Search results for: left ventricular assist device

Authors: A. K. Tekile, I. L. Kim, J. Y. Lee

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Human activities put freshwater quality under risk, mainly due to expansion of agriculture and industries, damming, diversion and discharge of inadequately treated wastewaters. The rapid human population growth and climate change escalated the problem. External controlling actions on point and non-point pollution sources are long-term solution to manage water quality. To have a holistic approach, these mechanisms should be coupled with the in-water control strategies. The available in-lake or river methods are either costly or they have some adverse effect on the ecological system that the search for an alternative and effective solution with a reasonable balance is still going on. This study aimed at the physical and chemical water quality improvement in a stagnant Yeo-cheon River reach (Korea), which has recently shown sign of water quality problems such as scum formation and fish death. The river water quality was monitored, for the duration of three months by operating only water flow generator in the first two weeks and then ultrasonic irradiation device was coupled to the flow unit for the remaining duration of the experiment. In addition to assessing the water quality improvement, the correlation among the parameters was analyzed to explain the contribution of the ultra-sonication. Generally, the combined strategy showed localized improvement of water quality in terms of dissolved oxygen, Chlorophyll-a and dissolved reactive phosphate. At locations under limited influence of the system operation, chlorophyll-a was highly increased, but within 25 m of operation the low initial value was maintained. The inverse correlation coefficient between dissolved oxygen and chlorophyll-a decreased from 0.51 to 0.37 when ultrasonic irradiation unit was used with the flow, showing that ultrasonic treatment reduced chlorophyll-a concentration and it inhibited photosynthesis. The relationship between dissolved oxygen and reactive phosphate also indicated that influence of ultra-sonication was higher than flow on the reactive phosphate concentration. Even though flow increased turbidity by suspending sediments, ultrasonic waves canceled out the effect due to the agglomeration of suspended particles and the follow-up settling out. There has also been variation of interaction in the water column as the decrease of pH and dissolved oxygen from surface to the bottom played a role in phosphorus release into the water column. The variation of nitrogen and dissolved organic carbon concentrations showed mixed trend probably due to the complex chemical reactions subsequent to the operation. Besides, the intensive rainfall and strong wind around the end of the field trial had apparent impact on the result. The combined effect of water flow and ultrasonic irradiation was a cumulative water quality improvement and it maintained the dissolved oxygen and chlorophyll-a requirement of the river for healthy ecological interaction. However, the overall improvement of water quality is not guaranteed as effectiveness of ultrasonic technology requires long-term monitoring of water quality before, during and after treatment. Even though, the short duration of the study conducted here has limited nutrient pattern realization, the use of ultrasound at field scale to improve water quality is promising.

Keywords: stagnant, ultrasonic irradiation, water flow, water quality

Procedia PDF Downloads 189

Authors: C. Virgilio, J. Carlier, P. Campistron, M. Toubal, P. Garnier, L. Broussous, V. Thomy, B. Nongaillard

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Wetting efficiency of microstructures or nanostructures patterned on Si wafers is a real challenge in integrated circuits manufacturing. In fact, bad or non-uniform wetting during wet processes limits chemical reactions and can lead to non-complete etching or cleaning inside the patterns and device defectivity. This issue is more and more important with the transistors size shrinkage and concerns mainly high aspect ratio structures. Deep Trench Isolation (DTI) structures enabling pixels’ isolation in imaging devices are subject to this phenomenon. While low-frequency acoustic reflectometry principle is a well-known method for Non Destructive Test applications, we have recently shown that it is also well suited for nanostructures wetting characterization in a higher frequency range. In this paper, we present a high-frequency acoustic reflectometry characterization of DTI wetting through a confrontation of both experimental and modeling results. The acoustic method proposed is based on the evaluation of the reflection of a longitudinal acoustic wave generated by a 100 µm diameter ZnO piezoelectric transducer sputtered on the silicon wafer backside using MEMS technologies. The transducers have been fabricated to work at 5 GHz corresponding to a wavelength of 1.7 µm in silicon. The DTI studied structures, manufactured on the wafer frontside, are crossing trenches of 200 nm wide and 4 µm deep (aspect ratio of 20) etched into a Si wafer frontside. In that case, the acoustic signal reflection occurs at the bottom and at the top of the DTI enabling its characterization by monitoring the electrical reflection coefficient of the transducer. A Finite Difference Time Domain (FDTD) model has been developed to predict the behavior of the emitted wave. The model shows that the separation of the reflected echoes (top and bottom of the DTI) from different acoustic modes is possible at 5 Ghz. A good correspondence between experimental and theoretical signals is observed. The model enables the identification of the different acoustic modes. The evaluation of DTI wetting is then performed by focusing on the first reflected echo obtained through the reflection at Si bottom interface, where wetting efficiency is crucial. The reflection coefficient is measured with different water / ethanol mixtures (tunable surface tension) deposited on the wafer frontside. Two cases are studied: with and without PFTS hydrophobic treatment. In the untreated surface case, acoustic reflection coefficient values with water show that liquid imbibition is partial. In the treated surface case, the acoustic reflection is total with water (no liquid in DTI). The impalement of the liquid occurs for a specific surface tension but it is still partial for pure ethanol. DTI bottom shape and local pattern collapse of the trenches can explain these incomplete wetting phenomena. This high-frequency acoustic method sensitivity coupled with a FDTD propagative model thus enables the local determination of the wetting state of a liquid on real structures. Partial wetting states for non-hydrophobic surfaces or low surface tension liquids are then detectable with this method.

Keywords: wetting, acoustic reflectometry, gigahertz, semiconductor

Procedia PDF Downloads 325

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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Authors: Patrick Louie Robles, Jerry Suls, Ciaran Friel, Mark Butler, Samantha Gordon, Frank Vicari, Joan Duer-Hefele, Karina W. Davidson

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Physical activity guidelines focus on increasing moderate-intensity activity for older adults, but adherence to recommendations remains low. This is despite the fact that scientific evidence finds increasing physical activity is positively associated with health benefits. Behavior change techniques (BCTs) have demonstrated some effectiveness in reducing sedentary behavior and promoting physical activity. This pilot study uses a personalized trials (N-of-1) design, delivered virtually, to evaluate the efficacy of using five BCTs in increasing low-intensity physical activity (by 2,000 steps of walking per day) in adults aged 45-75 years old. The 5 BCTs described in habit formation theory are goal setting, action planning, rehearsal, rehearsal in a consistent context, and self-monitoring. The study recruited health system employees in the target age range who had no mobility restrictions and expressed interest in increasing their daily activity by a minimum of 2,000 steps per day at least five days per week. Participants were sent a Fitbit Charge 4 fitness tracker with an established study account and password. Participants were recommended to wear the Fitbit device 24/7 but were required to wear it for a minimum of ten hours per day. Baseline physical activity was measured by Fitbit for two weeks. Participants then engaged remotely with a clinical research coordinator to establish a “walking plan” that included a time and day interval (e.g., between 7am -8am on Monday-Friday), a location for the walk (e.g., park), and how much time the plan would need to achieve a minimum of 2,000 steps over their baseline average step count (20 minutes). All elements of the walking plan were required to remain consistent throughout the study. In the 10-week intervention phase of the study, participants received all five BCTs in a single, time-sensitive text message. The text message was delivered 30 minutes prior to the established walk time and signaled participants to begin walking when the context (i.e., day of the week, time of day) they pre-selected is encountered. Participants were asked to log both the start and conclusion of their activity session by pressing a button on the Fitbit tracker. Within 30 minutes of the planned conclusion of the activity session, participants received a text message with a link to a secure survey. Here, they noted whether they engaged in the BCTs when prompted and completed an automaticity survey to identify how “automatic” their walking behavior had become. At the end of their trial, participants received a personalized summary of their step data over time, helping them learn more about their responses to the five BCTs. Whether the use of these 5 ‘habit formation’ BCTs in combination elicits a change in physical activity behavior among older adults will be reported. This study will inform the feasibility of a virtually-delivered N-of-1 study design to effectively promote physical activity as a component of healthy aging.

