good start towards multicultural oral health care. More experiences are needed before graduation. Health education themes should be held simple regardless of the target group. The heterogeneity of the group does not pose a problem. Open discussion with questions leading to the theme works well in clarifying the target group’s knowledge level. Sharing own experiences strengthens the sense of equality among the participants and encourages them to express own opinions. Motivational interview method turned out to be successful. In the future coaching occasions must confirm active participation of everyone. This could be realized by dividing the participants to even smaller groups. The different languages impose challenges but they can be solved by using more interpreters. Their presence ensures that everyone understands the issues properly although the use of plain and sign languages are helpful. In further development, it would be crucial to arrange a rehearsal occasion to the same participants in two/three months’ time. This would strengthen the adaption of self-care practices and give the youngsters opportunity to pose more open questions. The students would gain valuable feedback regarding the effectiveness of their work.

Keywords: cooperative learning, interactive methods, motivational interviewing, oral health promotion, underage asylum seekers

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Authors: Patrizia Firmani, Sara Perucchini, Irene Rapone, Raffella Borrelli, Stefano Chiaberge, Manuela Grande, Rosamaria Marrazzo, Alberto Savoini, Andrea Siviero, Silvia Spera, Fabio Vago, Davide Deriu, Sergio Fanutti, Alessandro Oldani

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According to the Renewable Energy Directive II, the use of palm oil in diesel will be gradually reduced from 2023 and should reach zero in 2030 due to the deforestation caused by its production. Eni aims at finding alternative feedstocks for its biorefineries to eliminate the use of palm oil by 2023. Therefore, the ideal vegetable oils to be used in bio-refineries are those obtainable from plants that grow in marginal lands and with low impact on food-and-feed chain; hence, Eni research is studying the possibility of using oleaginous seeds, such as castor, croton, and cotton, to extract the oils to be exploited as feedstock in bio-refineries. To verify their suitability for the upgrading processes, an analytical protocol for their characterization has been drawn up and applied. The analytical characterizations include a step of water and ashes content determination, elemental analysis (CHNS analysis, X-Ray Fluorescence, Inductively Coupled Plasma - Optical Emission Spectroscopy, ICP– Mass Spectrometry), and total acid number determination. Gas chromatography coupled to flame ionization detector (GC-FID) is used to quantify the lipid content in terms of free fatty acids, mono-, di- and triacylglycerols, and fatty acids composition. Eventually, Nuclear Magnetic Resonance and Fourier Transform-Infrared spectroscopies are exploited with GC-MS and Fourier Transform-Ion Cyclotron Resonance to study the composition of the oils. This work focuses on the GC-FID analysis of the lipid fraction of these oils, as the main constituent and of greatest interest for bio-refinery processes. Specifically, the lipid component of the extracted oil was quantified after sample silanization and transmethylation: silanization allows the elution of high-boiling compounds and is useful for determining the quantity of free acids and glycerides in oils, while transmethylation leads to a mixture of fatty acid esters and glycerol, thus allowing to evaluate the composition of glycerides in terms of Fatty Acids Methyl Esters (FAME). Cotton oil was extracted from cotton oilcake, croton oil was obtained by seeds pressing and seeds and oilcake ASE extraction, while castor oil comes from seed pressing (not performed in Eni laboratories). GC-FID analyses reported that the cotton oil is 90% constituted of triglycerides and about 6% diglycerides, while free fatty acids are about 2%. In terms of FAME, C18 acids make up 70% of the total and linoleic acid is the major constituent. Palmitic acid is present at 17.5%, while the other acids are in low concentration (<1%). Both analyzes show the presence of non-gas chromatographable compounds. Croton oils from seed pressing and extraction mainly contain triglycerides (98%). Concerning FAME, the main component is linoleic acid (approx. 80%). Oilcake croton oil shows higher abundance of diglycerides (6% vs ca 2%) and a lower content of triglycerides (38% vs 98%) compared to the previous oils. Eventually, castor oil is mostly constituted of triacylglycerols (about 69%), followed by diglycerides (about 10%). About 85.2% of total FAME is ricinoleic acid, as a constituent of triricinolein, the most abundant triglyceride of castor oil. Based on the analytical results, these oils represent feedstocks of interest for possible exploitation as advanced biofuels.

Keywords: analytical protocol, biofuels, biorefinery, gas chromatography, vegetable oil

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Authors: Oluwaseun Adeleke, Samuel O. Ikani, Fidelis Edet, Anthony Nwala, Mopelola Raji, Simeon Christian Chukwu

