Search results for: teacher performance evaluation

Authors: Naser Zouri

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Purpose: Measures of formulate and implementation strategy shows amount of product rate-market based strategic management category such as courtesy, competence, and compliance to reach the high loyalty of financial ecosystem. Despite, it solves the market place error intention to fair trade organization. Finding: Finding shows the ability of executives’ level of management to motivate and better decision-making to solve the treatments in business organization. However, it made ideal level of each interposition policy for a hypothetical household. Methodology/design. Style of questionnaire about the data collection was selected to survey of both pilot test and real research. Also, divide of questionnaire and using of Free Scale Semiconductor`s between the finance employee was famous of this instrument. Respondent`s nominated basic on non-probability sampling such as convenience sampling to answer the questionnaire. The way of realization costs to performed the questionnaire divide among the respondent`s approximately was suitable as a spend the expenditure to reach the answer but very difficult to collect data from hospital. However, items of research survey was formed of implement strategy, environment, supply chain, employee from impact of implementation strategy on reach to better financial consequences and also formulate strategy, comprehensiveness strategic design, organization performance from impression on formulate strategy and financial consequences. Practical Implication: Dynamic capability approach of formulate and implement strategy focuses on the firm-specific processes through which firms integrate, build, or reconfigure resources valuable for making a theoretical contribution. Originality/ value of research: Going beyond the current discussion, we show that case studies have the potential to extend and refine theory. We present new light on how dynamic capabilities can benefit from case study research by discovering the qualifications that shape the development of capabilities and determining the boundary conditions of the dynamic capabilities approach. Limitation of the study :Present study also relies on survey of methodology for data collection and the response perhaps connection by financial employee was difficult to responds the question because of limitation work place.

Keywords: financial ecosystem, loyalty, Malaysian market error, dynamic capability approach, rate-market, optimization intelligence strategy, courtesy, competence, compliance

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Authors: Mahmoud M. AbuAlSamen, Tamam El-Elimat

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Amid the economic crisis in Jordan, the Jordanian government has opted for a knowledge economy where education is promoted as a mean for economic development. University education usually comes at the expense of study-related stress that may adversely impact the health of students. Since stress is a latent variable that is difficult to measure, a valid tool should be used in doing so. The effort-reward imbalance (ERI) is a model used as a measurement tool for occupational stress. The model was built on the notion of reciprocity, which relates ‘effort’ to ‘reward’ through the mediating ‘over-commitment’. Reciprocity assumes equilibrium between both effort and reward, where ‘high’ effort is adequately compensated with ‘high’ reward. When this equilibrium is violated (i.e., high effort with low reward), this may elicit negative emotions and stress, which have been correlated to adverse health conditions. The theory of ERI was established in many different parts of the world, and associations with chronic diseases and the health of workers were explored at length. While much of the effort-reward imbalance was investigated in work conditions, there has been a growing interest in understanding the validity of the ERI model when applied to other social settings such as schools and universities. The ERI questionnaire was developed in Arabic recently to measure ERI among high school teachers. However, little information is available on the validity of the ERI questionnaire in university students. A cross-sectional study was conducted on 833 students in Jordan to measure the validity and reliability of the ERI questionnaire in Arabic among university students. Reliability, as measured by Cronbach’s alpha of the effort, reward, and overcommitment scales, was 0.73, 0.76, and 0.69, respectively, suggesting satisfactory reliability. The factorial structure was explored using principal axis factoring. The results fitted a five-solution model where both the effort and overcommitment were uni-dimensional while the reward scale was three-dimensional with its factors, namely being ‘support’, ‘esteem’, and ‘security’. The solution explained 56% of the variance in the data. The established ERI theory was replicated with excellent validity in this study. The effort-reward ratio in university students was 1.19, which suggests a slight degree of failed reciprocity. The study also investigated the association of effort, reward, overcommitment, and ERI with participants’ demographic factors and self-reported health. ERI was found to be significantly associated with absenteeism (p < 0.0001), past history of failed courses (p=0.03), and poor academic performance (p < 0.001). Moreover, ERI was found to be associated with poor self-reported health among university students (p=0.01). In conclusion, the Arabic ERI questionnaire is reliable and valid for use in measuring effort-reward imbalance in university students in Jordan. The results of this research are important in informing higher education policy in Jordan.

Keywords: effort-reward imbalance, factor analysis, validity, self-reported health

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: Freja Rydahl Rasmussen, Naja Villadsen, Stig Koust

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Air purifiers have become widely implemented in a wide range of settings, including households, schools, institutions, and hospitals, as they tackle the pressing issue of indoor air pollution. With their ability to enhance indoor air quality and create healthier environments, air purifiers are particularly vital when ventilation options are limited. These devices incorporate a diverse array of technologies, including HEPA filters, active carbon filters, UV-C light, photocatalytic oxidation, and ionizers, each designed to combat specific pollutants and improve air quality within enclosed spaces. However, the safety of air purifiers has not been investigated thoroughly, and many questions still arise when applying them. Certain air purification technologies, such as UV-C light or ionization, can unintentionally generate undesirable byproducts that can negatively affect indoor air quality and health. It is well-established that these technologies can inadvertently generate nanoparticles or convert common gaseous compounds into harmful ones, thus exacerbating air pollution. However, the formation of byproducts can vary across products, necessitating further investigation. There is a particular concern about the formation of the carcinogenic substance formaldehyde from common gases like acetone. Many air purifiers use mechanical filtration to remove particles, dust, and pollen from the air. Filters need to be replaced periodically for optimal efficiency, resulting in an additional cost for end-users. Currently, there are no guidelines for filter lifespan, and replacement recommendations solely rely on manufacturers. A market screening revealed that manufacturers' recommended lifespans vary greatly (from 1 month to 10 years), and there is a need for general recommendations to guide consumers. Activated carbon filters are used to adsorb various types of chemicals that can pose health risks or cause unwanted odors. These filters have a certain capacity before becoming saturated. If not replaced in a timely manner, the adsorbed substances are likely to be released from the filter through off-gassing or losing adsorption efficiency. The goal of this study is to investigate the lifespan of filters as well as investigate the potentially harmful effects of air purifiers. Understanding the lifespan of filters used in air purifiers and the potential formation of harmful byproducts is essential for ensuring their optimal performance, guiding consumers in their purchasing decisions, and establishing industry standards for safer and more effective air purification solutions. At this time, a selection of air purifiers has been chosen, and test methods have been established. In the following 3 months, the tests will be conducted, and the results will be ready for presentation later.

Keywords: air purifiers, activated carbon filters, byproducts, clean air, indoor air quality

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Authors: Christofas Stergianos, Jason Atkin, Herve Morvan

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As air traffic increases, more airports are interested in utilizing optimization methods. Many processes happen in parallel at an airport, and complex models are needed in order to have a reliable solution that can be implemented for ground movement operations. The ground movement for aircraft in an airport, allocating a path to each aircraft to follow in order to reach their destination (e.g. runway or gate), is one process that could be optimized. The Quickest Path Problem with Time Windows (QPPTW) algorithm has been developed to provide a conflict-free routing of vehicles and has been applied to routing aircraft around an airport. It was subsequently modified to increase the accuracy for airport applications. These modifications take into consideration specific characteristics of the problem, such as: the pushback process, which considers the extra time that is needed for pushing back an aircraft and turning its engines on; stand holding where any waiting should be allocated to the stand; and runway sequencing, where the sequence of the aircraft that take off is optimized and has to be respected. QPPTW involves searching for the quickest path by expanding the search in all directions, similarly to Dijkstra’s algorithm. Finding a way to direct the expansion can potentially assist the search and achieve a better performance. We have further modified the QPPTW algorithm to use a heuristic approach in order to guide the search. This new algorithm is based on the A-star search method but estimates the remaining time (instead of distance) in order to assess how far the target is. It is important to consider the remaining time that it is needed to reach the target, so that delays that are caused by other aircraft can be part of the optimization method. All of the other characteristics are still considered and time windows are still used in order to route multiple aircraft rather than a single aircraft. In this way the quickest path is found for each aircraft while taking into account the movements of the previously routed aircraft. After running experiments using a week of real aircraft data from Zurich Airport, the new algorithm (A-star QPPTW) was found to route aircraft much more quickly, being especially fast in routing the departing aircraft where pushback delays are significant. On average A-star QPPTW could route a full day (755 to 837 aircraft movements) 56% faster than the original algorithm. In total the routing of a full week of aircraft took only 12 seconds with the new algorithm, 15 seconds faster than the original algorithm. For real time application, the algorithm needs to be very fast, and this speed increase will allow us to add additional features and complexity, allowing further integration with other processes in airports and leading to more optimized and environmentally friendly airports.