Keywords: aging, exercise, habit, walking

Procedia PDF Downloads 136

Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Adine Gericke, Jiri Militky, Mohanapriya Venkataraman

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Mohair, obtained from the Angora goat, is a luxury fiber and recognized as one of the best quality natural fibers. Expansion of the use of mohair into technical and functional textile products necessitates the need for a better understanding of how the use of mohair in fabrics will impact on its thermo-physiological comfort related properties. Despite its popularity, very little information is available on the quantification of the thermal and moisture management properties of mohair fabrics. This study investigated the effect of fibrous matter composition and fabric structural parameters on conductive and convective heat transfers to attain more information on the thermal comfort properties of mohair fabrics. Dry heat transfer through textiles may involve conduction through the fibrous phase, radiation through fabric interstices and convection of air within the structure. Factors that play a major role in heat transfer by conduction are fabric areal density (g/m2) and derived quantities such as cover factor and porosity. Convective heat transfer through fabrics is found in environmental conditions where there is wind-flow or the object is moving (e.g. running or walking). The thermal comfort properties of mohair fibers were objectively evaluated firstly in comparison with other textile fibers and secondly in a variety of fabric structures. Two sample sets were developed for this purpose, with fibre content, yarn structure and fabric design as main variables. SEM and microscopic images were obtained to closely examine the physical structures of the fibers and fabrics. Thermal comfort properties such as thermal resistance and thermal conductivity, as well as fabric thickness, were measured on the well-known Alambeta test instrument. Clothing insulation (clo) was calculated from the above. The thermal properties of fabrics under heat convection was evaluated using a laboratory model device developed at the Technical University of Liberec (referred to as the TP2-instrument). The effects of the different variables on fabric thermal comfort properties were analyzed statistically using TIBCO Statistica Software. The results showed that fabric structural properties, specifically sample thickness, played a significant role in determining the thermal comfort properties of the fabrics tested. It was found that regarding thermal resistance related to conductive heat flow, the effect of fiber type was not always statistically significant, probably as a result of the amount of trapped air within the fabric structure. The very low thermal conductivity of air, compared to that of the fibers, had a significant influence on the total conductivity and thermal resistance of the samples. This was confirmed by the high correlation of these factors with sample thickness. Regarding convective heat flow, the most important factor influencing the ability of the fabric to allow dry heat to move through the structure, was again fabric thickness. However, it would be wrong to totally disregard the effect of fiber composition on the thermal resistance of textile fabrics. In this study, the samples containing mohair or mohair/wool were consistently thicker than the others even though weaving parameters were kept constant. This can be ascribed to the physical properties of the mohair fibers that renders it exceptionally well towards trapping air among fibers (in a yarn) as well as among yarns (inside a fabric structure). The thicker structures trap more air to provide higher thermal insulation, but also prevent the free flow of air that allow thermal convection.

Keywords: mohair fabrics, convective heat transfer, thermal comfort properties, thermal resistance

Procedia PDF Downloads 139

Authors: Sarah Pasala, Elizabeth Zacharias

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Vital sign monitoring is crucial for both everyday health and medical diagnosis. A significant factor in assessing a human's health is their vital signs, which include heart rate, breathing rate, blood pressure, and electrocardiogram (ECG) readings. Vital sign monitoring has been the focus of many system and method innovations recently. Piezoelectrics are materials that convert mechanical energy into electrical energy and can be used for vital sign monitoring. Piezoelectric energy harvesters that are stretchable and flexible can detect very low frequencies like airflow, heartbeat, etc. Current advancements in piezoelectric materials and flexible sensors have made it possible to create wearable and implantable medical devices that can continuously monitor physiological signals in humans. But because of their non-biocompatible nature, they also produce a large amount of e-waste and require another surgery to remove the implant. This paper presents a biocompatible and flexible piezoelectric composite material for wearable and implantable devices that offers a high-performance platform for seamless and continuous monitoring of human physiological signals and tactile stimuli. It also addresses the issue of e-waste and secondary surgery. A Lead-free piezoelectric, SrBi4Ti4O15, is found to be suitable for this application because the properties can be tailored by suitable substitutions and also by varying the synthesis temperature protocols. In the present work, SrBi4Ti4O15 modified by rare-earth has been synthesized and studied. Coupling factors are calculated from resonant (fr) and anti-resonant frequencies (fa). It is observed that Samarium substitution in SBT has increased the Curie temperature, dielectric and piezoelectric properties. From impedance spectroscopy studies, relaxation, and non-Debye type behaviour are observed. The composite of bioresorbable poly(l-lactide) and Lead-free rare earth modified Bismuth Layered Ferroelectrics leads to a flexible piezoelectric device for non-invasive measurement of vital signs, such as heart rate, breathing rate, blood pressure, and electrocardiogram (ECG) readings and also artery pulse signals in near-surface arteries. These composites are suitable to detect slight movement of the muscles and joints. This Lead-free rare earth modified Bismuth Layered Ferroelectrics – polymer composite is synthesized using a ball mill and the solid-state double sintering method. XRD studies indicated the two phases in the composite. SEM studies revealed the grain size to be uniform and in the range of 100 nm. The electromechanical coupling factor is improved. The elastic constants are calculated and the mechanical flexibility is found to be improved as compared to the single-phase rare earth modified Bismuth Latered piezoelectric. The results indicate that this composite is suitable for the non-invasive detection of multiple vital signs of humans.

Keywords: composites, flexible, non-invasive, piezoelectric

Procedia PDF Downloads 34

Authors: Akiko Ohta, Masahiro Minami, Yusra Qadir, Jennifer York

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The Home Instruction for Parents of Preschool Youngsters (HIPPY) is a home instruction program for mothers of children 3 to 5 years old. Using role-play as a method of teaching, the participating mothers work with their home visitors and learn how to deliver the HIPPY curriculum to their children. Applying HIPPY, Reviving Hope and Home for High-risk Refugee Mothers Program (RHH) was created to provide more personalized peer support and to respond to ongoing settlement challenges for isolated and vulnerable Government Assisted Refugee (GAR) mothers. GARs often have greater needs and vulnerabilities than other refugee groups. While the support is available, they often face various challenges and barriers in starting their new lives in Canada, such as inadequate housing, low first-language literacy levels, low competency in English or French, and social isolation. The pilot project was operated by Mothers Matter Centre (MMC) from January 2019 to March 2021 in partnership with the Immigrant Services Society of BC (ISSofBC). The formative evaluation was conducted by a research team at Simon Fraser University. In order to provide more suitable support for GAR mothers, RHH intended to offer more flexibility in HIPPY delivery, supported by a home visitor, to meet the need of refugee mothers facing various conditions and challenges; to have a pool of financial resources to be used for the RHH families when necessitated during the program period; to have another designated staff member, called a community navigator, assigned to facilitate the support system for the RHH families in their settlement; to have a portable device available for each RHH mother to navigate settlement support resources; and to provide other variations of the HIPPY curriculum as an option for the RHH mothers, including a curriculum targeting pre-HIPPY age children. Reflections on each program component was collected from RHH mothers and staff members of MMC and ISSofBC, including frontline workers and management staff, through individual interviews and focus group discussions. Each of the RHH program components was analyzed and evaluated by applying Moore’s four domains framework to identify key information and generate new knowledge (data). To capture RHH mothers’ program experience more in depth based on their own reflections, the photovoice method was used. Some photos taken by the mothers will be shared to illustrate their RHH experience as part of their life stories. Over the period of the program, this evaluation observed how RHH mothers became more confident in various domains, such as communicating with others, taking public transportations alone, and teaching their own child(ren). One of the major factors behind the success was their home visitors’ flexibility and creativity to create a more meaningful and tailored approach for each mother, depending on her background and personal situation. The role of the community navigator was tested out and improved during the program period. The community navigators took the key role to assess the needs of the RHH families and connect them with community resources. Both the home visitors and community navigators were immigrant mothers themselves and owing to their dedicated care for the RHH mothers; they were able to gain trust and work closely and efficiently with RHH mothers.

Keywords: refugee mothers, settlement support, program evaluation, Canada

Procedia PDF Downloads 170

Authors: Marcin Zieliński, Marcin Dębowski, Mirosław Krzemieniewski

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The anaerobic degradation of substrates is limited especially by the rate and effectiveness of the first (hydrolytic) stage of fermentation. This stage may be intensified through pre-treatment of substrate aimed at disintegration of the solid phase and destruction of substrate tissues and cells. The most frequently applied criterion of disintegration outcomes evaluation is the increase in biogas recovery owing to the possibility of its use for energetic purposes and, simultaneously, recovery of input energy consumed for the pre-treatment of substrate before fermentation. Hydrodynamic cavitation is one of the methods for organic substrate disintegration that has a high implementation potential. Cavitation is explained as the phenomenon of the formation of discontinuity cavities filled with vapor or gas in a liquid induced by pressure drop to the critical value. It is induced by a varying field of pressures. A void needs to occur in the flow in which the pressure first drops to the value close to the pressure of saturated vapor and then increases. The process of cavitation conducted under controlled conditions was found to significantly improve the effectiveness of anaerobic conversion of organic substrates having various characteristics. This phenomenon allows effective damage and disintegration of cellular and tissue structures. Disintegration of structures and release of organic compounds to the dissolved phase has a direct effect on the intensification of biogas production in the process of anaerobic fermentation, on reduced dry matter content in the post-fermentation sludge as well as a high degree of its hygienization and its increased susceptibility to dehydration. A device the efficiency of which was confirmed both in laboratory conditions and in systems operating in the technical scale is a hydrodynamic generator of cavitation. Cavitators, agitators and emulsifiers constructed and tested worldwide so far have been characterized by low efficiency and high energy demand. Many of them proved effective under laboratory conditions but failed under industrial ones. The only task successfully realized by these appliances and utilized on a wider scale is the heating of liquids. For this reason, their usability was limited to the function of heating installations. Design of the presented cavitation generator allows achieving satisfactory energy efficiency and enables its use under industrial conditions in depolymerization processes of biomass with various characteristics. Investigations conducted on the laboratory and industrial scale confirmed the effectiveness of applying cavitation in the process of biomass destruction. The use of the cavitation generator in laboratory studies for disintegration of sewage sludge allowed increasing biogas production by ca. 30% and shortening the treatment process by ca. 20 - 25%. The shortening of the technological process and increase of wastewater treatment plant effectiveness may delay investments aimed at increasing system output. The use of a mechanical cavitator and application of repeated cavitation process (4-6 times) enables significant acceleration of the biogassing process. In addition, mechanical cavitation accelerates increases in COD and VFA levels.

