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Authors: Susana Barreto

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This paper explores a pedagogical exercise that employs family photos as catalysts for teaching visual analysis and inspiring academic writing among MA students. The study aimed to achieve two primary objectives: to impart students with the skills of analyzing images or artifacts and to ignite their writing for research purposes. Conducted at Viana Polytechnic in Portugal, the exercise involved two classes on Arts Management and Art Education Master course comprising approximately twenty students from diverse academic backgrounds, including Economics, Design, Fine Arts, and Sociology, among others. The exploratory exercise involved selecting an old family photo, analyzing its content and context, and deconstructing the chosen images in an intuitive and systematic manner. Students were encouraged to engage in photo elicitation, seeking insights from family/friends to gain multigenerational perspectives on the images. The feedback received from this exercise was consistently positive, largely due to the personal connection students felt with the objects of analysis. Family photos, with their emotional significance, fostered deeper engagement and motivation in the learning process. Furthermore, visual analysing family photos stimulated critical thinking as students interpreted the composition, subject matter, and potential meanings embedded in the images. This practice enhanced their ability to comprehend complex visual representations and construct compelling visual narratives, thereby facilitating the writing process. The exercise also facilitated the identification of patterns, similarities, and differences by comparing different family photos, leading to a more comprehensive analysis of visual elements and themes. Throughout the exercise, students found analyzing their own photographs both enjoyable and insightful. They progressed through preliminary analysis, explored content and context, and artfully interwove these components. Additionally, students experimented with various techniques such as converting photos to black and white, altering framing angles, and adjusting sizes to unveil hidden meanings.The methodology employed included observation, documental analysis of written reports, and student interviews. By including students from diverse academic backgrounds, the study enhanced its external validity, enabling a broader range of perspectives and insights during the exercise. Furthermore, encouraging students to seek multigenerational perspectives from family and friends added depth to the analysis, enriching the learning experience and broadening the understanding of the cultural and historical context associated with the family photos Highlighting the emotional significance of these family photos and the personal connection students felt with the objects of analysis fosters a deeper connection to the subject matter. Moreover, the emphasis on stimulating critical thinking through the analysis of composition, subject matter, and potential meanings in family photos suggests a targeted approach to developing analytical skills. This improvement focuses specifically on critical thinking and visual analysis, enhancing the overall quality of the exercise. Additionally, the inclusion of a step where students compare different family photos to identify patterns, similarities, and differences further enhances the depth of the analysis. This comparative approach adds a layer of complexity to the exercise, ultimately leading to a more comprehensive understanding of visual elements and themes. The expected results of this study will culminate in a set of practical recommendations for implementing this exercise in academic settings.

Keywords: visual analysis, academic writing, pedagogical exercise, family photos

Procedia PDF Downloads 53

Authors: Makhan Maharjan, Mani Ulaganathan, Vanchiappan Aravindan, Srinivasan Madhavi, Jing-Yuan Wang, Tuti Mariana Lim

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There is great interest to exploit sustainable, low-cost, renewable resources as carbon precursors for energy storage applications. Research on development of energy storage devices has been growing rapidly due to mismatch in power supply and demand from renewable energy sources This paper reported the synthesis of porous activated carbon from biomass waste and evaluated its performance in supercapicators. In this work, we employed orange peel (waste material) as the starting material and synthesized activated carbon by pyrolysis of KOH impregnated orange peel char at 800 °C in argon atmosphere. The resultant orange peel-derived activated carbon (OP-AC) exhibited a high BET surface area of 1,901 m2 g-1, which is the highest surface area so far reported for the orange peel. The pore size distribution (PSD) curve exhibits the pores centered at 11.26 Å pore width, suggesting dominant microporosity. The OP-AC was studied as positive electrode in combination with different negative electrode materials, such as pre-lithiated graphite (LiC6) and Li4Ti5O12 for making different hybrid capacitors. The lithium ion capacitor (LIC) fabricated using OP-AC with pre-lithiated graphite delivered a high energy density of ~106 Wh kg–1. The energy density for OP-AC||Li4Ti5O12 capacitor was ~35 Wh kg–1. For comparison purpose, configuration of OP-AC||OP-AC capacitors were studied in both aqueous (1M H2SO4) and organic (1M LiPF6 in EC-DMC) electrolytes, which delivered the energy density of 6.6 Wh kg-1 and 16.3 Wh kg-1, respectively. The cycling retentions obtained at current density of 1 A g–1 were ~85.8, ~87.0 ~82.2 and ~58.8% after 2500 cycles for OP-AC||OP-AC (aqueous), OP-AC||OP-AC (organic), OP-AC||Li4Ti5O12 and OP-AC||LiC6 configurations, respectively. In addition, characterization studies were performed by elemental and proximate composition, thermogravimetry, field emission-scanning electron microscopy, Raman spectra, X-ray diffraction (XRD) pattern, Fourier transform-infrared, X-ray photoelectron spectroscopy (XPS) and N2 sorption isotherms. The morphological features from FE-SEM exhibited well-developed porous structures. Two typical broad peaks observed in the XRD framework of the synthesized carbon implies amorphous graphitic structure. The ratio of 0.86 for ID/IG in Raman spectra infers high degree of graphitization in the sample. The band spectra of C 1s in XPS display the well resolved peaks related to carbon atoms in various chemical environments; for instances, the characteristics binding energies appeared at ~283.83, ~284.83, ~286.13, ~288.56, and ~290.70 eV which correspond to sp2 -graphitic C, sp3 -graphitic C, C-O, C=O and π-π*, respectively. Characterization studies revealed the synthesized carbon to be promising electrode material towards the application for energy storage devices. The findings opened up the possibility of developing high energy LICs from abundant, low-cost, renewable biomass waste.

Keywords: lithium-ion capacitors, orange peel, pre-lithiated graphite, supercapacitors

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Authors: Eszter Repasi, Akos Koller

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Our genetic information determines our look, physiology, sports performance and all our features. Maximizing the performances of athletes have adopted a science-based approach to the nutritional support. Nowadays genetics studies have blended with nutritional sciences, and a dynamically evolving, new research field have appeared. Nutritional genomics is needed to be used by nutritional experts. This is a recent field of nutritional science, which can provide a solution to reach the best sport performance using correlations between the athlete’s genome, nutritions, molecules, included human microbiome (links between food, microbiome and epigenetics), nutrigenomics and nutrigenetics. Nutritional genomics has a tremendous potential to change the future of dietary guidelines and personal recommendations. Experts need to use new technology to get information about the athletes, like nutritional genomics profile (included the determination of the oral and gut microbiome and DNA coded reaction for food components), which can modify the preparation term and sports performance. The influence of nutrients on the genes expression is called Nutrigenomics. The heterogeneous response of gene variants to nutrients, dietary components is called Nutrigenetics. The human microbiome plays a critical role in the state of health and well-being, and there are more links between food or nutrition and the human microbiome composition, which can develop diseases and epigenetic changes as well. A nutritional genomics-based profile of athletes can be the best technic for a dietitian to make a unique sports nutrition diet plan. Using functional food and the right food components can be effected on health state, thus sports performance. Scientists need to determine the best response, due to the effect of nutrients on health, through altering genome promote metabolites and result changes in physiology. Nutritional biochemistry explains why polymorphisms in genes for the absorption, circulation, or metabolism of essential nutrients (such as n-3 polyunsaturated fatty acids or epigallocatechin-3-gallate), would affect the efficacy of that nutrient. Controlled nutritional deficiencies and failures, prevented the change of health state or a newly discovered food intolerance are observed by a proper medical team, can support better sports performance. It is important that the dietetics profession informed on gene-diet interactions, that may be leading to optimal health, reduced risk of injury or disease. A special medical application for documentation and monitoring of data of health state and risk factors can uphold and warn the medical team for an early action and help to be able to do a proper health service in time. This model can set up a personalized nutrition advice from the status control, through the recovery, to the monitoring. But more studies are needed to understand the mechanisms and to be able to change the composition of the microbiome, environmental and genetic risk factors in cases of athletes.