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Background: The DISC project collaborated with partners to implement demand creation and service delivery interventions, including the MoT (Moment of Truth) innovation, in over 500 health facilities across 15 states. This has increased the voluntary conversion rate to self-injection among women who opt for injectable contraception. While some facilities recorded an increasing trend in key performance indicators, few others persistently performed sub-optimally due to provider and system-related barriers. Methodology: Twenty-two facilities performing sub-optimally were selected purposively from three Nigerian states. Low productivity was appraised using low reporting rates and poor SI conversion rates as indicators. Interviews were conducted with health providers across these health facilities using a rapid diagnosis tool. The project also conducted a data quality assessment that evaluated the veracity of data elements reported across the three major sources of family planning data in the facility. Findings: The inability and sometimes refusal of providers to support clients to self-inject effectively was associated with the misunderstanding of its value to their work experience. It was also observed that providers still held a strong influence over clients’ method choices. Furthermore, providers held biases and misconceptions about DMPA-SC that restricted the access of obese clients and new acceptors to services – a clear departure from the recommendations of the national guidelines. Additionally, quality of care standards was compromised because job aids were not used to inform service delivery. Facilities performing sub-optimally often under-reported DMPA-SC utilization data, and there were multiple uncoordinated responsibilities for recording and reporting. Additionally, data validation meetings were not regularly convened, and these meetings were ineffective in authenticating data received from health facilities. Other reasons for sub-optimal performance included poor documentation and tracking of stock inventory resulting in commodity stockouts, low client flow because of poor positioning of health facilities, and ineffective messaging. Some facilities lacked adequate human and material resources to provide services effectively and received very few supportive supervision visits. Supportive supervision visits and Data Quality Audits have been useful to address the aforementioned performance barriers. The project has deployed digital DMPA-SC self-injection checklists that have been aligned with nationally approved templates. During visits, each provider and community mobilizer is accorded special attention by the supervisor until he/she can perform procedures in line with best practice (protocol). Conclusion: This narrative provides a summary of a range of factors that identify health facilities performing sub-optimally in their provision of DMPA-SC services. Findings from this assessment will be useful during project design to inform effective strategies. As the project enters its final stages of implementation, it is transitioning high-impact activities to state institutions in the quest to sustain the quality of service beyond the tenure of the project. The project has flagged activities, as well as created protocols and tools aimed at placing state-level stakeholders at the forefront of improving productivity in health facilities.

Keywords: family planning, contraception, DMPA-SC, self-care, self-injection, barriers, opportunities, performance

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Authors: Dawid Jakimiuk, Krzysztof Mitura, Leszek Szpakowski, Sławomir Pilip, Daniel Celiński

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The Emergency Medical Teams (EMS) of the Ambulance Service in Siedlce serve the population living in the Mazowieckie Voivodeship (the area of eastern Poland with approximately 550,000 inhabitants). They provide health services at the pre-hospital stage to all life-threatening patients. The analysis covered the interventions of emergency medical teams in cases of suicide attempts that occurred in the years 2015-2018. The study was retrospective. The data was obtained on the basis of digital medical records of completed call-outs. When defining the disease entity, the International Statistical Classification of Diseases and Health Problems ICD-10 prepared by WHO was used. The relationship between selected disease entities and the area of EMT intervention, the patient's sex and age, and the time of occurrence of the event were investigated. Non-urban area was defined as the area inhabited by a population below 10,000 residents. Statistical analysis was performed using Pearson's Chi ^ 2 test and presenting the percentage of cases in the study group. Of all the suicide attempts, drug abuse cases were the most frequent, including: X60 (Intentional self-poisoning by and exposure to nonopioid analgesics, antipyretics and antirheumatics); X61 (Intentional self-poisoning by and exposure to antiepileptic, sedative-hypnotic, antiparkinsonian and psychotropic drugs, not elsewhere classified); X62 (Intentional self-poisoning by and exposure to narcotics and psycholeptics [hallucinogens], not elsewhere classified); X63 (Intentional self-poisoning by and exposure to other drugs acting on the autonomic nervous system); X64 (Intentional self-poisoning by and exposure to other and unspecified drugs, medicaments and biological substance) oraz X70 (Intentional self-harm by hanging, strangulation and suffocation). In total, they accounted for 69.4% of all interventions to suicide attempts in the studied period. Statistical analysis shows significant differences (χ2 = 39.30239, p <0.0001, n = 561) between the area of EMT intervention and the type of suicide attempt. In non-urban areas, a higher percentage of X70 diagnoses was recorded (55.67%), while in urban areas, X60-X64 (72.53%). In non-urban areas, a higher proportion of patients attempting suicide was observed compared to patients living in urban areas. For X70 and X60 - X64 in total, the incidence rates in non-urban areas were 80.8% and 56%, respectively. Significant differences were found (χ2 = 119.3304, p <0.0001, n = 561) depending on the method of attempting suicide in relation to the patient's sex. The percentage of women diagnosed with X60-X64 versus X70 was 87.50%, which was the largest number of patients (n = 154) as compared to men. In the case of X70 in relation to X60-X64, the percentage of men was 62.08%, which was the largest number of patients (n = 239) as compared to women (n = 22). In the case of X70, the percentage of men compared to women was as high as 92%. Significant differences were observed (χ2 = 14.94848, p <0.01058) between the hour of EMT intervention and the type of suicide attempt. The highest percentage of X70 occurred between 04:01 - 08:00 (64.44%), while X60-X64 between 00:01 - 04:00 (70.45%). The largest number of cases of all tested suicide attempts was recorded between 16:01 - 20:00 for X70 (n = 62), X60 - X64 (n = 82), respectively. The highest percentage of patients undertaking all suicide attempts studied at work was observed in the age range of 18-30 (31.5%), while the lowest was in the age group over 60 years of age. (11%). There was no significant correlation between the day of the week or individual months of the year and the type of suicide attempt - respectively (χ2 = 6.281729, p <0.39238, n = 561) and (χ2 = 3.348913, p <0.9857, n = 561). There were also no significant differences in the incidence of suicide attempts for each year in the study period (χ2 = 3.348913, p <0.9857 n = 561). The obtained results suggest the necessity to undertake preventive measures in order to minimize the number of suicide attempts. Such activities should be directed especially at young patients living in non-urban areas.