Keywords: a-star search, airport operations, ground movement optimization, routing and scheduling

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Authors: Silvia Portarena, Chiara Anselmi, Chiara Baldacchini, Enrico Brugnoli

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Extra virgin olive oil (EVOO) is a complex matrix mainly composed by fatty acid and other minor compounds, among which carotenoids are well known for their antioxidative function that is a key mechanism of protection against cancer, cardiovascular diseases, and macular degeneration in humans. EVOO composition in terms of such constituents is generally the result of a complex combination of genetic, agronomical and environmental factors. To selectively improve the quality of EVOOs, the role of each factor on its biochemical composition need to be investigated. By selecting fruits from four different cultivars similarly grown and harvested, it was demonstrated that Raman spectroscopy, combined with chemometric analysis, is able to discriminate the different cultivars, also as a function of the harvest date, based on the relative content and composition of fatty acid and carotenoids. In particular, a correct classification up to 94.4% of samples, according to the cultivar and the maturation stage, was obtained. Moreover, by using gas chromatography and high-performance liquid chromatography as reference techniques, the Raman spectral features further allowed to build models, based on partial least squares regression, that were able to predict the relative amount of the main fatty acids and the main carotenoids in EVOO, with high coefficients of determination. Besides genetic factors, climatic parameters, such as light exposition, distance from the sea, temperature, and amount of precipitations could have a strong influence on EVOO composition of both major and minor compounds. This suggests that the Raman spectra could act as a specific fingerprint for the geographical discrimination and authentication of EVOO. To understand the influence of environment on EVOO Raman spectra, samples from seven regions along the Italian coasts were selected and analyzed. In particular, it was used a dual approach combining Raman spectroscopy and isotope ratio mass spectrometry (IRMS) with principal component and linear discriminant analysis. A correct classification of 82% EVOO based on their regional geographical origin was obtained. Raman spectra were obtained by Super Labram spectrometer equipped with an Argon laser (514.5 nm wavelenght). Analyses of stable isotope content ratio were performed using an isotope ratio mass spectrometer connected to an elemental analyzer and to a pyrolysis system. These studies demonstrate that RR spectroscopy is a valuable and useful technique for the analysis of EVOO. In combination with statistical analysis, it makes possible the assessment of specific samples’ content and allows for classifying oils according to their geographical and varietal origin.

Keywords: authentication, chemometrics, olive oil, raman spectroscopy

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Authors: Maria Arechavaleta, Mark Halpin

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In the United States, costs of solar energy systems have declined to the point that they are viable options for most consumers. However, there are no consistent procedures for specifying sufficient systems. The factors that must be considered are energy consumption, potential solar energy production, and cost. The traditional method of specifying solar energy systems is based on assumed daily levels of available solar energy and average amounts of daily energy consumption. The mismatches between energy production and consumption are usually mitigated using battery energy storage systems, and energy use is curtailed when necessary. The main consumer decision question that drives the total system cost is how much unserved (or curtailed) energy is acceptable? Of course additional solar conversion equipment can be installed to provide greater peak energy production and extra energy storage capability can be added to mitigate longer lasting low solar energy production periods. Each option increases total cost and provides a benefit which is difficult to quantify accurately. An approach to quantify the cost-benefit of adding additional resources, either production or storage or both, based on the statistical concepts of loss-of-energy probability and expected unserved energy, is presented in this paper. Relatively simple calculations, based on site-specific energy availability and consumption data, can be used to show the value of each additional increment of production or storage. With this incremental benefit-cost information, consumers can select the best overall performance combination for their application at a cost they are comfortable paying. The approach is based on a statistical analysis of energy consumption and production characteristics over time. The characteristics are in the forms of curves with each point on the curve representing an energy consumption or production value over a period of time; a one-minute period is used for the work in this paper. These curves are measured at the consumer location under the conditions that exist at the site and the duration of the measurements is a minimum of one week. While greater accuracy could be obtained with longer recording periods, the examples in this paper are based on a single week for demonstration purposes. The weekly consumption and production curves are overlaid on each other and the mismatches are used to size the battery energy storage system. Loss-of-energy probability and expected unserved energy indices are calculated in addition to the total system cost. These indices allow the consumer to recognize and quantify the benefit (probably a reduction in energy consumption curtailment) available for a given increase in cost. Consumers can then make informed decisions that are accurate for their location and conditions and which are consistent with their available funds.

Keywords: battery energy storage systems, loss of load probability, residential renewable energy, solar energy systems

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Authors: Sophie Baudel, Aline Duplaa, Jean Muller, Stephan Lauriol, Yann Bernard

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Argos is the main satellite telemetry system used by the wildlife research community, since its creation in 1978, for animal tracking and scientific data collection all around the world, to analyze and understand animal migrations and behavior. The marine mammals' biology is one of the major disciplines which had benefited from Argos telemetry, and conversely, marine mammals biologists’ community has contributed a lot to the growth and development of Argos use cases. The Argos constellation with 6 satellites in orbit in 2017 (Argos 2 payload on NOAA 15, NOAA 18, Argos 3 payload on NOAA 19, SARAL, METOP A and METOP B) is being extended in the following years with Argos 3 payload on METOP C (launch in October 2018), and Argos 4 payloads on Oceansat 3 (launch in 2019), CDARS in December 2021 (to be confirmed), METOP SG B1 in December 2022, and METOP-SG-B2 in 2029. Argos 4 will allow more frequency bands (600 kHz for Argos4NG, instead of 110 kHz for Argos 3), new modulation dedicated to animal (sea turtle) tracking allowing very low transmission power transmitters (50 to 100mW), with very low data rates (124 bps), enhancement of high data rates (1200-4800 bps), and downlink performance, at the whole contribution to enhance the system capacity (50,000 active beacons per month instead of 20,000 today). In parallel of this ‘institutional Argos’ constellation, in the context of a miniaturization trend in the spatial industry in order to reduce the costs and multiply the satellites to serve more and more societal needs, the French Space Agency CNES, which designs the Argos payloads, is innovating and launching the Argos ANGELS project (Argos NEO Generic Economic Light Satellites). ANGELS will lead to a nanosatellite prototype with an Argos NEO instrument (30 cm x 30 cm x 20cm) that will be launched in 2019. In the meantime, the design of the renewal of the Argos constellation, called Argos For Next Generations (Argos4NG), is on track and will be operational in 2022. Based on Argos 4 and benefitting of the feedback from ANGELS project, this constellation will allow revisiting time of fewer than 20 minutes in average between two satellite passes, and will also bring more frequency bands to improve the overall capacity of the system. The presentation will then be an overview of the Argos system, present and future and new capacities coming with it. On top of that, use cases of two Argos hardware modules will be presented: the goniometer pathfinder allowing recovering Argos beacons at sea or on the ground in a 100 km radius horizon-free circle around the beacon location and the new Argos 4 chipset called ‘Artic’, already available and tested by several manufacturers.