Keywords: gene-diet interaction, multidisciplinary team, microbiome, diet plan

Procedia PDF Downloads 164

Authors: Safaa M. Hassan; Safwat S. Gabr, Mohamed F. Sadek

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This study is proposed for the lithological and iron oxides detection in the old mine areas of El-Bahariya Depression, Western Desert, using ASTER and Landsat-8 remote sensing data. Four old iron ore occurrences, namely; El-Gedida, El-Haraa, Ghurabi, and Nasir mine areas found in the El-Bahariya area. This study aims to find new high potential areas for iron mineralization around El-Baharyia depression. Image processing methods such as principle component analysis (PCA) and band ratios (b4/b5, b5/b6, b6/b7, and 4/2, 6/7, band 6) images were used for lithological identification/mapping that includes the iron content in the investigated area. ASTER and Landsat-8 visible and short-wave infrared data found to help mapping the ferruginous sandstones, iron oxides as well as the clay minerals in and around the old mines area of El-Bahariya depression. Landsat-8 band ratio and the principle component of this study showed well distribution of the lithological units, especially ferruginous sandstones and iron zones (hematite and limonite) along with detection of probable high potential areas for iron mineralization which can be used in the future and proved the ability of Landsat-8 and ASTER data in mapping these features. Minimum Noise Fraction (MNF), Mixture Tuned Matched Filtering (MTMF), pixel purity index methods as well as Spectral Ange Mapper classifier algorithm have been successfully discriminated the hematite and limonite content within the iron zones in the study area. Various ASTER image spectra and ASD field spectra of hematite and limonite and the surrounding rocks are compared and found to be consistent in terms of the presence of absorption features at range from 1.95 to 2.3 μm for hematite and limonite. Pixel purity index algorithm and two sub-pixel spectral methods, namely Mixture Tuned Matched Filtering (MTMF) and matched filtering (MF) methods, are applied to ASTER bands to delineate iron oxides (hematite and limonite) rich zones within the rock units. The results are validated in the field by comparing image spectra of spectrally anomalous zone with the USGS resampled laboratory spectra of hematite and limonite samples using ASD measurements. A number of iron oxides rich zones in addition to the main surface exposures of the El-Gadidah Mine, are confirmed in the field. The proposed method is a successful application of spectral mapping of iron oxides deposits in the exposed rock units (i.e., ferruginous sandstone) and present approach of both ASTER and ASD hyperspectral data processing can be used to delineate iron-rich zones occurring within similar geological provinces in any parts of the world.

Keywords: Landsat-8, ASTER, lithological mapping, iron exploration, western desert

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Authors: Jan F. Talts, Amit Saxena, Kåre Engkilde

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Chemotherapy-induced peripheral neuropathy (CIPN) is one of the most frequent side effects caused by anti-neoplastic agents, with a prevalence from 19 % to 85 %. Clinically, CIPN is a mostly sensory neuropathy leading to pain and to motor and autonomic changes. Due to its high prevalence among cancer patients, CIPN constitutes a major problem for both cancer patients and survivors, especially because currently, there is no single effective method of preventing CIPN. Hearing loss is the most common form of sensory impairment in humans and can be caused by ototoxic chemical compounds such as chemotherapy (platinum-based antineoplastic agents).In rodents, single or repeated cisplatin injections induce peripheral neuropathy and hearing impairment mimicking human disorder, allowing studying the efficacy of new pharmacological candidates in chemotherapy-induced hearing loss and peripheral neuropathy. RNA sequencing data from full term amniotic fluid (TAF) mesenchymal stemcell (MSC) clones was used to identify neural-specific markers present on TAF-MSC. Several prospective neural markers were tested by flow cytometry on cultured TAF-MSC. One of these markers was used for cell-sorting using Tyto MACSQuant cell sorter, and the neural marker positive cell population was expanded for several passages to the final therapeutic product stage. Peripheral neuropathy and hearing loss was induced in mice by administration of cisplatin in three week-long cycles. The efficacy of neural-specific TAF-MSC in treating hearing loss and pain perception was evaluated by administration of three injections of 3 million cells/kg by intravenous route or three injections of 3 million cells/kg by intra-arterial route after each cisplatin cycle treatment. Auditory brainstem responses (ABR) are electric potentials recorded from scalp electrodes, and the first ABR wave represents the summed activity of the auditory nerve fibers contacting the inner hair cells. For ABR studies, mice were anesthetized, then earphones were placed in the left ear of each mouse, an active electrode was placed in the vertex of the skull, a reference electrode under the skin of the mastoid bone, and a ground electrode in the neck skin. The stimuli consisted of tone pips of five frequencies (2, 4, 6, 12, 16, and 24 kHz) at various sound levels (from 0 to 90 dB) ranging to cover the mouse auditory frequency range. The von Frey test was used to assess the onset and maintenance of mechanical allodynia over time. Mice were placed in clear plexiglass cages on an elevated mesh floor and tested after 30 min of habituation. Mechanical paw withdrawal threshold was examined using an electronic von Frey anesthesiometer. Cisplatin groups treated with three injections of 3 million cells/kg by intravenous route and three injections of 3 million cells/kg by intra-arterial route after each cisplatin cycle treatment presented, a significant increase of hearing acuity characterized by a decrease of ABR threshold and a decrease of neuropathic pain characterized by an increase of von Frey paw withdrawal threshold compared to controls only receiving cisplatin. This study shows that treatment with MSCselected for neural specificity presents significant positive efficacy on the chemotherapy-induced neuropathic pain and the chemotherapy-induced hearing loss.

Keywords: mesenchymal stem cell, peripheral neuropathy, amniotic fluid, regenerative medicine

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Authors: Ionut Vintu, Stefan Laible, Ruth Schulz

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Agricultural robotics has been developing steadily over recent years, with the goal of reducing and even eliminating pesticides used in crops and to increase productivity by taking over human labor. The majority of crops are arranged in rows. The first step towards autonomous robots, capable of driving in fields and performing crop-handling tasks, is for robots to robustly detect the rows of plants. Recent work done towards autonomous driving between plant rows offers big robotic platforms equipped with various expensive sensors as a solution to this problem. These platforms need to be driven over the rows of plants. This approach lacks flexibility and scalability when it comes to the height of plants or distance between rows. This paper proposes instead an algorithm that makes use of cheaper sensors and has a higher variability. The main application is in tree nurseries. Here, plant height can range from a few centimeters to a few meters. Moreover, trees are often removed, leading to gaps within the plant rows. The core idea is to combine row detection algorithms with graph-based localization methods as they are used in SLAM. Nodes in the graph represent the estimated pose of the robot, and the edges embed constraints between these poses or between the robot and certain landmarks. This setup aims to improve individual plant detection and deal with exception handling, like row gaps, which are falsely detected as an end of rows. Four methods were developed for detecting row structures in the fields, all using a point cloud acquired with a 3D LiDAR as an input. Comparing the field coverage and number of damaged plants, the method that uses a local map around the robot proved to perform the best, with 68% covered rows and 25% damaged plants. This method is further used and combined with a graph-based localization algorithm, which uses the local map features to estimate the robot’s position inside the greater field. Testing the upgraded algorithm in a variety of simulated fields shows that the additional information obtained from localization provides a boost in performance over methods that rely purely on perception to navigate. The final algorithm achieved a row coverage of 80% and an accuracy of 27% damaged plants. Future work would focus on achieving a perfect score of 100% covered rows and 0% damaged plants. The main challenges that the algorithm needs to overcome are fields where the height of the plants is too small for the plants to be detected and fields where it is hard to distinguish between individual plants when they are overlapping. The method was also tested on a real robot in a small field with artificial plants. The tests were performed using a small robot platform equipped with wheel encoders, an IMU and an FX10 3D LiDAR. Over ten runs, the system achieved 100% coverage and 0% damaged plants. The framework built within the scope of this work can be further used to integrate data from additional sensors, with the goal of achieving even better results.