Keywords: emergency med, emergency medical team, attempted suicide, pre-hospital

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Authors: Oleg Shovkovyy

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This research conducted in response to one of the most pressing questions on the agenda of many public administration offices around the world: “What could be done for better integration and assimilation of immigrants into hosting communities?” In author’s view, the answer could be suggested by immigrants themselves. They, often ‘bogged down in the past,’ snared by own idols and demons, perceive things differently, which, in turn, may result in their inability to integrate smoothly into hosting communities. Brief literature review suggests that perceptions of immigrants are completely neglected or something unsought in the current research on migrants, which, often, based on opinion polls by members of hosting communities themselves or superficial research data by various research organizations. Even those specimens that include voices of immigrants, unlikely to shed any additional light onto the problem simply because certain things are not made to speak out loud, especially to those in whose hands immigrants’ fate is (authorities). In this regard, this qualitative study, conducted by an insider to a few Russian-speaking communities, represents a unique opportunity for all stakeholders to look at the question of integration through the eyes of immigrants, from a different perspective and thus, makes research findings especially valuable for better understanding of the problem. Case study research employed ethnographic methods of gathering data where, approximately 200 Russian-speaking immigrants of first and second generations were closely observed by the Russian-speaking researcher in their usual setting, for eight months, and at different venues. The number of informal interviews with 27 key informants, with whom the researcher managed to establish a good rapport and who were keen enough to share their experiences voluntarily, were conducted. The field notes were taken at 14 locations (study sites) within the Brisbane region of Queensland, Australia. Moreover, all this time, researcher lived in dwelling of one of the immigrants and was an active participant in the social life (worship, picnics, dinners, weekend schools, concerts, cultural events, social gathering, etc.) of observed communities, whose members, to a large extent, belong to various religious lines of the Russian and Protestant Church. It was found that the majority of immigrants had experienced some discrimination in matters of hiring, employment, recognition of educational qualifications from home countries, and simply felt a sort of dislike from society in various everyday situations. Many noted complete absences or very limited state assistance in terms of employment, training, education, and housing. For instance, the Australian Government Department of Human Services not only does not stimulate job search but, on the contrary, encourages to refuse short-term works and employment. On the other hand, offered free courses on adaptation, and the English language proved to be ineffective and unpopular amongst immigrants. Many interviewees have reported overstated requirements for English proficiency and local work experience, whereas it was not critical for the given task or job. Based on the result of long-term monitoring, the researcher also had the courage to assert the negative and decelerating roles of immigrants’ communities, particularly religious communities, on processes of integration and assimilation. The findings suggest that governments should either change current immigration policies in the direction of their toughening or to take more proactive and responsible role in dealing with immigrant-related issues; for instance, increasing assistance and support to all immigrants and probably, paying more attention to and taking stake in managing and organizing lives of immigrants’ communities rather, simply leaving it all to chance.

Keywords: Australia, immigration, integration, perceptions

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Authors: Casey Keenan Joiner, Shayna Tayloe

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Classical voice training for the novice singer has long relied on the guidance and instruction of vocalise collections, such as those written and compiled by Marchesi, Lütgen, Vaccai, and Lamperti. These vocalise collections purport to encourage healthy vocal habits and instill technical longevity in both aspiring and established singers, though their scope has long been somewhat confined to the classical idiom. For pedagogues and students specializing in other vocal genres, such as musical theatre and CCM (contemporary commercial music,) low-impact and pertinent vocal training aids are in short supply, and much of the suggested literature derives from classical methodology. While the tenants of healthy vocal production remain ubiquitous, specific stylistic needs and technical emphases differ from genre to genre and may require a specified extension of vocal acuity. As musical theatre continues to grow in popularity at both the professional and collegiate levels, the need for specialized training grows as well. Pedagogical literature geared specifically towards musical theatre (MT) singing and vocal production, while relatively uncommon, is readily accessible to the contemporary educator. Practitioners such as Norman Spivey, Mary Saunders Barton, Claudia Friedlander, Wendy Leborgne, and Marci Rosenberg continue to publish relevant research in the field of musical theatre voice pedagogy and have successfully identified many common MT vocal faults, their subsequent diagnoses, and their eventual corrections. Where classical methodology would suggest specific vocalises or training exercises to maintain corrected vocal posture following successful fault diagnosis, musical theatre finds itself without a relevant body of work towards which to transition. By analyzing the existing vocalise literature by means of a specialized set of parameters, including but not limited to melodic variation, rhythmic complexity, vowel utilization, and technical targeting, we have composed a set of vocalises meant specifically to address the training and conditioning of adult musical theatre voices. These vocalises target many pedagogical tenants in the musical theatre genre, including but not limited to thyroarytenoid-dominant production, twang resonance, lateral vowel formation, and “belt-mix.” By implementing these vocalises in the musical theatre voice studio, pedagogues can efficiently communicate proper musical theatre vocal posture and kinesthetic connection to their students, regardless of age or level of experience. The composition of these vocalises serves MT pedagogues on both a technical level as well as a sociological one. MT is a relative newcomer on the collegiate stage and the academization of musical theatre methodologies has been a slow and arduous process. The conflation of classical and MT techniques and training methods has long plagued the world of voice pedagogy and teachers often find themselves in positions of “cross-training,” that is, teaching students of both genres in one combined voice studio. As MT continues to establish itself on academic platforms worldwide, genre-specific literature and focused studies are both rare and invaluable. To ensure that modern students receive exacting and definitive training in their chosen fields, it becomes increasingly necessary for genres such as musical theatre to boast specified literature and a collection of musical theatre-specific vocalises only aids in this effort. This collection of musical theatre vocalises is the first of its kind and provides genre-specific studios with a basis upon which to grow healthy, balanced voices built for the harsh conditions of the modern theatre stage.