Keywords: Argos satellite telemetry, marine protected areas, oceanography, maritime services

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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Authors: Diom Loreen Ndum, Omarine Njimanted

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With increasing automation in clinical laboratories, the requirements for quality control materials have greatly increased in order to monitor daily performance. The constant use of commercial control material is not economically feasible for many developing countries because of non-availability or the high-cost of the materials. Therefore, preparation and use of in-house quality control serum will be a very cost-effective measure with respect to laboratory needs.The objective of this study was to determine the efficacy of in-house prepared pooled sera with respect to commercially acquired control sample for routine internal quality control at the Nkwen District Hospital Laboratory. This was an analytical study, serum was taken from leftover serum samples of 5 healthy adult blood donors at the blood bank of Nkwen District Hospital, which had been screened negative for human immunodeficiency virus (HIV), hepatitis C virus (HCV) and Hepatitis B antigens (HBsAg), and were pooled together in a sterile container. From the pooled sera, sixty aliquots of 150µL each were prepared. Forty aliquots of 150µL each of commercially acquired samples were prepared after reconstitution and stored in a deep freezer at − 20°C until it was required for analysis. This study started from the 9th June to 12th August 2022. Every day, alongside with commercial control sample, one aliquot of pooled sera was removed from the deep freezer and allowed to thaw before analyzed for the following parameters: blood urea, serum creatinine, aspartate aminotransferase (AST), alanine aminotransferase (ALT), potassium and sodium. After getting the first 20 values for each parameter of pooled sera, the mean, standard deviation and coefficient of variation were calculated, and a Levey-Jennings (L-J) chart established. The mean and standard deviation for commercially acquired control sample was provided by the manufacturer. The following results were observed; pooled sera had lesser standard deviation for creatinine, urea and AST than commercially acquired control samples. There was statistically significant difference (p<0.05) between the mean values of creatinine, urea and AST for in-house quality control when compared with commercial control. The coefficient of variation for the parameters for both commercial control and in-house control samples were less than 30%, which is an acceptable difference. The L-J charts revealed shifts and trends (warning signs), so troubleshooting and corrective measures were taken. In conclusion, in-house quality control sample prepared from pooled serum can be a good control sample for routine internal quality control.

Keywords: internal quality control, levey-jennings chart, pooled sera, shifts, trends, westgard rules

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Authors: V. Samulionis, J. Banys, A. Sánchez-Ferrer

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Inorganic nanoparticles are used for fabrication of various composites based on polymer materials because they exhibit a good homogeneity and solubility of the composite material. Multifunctional materials based on composites of a polymer containing inorganic nanotubes are expected to have a great impact on industrial applications in the future. An emerging family of such composites are polyurea elastomers with inorganic MoS2 nanotubes or MoSI nanowires. Polyurea elastomers are a new kind of materials with higher performance than polyurethanes. The improvement of mechanical, chemical and thermal properties is due to the presence of hydrogen bonds between the urea motives which can be erased at high temperature softening the elastomeric network. Such materials are the combination of amorphous polymers above glass transition and crosslinkers which keep the chains into a single macromolecule. Polyurea exhibits a phase separated structure with rigid urea domains (hard domains) embedded in a matrix of flexible polymer chains (soft domains). The elastic properties of polyurea can be tuned over a broad range by varying the molecular weight of the components, the relative amount of hard and soft domains, and concentration of nanoparticles. Ultrasonic methods as non-destructive techniques can be used for elastomer composites characterization. In this manner, we have studied the temperature dependencies of the longitudinal ultrasonic velocity and ultrasonic attenuation of these new polyurea elastomers and composites with inorganic nanoparticles. It was shown that in these polyurea elastomers large ultrasonic attenuation peak and corresponding velocity dispersion exists at 10 MHz frequency below room temperature and this behaviour is related to glass transition Tg of the soft segments in the polymer matrix. The relaxation parameters and Tg depend on the segmental molecular weight of the polymer chains between crosslinking points, the nature of the crosslinkers in the network and content of MoS2 nanotubes or MoSI nanowires. The increase of ultrasonic velocity in composites modified by nanoparticles has been observed, showing the reinforcement of the elastomer. In semicrystalline polyurea elastomer matrices, above glass transition, the first order phase transition from quasi-crystalline to the amorphous state has been observed. In this case, the sharp ultrasonic velocity and attenuation anomalies were observed near the transition temperature TC. Ultrasonic attenuation maximum related to glass transition was reduced in quasicrystalline polyureas indicating less influence of soft domains below TC. The first order phase transition in semicrystalline polyurea elastomer samples has large temperature hysteresis (> 10 K). The impact of inorganic MoS2 nanotubes resulted in the decrease of the first order phase transition temperature in semicrystalline composites.

Keywords: inorganic nanotubes, polyurea elastomer composites, ultrasonic velocity, ultrasonic attenuation

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Authors: Sara A. Pakvis, Giulia Scalet, Stefania Marconi, Ferdinando Auricchio, Matthijs Langelaar

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In recent developments in the field of multi-material additive manufacturing, differences in material properties are exploited to create printed shape-memory structures, which are referred to as 4D-printed structures. New printing techniques allow for the deliberate introduction of prestresses in the specimen during manufacturing, and, in combination with the right design, this enables new functionalities. This research focuses on bi-polymer 4D-printed structures, where the transformation process is based on a heat-induced glass transition in one material lowering its Young’s modulus, combined with an initial prestress in the other material. Upon the decrease in stiffness, the prestress is released, which results in the realization of an essentially pre-programmed deformation. As the design of such functional multi-material structures is crucial but far from trivial, a systematic methodology to find the design of 4D-printed structures is developed, where a finite element model is combined with a density-based topology optimization method to describe the material layout. This modeling approach is verified by a convergence analysis and validated by comparing its numerical results to analytical and published data. Specific aspects that are addressed include the interplay between the definition of the prestress and the material interpolation function used in the density-based topology description, the inclusion of a temperature-dependent stiffness relationship to simulate the glass transition effect, and the importance of the consideration of geometric nonlinearity in the finite element modeling. The efficacy of topology optimization to design 4D-printed structures is explored by applying the methodology to a variety of design problems, both in 2D and 3D settings. Bi-layer designs composed of thermoplastic polymers are printed by means of the fused deposition modeling (FDM) technology. Acrylonitrile butadiene styrene (ABS) polymer undergoes the glass transition transformation, while polyurethane (TPU) polymer is prestressed by means of the 3D-printing process itself. Tests inducing shape transformation in the printed samples through heating are performed to calibrate the prestress and validate the modeling approach by comparing the numerical results to the experimental findings. Using the experimentally obtained prestress values, more complex designs have been generated through topology optimization, and samples have been printed and tested to evaluate their performance. This study demonstrates that by combining topology optimization and 4D-printing concepts, stimuli-responsive structures with specific properties can be designed and realized.

Keywords: 4D-printing, glass transition, shape memory polymer, topology optimization

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Authors: Tamar Grdzelishvili, Zaza Sinauridze

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Introduction: Preeclampsia is a complication of the second trimester of pregnancy, which is characterized by high morbidity and multiorgan damage. Many complex pathogenic mechanisms are now implicated to be responsible for this disease (1). Preeclampsia is one of the leading causes of maternal mortality worldwide. Statistics are enough to convince you of the seriousness of this pathology: about 100,000 women die of preeclampsia every year. It occurs in 3-14% (varies significantly depending on racial origin or ethnicity and geographical region) of pregnant women, in 75% of cases - in a mild form, and in 25% - in a severe form. During severe pre-eclampsia-eclampsia, perinatal mortality increases by 5 times and stillbirth by 9.6 times. Considering that the only way to treat the disease is to end the pregnancy, the main thing is timely diagnosis and prevention of the disease. Identification of high-risk pregnant women for PE and giving prophylaxis would reduce the incidence of preterm PE. First-trimester screening model developed by the Fetal Medicine Foundation (FMF), which uses the Bayes-theorem to combine maternal characteristics and medical history together with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, has been proven to be effective and have superior screening performance to that of traditional risk factor-based approach for the prediction of PE (2) Methods: Retrospective single center screening study. The study population consisted of women from the Tbilisi maternity hospital “Pineo medical ecosystem” who met the following criteria: they spoke Georgian, English, or Russian and agreed to participate in the study after discussing informed consent and answering questions. Prior to the study, the informed consent forms approved by the Institutional Review Board were obtained from the study subjects. Early assessment of preeclampsia was performed between 11-13 weeks of pregnancy. The following were evaluated: anamnesis, dopplerography of the uterine artery, mean arterial blood pressure, and biochemical parameter: Pregnancy-associated plasma protein A (PAPP-A). Individual risk assessment was performed with performed by Fast Screen 3.0 software ThermoFisher scientific. Results: A total of 513 women were recruited and through the study, 51 women were diagnosed with preeclampsia (34.5% in the pregnant women with high risk, 6.5% in the pregnant women with low risk; P<0.000 1). Conclusions: First-trimester screening combining maternal factors with uterine artery Doppler, blood pressure, and pregnancy-associated plasma protein-A is useful to predict PE in a routine care setting. More patient studies are needed for final conclusions. The research is still ongoing.