Keywords: hydrodynamic cavitation, pretreatment, biomass, methane fermentation, Virginia fanpetals

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Authors: Kaustav Mukherjee

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In this paper we propose a Neural Style Transfer solution whereby we have created a Lightweight Separable Convolution Kernel Based GAN Architecture (SC-GAN) which will very useful for designing filter for Mobile Phone Cameras and also Edge Devices which will convert any image to its 2D ANIMATED COMIC STYLE Movies like HEMAN, SUPERMAN, JUNGLE-BOOK. This will help the 2D animation artist by relieving to create new characters from real life person's images without having to go for endless hours of manual labour drawing each and every pose of a cartoon. It can even be used to create scenes from real life images.This will reduce a huge amount of turn around time to make 2D animated movies and decrease cost in terms of manpower and time. In addition to that being extreme light-weight it can be used as camera filters capable of taking Comic Style Shots using mobile phone camera or edge device cameras like Raspberry Pi 4,NVIDIA Jetson NANO etc. Existing Methods like CartoonGAN with the model size close to 170 MB is too heavy weight for mobile phones and edge devices due to their scarcity in resources. Compared to the current state of the art our proposed method which has a total model size of 31 MB which clearly makes it ideal and ultra-efficient for designing of camera filters on low resource devices like mobile phones, tablets and edge devices running OS or RTOS. .Owing to use of high resolution input and usage of bigger convolution kernel size it produces richer resolution Comic-Style Pictures implementation with 6 times lesser number of parameters and with just 25 extra epoch trained on a dataset of less than 1000 which breaks the myth that all GAN need mammoth amount of data. Our network reduces the density of the Gan architecture by using Depthwise Separable Convolution which does the convolution operation on each of the RGB channels separately then we use a Point-Wise Convolution to bring back the network into required channel number using 1 by 1 kernel.This reduces the number of parameters substantially and makes it extreme light-weight and suitable for mobile phones and edge devices. The architecture mentioned in the present paper make use of Parameterised Batch Normalization Goodfellow etc al. (Deep Learning OPTIMIZATION FOR TRAINING DEEP MODELS page 320) which makes the network to use the advantage of Batch Norm for easier training while maintaining the non-linear feature capture by inducing the learnable parameters

Keywords: comic stylisation from camera image using GAN, creating 2D animated movie style custom stickers from images, depth-wise separable convolutional neural network for light-weight GAN architecture for EDGE devices, GAN architecture for 2D animated cartoonizing neural style, neural style transfer for edge, model distilation, perceptual loss

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Authors: Jo Mitchell, Daniel Johnson

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MindMax is a digital community and learning platform built to maximise the wellbeing and resilience of AFL Players and Australian men. The MindMax application engages men, via their existing connection with sport and video games, in a range of wellbeing ideas, stories and actions, because we believe fit minds, kick goals. MindMax is an AFL Players Association led project, supported by a Movember Foundation grant, to improve the mental health of Australian males aged between 16-35 years. The key engagement and delivery strategy for the project was digital technology, sport (AFL) and video games, underpinned by evidenced based wellbeing science. The project commenced April 2015, and the expected completion date is March 2017. This paper describes the conceptual model underpinning product development, including progress, key learnings and challenges, as well as the research agenda. Evaluation of the MindMax project is a multi-pronged approach of qualitative and quantitative methods, including participatory design workshops, online reference groups, longitudinal survey methods, a naturalistic efficacy trial and evaluation of the social and economic return on investment. MindMax is focused on the wellness pathway and maximising our mind's capacity for fitness by sharing and promoting evidence-based actions that support this. A range of these ideas (from ACT, mindfulness and positive psychology) are already being implemented in AFL programs and services, mostly in face-to-face formats, with strong engagement by players. Player's experience features strongly as part of the product content. Wellbeing science is a discipline of psychology that explores what helps individuals and communities to flourish in life. Rather than ask questions about illness and poor functioning, wellbeing scientists and practitioners ask questions about wellness and optimal functioning. While illness and wellness are related, they operate as separate constructs and as such can be influenced through different pathways. The essential idea was to take the evidence-based wellbeing science around building psychological fitness to the places and spaces that men already frequent, namely sport and video games. There are 800 current senior AFL players, 5000+ past players, and 11 million boys and men that are interested in the lives of AFL Players; what they think and do to be their best both on and off field. AFL Players are also keen video gamers – using games as one way to de-stress, connect and build wellbeing. There are 9.5 million active gamers in Australia with 93% of households having a device for playing games. Video games in MindMax will be used as an engagement and learning tool. Gamers (including AFL players) can also share their personal experience of how games help build their mental fitness. Currently available games (i.e., we are not in the game creation business) will also be used to motivate and connect MindMax participants. The MindMax model is built with replication by other sport codes (e.g., Cricket) in mind. It is intended to not only support our current crop of athletes but also the community that surrounds them, so they can maximise their capacity for health and wellbeing.

Keywords: Australian football league, digital application, positive psychology, wellbeing

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Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

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Authors: Nicole Merkle, Stefan Zander

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Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

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Authors: Pavel Bulai, Taras Pitlik, Tatsiana Kulahava, Timofei Lipski

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The method of Electrocardiography (ECG) interpretation for post-exercise recovery tracking was developed. Metabolic indices (aerobic and anaerobic) were designed using ECG-derived features. This study reports the associations between aerobic and anaerobic indices and classical parameters of the person’s physiological state, including blood biochemistry, glycogen concentration and VO2max changes. During the study 9 participants, healthy, physically active medium trained men and women, which trained 2-4 times per week for at least 9 weeks, fulfilled (i) ECG monitoring using Apple Watch Series 4 (AWS4); (ii) blood biochemical analysis; (iii) maximal oxygen consumption (VO2max) test, (iv) bioimpedance analysis (BIA). ECG signals from a single-lead wrist-wearable device were processed with detection of QRS-complex. Aerobic index (AI) was derived as the normalized slope of QR segment. Anaerobic index (ANI) was derived as the normalized slope of SJ segment. Biochemical parameters, glycogen content and VO2max were evaluated eight times within 3-60 hours after training. ECGs were recorded 5 times per day, plus before and after training, cycloergometry and BIA. The negative correlation between AI and blood markers of the muscles functional status including creatine phosphokinase (r=-0.238, p < 0.008), aspartate aminotransferase (r=-0.249, p < 0.004) and uric acid (r = -0.293, p<0.004) were observed. ANI was also correlated with creatine phosphokinase (r= -0.265, p < 0.003), aspartate aminotransferase (r = -0.292, p < 0.001), lactate dehydrogenase (LDH) (r = -0.190, p < 0.050). So, when the level of muscular enzymes increases during post-exercise fatigue, AI and ANI decrease. During recovery, the level of metabolites is restored, and metabolic indices rising is registered. It can be concluded that AI and ANI adequately reflect the physiology of the muscles during recovery. One of the markers of an athlete’s physiological state is the ratio between testosterone and cortisol (TCR). TCR provides a relative indication of anabolic-catabolic balance and is considered to be more sensitive to training stress than measuring testosterone and cortisol separately. AI shows a strong negative correlation with TCR (r=-0.437, p < 0.001) and correctly represents post-exercise physiology. In order to reveal the relation between the ECG-derived metabolic indices and the state of the cardiorespiratory system, direct measurements of VO2max were carried out at various time points after training sessions. The negative correlation between AI and VO2max (r = -0.342, p < 0.001) was obtained. These data testifying VO2max rising during fatigue are controversial. However, some studies have revealed increased stroke volume after training, that agrees with findings. It is important to note that post-exercise increase in VO2max does not mean an athlete’s readiness for the next training session, because the recovery of the cardiovascular system occurs over a substantially longer period. Negative correlations registered for ANI with glycogen (r = -0.303, p < 0.001), albumin (r = -0.205, p < 0.021) and creatinine (r = -0.268, p < 0.002) reflect the dehydration status of participants after training. Correlations between designed metabolic indices and physiological parameters revealed in this study can be considered as the sufficient evidence to use these indices for assessing the state of person’s aerobic and anaerobic metabolic systems after training during fatigue, recovery and supercompensation.