Keywords: voice pedagogy, targeted methodology, musical theatre, singing

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Authors: Keshari Shrestha, Philip Vatterott

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Introduction: Drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome is a rare and potentially fatal drug-related syndrome. DRESS classically presents with a diffuse maculopapular rash, fevers, and eosinophilia more than three weeks after drug exposure. DRESS can present with multi-organ involvement, with liver damage being the most common and severe. Pulmonary involvement is a less common manifestation and is associated with poor clinical outcomes. Chest imaging is often nonspecific, and symptoms can range from mild cough to acute respiratory distress syndrome (ARDS) . This is a case of a 49-year-old female with a history of recent clostridium difficile colitis status post treatment with oral vancomycin who presented with rash, acute liver and kidney failure, as well as diffuse nodular alveolar lung opacities concerning for DRESS syndrome with multi-organ involvement. Clinical Course: This patient initially presented to an outside hospital with clostridium difficile colitis, acute liver injury, and acute kidney injury. She developed a desquamating maculopapular rash in the setting of recent oral vancomycin, meloxicam, and furosemide initiation. She was hospitalized on two additional occasions with worsening altered mental status, liver injury, and acute kidney injury and was initiated on intermittent hemodialysis. Notably, she was found to have systemic eosinophilia (4100 cells/microliter) several weeks prior. She was transferred to this institution for further management where she was found to have encephalopathy, jaundice, lower extremity edema, and diffuse bilateral rhonchorous breath sounds on pulmonary examination. The patient was started on methylprednisolone for suspected DRESS syndrome. She underwent an evaluation for alternative causes of her organ failure. Her workup included a negative infectious, autoimmune, metabolic, toxic, and malignant work-up. Abdominal computed tomography (CT) and ultrasound were remarkable for evidence of hepatic steatosis and possible cirrhotic morphology. Additionally, a chest CT demonstrated diffuse and symmetric nodular alveolar lung opacities with peripheral sparing not consistent with acute respiratory distress syndrome or edema. Ultimately, her condition continued to decline, and she required intubation on several occasions. On hospital day 25 she succumbed to distributive shock in the setting of probable sepsis and multi-organ failure. Discussion: DRESS syndrome occurs in 1 in 1,000 to 10,000 patients with a mortality rate of around 10%. Anti-convulsant, anti-bacterial, anti-viral, and sulfonamide drugs are the most common drugs implicated in the development of DRESS syndrome; however, the list of offending agents is extensive . The diagnosis of DRESS syndrome is made after excluding other causes of disease such as infectious and autoimmune etiologies. The RegiSCAR scoring system is used to diagnose DRESS syndrome with 2-3 points indicating possible disease, 4-5 probable disease, and >5 definite disease. This patient scored a 7 on the RegiSCAR scale for eosinophilia, rash, organ involvement, and exclusion of other causes (infectious and autoimmune). While the pharmacologic trigger in this case is unknown, it is speculated to be caused by vancomycin, meloxicam, or furosemide due to the favorable timeline of initiation. Despite aggressive treatment, DRESS syndrome can often be fatal. Because of this, early diagnosis and treatment of patients with suspected DRESS syndrome is imperative.

Keywords: drug reaction with eosinophilia and systemic symptoms, multi-organ failure, pulmonary involvement, renal failure

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Authors: Michael R. Shurin, Galina Shurin, Vladimir A. Kirichenko