Keywords: 3D LiDAR, agricultural robots, graph-based localization, row detection

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Authors: Delsy Salinas, Andreia Garcês, Augusto Silva, Paula Brilhante Simões

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Urinary tract infection (UTI) is a common disease affecting dogs and cats in both community and hospital environment. Bacteria is the most frequent agent isolated, fewer than 1% of infections are due to parasitic, fungal, or viral agents. Common symptoms and laboratory abnormalities includeabdominal pain, pyrexia, renomegaly, and neutrophilia with left shift. A rapid and precise identification of the bacterial agent is still a challenge in veterinarian laboratories. Therefore, this cross-sectional study aims to describe bacterial colony patterns of urine samples by using chromID™ CPS® EliteAgar (BioMérieux, France) from canine and feline specimens submitted to a veterinary laboratory in Portugal (INNO Veterinary Laboratory, Braga)from January to March2022. All urine samples were cultivated in CPS Elite Agar with calibrated 1 µL inoculating loop and incubated at 37ºC for 18-24h. Color,size, and shape (regular or irregular outline)were recorded for all samples. All colonies were classified as Gram-negative or Gram-positive bacteriausing Gram stain (PREVI® Color BioMérieux, France) and determined if they were pure colonies. Identification of bacteria species was performed using GP and GN cards inVitek 2® Compact(BioMérieux, France). A total of 256/1003 submitted urine samples presented bacterial growth, from which 172 isolates were included in this study. The sample’s population included 111 dogs (n=45 males and n=66 females) and 61 cats (n=35 males and n=26 females). The most frequent isolated bacteria wasEscherichia coli (44,7%), followed by Proteus mirabilis (13,4%). All Escherichia coli isolates presented red to burgundy colonies, a colony diameter between 2 to 6 mm, and regular or irregular outlines. Similarly, 100% of Proteus mirabilis isolates were dark yellow colonies with a diffuse pigment and the same size and shape as Escherichia coli. White and pink pale colonies where Staphylococcus species exclusively and S. pseudintermedius was the most frequent (8,2 %). Cian to blue colonies were mostly Enterococcusspp. (8,2%) and Streptococcus spp. (4,6%). Beige to brown colonies were Pseudomonas aeruginosa (2,9%) and Citrobacter spp. (1,2%).Klebsiella spp.,Serratia spp. and Enterobacter spp were green colonies. All Gram-positive isolates were 1 to 2 mm diameter long and had a regular outline, meanwhile, Gram-negative rods presented variable patterns. This results showed that theprevalence of E coli and P. mirabilis as uropathogenic agents follows the same trends in Europe as previously described in other studies. Both agents presented a particular color pattern in CPS Elite Agar to identify them without needing complementary tests. No other bacteria genus could be correlated strongly to a specific color pattern, and similar results have been observed instudies using human’s samples. Chromogenic media shows a great advantage for common urine bacteria isolation than traditional COS, McConkey, and CLEDAgar mediums in a routine context, especially when mixed fermentative Gram-negative agents grow simultaneously. In addition, CPS Elite Agar is versatile for Artificial Intelligent Reading Plates Systems. Routine veterinarian laboratories could use CPS Elite Agar for a rapid screening for bacteria identification,mainlyE coli and P.mirabilis, saving 6h to 10h of automatized identification.

Keywords: cats, CPS elite agar, dogs, urine pathogens

Procedia PDF Downloads 95

Authors: Gerhard Gritsch, Ana Skupch, Manfred Hartmann, Wolfgang Frühwirt, Hannes Perko, Dieter Grossegger, Tilmann Kluge

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Rehabilitation of stroke patients is dominated by classical physiotherapy. Nowadays, a field of research is the application of neurofeedback techniques in order to help stroke patients to get rid of their motor impairments. Especially, if a certain limb is completely paralyzed, neurofeedback is often the last option to cure the patient. Certain exercises, like the imagination of the impaired motor function, have to be performed to stimulate the neuroplasticity of the brain, such that in the neighboring parts of the injured cortex the corresponding activity takes place. During the exercises, it is very important to keep the motivation of the patient at a high level. For this reason, the missing natural feedback due to a movement of the effected limb may be replaced by a synthetic feedback based on the motor-related brain function. To generate such a synthetic feedback a system is needed which measures, detects, localizes and visualizes the motor related µ-rhythm. Fast therapeutic success can only be achieved if the feedback features high specificity, comes in real-time and without large delay. We describe such an approach that offers a 3D visualization of µ-rhythms in real time with a delay of 500ms. This is accomplished by combining smart EEG preprocessing in the frequency domain with source localization techniques. The algorithm first selects the EEG channel featuring the most prominent rhythm in the alpha frequency band from a so-called motor channel set (C4, CZ, C3; CP6, CP4, CP2, CP1, CP3, CP5). If the amplitude in the alpha frequency band of this certain electrode exceeds a threshold, a µ-rhythm is detected. To prevent detection of a mixture of posterior alpha activity and µ-activity, the amplitudes in the alpha band outside the motor channel set are not allowed to be in the same range as the main channel. The EEG signal of the main channel is used as template for calculating the spatial distribution of the µ - rhythm over all electrodes. This spatial distribution is the input for a inverse method which provides the 3D distribution of the µ - activity within the brain which is visualized in 3D as color coded activity map. This approach mitigates the influence of lid artifacts on the localization performance. The first results of several healthy subjects show that the system is capable of detecting and localizing the rarely appearing µ-rhythm. In most cases the results match with findings from visual EEG analysis. Frequent eye-lid artifacts have no influence on the system performance. Furthermore, the system will be able to run in real-time. Due to the design of the frequency transformation the processing delay is 500ms. First results are promising and we plan to extend the test data set to further evaluate the performance of the system. The relevance of the system with respect to the therapy of stroke patients has to be shown in studies with real patients after CE certification of the system. This work was performed within the project ‘LiveSolo’ funded by the Austrian Research Promotion Agency (FFG) (project number: 853263).

Keywords: real-time EEG neuroimaging, neurofeedback, stroke, EEG–signal processing, rehabilitation

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

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

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

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Authors: Anita Burgund Isakov, Cristina Nunes, Nevenka Zegarac, Ana Antunes

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Contemporary societies are facing a noticeable shift in family realities, urging to need for the development of new policies, service, and practice orientation that has application across different sectors who serves families with children across the world. A challenge for the field of family support is diversity in conceptual assumptions and epistemological frameworks. Since many disciplines and professionals are working in the family support field, there is a need to map and gain a deeper insight into the skills for the workforce in this field. Under the umbrella of the COST action 'The Pan-European Family Support Research Network: A bottom-up, evidence-based and multidisciplinary approach', a review of the current state of knowledge published from the European studies on family support workforce skills standards is performed. Contributing to the aim of mapping and catalogization of skills standards, key stages of literature review were identified in order to extract and systematize the data. We have considered inclusion and exclusion criteria for this literature review. Inclusion criteria were: a) families living with their children and families using family support services; different methodological approaches were included: qualitative, quantitative, mix method, literature review and theoretical reflections various topic appeared in journals like working with families that are facing difficulties or culturally sensitive practice and relationship-based approaches; b) the dates ranged from 1995 to February 2020. Articles published prior to 1995 were excluded due to modernization of family support services across world; c) the sources and languages included peer-reviewed articles published in scientific journals in English. Six databases were searched and once we have extracted all the relevant papers (n=29), we searched the list of reference in each and we found 11 additional papers. In total 40 papers have been extracted from six data basis. Findings could be summarized in: 1) only five countries emerged with production in the specific topic, that is, workforce skills to family support (UK, USA, Canada, Australia, and Spain), 2) studies revealed that diverse skills support family topics were investigated, namely the professional support skills to help families of neglected/abused children or in care; the professional support skills to help families with children who suffer from behavioral problems and families with children with disabilities; and the professional support skills to help minority ethnic parents, 3) social workers were the main targeted professionals' studies albeit other child protection workers were studied too, 4) the workforce skills to family support were grouped in three topics: the qualities of the professionals (attitudes and attributes); technical skills, and specific knowledge. The framework of analyses, literature strategy and findings with study limitations will be further discussed. As an implication, this study contributes and advocates for the structuring of a common base for cross-sectoral and interdisciplinary qualification standards for the family support workforce.