Keywords: aerobic index, anaerobic index, electrocardiography, supercompensation

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Authors: Ramazan Bakir, Gizem Kayar

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It is known that Alzheimer and Dementia are the two most common types of Neurodegenerative diseases and their visibility is getting accelerated for the last couple of years. As the population sees older ages all over the world, researchers expect to see the rate of this acceleration much higher. However, unfortunately, there is no known pharmacological cure for both, although some help to reduce the rate of cognitive decline speed. This is why we encounter with non-pharmacological treatment and tracking methods more for the last five years. Many researchers, including well-known associations and hospitals, lean towards using non-pharmacological methods to support cognitive function and improve the patient’s life quality. As the dementia symptoms related to mind, learning, memory, speaking, problem-solving, social abilities and daily activities gradually worsen over the years, many researchers know that cognitive support should start from the very beginning of the symptoms in order to slow down the decline. At this point, life of a patient and caregiver can be improved with some daily activities and applications. These activities include but not limited to basic word puzzles, daily cleaning activities, taking notes. Later, these activities and their results should be observed carefully and it is only possible during patient/caregiver and M.D. in-person meetings in hospitals. These meetings can be quite time-consuming, exhausting and financially ineffective for hospitals, medical doctors, caregivers and especially for patients. On the other hand, digital support systems are showing positive results for all stakeholders of healthcare systems. This can be observed in countries that started Telemedicine systems. The biggest potential of our system is setting the inter-user communication up in the best possible way. In our project, we propose Machine Learning based digitalization of validated traditional cognitive tests (e.g. MOCA, Afazi, left-right hemisphere), their analyses for high-quality follow-up and communication systems for all stakeholders. R. Bakir and G. Kayar are with Gefeasoft, Inc, R&D – Software Development and Health Technologies company. Emails: ramazan, gizem @ gefeasoft.com This platform has a high potential not only for patient tracking but also for making all stakeholders feel safe through all stages. As the registered hospitals assign corresponding medical doctors to the system, these MDs are able to register their own patients and assign special tasks for each patient. With our integrated machine learning support, MDs are able to track the failure and success rates of each patient and also see general averages among similarly progressed patients. In addition, our platform also supports multi-player technology which helps patients play with their caregivers so that they feel much safer at any point they are uncomfortable. By also gamifying the daily household activities, the patients will be able to repeat their social tasks and we will provide non-pharmacological reminiscence therapy (RT – life review therapy). All collected data will be mined by our data scientists and analyzed meaningfully. In addition, we will also add gamification modules for caregivers based on Naomi Feil’s Validation Therapy. Both are behaving positively to the patient and keeping yourself mentally healthy is important for caregivers. We aim to provide a therapy system based on gamification for them, too. When this project accomplishes all the above-written tasks, patients will have the chance to do many tasks at home remotely and MDs will be able to follow them up very effectively. We propose a complete platform and the whole project is both time and cost-effective for supporting all stakeholders.

Keywords: alzheimer’s, dementia, cognitive functionality, cognitive tests, serious games, machine learning, artificial intelligence, digitalization, non-pharmacological, data analysis, telemedicine, e-health, health-tech, gamification

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Authors: Shanaka Gunasekara, Maleen Jayasuriya, Nalin Harischandra, Lilantha Samaranayake, Gamini Dissanayake

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One serious facet of the worsening Human-Elephant conflict (HEC) in nations such as Sri Lanka involves elephant-train collisions. Endangered Asian elephants are maimed or killed during such accidents, which also often result in orphaned or disabled elephants, contributing to the phenomenon of lone elephants. These lone elephants are found to be more likely to attack villages and showcase aggressive behaviour, which further exacerbates the overall HEC. Furthermore, Railway Services incur significant financial losses and disruptions to services annually due to such accidents. Most elephant-train collisions occur due to a lack of adequate reaction time. This is due to the significant stopping distance requirements of trains, as the full braking force needs to be avoided to minimise the risk of derailment. Thus, poor driver visibility at sharp turns, nighttime operation, and poor weather conditions are often contributing factors to this problem. Initial investigations also indicate that most collisions occur in localised “hotspots” where elephant pathways/corridors intersect with railway tracks that border grazing land and watering holes. Taking these factors into consideration, this work proposes the leveraging of recent developments in Convolutional Neural Network (CNN) technology to detect elephants using an RGB/infrared capable camera around known hotspots along the railway track. The CNN was trained using a curated dataset of elephants collected on field visits to elephant sanctuaries and wildlife parks in Sri Lanka. With this vision-based detection system at its core, a prototype unit of an early warning system was designed and tested. This weatherised and waterproofed unit consists of a Reolink security camera which provides a wide field of view and range, an Nvidia Jetson Xavier computing unit, a rechargeable battery, and a solar panel for self-sufficient functioning. The prototype unit was designed to be a low-cost, low-power and small footprint device that can be mounted on infrastructures such as poles or trees. If an elephant is detected, an early warning message is communicated to the train driver using the GSM network. A mobile app for this purpose was also designed to ensure that the warning is clearly communicated. A centralized control station manages and communicates all information through the train station network to ensure coordination among important stakeholders. Initial results indicate that detection accuracy is sufficient under varying lighting situations, provided comprehensive training datasets that represent a wide range of challenging conditions are available. The overall hardware prototype was shown to be robust and reliable. We envision a network of such units may help contribute to reducing the problem of elephant-train collisions and has the potential to act as an important surveillance mechanism in dealing with the broader issue of human-elephant conflicts.

Keywords: computer vision, deep learning, human-elephant conflict, wildlife early warning technology

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Authors: Asmat Nawaz, Ceylan Zafer, Ali K. Erdinc, Kaiying Wang, M. Nadeem Akram

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Hybrid halide Perovskites with the general formula ABX₃, where X = Cl, Br or I, are considered as an ideal candidates for the preparation of photovoltaic devices. The most commonly and successfully used hybrid halide perovskite for photovoltaic applications is CH₃NH₃PbI₃ and its analogue prepared from lead chloride, commonly symbolized as CH₃NH₃PbI₃_ₓClₓ. Some researcher groups are using lead free (Sn replaces Pb) and mixed halide perovskites for the fabrication of the devices. Both mesoporous and planar structures have been developed. By Comparing mesoporous structure in which the perovskite materials infiltrate into mesoporous metal oxide scaffold, the planar architecture is much simpler and easy for device fabrication. In a typical perovskite solar cell, a perovskite absorber layer is sandwiched between the hole and electron transport. Upon the irradiation, carriers are created in the absorber layer that can travel through hole and electron transport layers and the interface in between. We fabricated inverted planar heterojunction structure ITO/PEDOT/ Perovskite/PCBM/Al, based solar cell via two-step spin coating method. This is also called Sequential deposition method. A small amount of cheap additive H₂O was added into PbI₂/DMF to make a homogeneous solution. We prepared four different solution such as (W/O H₂O, 1% H₂O, 2% H₂O, 3% H₂O). After preparing, the whole night stirring at 60℃ is essential for the homogenous precursor solutions. We observed that the solution with 1% H₂O was much more homogenous at room temperature as compared to others. The solution with 3% H₂O was precipitated at once at room temperature. The four different films of PbI₂ were formed on PEDOT substrates by spin coating and after that immediately (before drying the PbI₂) the substrates were immersed in the methyl ammonium iodide solution (prepared in isopropanol) for the completion of the desired perovskite film. After getting desired films, rinse the substrates with isopropanol to remove the excess amount of methyl ammonium iodide and finally dried it on hot plate only for 1-2 minutes. In this study, we added H₂O in the PbI₂/DMF precursor solution. The concept of additive is widely used in the bulk- heterojunction solar cells to manipulate the surface morphology, leading to the enhancement of the photovoltaic performance. There are two most important parameters for the selection of additives. (a) Higher boiling point w.r.t host material (b) good interaction with the precursor materials. We observed that the morphology of the films was improved and we achieved a denser, uniform with less cavities and almost full surface coverage films but only using precursor solution having 1% H₂O. Therefore, we fabricated the complete perovskite solar cell by sequential deposition technique with precursor solution having 1% H₂O. We concluded that with the addition of additives in the precursor solutions one can easily be manipulate the morphology of the perovskite film. In the sequential deposition method, thickness of perovskite film is in µm and the charge diffusion length of PbI₂ is in nm. Therefore, by controlling the thickness using other deposition methods for the fabrication of solar cells, we can achieve the better efficiency.