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Background. Visibility of hepatic malignancies is poor on non-contrast imaging for daily verification of liver malignancies prior to radiation therapy on MRI-guided Linear Accelerators (MR-Linac). Ferumoxytol® (Feraheme, AMAG Pharmaceuticals, Waltham, MA) is a SPION agent that is increasingly utilized off-label as hepatic MRI contrast. This agent has the advantage of providing a functional assessment of the liver based upon its uptake by hepatic Kupffer cells proportionate to vascular perfusion, resulting in strong T1, T2 and T2* relaxation effects and enhanced contrast of malignant tumors, which lack Kupffer cells. The latter characteristic has been recently utilized for MRI-guided radiotherapy planning with precision targeting of liver malignancies. However potential radiotoxicity of SPION has never been addressed for its safe use as an MRI-contrast agent during liver radiotherapy on MRI-Linac. This study defines the radiomodulating properties of SPIONs in vitro on human monocyte and macrophage cell lines exposed to 60Go gamma-rays within clinical radiotherapy dose range. Methods. Human monocyte and macrophages cell line in cultures were loaded with a clinically relevant concentration of Ferumoxytol (30µg/ml) for 2 and 24 h and irradiated to 3Gy, 5Gy and 10Gy. Cells were washed and cultured for additional 24 and 48 h prior to assessing their phenotypic activation by flow cytometry and function, including viability (Annexin V/PI assay), proliferation (MTT assay) and cytokine expression (Luminex assay). Results. Our results reveled that SPION affected both human monocytes and macrophages in vitro. Specifically, iron oxide nanoparticles decreased radiation-induced apoptosis and prevented radiation-induced inhibition of human monocyte proliferative activity. Furthermore, Ferumoxytol protected monocytes from radiation-induced modulation of phenotype. For instance, while irradiation decreased polarization of monocytes to CD11b+CD14+ and CD11bnegCD14neg phenotype, Ferumoxytol prevented these effects. In macrophages, Ferumoxytol counteracted the ability of radiation to up-regulate cell polarization to CD11b+CD14+ phenotype and prevented radiation-induced down-regulation of expression of HLA-DR and CD86 molecules. Finally, Ferumoxytol uptake by human monocytes down-regulated expression of pro-inflammatory chemokines MIP-1α (Macrophage inflammatory protein 1α), MIP-1β (CCL4) and RANTES (CCL5). In macrophages, Ferumoxytol reversed the expression of IL-1RA, IL-8, IP-10 (CXCL10) and TNF-α, and up-regulates expression of MCP-1 (CCL2) and MIP-1α in irradiated macrophages. Conclusion. SPION agent Ferumoxytol increases resistance of human monocytes to radiation-induced cell death in vitro and supports anti-inflammatory phenotype of human macrophages under radiation. The effect is radiation dose-dependent and depends on the duration of Feraheme uptake. This study also finds strong evidence that SPIONs reversed the effect of radiation on the expression of pro-inflammatory cytokines involved in initiation and development of radiation-induced liver damage. Correlative translational work at our institution will directly assess the cyto-protective effects of Ferumoxytol on human Kupfer cells in vitro and ex vivo analysis of explanted liver specimens in a subset of patients receiving Feraheme-enhanced MRI-guided radiotherapy to the primary liver tumors as a bridge to liver transplant.

Keywords: superparamagnetic iron oxide nanoparticles, radioprotection, magnetic resonance imaging, liver

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Authors: Yi-Chu Liu, Hsiu-Huei Hung, Li-Hui Yang, Ming-Jyh Chen

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introduction: To promote environmental sustainability, the hospital formed a corporate volunteer team in 2016 to build the Green Experiential Education Center. Our green creation center utilizes attic space to achieve sustainability objectives such as energy efficiency and carbon reduction. Other than executing sustainable plans, the center emphasizes experiential education. We invite our community to actively participate in building a sustainable, economically viable environment. Since 2020, the China Medical University Hospital has provided medical care to the Tgbin community in Taichung City's Heping District. The tribe, primarily composed of Atayal people, the elderly comprise 18% of the total population, and these families' per capita income is relatively low compared to Taiwanese citizens elsewhere. Purpose / Methods: With the experiences at the Green Experiential Education Center, CMUH team identifies the following objectives: Create an aquaponic system to supply vulnerable local households with food. Create a solar renewable energy system to meet the electricity needs of vulnerable local households. Promote the purchase of green electricity certificates to reduce the hospital's carbon emissions and generate additional revenue for the local community. Materials and Methods: In March 2020, we visited the community and installed The aquaponic system in January 2021. CMUH spent 150,000NT (approximately 5000US dollars) in March 2021 to build a 100-square-meter aquaponic system. The production of vegetables and fish caught determines the number of vulnerable families that can be supported. The aquaponics system is a kind of Low energy consumption and environmentally friendly production method, and can simultaneously achieve energy saving, water saving, and fertilizer saving .In September 2023, CMUH will complete a solar renewable energy system. The system will cover an area of 308 square meters and costs approximately NT$240,000 (approximately US$8,000). The installation of electricity meters will enable statistical analysis of power generation. And complete the Taiwan National Renewable Energy Certificate application process. The green electricity certificate will be obtained based on the monthly power generation from the solar renewable energy system. Results: I Food availability and access are crucial considering the remote location and aging population. By creating a fish and vegetable symbiosis system, the vegetables and catches produced will enable economically disadvantaged families to lower food costs. In 2021 and 2022, the aquaponic system produced 52 kilograms of vegetables and 75 kilograms of catch. The production ensures the daily needs of 8 disadvantaged families. Conclusions: The hospital serves as a fortress for public health and the ideal setting for corporate social responsibility. China Medical University Hospital and the Green Experiential Education Center work to strengthen ties with rural communities and offer top-notch specialty medical care. We are committed to assisting people in escaping poverty and hunger as part of the 2030 Sustainable Development Goals.