Keywords: first-trimester, preeclampsia, screening, pregnancy-associated plasma protein

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Authors: Qian Li, Zhaoping Zhong

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Sewage sludge, a typical solid waste, has inevitably been produced in enormous quantities in China. Still worse, the amount of sewage sludge produced has been increasing due to rapid economic development and urbanization. Compared to the conventional method to treat sewage sludge, pyrolysis has been considered an economic and ecological technology because it can significantly reduce the sludge volume, completely kill pathogens, and produce valuable solid, gas, and liquid products. However, the large-scale utilization of sludge biochar has been limited due to the considerable risk posed by heavy metals in the sludge. Heavy metals enriched in pyrolytic biochar could be divided into exchangeable, reducible, oxidizable, and residual forms. The residual form of heavy metals is the most stable and cannot be used by organisms. Kaolin and zeolite are environmentally friendly inorganic minerals with a high surface area and heat resistance characteristics. So, they exhibit the enormous potential to immobilize heavy metals. In order to reduce the risk of leaching heavy metals in the pyrolysis biochar, this study pyrolyzed sewage sludge mixed with kaolin/zeolite in a small rotary kiln. The influences of additives and pyrolysis temperature on the leaching concentration and morphological transformation of heavy metals in pyrolysis biochar were investigated. The potential mechanism of stabilizing heavy metals in the co-pyrolysis of sludge blended with kaolin/zeolite was explained by scanning electron microscopy, X-ray diffraction, and specific surface area and porosity analysis. The European Community Bureau of Reference sequential extraction procedure has been applied to analyze the forms of heavy metals in sludge and pyrolysis biochar. All the concentrations of heavy metals were examined by flame atomic absorption spectrophotometry. Compared with the proportions of heavy metals associated with the F4 fraction in pyrolytic carbon prepared without additional agents, those in carbon obtained by co-pyrolysis of sludge and kaolin/zeolite increased. Increasing the additive dosage could improve the proportions of the stable fraction of various heavy metals in biochar. Kaolin exhibited a better effect on stabilizing heavy metals than zeolite. Aluminosilicate additives with excellent adsorption performance could capture more released heavy metals during sludge pyrolysis. Then heavy metal ions would react with the oxygen ions of additives to form silicate and aluminate, causing the conversion of heavy metals from unstable fractions (sulfate, chloride, etc.) to stable fractions (silicate, aluminate, etc.). This study reveals that the efficiency of stabilizing heavy metals depends on the formation of stable mineral compounds containing heavy metals in pyrolysis biochar.

Keywords: co-pyrolysis, heavy metals, immobilization mechanism, sewage sludge

Procedia PDF Downloads 66

Authors: Thomas Larm, Anna Wahlsten

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An international literature study has been carried out for comparison of commonly used methods for the dimensioning of transport systems and stormwater facilities for flow detention. The focus of the literature study regarding the calculation of design flow and detention has been the widely used Rational method and its underlying parameters. The impact of chosen design parameters such as return time, rain intensity, runoff coefficient, and climate factor have been studied. The parameters used in the calculations have been analyzed regarding how they can be calculated and within what limits they can be used. Data used within different countries have been specified, e.g., recommended rainfall return times, estimated runoff times, and climate factors used for different cases and time periods. The literature study concluded that the determination of runoff coefficients is the most uncertain parameter that also affects the calculated flow and required detention volume the most. Proposals have been developed for new runoff coefficients, including a new proposed method with equations for calculating runoff coefficients as a function of return time (years) and rain intensity (l/s/ha), respectively. Suggestions have been made that it is recommended not to limit the use of the Rational Method to a specific catchment size, contrary to what many design manuals recommend, with references to this. The proposed relationships between return time or rain intensity and runoff coefficients need further investigation and to include the quantification of uncertainties. Examples of parameters that have not been considered are the influence on the runoff coefficients of different dimensioning rain durations and the degree of water saturation of green areas, which will be investigated further. The influence of climate effects and design rain on the dimensioning of the stormwater facilities grassed ditches and biofilters (bio retention systems) has been studied, focusing on flow detention capacity. We have investigated how the calculated runoff coefficients regarding climate effect and the influence of changed (increased) return time affect the inflow to and dimensioning of the stormwater facilities. We have developed a smart design of ditches and biofilters that results in both high treatment and flow detention effects and compared these with the effect from dry and wet ponds. Studies of biofilters have generally before focused on treatment of pollutants, but their effect on flow volume and how its flow detention capability can improve is only rarely studied. For both the new type of stormwater ditches and biofilters, it is required to be able to simulate their performance in a model under larger design rains and future climate, as these conditions cannot be tested in the field. The stormwater model StormTac Web has been used on case studies. The results showed that the new smart design of ditches and biofilters had similar flow detention capacity as dry and wet ponds for the same facility area.

Keywords: runoff coefficients, flow detention, smart design, biofilter, ditch

Procedia PDF Downloads 87

Authors: Chi Zhang, Hua-Peng Chen

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With the increasingly demanding resources in the word, renewable and clean energy has been considered as an alternative way to replace traditional ones. Thus, one of practical examples for using wind energy is wind turbine, which has gained more attentions in recent research. Like most offshore structures, the blades, which is the most critical components of the wind turbine, will be subjected to millions of loading cycles during service life. To operate safely in marine environments, the blades are typically made from fibre reinforced composite materials to resist fatigue delamination and harsh environment. The fatigue crack development of blades is uncertain because of indeterminate mechanical properties for composite and uncertainties under offshore environment like wave loads, wind loads, and humid environments. There are three main delamination failure modes for composite blades, and the most common failure type in practices is subjected to mixed mode loading, typically a range of opening (mode 1) and shear (mode 2). However, the fatigue crack development for mixed mode cannot be predicted as deterministic values because of various uncertainties in realistic practical situation. Therefore, selecting an effective stochastic model to evaluate the mixed mode behaviour of wind turbine blades is a critical issue. In previous studies, gamma process has been considered as an appropriate stochastic approach, which simulates the stochastic deterioration process to proceed in one direction such as realistic situation for fatigue damage failure of wind turbine blades. On the basis of existing studies, various Paris Law equations are discussed to simulate the propagation of the fatigue crack growth. This paper develops a Paris model with the stochastic deterioration modelling according to gamma process for predicting fatigue crack performance in design service life. A numerical example of wind turbine composite materials is investigated to predict the mixed mode crack depth by Paris law and the probability of fatigue failure by gamma process. The probability of failure curves under different situations are obtained from the stochastic deterioration model for comparisons. Compared with the results from experiments, the gamma process can take the uncertain values into consideration for crack propagation of mixed mode, and the stochastic deterioration process shows a better agree well with realistic crack process for composite blades. Finally, according to the predicted results from gamma stochastic model, assessment strategies for composite blades are developed to reduce total lifecycle costs and increase resistance for fatigue crack growth.

Keywords: Reinforced fibre composite, Wind turbine blades, Fatigue delamination, Mixed failure mode, Stochastic process.