Keywords: family support, skill standards, systemic review, workforce

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Authors: Dmitriy Babenko, Sergey Yegorov, Ilya Korshukov, Aidana Sultanbekova, Valentina Barkhanskaya, Tatiana Bashirova, Yerzhan Zhunusov, Yevgeniya Li, Viktoriya Parakhina, Svetlana Kolesnichenko, Yeldar Baiken, Aruzhan Pralieva, Zhibek Zhumadilova, Matthew S. Miller, Gonzalo H. Hortelano, Anar Turmuhambetova, Antonella E. Chesca, Irina Kadyrova

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Introduction: The rapidly evolving COVID-19 pandemic, along with the re-emergence of pathogens causing acute respiratory infections (ARI), has necessitated the development of novel diagnostic tools to differentiate various causes of ARI. MALDI-MS, due to its wide usage and affordability, has been proposed as a potential instrument for diagnosing SARS-CoV-2 versus non-SARS-CoV-2 ARI. The aim of this study was to investigate the potential of MALDI-MS in conjunction with a machine learning model to accurately distinguish between symptomatic infections caused by SARS-CoV-2 and non-SARS-CoV-2 during both the early and later phases of the pandemic. Furthermore, this study aimed to analyze mass spectrometry (MS) data obtained from nasal swabs of healthy individuals. Methods: We gathered mass spectra from 252 samples, comprising 108 SARS-CoV-2-positive samples obtained in 2020 (Covid 2020), 7 SARS-CoV- 2-positive samples obtained in 2023 (Covid 2023), 71 samples from symptomatic individuals without SARS-CoV-2 (Control non-Covid ARVI), and 66 samples from healthy individuals (Control healthy). All the samples were subjected to RT-PCR testing. For data analysis, we employed the caret R package to train and test seven machine-learning algorithms: C5.0, KNN, NB, RF, SVM-L, SVM-R, and XGBoost. We conducted a training process using a five-fold (outer) nested repeated (five times) ten-fold (inner) cross-validation with a randomized stratified splitting approach. Results: In this study, we utilized the Covid 2020 dataset as a case group and the non-Covid ARVI dataset as a control group to train and test various machine learning (ML) models. Among these models, XGBoost and SVM-R demonstrated the highest performance, with accuracy values of 0.97 [0.93, 0.97] and 0.95 [0.95; 0.97], specificity values of 0.86 [0.71; 0.93] and 0.86 [0.79; 0.87], and sensitivity values of 0.984 [0.984; 1.000] and 1.000 [0.968; 1.000], respectively. When examining the Covid 2023 dataset, the Naive Bayes model achieved the highest classification accuracy of 43%, while XGBoost and SVM-R achieved accuracies of 14%. For the healthy control dataset, the accuracy of the models ranged from 0.27 [0.24; 0.32] for k-nearest neighbors to 0.44 [0.41; 0.45] for the Support Vector Machine with a radial basis function kernel. Conclusion: Therefore, ML models trained on MALDI MS of nasopharyngeal swabs obtained from patients with Covid during the initial phase of the pandemic, as well as symptomatic non-Covid individuals, showed excellent classification performance, which aligns with the results of previous studies. However, when applied to swabs from healthy individuals and a limited sample of patients with Covid in the late phase of the pandemic, ML models exhibited lower classification accuracy.

Keywords: SARS-CoV-2, MALDI-TOF MS, ML models, nasopharyngeal swabs, classification

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Authors: Archana Sharma, Vijayashree Nayak, Ashok Kumar

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Three-dimensional matrices were fabricated from blend of natural-natural polymers like carrageenan-gelatin and synthetic -natural polymers such as PEG- gelatin (PEG of different molecular weights (2,000 and 6,000) using two different crosslinkers; glutaraldehyde and EDC-NHS by cryogelation technique. Blends represented a feasible approach to design 3-D scaffolds with controllable mechanical, physical and biochemical properties without compromising biocompatibility and biodegradability. These matrices possessed interconnected porous structure, good mechanical strength, biodegradable nature, constant swelling kinetics, ability to withstand high temperature and visco-elastic behavior. Hemocompatibility of cryogel matrices was determined by coagulation assays and hemolytic activity assay which demonstrated that these cryogels have negligible effects on coagulation time and have excellent blood compatibility. In vitro biocompatibility (cell-matrix interaction) inferred good cell adhesion, proliferation, and secretion of ECM on matrices. These matrices provide a microenvironment for the growth, proliferation, differentiation and secretion of ECM of different cell types such as IMR-32, C2C12, Cos-7, rat bone marrow derived MSCs and human bone marrow MSCs. Hoechst 33342 and PI staining also confirmed that the cells were uniformly distributed, adhered and proliferated properly on the cryogel matrix. An ideal scaffold used for tissue engineering application should allow the cells to adhere, proliferate and maintain their functionality. Neurotransmitter analysis has been done which indicated that IMR-32 cells adhered, proliferated and secreted neurotransmitters when they interacted with these matrices which showed restoration of their functionality. The cell-matrix interaction up to molecular level was also evaluated so to check genotoxicity and protein expression profile which indicated that these cryogel matrices are non-genotoxic and maintained biofunctionality of cells growing on these matrices. All these cryogels, when implanted subcutaneously in balb/c mice, showed no adverse systemic or local toxicity effects at implantation site. There was no significant increase in inflammatory cell count has otherwise been observed after scaffold implantation. These cryogels are supermacroporous and this porous structure allows cell infiltration and proliferation of host cells. This showed the integration and presence of infiltrated cells into the cryogel implants. Histological analysis confirmed that the implanted cryogels do not have any adverse effect in spite of host immune system recognition at the site of implantation, on its surrounding tissues and other vital host organs. In vivo biocompatibility study after in vitro biocompatibility analysis has also concluded that these synthesized cryogels act as important biological substitutes, more adaptable and appropriate for transplantation. Thus, these cryogels showed their potential for soft tissue engineering applications.

Keywords: cryogelation, hemocompatibility, in vitro biocompatibility, in vivo biocompatibility, soft tissue engineering applications

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Authors: Innocent Atuhe, Babra Nalwadda, Grace Mulyowa Kitunzi, Annabella Haninka Ejiri

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Background: Atopic Dermatitis (AD) is one of the most prevalent and growing chronic inflammatory skin diseases in African prisons. AD care is limited in African due to lack of information about the disease amongst primary care workers, limited access to dermatologists, lack of proper training of healthcare workers, and shortage of appropriate treatments. We designed and implemented the Prisons Telederma project based on the recommendations of the International Society of Atopic Dermatitis. Our overall goal was to increase access to dermatologist-led care for prisoners with AD through teledermatology in Uganda. We aimed to; i) to increase awareness and understanding of teledermatology among prison health workers; and ii) to improve treatment outcomes of prisoners with atopic dermatitis through increased access to and utilization of consultant dermatologists through teledermatology in Uganda prisons: Approach: We used Store-and-forward Teledermatology (SAF-TD) to increase access to dermatologist-led care for prisoners and prisons staff with AD. We conducted a five days training for prison health workers using an adapted WHO training guide on recognizing neglected tropical diseases through changes on the skin together with an adapted American Academy of Dermatology (AAD) Childhood AD Basic Dermatology Curriculum designed to help trainees develop a clinical approach to the evaluation and initial management of patients with AD. This training was followed by blended e-learning, webinars facilitated by consultant Dermatologists with local knowledge of medication and local practices, apps adjusted for pigmented skin, WhatsApp group discussions, and sharing pigmented skin AD pictures and treatment via zoom meetings. We hired a team of Ugandan Senior Consultant dermatologists to draft an iconographic atlas of the main dermatoses in pigmented African skin and shared this atlas with prison health staff for use as a job aid. We had planned to use MySkinSelfie mobile phone application to take and share skin pictures of prisoners with AD with Consultant Dermatologists, who would review the pictures and prescribe appropriate treatment. Unfortunately, the National Health Service withdrew the app from the market due to technical issues. We monitored and evaluated treatment outcomes using the Patient Oriented Eczema Measure (POEM) tool. We held four advocacy meetings to persuade relevant stakeholders to increase supplies and availability of first-line AD treatments such as emollients in prison health facilities. Results: Draft iconographic atlas of the main dermatoses in pigmented African skin Increased proportion of prison health staff with adequate knowledge of AD and teledermatology from 20% to 80% Increased proportion of prisoners with AD reporting improvement in disease severity (POEM scores) from 25% to 35% in one year. Increased proportion of prisoners with AD seen by consultant dermatologist through teledermatology from 0% to 20% in one year. Increased the availability of AD recommended treatments in prisons health facilities from 5% to 10% in one year