Keywords: environmental education, sustainability, energy conservation, carbon emissions, rural area development

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Authors: Sajeli A. Begum, Ameer Basha, Kirti Hira, Rukaiyya Khan

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Cyclic dipeptides are simple diketopiperazine derivatives being investigated by several scientists for their biological effects which include anticancer, antimicrobial, haematological, anticonvulsant, immunomodulatory effect, etc. They are potentially active microbial metabolites having been synthesized too, for developing into drug candidates. Cultures of Pseudomonas species have earlier been reported to produce cyclic dipeptides, helping in quorum sensing signals and bacterial–host colonization phenomena during infections, causing cell anti-proliferation and immunosuppression. Fluorescing Pseudomonas species have been identified to secrete lipid derivatives, peptides, pyrroles, phenazines, indoles, aminoacids, pterines, pseudomonic acids and some antibiotics. In the present work, results of investigation on the cyclic dipeptide metabolites secreted by the culture broth of Pseudomonas species as potent pro-inflammatory cytokine inhibitors are discussed. The bacterial strain was isolated from the rhizospheric soil of groundnut crop and identified as Pseudomonas aeruginosa by 16S rDNA sequence (GenBank Accession No. KT625586). Culture broth of this strain was prepared by inoculating into King’s B broth and incubating at 30 ºC for 7 days. The ethyl acetate extract of culture broth was prepared and lyophilized to get a dry residue (EEPA). Lipopolysaccharide (LPS)-induced ELISA assay proved the inhibition of tumor necrosis factor-alpha (TNF-α) secretion in culture supernatant of RAW 264.7 cells by EEPA (IC50 38.8 μg/mL). The effect of oral administration of EEPA on plasma TNF-α level in rats was tested by ELISA kit. The LPS mediated plasma TNF-α level was reduced to 45% with 125 mg/kg dose of EEPA. Isolation of the chemical constituents of EEPA through column chromatography yielded ten cyclic dipeptides, which were characterized using nuclear magnetic resonance and mass spectroscopic techniques. These cyclic dipeptides are biosynthesized in microorganisms by multifunctional assembly of non-ribosomal peptide synthases and cyclic dipeptide synthase. Cyclo (Gly-L-Pro) was found to be more potentially (IC50 value 4.5 μg/mL) inhibiting TNF-α production followed by cyclo (trans-4-hydroxy-L-Pro-L-Phe) (IC50 value 14.2 μg/mL) and the effect was equal to that of standard immunosuppressant drug, prednisolone. Further, the effect was analyzed by determining mRNA expression of TNF-α in LPS-stimulated RAW 264.7 macrophages using quantitative real-time reverse transcription polymerase chain reaction. EEPA and isolated cyclic dipeptides demonstrated diminution of TNF-α mRNA expression levels in a dose-dependent manner under the tested conditions. Also, they were found to control the expression of other pro-inflammatory cytokines like IL-1β and IL-6, when tested through their mRNA expression levels in LPS-stimulated RAW 264.7 macrophages under LPS-stimulated conditions. In addition, significant inhibition effect was found on Nitric oxide production. Further all the compounds exhibited weak toxicity to LPS-induced RAW 264.7 cells. Thus the outcome of the study disclosed the effectiveness of EEPA and the isolated cyclic dipeptides in down-regulating key cytokines involved in pathophysiology of autoimmune diseases.In another study led by the investigators, microbial cyclic dipeptides were found to exhibit excellent antimicrobial effect against Fusarium moniliforme which is an important causative agent of Sorghum grain mold disease. Thus, cyclic dipeptides are emerging small molecular drug candidates for various autoimmune diseases.

Keywords: cyclic dipeptides, cytokines, Fusarium moniliforme, Pseudomonas, TNF-alpha

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Authors: Ananya Barui, Provas Banerjee, Jyotirmoy Chatterjee

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Application of optical technology in medicine and biology has a long track-record. In this endeavor, OCT is able to attract both engineers and biologists to work together in the field of photonics for establishing a striking non-invasive imaging technology. In contrast to other in vivo imaging modalities like Raman imaging, confocal imaging, two-photon microscopy etc. which can perform in vivo imaging upto 100-200 micron depth due to limitation in numerical aperture or scattering, however, OCT can achieve high-resolution imaging upto few millimeters of tissue structures depending on their refractive index in different anatomical location. This tomographic system depends on interference of two light waves in an interferometer to produce a depth profile of specimen. In wound healing, frequent collection of biopsies for follow-up of repair process could be avoided by such imaging technique. Real time skin OCT (the optical biopsy) has efficacy in deeper and faster illumination of cutaneou tissue to acquire high resolution cross sectional images of their internal micro-structure. Swept Source-OCT (SS-OCT), a novel imaging technique, can generate high-speed depth profile (~ 2 mm) of wound at a sweeping rate of laser with micron level resolution and optimum coherent length of 5-6 mm. Normally multi-layered skin tissue depicts different optical properties along with variation in thickness, refractive index and composition (i.e. keratine layer, water, fat etc.) according to their anatomical location. For instance, stratum corneum, the upper-most and relatively dehydrated layer of epidermis reflects more light and produces more lucid and a sharp demarcation line with rest of the hydrated epidermal region. During wound healing or regeneration, optical properties of cutaneous tissue continuously altered with maturation of wound bed. More mature and less hydrated tissue component reflects more light and becomes visible as a brighter area in comparison to immature region which content higher amount water or fat that depicts as a darker area in OCT image. Non-healing wound possess prolonged inflammation and inhibits nascent proliferative stage. Accumulation of necrotic tissues also prevents the repair of non-healing wounds. Due to high resolution and potentiality to reflect the compositional aspects of tissues in terms of their optical properties, this tomographic method may facilitate in differentiating non-healing and acute wounds in addition to clinical observations. Non-invasive OCT offers better insight regarding specific biological status of tissue in health and pathological conditions, OCT images could be associated with histo-pathological ‘gold standard’. This correlated SS-OCT and microscopic evaluation of the wound edges can provide information regarding progressive healing and maturation of the epithelial components. In the context of searching analogy between two different imaging modalities, their relative performances in imaging of healing bed were estimated for probing an alternative approach. Present study validated utility of SS-OCT in revealing micro-anatomic structure in the healing bed with newer information. Exploring precise correspondence of OCT images features with histo-chemical findings related to epithelial integrity of the regenerated tissue could have great implication. It could establish the ‘optical biopsy’ as a potent non-invasive diagnostic tool for cutaneous pathology.