Procedia PDF Downloads 413

Authors: Abdolrasoul Daneshjoo

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Introduction: Soccer is a game which draws more attention in different countries especially in Brazil. Kicking among different skills in soccer and soccer players is an excellent role for the success and preference of a team. The way of point gaining in this game is passing the ball over the goal lines which are gained by shoot skill in attack time and or during the penalty kicks.Regarding the above assumption, identifying the effective factors in instep kicking in different distances shoot with maximum force and high accuracy or pass and penalty kick, may assist the coaches and players in raising qualitative level of performing the skill. Purpose: The aim of the present study was to study of a few kinematical parameters in instep kicking from 3 and 5 meter distance among the male and female elite soccer players. Methods: 24 right dominant lower limb subjects (12 males and 12 females) among Tehran elite soccer players with average and the standard deviation (22.5 ± 1.5) & (22.08± 1.31) years, height of (179.5 ± 5.81) & (164.3 ± 4.09) cm, weight of (69.66 ± 4.09) & (53.16 ± 3.51) kg, %BMI (21.06 ± .731) & (19.67 ± .709), having playing history of (4 ± .73) & (3.08 ± .66) years respectively participated in this study. They had at least two years of continuous playing experience in Tehran soccer league.For sampling player's kick; Kinemetrix Motion analysis with three cameras with 500 Hz was used. Five reflective markers were placed laterally on the kicking leg over anatomical points (the iliac crest, major trochanter, lateral epicondyle of femur, lateral malleolus, and lateral aspect of distal head of the fifth metatarsus). Instep kick was filmed, with one step approach and 30 to 45 degrees angle from stationary ball. Three kicks were filmed, one kick selected for further analyses. Using Kinemetrix 3D motion analysis software, the position of the markers was analyzed. Descriptive statistics were used to describe the mean and standard deviation, while the analysis of variance, and independent t-test (P < 0.05) were used to compare the kinematic parameters between two genders. Results and Discussion: Among the evaluated parameters, the knee acceleration, the thigh angular velocity, the angle of knee proportionately showed significant relationship with consequence of kick. While company performance on 5m in 2 genders, significant differences were observed in internal – external displacement of toe, ankle, hip and the velocity of toe, ankle and the acceleration of toe and the angular velocity of pelvic, thigh and before time contact. Significant differences showed the internal – external displacement of toe, the ankle, the knee and the hip, the iliac crest and the velocity of toe, the ankle and acceleration of ankle and angular velocity of the pelvic and the knee.

Keywords: biomechanics, kinematics, soccer, instep kick, male, female

Procedia PDF Downloads 415

Authors: Neha Sahu, Awantika Singh, Brijesh Kumar, K. R. Arya

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Taraxacum officinale Weber or dandelion (Asteraceae) is an important Indian traditional herb used to treat liver detoxification, digestive problems, spleen, hepatic and kidney disorders, etc. The plant is well known to possess important phenolic and flavonoids to serve as a potential source of antioxidative and chemoprotective agents. Biosynthesis of bioactive compounds through in vitro cultures is a requisite for natural resource conservation and to provide an alternative source for pharmaceutical applications. Thus an efficient and reproducible protocol was developed for in vitro biosynthesis of bioactive antioxidative compounds from leaf derived callus and in vitro regenerated cultures of Taraxacum officinale using MS media fortified with various combinations of auxins and cytokinins. MS media containing 0.25 mg/l 2, 4-D (2, 4-Dichloro phenoxyacetic acid) with 0.05 mg/l 2-iP [N6-(2-Isopentenyl adenine)] was found as an effective combination for the establishment of callus with 92 % callus induction frequency. Moreover, 2.5 mg/l NAA (α-Naphthalene acetic acid) with 0.5 mg/l BAP (6-Benzyl aminopurine) and 1.5 mg/l NAA showed the optimal response for in vitro plant regeneration with 80 % regeneration frequency and rooting respectively. In vitro regenerated plantlets were further transferred to soil and acclimatized. Quantitative variability of accumulated bioactive compounds in cultures (in vitro callus, plantlets and acclimatized) were determined through UPLC-MS/MS (ultra-performance liquid chromatography-triple quadrupole-linear ion trap mass spectrometry) and compared with wild plants. The phytochemical determination of in vitro and wild grown samples showed the accumulation of 6 compounds. In in vitro callus cultures and regenerated plantlets, two major antioxidative compounds i.e. chlorogenic acid (14950.0 µg/g and 4086.67 µg/g) and umbelliferone (10400.00 µg/g and 2541.67 µg/g) were found respectively. Scopoletin was found to be highest in vitro regenerated plants (83.11 µg/g) as compared to wild plants (52.75 µg/g). Notably, scopoletin is not detected in callus and acclimatized plants, but quinic acid (6433.33 µg/g) and protocatechuic acid (92.33 µg/g) were accumulated at the highest level in acclimatized plants as compared to other samples. Wild grown plants contained highest content (948.33 µg/g) of flavonoid glycoside i.e. luteolin-7-O-glucoside. Our data suggests that in vitro callus and regenerated plants biosynthesized higher content of antioxidative compounds in controlled conditions when compared to wild grown plants. These standardized cultural conditions may be explored as a sustainable source of plant materials for enhanced production and adequate supply of oxidative polyphenols.

Keywords: anti-oxidative compounds, in vitro cultures, Taraxacum officinale, UPLC-MS/MS

Procedia PDF Downloads 201

Authors: Mohd Azman Abdul Latif, Erwan Basiron

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A flaw or drift from expected operational performance in one component (NAND, PMIC, controller, DRAM, etc.) may affect the reliability of the entire Solid State Drive (SSD) system. Therefore, it is important to ensure the required quality of each individual component through qualification testing specified using standards or user requirements. Qualification testing is time-consuming and comes at a substantial cost for product manufacturers. A highly technical team, from all the eminent stakeholders is embarking on reliability prediction from beginning of new product development, identify critical to reliability parameters, perform full-blown characterization to embed margin into product reliability and establish control to ensure the product reliability is sustainable in the mass production. The paper will discuss a comprehensive development framework, comprehending SSD end to end from design to assembly, in-line inspection, in-line testing and will be able to predict and to validate the product reliability at the early stage of new product development. During the design stage, the SSD will go through intense reliability margin investigation with focus on assembly process attributes, process equipment control, in-process metrology and also comprehending forward looking product roadmap. Once these pillars are completed, the next step is to perform process characterization and build up reliability prediction modeling. Next, for the design validation process, the reliability prediction specifically solder joint simulator will be established. The SSD will be stratified into Non-Operating and Operating tests with focus on solder joint reliability and connectivity/component latent failures by prevention through design intervention and containment through Temperature Cycle Test (TCT). Some of the SSDs will be subjected to the physical solder joint analysis called Dye and Pry (DP) and Cross Section analysis. The result will be feedbacked to the simulation team for any corrective actions required to further improve the design. Once the SSD is validated and is proven working, it will be subjected to implementation of the monitor phase whereby Design for Assembly (DFA) rules will be updated. At this stage, the design change, process and equipment parameters are in control. Predictable product reliability at early product development will enable on-time sample qualification delivery to customer and will optimize product development validation, effective development resource and will avoid forced late investment to bandage the end-of-life product failures. Understanding the critical to reliability parameters earlier will allow focus on increasing the product margin that will increase customer confidence to product reliability.

Keywords: e2e reliability prediction, SSD, TCT, solder joint reliability, NUDD, connectivity issues, qualifications, characterization and control

Procedia PDF Downloads 174

Authors: Amiza Surmi, Azmi Shariff, Sow Mun Serene Lock

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In recent decades, there has been a significant emphasis on the pivotal role of Rotating Packed Beds (RPBs) in absorption processes, encompassing the removal of Volatile Organic Compounds (VOCs) from groundwater, deaeration, CO2 absorption, desulfurization, and similar critical applications. The primary focus is elevating mass transfer rates, enhancing separation efficiency, curbing power consumption, and mitigating pressure drops. Additionally, substantial efforts have been invested in exploring the adaptation of RPB technology for offshore deployment. This comprehensive study delves into the intricacies of nitrogen removal under low temperature and high-pressure conditions, employing the high gravity principle via innovative RPB distillation concept with a specific emphasis on optimizing mass transfer. Based on the author's knowledge and comprehensive research, no cryogenic experimental testing was conducted to remove nitrogen via RPB. The research identifies pivotal process control factors through meticulous experimental testing, with pressure, reflux ratio, and reboil ratio emerging as critical determinants in achieving the desired separation performance. The results are remarkable, with nitrogen removal reaching less than one mole% in the Liquefied Natural Gas (LNG) product and less than three moles% methane in the nitrogen-rich gas stream. The study further unveils the mass transfer coefficient, revealing a noteworthy trend of decreasing Number of Transfer Units (NTU) and Area of Transfer Units (ATU) as the rotational speed escalates. Notably, the condenser and reboiler impose varying demands based on the operating pressure, with lower pressures at 12 bar requiring a more substantial duty than the 15-bar operation of the RPB. In pursuit of optimal energy efficiency, a meticulous sensitivity analysis is conducted, pinpointing the ideal combination of pressure and rotating speed that minimizes overall energy consumption. These findings underscore the efficiency of the RPB distillation approach in effecting efficient separation, even when operating under the challenging conditions of low temperature and high pressure. This achievement is attributed to a rigorous process control framework that diligently manages the operational pressure and temperature profile of the RPB. Nonetheless, the study's conclusions point towards the need for further research to address potential scaling challenges and associated risks, paving the way for the industrial implementation of this transformative technology.