Keywords: teledermatology, prisoners, reaching, un-reachable

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Authors: Marija Mihajlovic Pereira

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

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

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Authors: Ankur Chaudhuri, Sibani Sen Chakraborty

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

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

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Authors: Mubashar Iqbal, Iqra Anjum, Muhammad Dildar Gogi, Muhammad Jalal Arif

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The present study was carried to screen out the effective entomopathogenic fungi (EPF) inoculation method in maize and to evaluate pathogenicity and oviposition-choice in C. partellus. Three entomopathogenic fungi (EPF) formulations Pacer® (Metarhizium anisopliae), Racer® (Beauveria bassiana) and Meailkil® (Verticillium lecanii) were evaluated at three concentrations (5000, 10000 and 20000 ppm) for their endophytism in maize and pathogenicity in C. partellus. The stock solution of the highest concentration (20,000 ppm) was prepared and next lower from stock solution. In the first experiment, three EPF was inoculated in maize plant by four methods, i.e., leaf-inoculation (LI), whorl-inoculation (WI), shoot-inoculation (SI) and root-inoculation (RI). Leaf-discs and stem-cutting were sampled in all four inoculation methods and placed on fungus growth media in Petri dishes. In the second experiment, pathogenicity, pupal formation, adult emergence, sex ratio, oviposition-choice, and growth index of C. partellus were calculated. The leaves and stem of the inoculated plants were given to the counted number of larvae of C. Partellus. The mortality of larvae was recorded on daily basis till the pupation. The result shows that maximum percent mortality (86.67%) was recorded at high concentration (20000ppm) of Beauveria bassiana by leaf inoculation method. For oviposition choice bioassay, the newly emerged adults were fed on diet (water, honey and yeast in 9:1:1) for 48 hours. One pair of C. Partellus were aspirated from the rearing cages and were detained in large test tube plugged with diet soaked cotton. A set of four plants for each treatment were prepared and randomized inside the large oviposition chamber. The test tubes were opened and fitted in the hole made in the wall of oviposition chamber in front of each treatment. The oviposition chamber was placed in a completely dark laboratory to eliminate the effect of light on moth’s behavior. The plants were removed from the oviposition chamber after the death of adults. The number of eggs deposited on the plant was counted. The results of 2nd experiment revealed that in all EPF and inoculation methods, the fecundity, egg fertility and growth index of C. partellus decreased with the increase in concentration being significantly higher at low concentration (5000ppm) and lower at higher concentration (20000ppm). Application of B. bassiana demonstrated that minimum fecundity (126.83), egg fertility (119.52) and growth index (15%) in C. partellus followed by M. anisopliae with fecundity (135.93), egg fertility (132.29) and growth index (17.50%) while V. lecanii show higher values of fecundity (137.37), egg fertility (1135.42) and growth index (20%). Overall leaf inoculation method showed least fecundity (123.89) with egg fertility (115.36) and growth index (14%) followed by whorl, shoot inoculation method and root inoculation method show higher values of fecundity, egg fertility and growth index.

Keywords: Beauveria bassiana, Chilo partellus, entomopathoganic, Metarhizium anisopliae, Verticillium lecanii

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Authors: Gousilin Leandra Rocha Da Silva, Stéfani T. A. Dantas, Bruna F. Rossi, Erika R. Bonsaglia, Ivana G. Castilho, Terue Sadatsune, Ary Fernandes Júnior, Vera l. M. Rall

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Kidney failure causes decreased diuresis and accumulation of nitrogenous substances in the body. To increase patient survival, hemodialysis is used as a partial substitute for renal function. However, contamination of the water used in this treatment, causing bacteremia in patients, is a worldwide concern. The Burkholderia cepacia complex (Bcc), a group of bacteria with more than 20 species, is frequently isolated from hemodialysis water samples and comprises opportunistic bacteria, affecting immunosuppressed patients, due to its wide variety of virulence factors, in addition to innate resistance to several antimicrobial agents, contributing to the permanence in the hospital environment and to the pathogenesis in the host. The objective of the present work was to characterize molecularly and phenotypically Bcc isolates collected from the water and dialysate of the Hemodialysis Unit and from the blood of patients at a Public Hospital in Botucatu, São Paulo, Brazil, between 2019 and 2021. We used 33 Bcc isolates, previously obtained from blood cultures from patients with bacteremia undergoing hemodialysis treatment (2019-2021) and 24 isolates obtained from water and dialysate samples in a Hemodialysis Unit (same period). The recA gene was sequenced to identify the specific species among the Bcc group. All isolates were tested for the presence of some genes that encode virulence factors such as cblA, esmR, zmpA and zmpB. Considering the epidemiology of the outbreak, the Bcc isolates were molecularly characterized by Multi Locus Sequence Type (MLST) and by pulsed-field gel electrophoresis (PFGE). The verification and quantification of biofilm in a polystyrene microplate were performed by submitting the isolates to different incubation temperatures (20°C, average water temperature and 35°C, optimal temperature for group growth). The antibiogram was performed with disc diffusion tests on agar, using discs impregnated with cefepime (30µg), ceftazidime (30µg), ciprofloxacin (5µg), gentamicin (10µg), imipenem (10µg), amikacin 30µg), sulfametazol/trimethoprim (23.75/1.25µg) and ampicillin/sulbactam (10/10µg). The presence of ZmpB was identified in all isolates, while ZmpA was observed in 96.5% of the isolates, while none of them presented the cblA and esmR genes. The antibiogram of the 33 human isolates indicated that all were resistant to gentamicin, colistin, ampicillin/sulbactam and imipenem. 16 (48.5%) isolates were resistant to amikacin and lower rates of resistance were observed for meropenem, ceftazidime, cefepime, ciprofloxacin and piperacycline/tazobactam (6.1%). All isolates were sensitive to sulfametazol/trimethoprim, levofloxacin and tigecycline. As for the water isolates, resistance was observed only to gentamicin (34.8%) and imipenem (17.4%). According to PFGE results, all isolates obtained from humans and water belonged to the same pulsotype (1), which was identified by recA sequencing as B. cepacia¸, belonging to sequence type ST-767. By observing a single pulse type over three years, one can observe the persistence of this isolate in the pipeline, contaminating patients undergoing hemodialysis, despite the routine disinfection of water with peracetic acid. This persistence is probably due to the production of biofilm, which protects bacteria from disinfectants and, making this scenario more critical, several isolates proved to be multidrug-resistant (resistance to at least three groups of antimicrobials), turning the patient care even more difficult.

Keywords: hemodialysis, burkholderia cepacia, PFGE, MLST, multi drug resistance

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

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

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

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Authors: Carlos Herrera Sierralta, Husain M. Muslim, Meshal T. Alsaiari, Daniel Fischer

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Preventing piping fatigue flow induced vibration in the Oil & Gas sector demands not only the constant development of engineering design methodologies based on available software packages, but also special piping support technologies for designing safe and reliable piping systems. The vast majority of piping vibration problems in the Oil & Gas industry are provoked by the process flow characteristics which are basically intrinsically related to the fluid properties, the type of service and its different operational scenarios. In general, the corrective actions recommended for flow induced vibration in piping systems can be grouped in two major areas: those which affect the excitation mechanisms typically associated to process variables, and those which affect the response mechanism of the pipework per se, and the pipework associated steel support structure. Where possible the first option is to try to solve the flow induced problem from the excitation mechanism perspective. However, in producing facilities the approach of changing process parameters might not always be convenient as it could lead to reduction of production rates or it may require the shutdown of the system in order to perform the required piping modification. That impediment might lead to a second option, which is to modify the response of the piping system to excitation generated by the type of process flow. In principle, the action of shifting the natural frequency of the system well above the frequency inherent to the process always favours the elimination, or considerably reduces, the level of vibration experienced by the piping system. Tightening up the clearances at the supports (ideally zero gap), and adding new static supports at the system, are typical ways of increasing the natural frequency of the piping system. However, only stiffening the piping system may not be sufficient to resolve the vibration problem, and in some cases, it might not be feasible to implement it at all, as the available piping layout could create limitations on adding supports due to thermal expansion/contraction requirements. In these cases, utilization of viscous damper supports could be recommended as these devices can allow relatively large quasi-static movement of piping while providing sufficient capabilities of dissipating the vibration. Therefore, when correctly selected and installed, viscous damper supports can provide a significant effect on the response of the piping system over a wide range of frequencies. Viscous dampers cannot be used to support sustained, static loads. This paper shows over a real case example, a methodology which allows to determine the selection of the viscous damper supports via a dynamic analysis model. By implementing this methodology, it was possible to resolve the piping vibration problem throughout redesigning adequately the existing static piping supports and by adding new viscous dampers supports. This was conducted on-stream at the oil crude pipeline in question without the necessity of reducing the production of the plant. Concluding that the application of the methodology of this paper can be applied to solve similar cases in a straightforward manner.