Keywords: histo-pathology, non invasive imaging, OCT, wound healing

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Authors: Mian Huang, Chi Ma, Junyu Lin, William Lu

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Introduction: Bone health attracts more attention recently and an intelligent question and answer (QA) chatbot for osteoporosis is helpful for science popularization. With Generative Pretrained Transformer (GPT) technology developing, we build an osteoporosis corpus dataset and then fine-tune LLaMA, a famous open-source GPT foundation large language model(LLM), on our self-constructed osteoporosis corpus. Evaluated by clinical orthopedic experts, our fine-tuned model outperforms vanilla LLaMA on osteoporosis QA task in Chinese. Three-dimensional quantitative computed tomography (QCT) measured bone mineral density (BMD) is considered as more accurate than DXA for BMD measurement in recent years. We develop an automatic Phantom-less QCT(PL-QCT) that is more efficient for BMD measurement since no need of an external phantom for calibration. Combined with LLM on osteoporosis, our PL-QCT provides efficient and accurate BMD measurement for our chatbot users. Material and Methods: We build an osteoporosis corpus containing about 30,000 Chinese literatures whose titles are related to osteoporosis. The whole process is done automatically, including crawling literatures in .pdf format, localizing text/figure/table region by layout segmentation algorithm and recognizing text by OCR algorithm. We train our model by continuous pre-training with Low-rank Adaptation (LoRA, rank=10) technology to adapt LLaMA-7B model to osteoporosis domain, whose basic principle is to mask the next word in the text and make the model predict that word. The loss function is defined as cross-entropy between the predicted and ground-truth word. Experiment is implemented on single NVIDIA A800 GPU for 15 days. Our automatic PL-QCT BMD measurement adopt AI-associated region-of-interest (ROI) generation algorithm for localizing vertebrae-parallel cylinder in cancellous bone. Due to no phantom for BMD calibration, we calculate ROI BMD by CT-BMD of personal muscle and fat. Results & Discussion: Clinical orthopaedic experts are invited to design 5 osteoporosis questions in Chinese, evaluating performance of vanilla LLaMA and our fine-tuned model. Our model outperforms LLaMA on over 80% of these questions, understanding ‘Expert Consensus on Osteoporosis’, ‘QCT for osteoporosis diagnosis’ and ‘Effect of age on osteoporosis’. Detailed results are shown in appendix. Future work may be done by training a larger LLM on the whole orthopaedics with more high-quality domain data, or a multi-modal GPT combining and understanding X-ray and medical text for orthopaedic computer-aided-diagnosis. However, GPT model gives unexpected outputs sometimes, such as repetitive text or seemingly normal but wrong answer (called ‘hallucination’). Even though GPT give correct answers, it cannot be considered as valid clinical diagnoses instead of clinical doctors. The PL-QCT BMD system provided by Bone’s QCT(Bone’s Technology(Shenzhen) Limited) achieves 0.1448mg/cm2(spine) and 0.0002 mg/cm2(hip) mean absolute error(MAE) and linear correlation coefficient R2=0.9970(spine) and R2=0.9991(hip)(compared to QCT-Pro(Mindways)) on 155 patients in three-center clinical trial in Guangzhou, China. Conclusion: This study builds a Chinese osteoporosis corpus and develops a fine-tuned and domain-adapted LLM as well as a PL-QCT BMD measurement system. Our fine-tuned GPT model shows better capability than LLaMA model on most testing questions on osteoporosis. Combined with our PL-QCT BMD system, we are looking forward to providing science popularization and early morning screening for potential osteoporotic patients.

Keywords: GPT, phantom-less QCT, large language model, osteoporosis

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Authors: Mozhdeh Khalili Kordabadi