Keywords: methylammonium lead iodide, perovskite solar cell, precursor composition, sequential deposition

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Authors: M. Isabel Santos, Ana Breda, Ana Margarida Almeida

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Research on academic abilities of individuals with autism spectrum disorder (ASD) underlines the importance of mathematics interventions. Yet the proposal of digital applications for children and youth with ASD continues to attract little attention, namely, regarding the development of mathematical reasoning, being the use of the digital technologies an area of great interest for individuals with this disorder and its use is certainly a facilitative strategy in the development of their mathematical abilities. The use of digital technologies can be an effective way to create innovative learning opportunities to these students and to develop creative, personalized and constructive environments, where they can develop differentiated abilities. The children with ASD often respond well to learning activities involving information presented visually. In this context, we present the digital Learning Environment on Mathematics for Autistic children (LEMA) that was a research project conducive to a PhD in Multimedia in Education and was developed by the Thematic Line Geometrix, located in the Department of Mathematics, in a collaboration effort with DigiMedia Research Center, of the Department of Communication and Art (University of Aveiro, Portugal). LEMA is a digital mathematical learning environment which activities are dynamically adapted to the user’s profile, towards the development of mathematical abilities of children aged 6–12 years diagnosed with ASD. LEMA has already been evaluated with end-users (both students and teacher’s experts) and based on the analysis of the collected data readjustments were made, enabling the continuous improvement of the prototype, namely considering the integration of universal design for learning (UDL) approaches, which are of most importance in ASD, due to its heterogeneity. The learning strategies incorporated in LEMA are: (i) provide options to custom choice of math activities, according to user’s profile; (ii) integrates simple interfaces with few elements, presenting only the features and content needed for the ongoing task; (iii) uses a simple visual and textual language; (iv) uses of different types of feedbacks (auditory, visual, positive/negative reinforcement, hints with helpful instructions including math concept definitions, solved math activities using split and easier tasks and, finally, the use of videos/animations that show a solution to the proposed activity); (v) provides information in multiple representation, such as text, video, audio and image for better content and vocabulary understanding in order to stimulate, motivate and engage users to mathematical learning, also helping users to focus on content; (vi) avoids using elements that distract or interfere with focus and attention; (vii) provides clear instructions and orientation about tasks to ease the user understanding of the content and the content language, in order to stimulate, motivate and engage the user; and (viii) uses buttons, familiarly icons and contrast between font and background. Since these children may experience little sensory tolerance and may have an impaired motor skill, besides the user to have the possibility to interact with LEMA through the mouse (point and click with a single button), the user has the possibility to interact with LEMA through Kinect device (using simple gesture moves).

Keywords: autism spectrum disorder, digital technologies, inclusion, mathematical abilities, mathematical learning activities

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Authors: Ciaran Friel, Jerry Suls, Mark Butler, Patrick Robles, Samantha Gordon, Frank Vicari, Karina W. Davidson

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Physical activity guidelines focus on increasing moderate-intensity activity for older adults, but adherence to recommendations remains low. This is despite the fact that scientific evidence supports that any increase in physical activity is positively correlated with health benefits. Behavior change techniques (BCTs) have demonstrated effectiveness in reducing sedentary behavior and promoting physical activity. This pilot study uses a Personalized Trials (N-of-1) design to evaluate the efficacy of using four BCTs to promote an increase in low-intensity physical activity (2,000 steps of walking per day) in adults aged 45-75 years old. The 4 BCTs tested were goal setting, action planning, feedback, and self-monitoring. BCTs were tested in random order and delivered by text message prompts requiring participant engagement. The study recruited health system employees in the target age range, without mobility restrictions and demonstrating interest in increasing their daily activity by a minimum of 2,000 steps per day for a minimum of five days per week. Participants were sent a Fitbit® fitness tracker with an established study account and password. Participants were recommended to wear the Fitbit device 24/7 but were required to wear it for a minimum of ten hours per day. Baseline physical activity was measured by Fitbit for two weeks. In the 8-week intervention phase of the study, participants received each of the four BCTs, in random order, for a two-week period. Text message prompts were delivered daily each morning at a consistent time. All prompts required participant engagement to acknowledge receipt of the BCT message. Engagement is dependent upon the BCT message and may have included recording that a detailed plan for walking has been made or confirmed a daily step goal (action planning, goal setting). Additionally, participants may have been directed to a study dashboard to view their step counts or compare themselves to their baseline average step count (self-monitoring, feedback). At the end of each two-week testing interval, participants were asked to complete the Self-Efficacy for Walking Scale (SEW_Dur), a validated measure that assesses the participant’s confidence in walking incremental distances, and a survey measuring their satisfaction with the individual BCT that they tested. At the end of their trial, participants received a personalized summary of their step data in response to each individual BCT. The analysis will examine the novel individual-level heterogeneity of treatment effect made possible by N-of-1 design and pool results across participants to efficiently estimate the overall efficacy of the selected behavioral change techniques in increasing low-intensity walking by 2,000 steps, five days per week. Self-efficacy will be explored as the likely mechanism of action prompting behavior change. This study will inform the providers and demonstrate the feasibility of an N-of-1 study design to effectively promote physical activity as a component of healthy aging.

Keywords: aging, exercise, habit, walking

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Authors: Renata Gerhardt, Detlev Belder

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Raman spectroscopy has attracted much attention as a structurally descriptive and label-free detection method. It is particularly suited for chemical analysis given as it is non-destructive and molecules can be identified via the fingerprint region of the spectra. In this work possibilities are investigated how to integrate Raman spectroscopy as a detection method for chip-based chromatography, making use of a droplet interface. A demanding task in lab-on-a-chip applications is the specific and sensitive detection of low concentrated analytes in small volumes. Fluorescence detection is frequently utilized but restricted to fluorescent molecules. Furthermore, no structural information is provided. Another often applied technique is mass spectrometry which enables the identification of molecules based on their mass to charge ratio. Additionally, the obtained fragmentation pattern gives insight into the chemical structure. However, it is only applicable as an end-of-the-line detection because analytes are destroyed during measurements. In contrast to mass spectrometry, Raman spectroscopy can be applied on-chip and substances can be processed further downstream after detection. A major drawback of Raman spectroscopy is the inherent weakness of the Raman signal, which is due to the small cross-sections associated with the scattering process. Enhancement techniques, such as surface enhanced Raman spectroscopy (SERS), are employed to overcome the poor sensitivity even allowing detection on a single molecule level. In SERS measurements, Raman signal intensity is improved by several orders of magnitude if the analyte is in close proximity to nanostructured metal surfaces or nanoparticles. The main gain of lab-on-a-chip technology is the building block-like ability to seamlessly integrate different functionalities, such as synthesis, separation, derivatization and detection on a single device. We intend to utilize this powerful toolbox to realize Raman detection in chip-based chromatography. By interfacing on-chip separations with a droplet generator, the separated analytes are encapsulated into numerous discrete containers. These droplets can then be injected with a silver nanoparticle solution and investigated via Raman spectroscopy. Droplet microfluidics is a sub-discipline of microfluidics which instead of a continuous flow operates with the segmented flow. Segmented flow is created by merging two immiscible phases (usually an aqueous phase and oil) thus forming small discrete volumes of one phase in the carrier phase. The study surveys different chip designs to realize coupling of chip-based chromatography with droplet microfluidics. With regards to maintaining a sufficient flow rate for chromatographic separation and ensuring stable eluent flow over the column different flow rates of eluent and oil phase are tested. Furthermore, the detection of analytes in droplets with surface enhanced Raman spectroscopy is examined. The compartmentalization of separated compounds preserves the analytical resolution since the continuous phase restricts dispersion between the droplets. The droplets are ideal vessels for the insertion of silver colloids thus making use of the surface enhancement effect and improving the sensitivity of the detection. The long-term goal of this work is the first realization of coupling chip based chromatography with droplets microfluidics to employ surface enhanced Raman spectroscopy as means of detection.