Keywords: mass transfer coefficient, nitrogen removal, liquefaction, rotating packed bed

Procedia PDF Downloads 54

Authors: Izuddin Fahmy Abu, Mohamad Haiqal Nizar Mohamad, Muhammad Fattah Fazel, Renu Agarwal, Igor Iezhitsa, Nor Salmah Bakar, Henrik Franzyk, Ian Mellor

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Glaucoma is the global leading cause of irreversible blindness. Currently, the available treatment strategy only involves lowering intraocular pressure (IOP); however, the condition often progresses despite lowered or normal IOP in some patients. N-methyl-D-aspartate receptor (NMDAR) excitotoxicity often occurs in neurodegeneration-related glaucoma; thus it is a relevant target to develop a therapy based on neuroprotection approach. This study investigated the effects of Philanthotoxin-343 (PhTX-343), an NMDAR antagonist, on the neuroprotection of NMDA-induced glaucoma to alleviate visual impairments. Male Sprague-Dawley rats were equally divided: Groups 1 (control) and 2 (glaucoma) were intravitreally injected with phosphate buffer saline (PBS) and NMDA (160nM), respectively, while group 3 was pre-treated with PhTX-343 (160nM) 24 hours prior to NMDA injection. Seven days post-treatments, rats were subjected to visual behavior assessments and subsequently euthanized to harvest their retina and optic nerve tissues for histological analysis and determination of nitrosative stress level using 3-nitrotyrosine ELISA. Visual behavior assessments via open field, object, and color recognition tests demonstrated poor visual performance in glaucoma rats indicated by high exploratory behavior. PhTX-343 pre-treatment appeared to preserve visual abilities as all test results were significantly improved (p < 0.05). H&E staining of the retina showed a marked reduction of ganglion cell layer thickness in the glaucoma group; in contrast, PhTX-343 significantly increased the number by 1.28-folds (p < 0.05). PhTX-343 also increased the number of cell nuclei/100μm2 within inner retina by 1.82-folds compared to the glaucoma group (p < 0.05). Toluidine blue staining of optic nerve tissues showed that PhTX-343 reduced the degeneration changes compared to the glaucoma group which exhibited vacuolation overall sections. PhTX-343 also decreased retinal 3- nitrotyrosine concentration by 1.74-folds compared to the glaucoma group (p < 0.05). All results in PhTX-343 group were comparable to control (p > 0.05). We conclude that PhTX-343 protects against NMDA-induced changes and visual impairments in the rat model by reducing nitrosative stress levels.

Keywords: excitotoxicity, glaucoma, nitrosative stress , NMDA receptor , N-methyl-D-aspartate , philanthotoxin, visual behaviour

Procedia PDF Downloads 137

Authors: Benjamin Blat Belmonte, Stephan Rinderknecht

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The transition to electric vehicles (EVs) stands at the forefront of innovative strategies designed to address environmental concerns and reduce fossil fuel dependency. As the number of EVs on the roads increases, so too does the potential for their integration into energy markets. This research dives deep into the transformative possibilities of using electric vehicle fleets, specifically electric bus fleets, not just as consumers but as active participants in the energy market. This paper investigates the feasibility and grid effects of electric vehicle fleet operators in the energy market. Our objective centers around a comprehensive exploration of the sector coupling domain, with an emphasis on the economic potential in both electricity and balancing markets. Methodologically, our approach combines data mining techniques with thorough pre-processing, pulling from a rich repository of electricity and balancing market data. Our findings are grounded in the actual operational realities of the bus fleet operator in Darmstadt, Germany. We employ a Mixed Integer Linear Programming (MILP) approach, with the bulk of the computations being processed on the High-Performance Computing (HPC) platform ‘Lichtenbergcluster’. Our findings underscore the compelling economic potential of EV fleets in the energy market. With electric buses becoming more prevalent, the considerable size of these fleets, paired with their substantial battery capacity, opens up new horizons for energy market participation. Notably, our research reveals that economic viability is not the sole advantage. Participating actively in the energy market also translates into pronounced positive effects on grid stabilization. Essentially, EV fleet operators can serve a dual purpose: facilitating transport while simultaneously playing an instrumental role in enhancing grid reliability and resilience. This research highlights the symbiotic relationship between the growth of EV fleets and the stabilization of the energy grid. Such systems could lead to both commercial and ecological advantages, reinforcing the value of electric bus fleets in the broader landscape of sustainable energy solutions. In conclusion, the electrification of transport offers more than just a means to reduce local greenhouse gas emissions. By positioning electric vehicle fleet operators as active participants in the energy market, there lies a powerful opportunity to drive forward the energy transition. This study serves as a testament to the synergistic potential of EV fleets in bolstering both economic viability and grid stabilization, signaling a promising trajectory for future sector coupling endeavors.

Keywords: electric vehicle fleet, sector coupling, optimization, electricity market, balancing market

Procedia PDF Downloads 74

Authors: Amparo Camacho

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ABET accredited programs must assess the development of student learning outcomes (SOs) in engineering programs. Different institutions implement different strategies for this assessment, and they are usually designed “in house.” This paper presents a proposal for including standardized tests to complement the ABET assessment model in an engineering college made up of six distinct engineering programs. The engineering college formulated a model of quality assurance in education to be implemented throughout the six engineering programs to regularly assess and evaluate the achievement of SOs in each program offered. The model uses diverse techniques and sources of data to assess student performance and to implement actions of improvement based on the results of this assessment. The model is called “Assessment Process Model” and it includes SOs A through K, as defined by ABET. SOs can be divided into two categories: “hard skills” and “professional skills” (soft skills). The first includes abilities, such as: applying knowledge of mathematics, science, and engineering and designing and conducting experiments, as well as analyzing and interpreting data. The second category, “professional skills”, includes communicating effectively, and understanding professional and ethnical responsibility. Within the Assessment Process Model, various tools were used to assess SOs, related to both “hard” as well as “soft” skills. The assessment tools designed included: rubrics, surveys, questionnaires, and portfolios. In addition to these instruments, the Engineering College decided to use tools that systematically gather consistent quantitative data. For this reason, an in-house exam was designed and implemented, based on the curriculum of each program. Even though this exam was administered during various academic periods, it is not currently considered standardized. In 2017, the Engineering College included three standardized tests: one to assess mathematical and scientific reasoning and two more to assess reading and writing abilities. With these exams, the college hopes to obtain complementary information that can help better measure the development of both hard and soft skills of students in the different engineering programs. In the first semester of 2017, the three exams were given to three sample groups of students from the six different engineering programs. Students in the sample groups were either from the first, fifth, and tenth semester cohorts. At the time of submission of this paper, the engineering college has descriptive statistical data and is working with various statisticians to have a more in-depth and detailed analysis of the sample group of students’ achievement on the three exams. The overall objective of including standardized exams in the assessment model is to identify more precisely the least developed SOs in order to define and implement educational strategies necessary for students to achieve them in each engineering program.