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Textiles play a vital role in human life, particularly in the form of clothing. However, the alarming rate at which textiles end up in landfills presents a significant environmental risk. With approximately one garbage truck per second being filled with discarded textiles, urgent measures are required to mitigate this trend. Governments and responsible organizations are calling upon various stakeholders to shift from a linear economy to a circular economy model in the textile industry. This article highlights several key approaches that can be undertaken to address this pressing issue. These approaches include the creation of renewable raw material sources, rethinking production processes, maximizing the use and reuse of textile products, implementing reproduction and recycling strategies, exploring redistribution to new markets, and finding innovative means to extend the lifespan of textiles. By adopting these strategies, the textile industry can contribute to a more sustainable and environmentally friendly future. Introduction: Textiles, particularly clothing, are essential to human existence. However, the rapid accumulation of textiles in landfills poses a significant threat to the environment. This article explores the urgent need for the textile industry to transition from a linear economy model to a circular economy model. The linear model, characterized by the creation, use, and disposal of textiles, is unsustainable in the long term. By adopting a circular economy approach, the industry can minimize waste, reduce environmental impact, and promote sustainable practices. This article outlines key approaches that can be undertaken to drive this transition. Approaches to Address Environmental Challenges: Creation of Renewable Raw Materials Sources: Exploring and promoting the use of renewable and sustainable raw materials, such as organic cotton, hemp, and recycled fibers, can significantly reduce the environmental footprint of textile production. Rethinking Production Processes: Implementing cleaner production techniques, optimizing resource utilization, and minimizing waste generation are crucial steps in reducing the environmental impact of textile manufacturing. Maximizing Use and Reuse of Textile Products: Encouraging consumers to prolong the lifespan of textile products through proper care, maintenance, and repair services can reduce the frequency of disposal and promote a culture of sustainability. Reproduction and Recycling Strategies: Investing in innovative technologies and infrastructure to enable efficient reproduction and recycling of textiles can close the loop and minimize waste generation. Redistribution of Textiles to New Markets: Exploring opportunities to redistribute textiles to new and parallel markets, such as resale platforms, can extend their lifecycle and prevent premature disposal. Improvising Means to Extend Textile Lifespan: Encouraging design practices that prioritize durability, versatility, and timeless aesthetics can contribute to prolonging the lifespan of textiles. Conclusion: The textile industry must urgently transition from a linear economy to a circular economy model to mitigate the adverse environmental impact caused by textile waste. By implementing the outlined approaches, such as sourcing renewable raw materials, rethinking production processes, promoting reuse and recycling, exploring new markets, and extending the lifespan of textiles, stakeholders can work together to create a more sustainable and environmentally friendly textile industry. These measures require collective action and collaboration between governments, organizations, manufacturers, and consumers to drive positive change and safeguard the planet for future generations.

Keywords: textiles, circular economy, environmental challenges, renewable raw materials, production processes, reuse, recycling, redistribution, textile lifespan extension.

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Authors: Magdy I. A. Alshourbagi

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Background: The National Institute for Deafness and Communication Disorders defines idiopathic sudden sensorineural hearing loss as the idiopathic loss of hearing of at least 30 dB across 3 contiguous frequencies occurring within 3 days.The most common clinical presentation involves an individual experiencing a sudden unilateral hearing loss, tinnitus, a sensation of aural fullness and vertigo. The etiologies and pathologies of ISSNHL remain unclear. Several pathophysiological mechanisms have been described including: vascular occlusion, viral infections, labyrinthine membrane breaks, immune associated disease, abnormal cochlear stress response, trauma, abnormal tissue growth, toxins, ototoxic drugs and cochlear membrane damage. The rationale for the use of hyperbaric oxygen to treat ISSHL is supported by an understanding of the high metabolism and paucity of vascularity to the cochlea. The cochlea and the structures within it require a high oxygen supply. The direct vascular supply, particularly to the organ of Corti, is minimal. Tissue oxygenation to the structures within the cochlea occurs via oxygen diffusion from cochlear capillary networks into the perilymph and the cortilymph. . The perilymph is the primary oxygen source for these intracochlear structures. Unfortunately, perilymph oxygen tension is decreased significantly in patients with ISSHL. To achieve a consistent rise of perilymph oxygen content, the arterial-perilymphatic oxygen concentration difference must be extremely high. This can be restored with hyperbaric oxygen therapy. Subject and Methods: A 37 year old man was presented at the clinic with a five days history of muffled hearing and tinnitus of the right ear. Symptoms were sudden onset, with no associated pain, dizziness or otorrhea and no past history of hearing problems or medical illness. Family history was negative. Physical examination was normal. Otologic examination revealed normal tympanic membranes bilaterally, with no evidence of cerumen or middle ear effusion. Tuning fork examination showed positive Rinne test bilaterally but with lateralization of Weber test to the left side, indicating right ear sensorineural hearing loss. Audiometric analysis confirmed sensorineural hearing loss across all frequencies of about 70- dB in the right ear. Routine lab work were all within normal limits. Clinical diagnosis of idiopathic sudden sensorineural hearing loss of the right ear was made and the patient began a medical treatment (corticosteroid, vasodilator and HBO therapy). The recommended treatment profile consists of 100% O2 at 2.5 atmospheres absolute for 60 minutes daily (six days per week) for 40 treatments .The optimal number of HBOT treatments will vary, depending on the severity and duration of symptomatology and the response to treatment. Results: As HBOT is not yet a standard for idiopathic sudden sensorineural hearing loss, it was introduced to this patient as an adjuvant therapy. The HBOT program was scheduled for 40 sessions, we used a 12-seat multi place chamber for the HBOT, which was started at day seven after the hearing loss onset. After the tenth session of HBOT, improvement of both hearing (by audiogram) and tinnitus was obtained in the affected ear (right). Conclusions: In conclusion, HBOT may be used for idiopathic sudden sensorineural hearing loss as an adjuvant therapy. It may promote oxygenation to the inner ear apparatus and revive hearing ability. Patients who fail to respond to oral and intratympanic steroids may benefit from this treatment. Further investigation is warranted, including animal studies to understand the molecular and histopathological aspects of HBOT and randomized control clinical studies.

Keywords: idiopathic sudden sensorineural hearing loss (issnhl), hyperbaric oxygen therapy (hbot), the decibel (db), oxygen (o2)

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