Keywords: chip-based separation, chip LC, droplets, Raman spectroscopy, SERS

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Authors: Rama Munajat

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Discourse information levels may be viewed from either a background-foreground distinction or a multi-level perspective, and cross-linguistic studies on this area suggest that each information level is marked by a specific linguistic device. In this sense, Sundanese, spoken in Indonesia’s West Javanese Province, further differentiates the background and foreground information into ordinary and significant types. This paper will report an ongoing shift from particle-to-active voice marking in the way Sundanese signals foregrounding events. The shift relates to decades of contact with Bahasa Indonesia (Indonesia’s official language) and linguistic compatibility between the two surface marking strategies. Representative data analyzed include three groups of short stories in both Sundanese and Bahasa Indonesia (Indonesian) published in three periods: before 1945, 1965-2006, and 2016-2019. In the first group of Sundanese data, forward-moving events dominantly appear in particle KA (Kecap Anteuran, word-accompanying) constructions, where the KA represents different particles that co-occur with a special group of verbs. The second group, however, shows that the foregrounded events are more frequently described in active-voice forms with a subject-predicate (SP) order. Subsequently, the third offers stronger evidence for the use of the SP structure. As for the Indonesian data, the foregrounding events in the first group occur in verb-initial and passive-voice constructions, while in the second and third, the events more frequently appear in active-voice structures (subject-predicate sequence). The marking shift above suggests a structural influence from Indonesian, stemmed from generational differences among authors of the Sundanese short stories, particularly related to their education and language backgrounds. The first group of short stories – published before 1945 or before Indonesia's independence from Dutch – were written by native speakers of Sundanese who spoke Indonesian as a foreign language and went through the Dutch education system. The second group of authors, on the other hand, represents a generation of Sundanese native speakers who spoke Indonesian as a second language. Finally, the third group consists of authors who are bilingual speakers of both Sundanese and Indonesian. The data suggest that the last two groups of authors completed the Indonesian education system. With these, the use of subject-predicate sequences to denote foregrounding events began to appear more frequently in the second group and then became more dominant in those of the third. The coded data also signify that cohesion, coherence, and pragmatic purposes in Particle KA constructions are intact in their respective active-voice structure counterparts. For instance, the foregrounding events in Particle KA constructions occur in Sentence-initial KA and Pre-verbal KA forms, whereas those in the active-voice are described in Subject-Predicate (SP) and Zero-Subject active-voice patterns. Cross-language data further demonstrate that the Sentence-initial KA and the SP active-voice structures each contain an overt noun phrase (NP) co-referential with one of the entities introduced in a preceding context. Similarly, the pre-verbal KA and Zero-Subject active-voice patterns have a deleted noun phrase unambiguously referable to the only one entity previously mentioned. The presence and absence of an NP inform a pragmatic strategy to place prominence on topic/given and comment/new information, respectively.

Keywords: discourse analysis, foregrounding marking, pragmatics, language contact

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Authors: Leonie Bradfield, Stephen Fityus, John Simmons

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The shearing behavior of current and planned coal mine spoil dumps up to 400m in height is studied using large-sample-high-stress direct shear tests performed on a range of spoils common to the coalfields of Eastern Australia. The motivation for the study is to address industry concerns that some constructed spoil dump heights ( > 350m) are exceeding the scale ( ≤ 120m) for which reliable design information exists, and because modern geotechnical laboratories are not equipped to test representative spoil specimens at field-scale stresses. For more than two decades, shear strength estimation for spoil dumps has been based on either infrequent, very small-scale tests where oversize particles are scalped to comply with device specimen size capacity such that the influence of prototype-sized particles on shear strength is not captured; or on published guidelines that provide linear shear strength envelopes derived from small-scale test data and verified in practice by slope performance of dumps up to 120m in height. To date, these published guidelines appear to have been reliable. However, in the field of rockfill dam design there is a broad acceptance of a curvilinear shear strength envelope, and if this is applicable to coal mine spoils, then these industry-accepted guidelines may overestimate the strength and stability of dumps at higher stress levels. The pressing need to rationally define the shearing behavior of more representative spoil specimens at field-scale stresses led to the successful design, construction and operation of a large direct shear machine (LDSM) and its subsequent application to provide reliable design information for current and planned very-high dumps. The LDSM can test at a much larger scale, in terms of combined specimen size (720mm x 720mm x 600mm) and stress (σn up to 4.6MPa), than has ever previously been achieved using a direct shear machine for geotechnical testing of rockfill. The results of an extensive LDSM testing program on a wide range of coal-mine spoils are compared to a published framework that widely accepted by the Australian coal mining industry as the standard for shear strength characterization of mine spoil. A critical outcome is that the LDSM data highlights several non-compliant spoils, and stress-dependent shearing behavior, for which the correct application of the published framework will not provide reliable shear strength parameters for design. Shear strength envelopes developed from the LDSM data are also compared with dam engineering knowledge, where failure envelopes of rockfills are curved in a concave-down manner. The LDSM data indicates that shear strength envelopes for coal-mine spoils abundant with rock fragments are not in fact curved and that the shape of the failure envelope is ultimately determined by the strength of rock fragments. Curvilinear failure envelopes were found to be appropriate for soil-like spoils containing minor or no rock fragments, or hard-soil aggregates.

Keywords: coal mine, direct shear test, high dump, large scale, mine spoil, shear strength, spoil dump

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Authors: Marcela Davalos Lopez

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The history of the circulation of hygienic knowledge and the consolidation of public health in Latin American cities towards the end of the 19th century is well known. Among them, Mexico City was inserted in international politics, strengthened institutions, medical knowledge, applied parameters of modernity and built sanitary engineering works. Despite the power that this hygienist system achieved, its scope was relative: it cannot be generalized to all cities. From a comparative and contextual analysis, it will be shown that conclusions derived from modern urban historiography present, from our contemporary observations, fractures. Between 1890 and 1930, the small cities and areas surrounding the Mexican capital adapted in their own way the international and federal public health regulations. This will be shown for neighborhoods located around Mexico City and in a medium city, close to the Mexican capital (about 80 km), called Cuernavaca. While the inhabitants of the neighborhoods kept awaiting the evolutionary process and the forms that public hygiene policies were taking (because they were witnesses and affected in their territories), in Cuernavaca, the dictates came as an echo. While the capital was drained, large roads were opened, roundabouts were erected, residents were expelled, and drains, sewers, drinking water pipes, etc., were built; Cuernavaca was sheltered in other times and practices. What was this due to? Undoubtedly, the time and energy that it took politicians and the group of "scientists" to carry out these enormous works in the Mexican capital took them away from addressing the issue in remote villages. It was not until the 20th century that the federal hygiene policy began to be strengthened. Despite this, there are other factors that emphasize the particularities of each site. I would like to draw attention here to the different receptions that each town prepared on public hygiene. We will see that Cuernavaca responded to its own semi-rural culture, history, orography and functions, prolonging for much longer, for example, the use of its deep ravines as sewers. For their part, the neighborhoods surrounding the capital, although affected and excluded from hygienist policies, chose to move away from them and solve the deficiencies with their own resources (they resorted to the waste that was left from the dried lake of Mexico to continue their lake practices). All of this points to a paradox that shapes our contemporary concerns: on the one hand, the benefits derived from medical knowledge and its technological applications (in this work referring particularly to the urban health system) and, on the other, the alteration it caused in environmental settings. Places like Cuernavaca (classified by the nineteenth-century and hygienists of the first decades of the twentieth century as backward), as well as landscapes such as neighborhoods, affected by advances in sanitary engineering, keep in their memory buried practices that we observe today as possible ways to reestablish environmental balances: alternative uses of water; recycling of organic materials; local uses of fauna; various systems for breaking down excreta, and so on. In sum, what the nineteenth and first half of the twentieth centuries graduated as levels of backwardness or progress, turn out to be key information to rethink the routes of environmental conservation. When we return to the observations of the scientists, politicians and lawyers of that period, we find historically rejected cultural alterity. Populations such as Cuernavaca that, due to their history, orography and/or insufficiency of federal policies, kept different relationships with the environment, today give us clues to reorient basic elements of cities: alternative uses of water, waste of raw materials, organic or consumption of local products, among others. It is, therefore, a matter of unearthing the rejected that cries out to emerge to the surface.

Keywords: sanitary hygiene, Mexico city, cultural alterity, environmental conservation, environmental history