Keywords: assessment, hard skills, soft skills, standardized tests

Procedia PDF Downloads 284

Authors: Maggie Mosher, Adam Carreon, Sean Smith

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A systematic literature review was conducted to explore the evidence base on the use of augmented reality (AR), virtual reality (VR), mixed reality (MR), and extended reality (XR) to present social skill instruction to school-age students with autism spectrum disorder (ASD). Specifically, the systematic review focus was on a. the participants and intervention agents using AR, VR, MR, and XR for social skill acquisition b. the social skills taught through these mediums and c. the social validity measures (i.e., goals, procedures, and outcomes) reported in these studies. Forty-one articles met the inclusion criteria. Researchers in six studies taught social skills to students through AR, in 27 studies through non-immersive VR, and in 10 studies through immersive VR. No studies used MR or XR. The primary targeted social skills were relationship skills, emotion recognition, social awareness, cooperation, and executive functioning. An intervention to improve many social skills was implemented by 73% of researchers, 17% taught a single skill, and 10% did not clearly state the targeted skill. The intervention was considered effective in 26 of the 41 studies (63%), not effective in four studies (10%), and 11 studies (27%) reported mixed results. No researchers reported information for all 17 social validity indicators. The social validity indicators reported by researchers ranged from two to 14. Social validity measures on the feelings toward and use of the technology were provided in 22 studies (54%). Findings indicated both AR and VR are promising platforms for providing social skill instruction to students with ASD. Studies utilizing this technology show a number of social validity indicators. However, the limited information provided on the various interventions, participant characteristics, and validity measures, offers insufficient evidence of the impact of these technologies in teaching social skills to students with ASD. Future research should develop a protocol for training treatment agents to assess the role of different variables (i.e., whether agents are customizing content, monitoring student learning, using intervention specific vocabulary in their day to day instruction). Sustainability may be increased by providing training in the technology to both treatment agents and participants. Providing scripts of instruction occurring within the intervention would provide the needed information to determine the primary method of teaching within the intervention. These variables play a role in maintenance and generalization of the social skills. Understanding the type of feedback provided would help researchers determine if students were able to feel rewarded for progressing through the scenarios or if students require rewarding aspects within the intervention (i.e., badges, trophies). AR has the potential to generalize instruction and VR has the potential for providing a practice environment for performance deficits. Combining these two technologies into a mixed reality intervention may provide a more cohesive and effective intervention.

Keywords: autism, augmented reality, social and emotional learning, social skills, virtual reality

Procedia PDF Downloads 109

Authors: V. Stejskal, K. Lundova, R. Sebesta, T. Vanina, S. Roje

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Pure strain of Arctic char (AC) Salvelinus alpinus and hybrid (HB) Salvelinus alpinus vs. Salvelinus fontinalis Mitchill belong to fish, which with great potential for culture in recirculating aquaculture systems (RAS). Aquaculture of these fish currently use flow-through systems (FTS), especially in Nordic countries such as Iceland (biggest producer), Norway, Sweden, and Canada. Four different water saturation regimes included normoxia (NOR), permanent hyperoxia (HYP), intermittent hyperoxia (HYP ± ) and regimes where one day of normoxia was followed by one day of hyperoxia (HYP1/1) were tested during 63 days of experiment in both species in two parallel experiments. Fish were reared in two identical RAS system consisted of 24 plastic round tanks (300 L each), drum filter, biological filter with moving beads and submerged biofilter. The temperature was maintained using flow-through cooler during at level of 13.6 ± 0.8 °C. Different water saturation regimes were achieved by mixing of pure oxygen (O₂) with water in three (one for each hyperoxic regime) mixing tower equipped with flowmeter for regulation of gas inflow. The water in groups HYP, HYP1/1 and HYP± was enriched with oxygen up to saturation of 120-130%. In HYP group was this level kept during whole day. In HYP ± group was hyperoxia kept for daylight phase (08:00-20:00) only and during night time was applied normoxia in this group. The oxygen saturation of 80-90% in NOR group was created using intensive aeration in header tank. The fish were fed with commercial feed to slight excess at 2 h intervals within the light phase of the day. Water quality parameters like pH, temperature and level of oxygen was monitoring three times (7 am, 10 am and 6 pm) per day using handy multimeter. Ammonium, nitrite and nitrate were measured in two day interval using spectrophotometry. Initial body weight (BW) was 40.9 ± 8.7 g and 70.6 ± 14.8 in AC and HB group, respectively. Final survival of AC ranged from 96.3 ± 4.6 (HYP) to 100 ± 0.0% in all other groups without significant differences among these groups. Similarly very high survival was reached in trial with HB with levels from 99.2 ± 1.3 (HYP, HYP1/1 and NOR) to 100 ± 0.0% (HYP ± ). HB fish showed best growth performance in NOR group reached final body weight (BW) 180.4 ± 2.3 g. Fish growth under different hyperoxic regimes was significantly reduced and final BW was 164.4 ± 7.6, 162.1 ± 12.2 and 151.7 ± 6.8 g in groups HY1/1, HYP ± and HYP, respectively. AC showed different preference for hyperoxic regimes as there were no significant difference in BW among NOR, HY1/1 and HYP± group with final values of 72.3 ± 11.3, 68.3 ± 8.4 and 77.1 ± 6.1g. Significantly reduced growth (BW 61.8 ± 6.8 g) was observed in HYP group. It is evident from present study that there are differences between pure bred Arctic char and hybrid in relation to hyperoxic regimes. The study was supported by projects 'CENAKVA' (No. CZ.1.05/2.1.00/01.0024), 'CENAKVA II' (No. LO1205 under the NPU I program), NAZV (QJ1510077) and GAJU (No. 060/2016/Z).

Keywords: recirculating aquaculture systems, Salmonidae, hyperoxia, abiotic factors

Procedia PDF Downloads 182

Authors: Michael Nolte, Iwona Kasior, Kala Flagg, Spiro Karavatas

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Background: Cryotherapy has been used as a post-exercise recovery modality for decades. Whole-body cryotherapy (WBC) is an intervention which involves brief exposures to extremely cold air in order to induce therapeutic effects. It is currently being investigated for its effectiveness in treating certain exercise-induced impairments. Purpose: The purpose of this systematic review was to determine whether WBC as a recovery intervention is more, less, or equally as effective as other interventions at reducing perceived levels of muscle soreness and promoting recovery of muscle function after exercise-induced muscle damage (EIMD) from running. Methods: A systematic review of the current literature was performed utilizing the following MeSH terms: cryotherapy, whole-body cryotherapy, exercise-induced muscle damage, muscle soreness, muscle recovery, and running. The databases utilized were PubMed, CINAHL, EBSCO Host, and Google Scholar. Articles were included if they were published within the last ten years, had a CEBM level of evidence of IIb or higher, had a PEDro scale score of 5 or higher, studied runners as primary subjects, and utilized both perceived levels of muscle soreness and recovery of muscle function as dependent variables. Articles were excluded if subjects did not include runners, if the interventions included PBC instead of WBC, and if both muscle performance and perceived muscle soreness were not assessed within the study. Results: Two of the four articles revealed that WBC was significantly more effective than treatment interventions such as far-infrared radiation and passive recovery at reducing perceived levels of muscle soreness and restoring muscle power and endurance following simulated trail runs and high-intensity interval running, respectively. One of the four articles revealed no significant difference between WBC and passive recovery in terms of reducing perceived muscle soreness and restoring muscle power following sprint intervals. One of the four articles revealed that WBC had a harmful effect compared to CWI and passive recovery on both perceived muscle soreness and recovery of muscle strength and power following a marathon. Discussion/Conclusion: Though there was no consensus in terms of WBC’s effectiveness at treating exercise-induced muscle damage following running compared to other interventions, it seems as though WBC may at least have a time-dependent positive effect on muscle soreness and recovery following high-intensity interval runs and endurance running, marathons excluded. More research needs to be conducted in order to determine the most effective way to implement WBC as a recovery method for exercise-induced muscle damage, including the optimal temperature, timing, duration, and frequency of treatment.