Keywords: dynamic analysis, flow induced vibration, piping supports, turbulent flow, slug flow, viscous damper

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Authors: Sara Rejeb, Catherine Duveau, Tabea Rebafka

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To monitor the production process of turbofan aircraft engines, multiple measurements of various geometrical parameters are systematically recorded on manufactured parts. Engine parts are subject to extremely high standards as they can impact the performance of the engine. Therefore, it is essential to analyze these databases to better understand the influence of the different parameters on the engine's performance. Self-organizing maps are unsupervised neural networks which achieve two tasks simultaneously: they visualize high-dimensional data by projection onto a 2-dimensional map and provide clustering of the data. This technique has become very popular for data exploration since it provides easily interpretable results and a meaningful global view of the data. As such, self-organizing maps are usually applied to aircraft engine condition monitoring. As databases in this field are huge and complex, they naturally contain multiple missing entries for various reasons. The classical Kohonen algorithm to compute self-organizing maps is conceived for complete data only. A naive approach to deal with partially observed data consists in deleting items or variables with missing entries. However, this requires a sufficient number of complete individuals to be fairly representative of the population; otherwise, deletion leads to a considerable loss of information. Moreover, deletion can also induce bias in the analysis results. Alternatively, one can first apply a common imputation method to create a complete dataset and then apply the Kohonen algorithm. However, the choice of the imputation method may have a strong impact on the resulting self-organizing map. Our approach is to address simultaneously the two problems of computing a self-organizing map and imputing missing values, as these tasks are not independent. In this work, we propose an extension of self-organizing maps for partially observed data, referred to as missSOM. First, we introduce a criterion to be optimized, that aims at defining simultaneously the best self-organizing map and the best imputations for the missing entries. As such, missSOM is also an imputation method for missing values. To minimize the criterion, we propose an iterative algorithm that alternates the learning of a self-organizing map and the imputation of missing values. Moreover, we develop an accelerated version of the algorithm by entwining the iterations of the Kohonen algorithm with the updates of the imputed values. This method is efficiently implemented in R and will soon be released on CRAN. Compared to the standard Kohonen algorithm, it does not come with any additional cost in terms of computing time. Numerical experiments illustrate that missSOM performs well in terms of both clustering and imputation compared to the state of the art. In particular, it turns out that missSOM is robust to the missingness mechanism, which is in contrast to many imputation methods that are appropriate for only a single mechanism. This is an important property of missSOM as, in practice, the missingness mechanism is often unknown. An application to measurements on one type of part is also provided and shows the practical interest of missSOM.

Keywords: imputation method of missing data, partially observed data, robustness to missingness mechanism, self-organizing maps

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Authors: Valentina V. Goftman, Vladislav A. Pankratov, Alexey V. Markin, Tangi Aubert, Zeger Hens, Sarah De Saeger, Irina Yu. Goryacheva

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The most important requirements for biochemical applicability of quantum dots (QDs) are: 1) the surface cap should render intact or improved optical properties; 2) mono-dispersion and good stability in aqueous phase in a wide range of pH and ionic strength values; 3) presence of functional groups, available for bioconjugation; 4) minimal impact from the environment on the QDs’ properties and, vice versa, minimal influence of the QDs’ components on the environment; and 5) stability against chemical/biochemical/physical influence. The latter is especially important for in vitro and in vivo applications. For example, some physical intracellular delivery strategies (e.g., electroporation) imply a rapid high-voltage electric field impulse in order to temporarily generate hydrophilic pores in the cell plasma membrane, necessary for the passive transportation of QDs into the cell. In this regard, it is interesting to investigate how different capping layers, which can provide high stability and sufficient fluorescent properties of QDs in a water solution, behave under these abnormal conditions. In this contribution, hydrophobic core-shell CdSe/CdS/CdZnS/ZnS QDs (λem=600 nm), produced by means of the Successive Ion Layer Adsorption and Reaction (SILAR) technique, were transferred to a water solution using two of the most commonly used methods: (i) encapsulation in an amphiphilic brush polymer based on poly(maleic anhydride-alt-1-octadecene) (PMAO) modified with polyethylene glycol (PEG) chains and (ii) silica covering. Polymer encapsulation preserves the initial ligands on the QDs’ surface owing to the hydrophobic attraction between the hydrophobic groups of the amphiphilic molecules and the surface hydrophobic groups of the QDs. This covering process allows maintaining the initial fluorescent properties, but it leads to a considerable increase of the QDs’ size. However, covering with a silica shell, by means of the reverse microemulsion method, allows maintaining both size and fluorescent properties of the initial QDs. The obtained water solutions of polymer covered and silica-coated QDs in three different concentrations were exposed to a low-voltage electric field for a short time and the fluorescent properties were investigated. It is shown that the PMAO-PEG polymer acquires some additional charges in the presence of the electric field, which causes repulsion between the polymer and the QDs’ surface. This process destroys the homogeneity of the whole amphiphilic shell and it dramatically decreases the fluorescent properties (dropping to 10% from its initial value) because of the direct contact of the QDs with the strongly oxidative environment (water). In contrast, a silica shell possesses dielectric properties which allow retaining 90% of its initial fluorescence intensity, even after a longer electric impact. Thus, silica shells are clearly a preferable covering for bio-application of QDs, because – besides the high uniform morphology, controlled size and biocompatibility – it allows protecting QDs from oxidation, even under the influence of an electric field.

Keywords: electric field, polymer coating, quantum dots, silica covering, stability

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

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The detection of curvilinear structures often plays an important role in the analysis of images. In particular, it is considered as a crucial step for the diagnosis of chronic respiratory diseases to localize the fissures in chest CT imagery where the lung is divided into five lobes by the fissures that are characterized by linear features in appearance. However, the characteristic linear features for the fissures are often shown to be subtle due to the high intensity variability, pathological deformation or image noise involved in the imaging procedure, which leads to the uncertainty in the quantification of anatomical or functional properties of the lung. Thus, it is desired to enhance the linear features present in the chest CT images so that the distinctiveness in the delineation of the lobe is improved. We propose a recursive diffusion process that prefers coherent features based on the analysis of structure tensor in an anisotropic manner. The local image features associated with certain scales and directions can be characterized by the eigenanalysis of the structure tensor that is often regularized via isotropic diffusion filters. However, the isotropic diffusion filters involved in the computation of the structure tensor generally blur geometrically significant structure of the features leading to the degradation of the characteristic power in the feature space. Thus, it is required to take into consideration of local structure of the feature in scale and direction when computing the structure tensor. We apply an anisotropic diffusion in consideration of scale and direction of the features in the computation of the structure tensor that subsequently provides the geometrical structure of the features by its eigenanalysis that determines the shape of the anisotropic diffusion kernel. The recursive application of the anisotropic diffusion with the kernel the shape of which is derived from the structure tensor leading to the anisotropic scale-space where the geometrical features are preserved via the eigenanalysis of the structure tensor computed from the diffused image. The recursive interaction between the anisotropic diffusion based on the geometry-driven kernels and the computation of the structure tensor that determines the shape of the diffusion kernels yields a scale-space where geometrical properties of the image structure are effectively characterized. We apply our recursive anisotropic diffusion algorithm to the detection of curvilinear structure in the chest CT imagery where the fissures present curvilinear features and define the boundary of lobes. It is shown that our algorithm yields precise detection of the fissures while overcoming the subtlety in defining the characteristic linear features. The quantitative evaluation demonstrates the robustness and effectiveness of the proposed algorithm for the detection of fissures in the chest CT in terms of the false positive and the true positive measures. The receiver operating characteristic curves indicate the potential of our algorithm as a segmentation tool in the clinical environment. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: anisotropic diffusion, chest CT imagery, chronic respiratory disease, curvilinear structure, fissure detection, structure tensor