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Authors: Mingqian Zhang

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Tip-enhanced Raman spectroscopy (TERS) is a scanning probe technique for individual objects and structured surfaces investigation that provides a wealth of enhanced spectral information with nanoscale spatial resolution and high detection sensitivity. It has become a powerful and promising chemical and physical information detection method in the nanometer scale. The TERS technique uses a sharp metallic tip regulated in the near-field of a sample surface, which is illuminated with a certain incident beam meeting the excitation conditions of the wave-vector matching. The local electric field, and, consequently, the Raman scattering, from the sample in the vicinity of the tip apex are both greatly tip-enhanced owning to the excitation of localized surface plasmons and the lightning-rod effect. Typically, a TERS setup is composed of a scanning probe microscope, excitation and collection optical configurations, and a Raman spectroscope. In the illumination configuration, an objective lens or a parabolic mirror is always used as the most important component, in order to focus the incident beam on the tip apex for excitation. In this research, a novel TERS setup was built up by introducing a plasmonic lens to the excitation optics as a focusing device. A plasmonic lens with symmetry breaking semi-annular slits corrugated on gold film was designed for the purpose of generating concentrated sub-wavelength light spots with strong longitudinal electric field. Compared to conventional far-field optical components, the designed plasmonic lens not only focuses an incident beam to a sub-wavelength light spot, but also realizes a strong z-component that dominants the electric field illumination, which is ideal for the excitation of tip-enhancement. Therefore, using a PL in the illumination configuration of TERS contributes to improve the detection sensitivity by both reducing the far-field background and effectively exciting the localized electric field enhancement. The FDTD method was employed to investigate the optical near-field distribution resulting from the light-nanostructure interaction. And the optical field distribution was characterized using an scattering-type scanning near-field optical microscope to demonstrate the focusing performance of the lens. The experimental result is in agreement with the theoretically calculated one. It verifies the focusing performance of the plasmonic lens. The optical field distribution shows a bright elliptic spot in the lens center and several arc-like side-lobes on both sides. After the focusing performance was experimentally verified, the designed plasmonic lens was used as a focusing component in the excitation configuration of TERS setup to concentrate incident energy and generate a longitudinal optical field. A collimated linearly polarized laser beam, with along x-axis polarization, was incident from the bottom glass side on the plasmonic lens. The incident light focused by the plasmonic lens interacted with the silver-coated tip apex and enhanced the Raman signal of the sample locally. The scattered Raman signal was gathered by a parabolic mirror and detected with a Raman spectroscopy. Then, the plasmonic lens based setup was employed to investigate carbon nanotubes and TERS experiment was performed. Experimental results indicate that the Raman signal is considerably enhanced which proves that the novel TERS configuration is feasible and promising.

Keywords: longitudinal electric field, plasmonics, raman spectroscopy, tip-enhancement

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Authors: Juan Pablo Bertuzzi, Mauro Chiarella

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Employing a communication studies perspective and a socio-technological approach, this paper introduces a theoretical framework for understanding the concept of hybrid world; the avatarization phenomena; and the communicational archetype of co-hybridization. This analysis intends to make a contribution to future design of virtual reality experimental applications. Ultimately, this paper presents an ongoing research project that proposes the study of human-avatar interactions in digital educational environments, as well as an innovative reflection on inner digital communication. The aforementioned project presents the analysis of human-avatar interactions, through the development of an interactive experience in virtual reality. The goal is to generate an innovative communicational dimension that could reinforce the hypotheses presented throughout this paper. Being thought for its initial application in educational environments, the analysis and results of this research are dependent and have been prepared in regard of a meticulous planning of: the conception of a 3D digital platform; the interactive game objects; the AI or computer avatars; the human representation as hybrid avatars; and lastly, the potential of immersion, ergonomics and control diversity that can provide the virtual reality system and the game engine that were chosen. The project is divided in two main axes: The first part is the structural one, as it is mandatory for the construction of an original prototype. The 3D model is inspired by the physical space that belongs to an academic institution. The incorporation of smart objects, avatars, game mechanics, game objects, and a dialogue system will be part of the prototype. These elements have all the objective of gamifying the educational environment. To generate a continuous participation and a large amount of interactions, the digital world will be navigable both, in a conventional device and in a virtual reality system. This decision is made, practically, to facilitate the communication between students and teachers; and strategically, because it will help to a faster population of the digital environment. The second part is concentrated to content production and further data analysis. The challenge is to offer a scenario’s diversity that compels users to interact and to question their digital embodiment. The multipath narrative content that is being applied is focused on the subjects covered in this paper. Furthermore, the experience with virtual reality devices proposes users to experiment in a mixture of a seemingly infinite digital world and a small physical area of movement. This combination will lead the narrative content and it will be crucial in order to restrict user’s interactions. The main point is to stimulate and to grow in the user the need of his hybrid avatar’s help. By building an inner communication between user’s physicality and user’s digital extension, the interactions will serve as a self-guide through the gameworld. This is the first attempt to make explicit the avatarization phenomena and to further analyze the communicational archetype of co-hybridization. The challenge of the upcoming years will be to take advantage from these forms of generalized avatarization, in order to create awareness and establish innovative forms of hybridization.

Keywords: avatar, hybrid worlds, socio-technology, virtual reality

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Authors: Anitha Kandasamy, Thirumurugan Ramaiah

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Interestingly, organic materials exhibit large optical nonlinearity with quick responses and having the flexibility of molecular tailoring using computational modelling and favourable synthetic methodologies. Pyridine based organic compounds and carboxylic acid contained aromatic compounds play a crucial role in crystal engineering of NCS complexes that displays admirable optical nonlinearity with fast response and favourable physicochemical properties such as low dielectric constant, wide optical transparency and large laser damage threshold value requires for optoelectronics device applications. Based on these facts, it was projected to form an acentric molecule of π-conjugated system interaction with appropriately replaced electron donor and acceptor groups for achieving higher SHG activity in which quinoline-2-carboyxlic acid is chosen as an electron acceptor and capable of acting as an acid as well as a base molecule, while 2-amino-4-methylpyridine is used as an electron donor and previously employed in numerous proton transfer complexes for synthesis of NLO materials for optoelectronic applications. 2-amino-4-mehtylpyridinium quinoline-2-carboxylate molecular complex (2AQ) is having π-donor-acceptor groups in which 2-amino-4-methylpyridine donates one of its electron to quinoline -2-carboxylic acid thereby forming a protonated 2-amino-4-methyl pyridinium moiety and mono ionized quinoline-2-carboxylate moiety which are connected via N-H…O intermolecular interactions with non-centrosymmetric crystal packing arrangement at microscopic scale is accountable to the enhancement of macroscopic second order NLO activity. The 2AQ crystal was successfully grown by a slow evaporation solution growth technique and its structure was determined in orthorhombic crystal system with acentric, P212121, space group. Hirshfeld surface analysis reveals that O…H intermolecular interactions primarily contributed with 31.0 % to the structural stabilization of 2AQ. The molecular structure of title compound has been confirmed by 1H and 13C NMR spectral studies. The vibrational modes of functional groups present in 2AQ have been assigned by using FTIR and FT-Raman spectroscopy. The grown 2AQ crystal exhibits high optical transparency with lower cut-off wavelength (275 nm) within the region of 275-1500 nm. The laser study confirmed that 2AQ exhibits high SHG efficiency of 12.6 times greater than that of KDP. TGA-DTA analysis revealed that 2AQ crystal had a thermal stability of 223 °C. The low dielectric constant and low dielectric loss at higher frequencies confirmed good crystalline nature with fewer defects of grown 2AQ crystal. The grown crystal exhibits soft material and positive photoconduction behaviour. Mulliken atomic distribution and FMOs analysis suggested that the strong intermolecular hydrogen bonding which lead to the enhancement of NLO activity. These properties suggest that 2AQ crystal is a suitable material for optoelectronic and laser frequency conversion applications.

Keywords: crystal growth, NLO activity, proton transfer complex, quantum chemical investigation

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Authors: Lolwa Alansari, Hanen Mrabet, Kholoud Khaled, Abdelhamid Azhaghdani, Sufia Athar, Aska Kaima, Zaineb Mhamdia, Zubaria Altaf, Almunzer Zakaria, Tamara Alshadafat

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Introduction: The Obstetrics and Gynecology Emergency Department at Alwakra Hospital has faced significant challenges, which have been further worsened by the impact of the COVID-19 pandemic. These challenges involve issues such as overcrowding, extended wait times, and a notable surge in demand for emergency care services. Moreover, prolonged waiting times have emerged as a primary factor contributing to situations where patients leave without receiving attention, known as left without being seen (LWBS), and unexpectedly abscond. Addressing the issue of insufficient patient mobility in the obstetrics and gynecology emergency department has brought about substantial improvements in patient care, healthcare administration, and overall departmental efficiency. These changes have not only alleviated overcrowding but have also elevated the quality of emergency care, resulting in higher patient satisfaction, better outcomes, and operational rewards. Methodology: The COVID-19 pandemic has served as a catalyst for substantial transformations in the obstetrics and gynecology emergency, aligning seamlessly with the strategic direction of Hamad Medical Corporation (HMC). The fundamental aim of this initiative is to revolutionize the operational efficiency of the OB-GYN ED. To accomplish this mission, a range of transformations has been initiated, focusing on essential areas such as digitizing systems, optimizing resource allocation, enhancing budget efficiency, and reducing overall costs. The project utilized the Plan-Do-Study-Act (PDSA) model, involving a diverse team collecting baseline data and introducing throughput improvements. Post-implementation data and feedback were analysed, leading to the integration of effective interventions into standard procedures. These interventions included optimized space utilization, real-time communication, bedside registration, technology integration, pre-triage screening, enhanced communication and patient education, consultant presence, and a culture of continuous improvement. These strategies significantly reduced waiting times, enhancing both patient care and operational efficiency. Results: Results demonstrated a substantial reduction in overall average waiting time, dropping from 35 to approximately 14 minutes by August 2023. The wait times for priority 1 cases have been reduced from 22 to 0 minutes, and for priority 2 cases, the wait times have been reduced from 32 to approximately 13.6 minutes. The proportion of patients spending less than 8 hours in the OB ED observation beds rose from 74% in January 2022 to over 98% in 2023. Notably, there was a remarkable decrease in LWBS and absconded patient rates from 2020 to 2023. Conclusion: The project initiated a profound change in the department's operational environment. Efficiency became deeply embedded in the unit's culture, promoting teamwork among staff that went beyond the project's original focus and had a positive influence on operations in other departments. This effectiveness not only made processes more efficient but also resulted in significant cost reductions for the hospital. These cost savings were achieved by reducing wait times, which in turn led to fewer prolonged patient stays and reduced the need for additional treatments. These continuous improvement initiatives have now become an integral part of the Obstetrics and Gynecology Division's standard operating procedures, ensuring that the positive changes brought about by the project persist and evolve over time.