Keywords: cryotherapy, physical therapy intervention, physical therapy, whole body cryotherapy

Procedia PDF Downloads 240

Authors: Shaukat Ali Shahee, Usha Ananthakumar

Abstract:

A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: Ines Antunes, Andrea Massari, Concetta Bartucca

Abstract:

Greenhouse gasses (GHG) role in the atmosphere has been well known since the 19th century; however, researchers have begun to relate them to climate changes only in the second half of the following century. From this moment, scientists started to correlate the presence of GHG such as CO₂ with the global warming phenomena. This has raised the awareness not only of those who were experts in this field but also of public opinion, which is becoming more and more sensitive to environmental pollution and sustainability issues. Nowadays the reduction of GHG emissions is one of the principal objectives of EU nations. The target is an 80% reduction of emissions in 2050 and to reach the important goal of carbon neutrality. Road sector is responsible for an important amount of those emissions (about 20%). The most part is due to traffic, but a good contribution is also given directly or indirectly from road construction and maintenance. Raw material choice and reuse of post-consumer plastic rather than a cleverer design of roads have an important contribution to reducing carbon footprint. Bituminous membranes can be successfully used as reinforcement systems in asphalt layers to improve road pavement performance against cracking. Composite materials coupling membranes with grids and/or fabrics should be able to combine improved tensile properties of the reinforcement with stress absorbing and waterproofing effects of membranes. Polyglass, with its brand dedicated to road construction and maintenance called Polystrada, has done more than this. The company's target was not only to focus sustainability on the final application but also to implement a greener mentality from the cradle to the grave. Starting from production, Polyglass has made important improvements finalized to increase efficiency and minimize waste. The installation of a trigeneration plant and the usage of selected production scraps inside the products as well as the reduction of emissions into the environment, are one of the main efforts of the company to reduce impact during final product build-up. Moreover, the benefit given by installing Polystrada products brings a significant improvement in road lifetime. This has an impact not only on the number of maintenance or renewal that needs to be done (build less) but also on traffic density due to works and road deviation in case of operations. During the end of the life of a road, Polystrada products can be 100% recycled and milled with classical systems used without changing the normal maintenance procedures. In this work, all these contributions were quantified in terms of CO₂ emission thanks to an LCA analysis. The data obtained were compared with a classical system or a standard production of a membrane. What it is possible to see is that the usage of Polyglass products for street maintenance and building gives a significant reduction of emissions in case of membrane installation under the road wearing course.

Keywords: CO₂ emission, LCA, maintenance, sustainability

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Authors: Swati Tomar, Sunil Kumar Gupta

Abstract:

Anammox is a novel and promising technology that has changed the traditional concept of biological nitrogen removal. The process facilitates direct oxidation of ammonical nitrogen under anaerobic conditions with nitrite as an electron acceptor without the addition of external carbon sources. The present study investigated the feasibility of anammox hybrid reactor (AHR) combining the dual advantages of suspended and attached growth media for biodegradation of ammonical nitrogen in wastewater. The experimental unit consisted of 4 nos. of 5L capacity AHR inoculated with mixed seed culture containing anoxic and activated sludge (1:1). The process was established by feeding the reactors with synthetic wastewater containing NH4-H and NO2-N in the ratio 1:1 at HRT (hydraulic retention time) of 1 day. The reactors were gradually acclimated to higher ammonium concentration till it attained pseudo steady state removal at a total nitrogen concentration of 1200 mg/l. During this period, the performance of the AHR was monitored at twelve different HRTs varying from 0.25-3.0 d with increasing NLR from 0.4 to 4.8 kg N/m3d. AHR demonstrated significantly higher nitrogen removal (95.1%) at optimal HRT of 1 day. Filter media in AHR contributed an additional 27.2% ammonium removal in addition to 72% reduction in the sludge washout rate. This may be attributed to the functional mechanism of filter media which acts as a mechanical sieve and reduces the sludge washout rate many folds. This enhances the biomass retention capacity of the reactor by 25%, which is the key parameter for successful operation of high rate bioreactors. The effluent nitrate concentration, which is one of the bottlenecks of anammox process was also minimised significantly (42.3-52.3 mg/L). Process kinetics was evaluated using first order and Grau-second order models. The first-order substrate removal rate constant was found as 13.0 d-1. Model validation revealed that Grau second order model was more precise and predicted effluent nitrogen concentration with least error (1.84±10%). A new mathematical model based on mass balance was developed to predict N2 gas in AHR. The mass balance model derived from total nitrogen dictated significantly higher correlation (R2=0.986) and predicted N2 gas with least error of precision (0.12±8.49%). SEM study of biomass indicated the presence of the heterogeneous population of cocci and rod shaped bacteria of average diameter varying from 1.2-1.5 mm. Owing to enhanced NRE coupled with meagre production of effluent nitrate and its ability to retain high biomass, AHR proved to be the most competitive reactor configuration for dealing with nitrogen laden wastewater.

Keywords: anammox, filter media, kinetics, nitrogen removal

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Authors: Sh. Sousani, Z. Shadrokh, M. Hofbauerová, J. Kollár, M. Jergel, P. Nádaždy, M. Omastová, E. Majková

Abstract:

Perovskite quantum dots (PQDs) have the potential to increase the performance of the perovskite solar cell (PSCs). The integration of PQDs into PSCs can extend the absorption range and enhance photon harvesting and device efficiency. In addition, PQDs can stabilize the device structure by passivating surface defects and traps in the perovskite layer and enhance its stability. The integration of PQDs into PSCs is strongly affected by the type of ligands on the surface of PQDs. The ligands affect the charge transport properties of PQDs, as well as the formation of well-defined interfaces and stability of PSCs. In this work, the CsPbBr₃ QDs were synthesized by the conventional hot-injection method using cesium oleate, PbBr₂ and two different ligands, namely oleic acid (OA) oleylamine (OAm) and didodecyldimethylammonium bromide (DDAB). The STEM confirmed regular shape and relatively monodisperse cubic structure with an average size of about 10-14 nm of the prepared CsPbBr₃ QDs. Further, the photoluminescent (PL) properties of the PQDs/perovskite bilayer with the ligand OA, OAm and DDAB were studied. For this purpose, ITO/PQDs as well as ITO/PQDs/MAPI perovskite structures were prepared by spin coating and the effect of the ligand and oxygen plasma treatment was analyzed. The plasma treatment of the PQDs layer could be beneficial for the deposition of the MAPI perovskite layer and the formation of a well-defined PQDs/MAPI interface. The absorption edge in UV-Vis absorption spectra for OA, OAm CsPbBr₃ QDs is placed around 513 nm (the band gap 2.38 eV); for DDAB CsPbBr₃ QDs, it is located at 490 nm (the band gap 2.33 eV). The photoluminescence (PL) spectra of CsPbBr₃ QDs show two peaks located around 514 nm (503 nm) and 718 nm (708 nm) for OA, OAm (DDAB). The peak around 500 nm corresponds to the PL of PQDs, and the peak close to 710 nm belongs to the surface states of PQDs for both types of ligands. These surface states are strongly affected by the O₃ plasma treatment. For PQDs with DDAB ligand, the O₃ exposure (5, 10, 15 s) results in the blue shift of the PQDs peak and a non-monotonous change of the amplitude of the surface states' peak. For OA, OAm ligand, the O₃ exposition did not cause any shift of the PQDs peak, and the intensity of the PL peak related to the surface states is lower by one order of magnitude in comparison with DDAB, being affected by O₃ plasma treatment. The PL results indicate the possibility of tuning the position of the PL maximum by the ligand of the PQDs. Similar behavior of the PQDs layer was observed for the ITO/QDs/MAPI samples, where an additional strong PL peak at 770 nm coming from the perovskite layer was observed; for the sample with PQDs with DDAB ligands, a small blue shift of the perovskite PL maximum was observed independently of the plasma treatment. These results suggest the possibility of affecting the PL maximum position and the surface states of the PQDs by the combination of a suitable ligand and the O₃ plasma treatment.

Keywords: perovskite quantum dots, photoluminescence, O₃ plasma., Perovskite Solar Cells

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