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Authors: Ghadir Hummeid

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Undoubtedly, our world is leading all the purposes and efforts to achieve sustainable development in life in all respects. Sustainability has been regarded as a solution to many challenges of our world today, materiality and immateriality. With the new consequences and challenges our world today, such as global climate change, the use of non-renewable resources, environmental pollution, the decreasing of urban health, the urban areas’ aging, the highly increasing migrations into urban areas linked to many consequences such as highly infrastructure density, social segregation. All of that required new forms of governance, new urban policies, and more efficient efforts and urban applications. Based on the fact that cities are the core of life and it is a fundamental life axis, their development can increase or decrease the life quality of their inhabitants. Architects and planners see themselves today in the need to create new approaches and new sustainable policies to develop urban areas to correspond with the physical and non-physical transformations that cities are nowadays experiencing. To enhance people's lives and provide for their needs in this present without compromising the needs and lives of future generations. The application of sustainability has become an inescapable part of the development and projections of cities' planning. Yet its definition has been indefinable due to the plurality and difference of its applications. As the conceptualizations of technology are arising and have dominated all life aspects today, from smart citizens and smart life rhythms to smart production and smart structures to smart frameworks, it has influenced the sustainability applications as well in the planning and urbanization of cities. The term "smart city" emerged from this influence as one of the possible key solutions to sustainability. The term “smart city” has various perspectives of applications and definitions in the literature and in urban applications. However, after the observation of smart city applications in current cities, this paper defined the smart city as an urban environment that is controlled by technologies yet lacks the physical architectural representation of this smartness as the current smart applications are mostly obscured from the public as they are applied now on a diminutive scale and highly integrated into the built environment. Regardless of the importance of these technologies in improving the quality of people's lives and in facing cities' challenges, it is important not to neglect their architectural and urban presentations will affect the shaping and development of city neighborhoods. By investigating the concept of smart cities and exploring its potential applications on a neighbourhood scale, this paper aims to shed light on understanding the challenges faced by cities and exploring innovative solutions such as smart city applications in urban mobility and how they affect the different aspects of communities. The paper aims to shape better articulations of smart neighborhoods’ morphologies on the social, architectural, functional, and material levels. To understand how to create more sustainable and liveable future approaches to developing urban environments inside cities. The findings of this paper will contribute to ongoing discussions and efforts in achieving sustainable urban development.

Keywords: sustainability, urban development, smart city, resilience, sense of belonging

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Authors: Boudjelal Amel

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Arisarum vulgare, a member of the Araceae family, is an herbaceous perennial widely distributed in the Mediterranean region. A. vulgare is recognized for its medicinal properties and holds significant traditional importance in Algeria for the treatment of various human ailments, including pain, infections, inflammation, digestive disorders, skin problems, eczema, cancer, wounds, burns and gynecological diseases. Despite its extensive traditional use, scientific exploration of A. vulgare remains limited. The study aims to investigate for the first time the therapeutic potential of A. vulgare ethanolic extract obtained by ultrasound-assisted extraction. The chemical composition of the extract was determined by LC-MS/MS analysis. For in vitro phytopharmacological evaluation, several assays, including DPPH, ABTS, FRAP and reducing power, were employed to evaluate the antioxidant activity. The antibacterial activity was assessed againt Escherichia coli, Salmonella typhimurium, Staphylococus aureus, Enterococcus feacium by disk diffusion and microdilution methods. The possible inhibitory activity of ethanolic extract was analyzed against the cholinesterases enzymes (AChE and BChE). The DNA protection activity of A. vulgare ethanolic extract was estimated using the agarose gel electrophoresis method. The capacities of the extract to protect plasmid DNA (pBR322) from the oxidizing effects of H2O2 and UV treatment were evaluated by their DNA-breaking forms. The in vivo wound healing potential of a traditional ointment containing 5% of A. vulgare ethanolic extract was also investigated. The LC-MS/MS profiling of the extract revealed the presence of various bioactive compounds, including naringenin, chlorogenic, vanillic, cafeic, coumaric acids, trans-cinnamic and trans ferrulic acids. The plant extract presented considerable antioxidant potential, being the most active for Reducing power (0,07326±0.001 mg/ml) and DPPH (0.14±0.004 mg/ml). The extract showed the highest inhibition zone diameter against Enterococcus feacium (36±0.1 mm). The ethanolic extract of A. vulgare suppressed the growth of Staphylococus aureus, Escherichia coli and Salmonella typhimurium according to the MIC values. The extract of the plant significantly inhibited both AChE and BChE enzymes. DNA protection activity of the A. vulgare extract was determined as 90.41% for form I and 51.92% for form II. The in vivo experiments showed that 5% ethanolic extract ointment accelerated the wound healing process. The topical application of the traditional formulation enhanced wound closure (95,36±0,6 %) and improved histological parameters in the treated group compared to the control groups. The promising biological properties of Arisarum vulgare revealed that the plant could be appraised as a potential origin of bioactive molecules having multifunctional medicinal uses.

Keywords: arisarum vulgare, LC-MS/MS, antioxidant activity, antimicrobial activity, cholinesterases enzymes inhibition, dna-damage activity, in vivo wound healing

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Authors: Anna-Maria Ramezanzadeh

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Demand for Arabic language is growing worldwide, driven by increased interest in the multifarious purposes the language serves, both for the population of heritage learners and those studying Arabic as a foreign language. The diglossic, or indeed multiglossic nature of the language as used in Arabic speaking communities however, is seldom represented in the content of classroom courses. This disjoint between the nature of provision and students’ expectations can severely impact their engagement with course material, and their motivation to either commence or continue learning the language. The nature of motivation and its relationship to multiglossia is sparsely explored in current literature on Arabic. The theoretical framework here proposed aims to address this gap by presenting a model and instruments for the measurement of Arabic learners’ motivation in relation to the multiple strands of the language. It adopts and develops the Second Language Motivation Self-System model (L2MSS), originally proposed by Zoltan Dörnyei, which measures motivation as the desire to reduce the discrepancy between leaners’ current and future self-concepts in terms of the second language (L2). The tripartite structure incorporates measures of the Current L2 Self, Future L2 Self (consisting of an Ideal L2 Self, and an Ought-To Self), and the L2 Learning Experience. The strength of the self-concepts is measured across three different domains of Arabic: Classical, Modern Standard and Colloquial. The focus on learners’ self-concepts allows for an exploration of the effect of multiple factors on motivation towards Arabic, including religion. The relationship between Islam and Arabic is often given as a prominent reason behind some students’ desire to learn the language. Exactly how and why this factor features in learners’ L2 self-concepts has not yet been explored. Specifically designed surveys and interview protocols are proposed to facilitate the exploration of these constructs. The L2 Learning Experience component of the model is operationalized as learners’ task-based engagement. Engagement is conceptualised as multi-dimensional and malleable. In this model, situation-specific measures of cognitive, behavioural, and affective components of engagement are collected via specially designed repeated post-task self-report surveys on Personal Digital Assistant over multiple Arabic lessons. Tasks are categorised according to language learning skill. Given the domain-specific uses of the different varieties of Arabic, the relationship between learners’ engagement with different types of tasks and their overall motivational profiles will be examined to determine the extent of the interaction between the two constructs. A framework for this data analysis is proposed and hypotheses discussed. The unique combination of situation-specific measures of engagement and a person-oriented approach to measuring motivation allows for a macro- and micro-analysis of the interaction between learners and the Arabic learning process. By combining cross-sectional and longitudinal elements with a mixed-methods design, the model proposed offers the potential for capturing a comprehensive and detailed picture of the motivation and engagement of Arabic learners. The application of this framework offers a number of numerous potential pedagogical and research implications which will also be discussed.