Keywords: overcrowding, waiting time, person centered care, quality initiatives

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Authors: Stanislav Babaev, Vladimir Cuk, Sjef Cobben, Jan Desmet

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The procedures for performing harmonic studies for medium-voltage distribution feeders have become relatively mature topics since the early 1980s. The efforts of various electric power engineers and researchers were mainly focused on handling large harmonic non-linear loads connected scarcely at several buses of medium-voltage feeders. In order to assess the impact of these loads on the voltage quality of the distribution system, specific modeling and simulation strategies were proposed. These methodologies could deliver a reasonable estimation accuracy given the requirements of least computational efforts and reduced complexity. To uphold these requirements, certain analysis assumptions have been made, which became de facto standards for establishing guidelines for harmonic analysis. Among others, typical assumptions include balanced conditions of the study and the negligible impact of impedance frequency characteristics of various power system components. In latter, skin and proximity effects are usually omitted, and resistance and reactance values are modeled based on the theoretical equations. Further, the simplifications of the modelling routine have led to the commonly accepted practice of neglecting phase angle diversity effects. This is mainly associated with developed load models, which only in a handful of cases are representing the complete harmonic behavior of a certain device as well as accounting on the harmonic interaction between grid harmonic voltages and harmonic currents. While these modelling practices were proven to be reasonably effective for medium-voltage levels, similar approaches have been adopted for low-voltage distribution systems. Given modern conditions and massive increase in usage of residential electronic devices, recent and ongoing boom of electric vehicles, and large-scale installing of distributed solar power, the harmonics in current low-voltage grids are characterized by high degree of variability and demonstrate sufficient diversity leading to a certain level of cancellation effects. It is obvious, that new modelling algorithms overcoming previously made assumptions have to be accepted. In this work, a simulation approach aimed to deal with some of the typical assumptions is proposed. A practical low-voltage feeder is modeled in PowerFactory. In order to demonstrate the importance of diversity effect and harmonic interaction, previously developed measurement-based models of photovoltaic inverter and battery charger are used as loads. The Python-based script aiming to supply varying voltage background distortion profile and the associated current harmonic response of loads is used as the core of unbalanced simulation. Furthermore, the impact of uncertainty of feeder frequency-impedance characteristics on total harmonic distortion levels is shown along with scenarios involving linear resistive loads, which further alter the impedance of the system. The comparative analysis demonstrates sufficient differences with cases when all the assumptions are in place, and results indicate that new modelling and simulation procedures need to be adopted for low-voltage distribution systems with high penetration of non-linear loads and renewable generation.

Keywords: electric power system, harmonic distortion, power quality, public low-voltage network, harmonic modelling

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Authors: Arjun Kumar Rath, Titus Dhanasingh

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Embedded product development requires software to test hardware functionality during development and finding issues during manufacturing in larger quantities. As the components are getting integrated, the devices are tested for their full functionality using advanced software tools. Benchmarking tools are used to measure and compare the performance of product features. At present, these tests are based on a variety of methods involving varying hardware and software platforms. Typically, these tests are custom built for every product and remain unusable for other variants. A majority of the tests goes undocumented, not updated, unusable when the product is released. To bridge this gap, a solution accelerator in the form of a framework can address these issues for running all these tests from one place, using an off-the-shelf tests library in a continuous integration environment. There are many open-source test frameworks or tools (fuego. LAVA, AutoTest, KernelCI, etc.) designed for testing embedded system devices, with each one having several unique good features, but one single tool and framework may not satisfy all of the testing needs for embedded systems, thus an extensible framework with the multitude of tools. Embedded product testing includes board bring-up testing, test during manufacturing, firmware testing, application testing, and assembly testing. Traditional test methods include developing test libraries and support components for every new hardware platform that belongs to the same domain with identical hardware architecture. This approach will have drawbacks like non-reusability where platform-specific libraries cannot be reused, need to maintain source infrastructure for individual hardware platforms, and most importantly, time is taken to re-develop test cases for new hardware platforms. These limitations create challenges like environment set up for testing, scalability, and maintenance. A desirable strategy is certainly one that is focused on maximizing reusability, continuous integration, and leveraging artifacts across the complete development cycle during phases of testing and across family of products. To get over the stated challenges with the conventional method and offers benefits of embedded testing, an embedded test framework (ETF), a solution accelerator, is designed, which can be deployed in embedded system-related products with minimal customizations and maintenance to accelerate the hardware testing. Embedded test framework supports testing different hardwares including microprocessor and microcontroller. It offers benefits such as (1) Time-to-Market: Accelerates board brings up time with prepacked test suites supporting all necessary peripherals which can speed up the design and development stage(board bring up, manufacturing and device driver) (2) Reusability-framework components isolated from the platform-specific HW initialization and configuration makes the adaptability of test cases across various platform quick and simple (3) Effective build and test infrastructure with multiple test interface options and preintegrated with FUEGO framework (4) Continuos integration - pre-integrated with Jenkins which enabled continuous testing and automated software update feature. Applying the embedded test framework accelerator throughout the design and development phase enables to development of the well-tested systems before functional verification and improves time to market to a large extent.

Keywords: board diagnostics software, embedded system, hardware testing, test frameworks

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Authors: Irina Mizeva, Elena Potapova, Viktor Dremin, Mikhail Mezentsev, Valeri Shupletsov

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The local tissue perfusion is regulated by the microvascular tone which is under the control of a number of physiological mechanisms. Laser Doppler flowmetry (LDF) together with wavelet analyses is the most commonly used technique to study the regulatory mechanisms of cutaneous microcirculation. External factors such as temperature, local pressure of the probe on the skin, etc. influence on the blood flow characteristics and are used as physiological tests to evaluate microvascular regulatory mechanisms. Local probe pressure influences on the microcirculation parameters measured by optical methods: diffuse reflectance spectroscopy, fluorescence spectroscopy, and LDF. Therefore, further study of probe pressure effects can be useful to improve the reliability of optical measurement. During pressure tests variation of the mean perfusion measured by means of LDF usually is estimated. An additional information concerning the physiological mechanisms of the vascular tone regulation system in response to local pressure can be obtained using spectral analyses of LDF samples. The aim of the present work was to develop protocol and algorithm of data processing appropriate for study physiological response to the local pressure test. Involving 6 subjects (20±2 years) and providing 5 measurements for every subject we estimated intersubject and-inter group variability of response of both averaged and oscillating parts of the LDF sample on external surface pressure. The final purpose of the work was to find special features which further can be used in wider clinic studies. The cutaneous perfusion measurements were carried out by LAKK-02 (SPE LAZMA Ltd., Russia), the skin loading was provided by the originally designed device which allows one to distribute the pressure around the LDF probe. The probe was installed on the dorsal part of the distal finger of the index figure. We collected measurements continuously for one hour and varied loading from 0 to 180mmHg stepwise with a step duration of 10 minutes. Further, we post-processed the samples using the wavelet transform and traced the energy of oscillations in five frequency bands over time. Weak loading leads to pressure-induced vasodilation, so one should take into account that the perfusion measured under pressure conditions will be overestimated. On the other hand, we revealed a decrease in endothelial associated fluctuations. Further loading (88 mmHg) induces amplification of pulsations in all frequency bands. We assume that such loading leads to a higher number of closed capillaries, higher input of arterioles in the LDF signal and as a consequence more vivid oscillations which mainly are formed in arterioles. External pressure higher than 144 mmHg leads to the decrease of oscillating components, after removing the loading very rapid restore of the tissue perfusion takes place. In this work, we have demonstrated that local skin loading influence on the microcirculation parameters measured by optic technique; this should be taken into account while developing portable electronic devices. The proposed protocol of local loading allows one to evaluate PIV as far as to trace dynamic of blood flow oscillations. This study was supported by the Russian Science Foundation under project N 18-15-00201.

Keywords: blood microcirculation, laser Doppler flowmetry, pressure-induced vasodilation, wavelet analyses blood

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