Keywords: Arabic, diglossia, engagement, motivation, multiglossia, sociolinguistics

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Authors: Szymon Kuczynski, Krystian Liszka, Mariusz Laciak, Andrii Oliinyk, Adam Szurlej

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Currently, in automotive transport to power vehicles, almost exclusively hydrocarbon based fuels are used. Due to increase of hydrocarbon fuels consumption, quality parameters are tightend for clean environment. At the same time efforts are undertaken for development of alternative fuels. The reasons why looking for alternative fuels for petroleum and diesel are: to increase vehicle efficiency and to reduce the environmental impact, reduction of greenhouse gases emissions and savings in consumption of limited oil resources. Significant progress was performed on development of alternative fuels such as methanol, ethanol, natural gas (CNG / LNG), LPG, dimethyl ether (DME) and biodiesel. In addition, biggest vehicle manufacturers work on fuel cell vehicles and its introduction to the market. Alcohols such as methanol and ethanol create the perfect fuel for spark-ignition engines. Their advantages are high-value antiknock which determines their application as additive (10%) to unleaded petrol and relative purity of produced exhaust gasses. Ethanol is produced in distillation process of plant products, which value as a food can be irrational. Ethanol production can be costly also for the entire economy of the country, because it requires a large complex distillation plants, large amounts of biomass and finally a significant amount of fuel to sustain the process. At the same time, the fermentation process of plants releases into the atmosphere large quantities of carbon dioxide. Natural gas cannot be directly converted into liquid fuels, although such arrangements have been proposed in the literature. Going through stage of intermediates is inevitable yet. Most popular one is conversion to methanol, which can be processed further to dimethyl ether (DME) or olefin (ethylene and propylene) for the petrochemical sector. Methanol uses natural gas as a raw material, however, requires expensive and advanced production processes. In relation to pollution emissions, the optimal vehicle fuel is LPG which is used in many countries as an engine fuel. Production of LPG is inextricably linked with production and processing of oil and gas, and which represents a small percentage. Its potential as an alternative for traditional fuels is therefore proportionately reduced. Excellent engine fuel may be biogas, however, follows to the same limitations as ethanol - the same production process is used and raw materials. Most essential fuel in the campaign of environment protection against pollution is natural gas. Natural gas as fuel may be either compressed (CNG) or liquefied (LNG). Natural gas can also be used for hydrogen production in steam reforming. Hydrogen can be used as a basic starting material for the chemical industry, an important raw material in the refinery processes, as well as a fuel vehicle transportation. Natural gas can be used as CNG which represents an excellent compromise between the availability of the technology that is proven and relatively cheap to use in many areas of the automotive industry. Natural gas can also be seen as an important bridge to other alternative sources of energy derived from fuel and harmless to the environment. For these reasons CNG as a fuel stimulates considerable interest in the worldwide.

Keywords: alternative fuels, CNG (Compressed Natural Gas), LNG (Liquefied Natural Gas), NGVs (Natural Gas Vehicles)

Procedia PDF Downloads 174

Authors: De-Shin Liu, Po-Chun Wen, Zhen-Wei Zhuang, Hsueh-Chih Liu, Pei-Chen Huang

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Wafer probing tests play an important role in semiconductor manufacturing procedures in accordance with the yield and reliability requirement of the wafer after the backend-of-the-line process. Accordingly, the stable physical and electrical contact between the probe and the tested wafer during wafer probing is regarded as an essential issue in identifying the known good die. The probe card can be integrated with multiple probe needles, which are classified as vertical, cantilever and micro-electro-mechanical systems type probe selections. Among all potential probe types, the vertical probe has several advantages as compared with other probe types, including maintainability, high probe density and feasibility for high-speed wafer testing. In the present study, the mechanical response of the wafer probing test with the vertical cobra probe on 720 μm thick silicon (Si) substrate with a 1.4 μm thick aluminum (Al) pad is investigated by the experiment and transient dynamic simulation approach. Because the deformation mechanism of the vertical cobra probe is determined by both bending and buckling mechanisms, the stable correlation between contact forces and overdrive (OD) length must be carefully verified. Moreover, the decent OD length with corresponding contact force contributed to piercing the native oxide layer of the Al pad and preventing the probing test-induced damage on the interconnect system. Accordingly, the scratch depth of the Al pad under various OD lengths is estimated by the atomic force microscope (AFM) and simulation work. In the wafer probing test configuration, the contact phenomenon between the probe needle and the tested object introduced large deformation and twisting of mesh gridding, causing the subsequent numerical divergence issue. For this reason, the arbitrary Lagrangian-Eulerian method is utilized in the present simulation work to conquer the aforementioned issue. The analytic results revealed a slight difference when the OD is considered as 40 μm, and the simulated is almost identical to the measured scratch depths of the Al pad under higher OD lengths up to 70 μm. This phenomenon can be attributed to the unstable contact of the probe at low OD length with the scratch depth below 30% of Al pad thickness, and the contact status will be being stable when the scratch depth over 30% of pad thickness. The splash of the Al pad is observed by the AFM, and the splashed Al debris accumulates on a specific side; this phenomenon is successfully simulated in the transient dynamic simulation. Thus, the preferred testing OD lengths are found as 45 μm to 70 μm, and the corresponding scratch depths on the Al pad are represented as 31.4% and 47.1% of Al pad thickness, respectively. The investigation approach demonstrated in this study contributed to analyzing the mechanical response of wafer probing test configuration under large strain conditions and assessed the geometric designs and material selections of probe needles to meet the requirement of high resolution and high-speed wafer-level probing test for thinned wafer application.

Keywords: wafer probing test, vertical probe, probe mark, mechanical response, FEA simulation

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Authors: Serdar Delice, Mehmet Isik, Nizami Hasanli, Kadir Goksen

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Researchers have donated great interest to ternary and quaternary semiconductor compounds especially with the improvement of the optoelectronic technology. The quaternary compound Tl2Ga2Se3S which was grown by Bridgman method carries the properties of ternary thallium chalcogenides group of semiconductors with layered structure. This compound can be formed from TlGaSe2 crystals replacing the one quarter of selenium atom by sulfur atom. Although Tl2Ga2Se3S crystals are not intentionally doped, some unintended defect types such as point defects, dislocations and stacking faults can occur during growth processes of crystals. These defects can cause undesirable problems in semiconductor materials especially produced for optoelectronic technology. Defects of various types in the semiconductor devices like LEDs and field effect transistor may act as a non-radiative or scattering center in electron transport. Also, quick recombination of holes with electrons without any energy transfer between charge carriers can occur due to the existence of defects. Therefore, the characterization of defects may help the researchers working in this field to produce high quality devices. Thermoluminescence (TL) is an effective experimental method to determine the kinetic parameters of trap centers due to defects in crystals. In this method, the sample is illuminated at low temperature by a light whose energy is bigger than the band gap of studied sample. Thus, charge carriers in the valence band are excited to delocalized band. Then, the charge carriers excited into conduction band are trapped. The trapped charge carriers are released by heating the sample gradually and these carriers then recombine with the opposite carriers at the recombination center. By this way, some luminescence is emitted from the samples. The emitted luminescence is converted to pulses by using an experimental setup controlled by computer program and TL spectrum is obtained. Defect characterization of Tl2Ga2Se3S single crystals has been performed by TL measurements at low temperatures between 10 and 300 K with various heating rate ranging from 0.6 to 1.0 K/s. The TL signal due to the luminescence from trap centers revealed one glow peak having maximum temperature of 36 K. Curve fitting and various heating rate methods were used for the analysis of the glow curve. The activation energy of 13 meV was found by the application of curve fitting method. This practical method established also that the trap center exhibits the characteristics of mixed (general) kinetic order. In addition, various heating rate analysis gave a compatible result (13 meV) with curve fitting as the temperature lag effect was taken into consideration. Since the studied crystals were not intentionally doped, these centers are thought to originate from stacking faults, which are quite possible in Tl2Ga2Se3S due to the weakness of the van der Waals forces between the layers. Distribution of traps was also investigated using an experimental method. A quasi-continuous distribution was attributed to the determined trap centers.

Keywords: chalcogenides, defects, thermoluminescence, trap centers

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Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

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Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

Procedia PDF Downloads 188

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

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

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

Procedia PDF Downloads 75