Search results for: Superior Vena Cava Obstruction

Authors: Liang Zhao, Chongquan Zhong

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Introduction: According to statistics, people spend 80% to 90% of time indoor, so indoor air quality, either at home or in the office, greatly impacts the quality of life, health and work efficiency. Therefore, indoor air quality is very important to human activities. With the acceleration of urbanization, people are spending more time in indoor activity. The time in indoor environment, the living space, and the frequency interior decoration are all increasingly increased. However, housing decoration materials contain formaldehyde and other harmful substances, causing environmental and air quality problems, which have brought serious damage to countless families and attracted growing attention. According to World Health Organization statistics, the indoor environments in more than 30% of buildings in China are polluted by poisonous and harmful gases. Indoor pollution has caused various health problems, and these widespread public health problems can lead to respiratory diseases. Long-term inhalation of low-concentration formaldehyde would cause persistent headache, insomnia, weakness, palpitation, weight loss and vomiting, which are serious impacts on human health and safety. On the other hand, as for offices, some surveys show that good indoor air quality helps to enthuse the staff and improve the work efficiency by 2%-16%. Therefore, people need to further understand the living and working environments. There is a need for easy-to-use indoor environment monitoring instruments, with which users only have to power up and monitor the environmental parameters. The corresponding real-time data can be displayed on the screen for analysis. Environment monitoring should have the sensitive signal alarm function and send alarm when harmful gases such as formaldehyde, CO, SO2, are excessive to human body. System design: According to the monitoring requirements of various gases, temperature and humidity, we designed a portable, light, real-time and accurate monitor for various environmental parameters, including temperature, humidity, formaldehyde, methane, and CO. This monitor will generate an alarm signal when a target is beyond the standard. It can conveniently measure a variety of harmful gases and provide the alarm function. It also has the advantages of small volume, convenience to carry and use. It has a real-time display function, outputting the parameters on the LCD screen, and a real-time alarm function. Conclusions: This study is focused on the research and development of a portable parameter monitoring instrument for indoor environment. On the platform of an STM32 development board, the monitored data are collected through an external sensor. The STM32 platform is for data acquisition and processing procedures, and successfully monitors the real-time temperature, humidity, formaldehyde, CO, methane and other environmental parameters. Real-time data are displayed on the LCD screen. The system is stable and can be used in different indoor places such as family, hospital, and office. Meanwhile, the system adopts the idea of modular design and is superior in transplanting. The scheme is slightly modified and can be used similarly as the function of a monitoring system. This monitor has very high research and application values.

Keywords: indoor air quality, gas concentration detection, embedded system, sensor

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Authors: Andrés Durán, Brian Castellanos, Marta Quicazán, Carlos Zuluaga-Domínguez

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Bee-pollen is an apicultural-derived food product, with a growing appreciation among consumers given the remarkable nutritional and functional composition, in particular, protein (24%), dietary fiber (15%), phenols (15 – 20 GAE/g) and carotenoids (600 – 900 µg/g). These properties are given by the geographical and climatic characteristics of the region where it is collected. There are several countries recognized by their pollen production, e.g. China, United States, Japan, Spain, among others. Beekeepers use traps in the entrance of the hive where bee-pollen is collected. After the removal of foreign particles and drying, this product is ready to be marketed. However, in countries located along the equator, the absence of seasons and a constant tropical climate throughout the year favors a more rapid spoilage condition for foods with elevated water activity. The climatic conditions also trigger the proliferation of microorganisms and insects. This, added to the factor that beekeepers usually do not have adequate processing systems for bee-pollen, leads to deficiencies in the quality and safety of the product. In contrast, the Andean region of South America, lying on equator, typically has a high production of bee-pollen of up to 36 kg/year/hive, being four times higher than in countries with marked seasons. This region is also located in altitudes superior to 2500 meters above sea level, having extremes sun ultraviolet radiation all year long. As a mechanism of defense of radiation, plants produce more secondary metabolites acting as antioxidant agents, hence, plant products such as bee-pollen contain remarkable more phenolics and carotenoids than collected in other places. Considering this, the improvement of bee-pollen processing facilities by technical modifications and the implementation of an integrated cleaning and drying system for the product in an apiary in the area was proposed. The beehives were modified through the installation of alternative bee-pollen traps to avoid sources of contamination. The processing facility was modified according to considerations of Good Manufacturing Practices, implementing the combined use of a cabin dryer with temperature control and forced airflow and a greenhouse-type solar drying system. Additionally, for the separation of impurities, a cyclone type system was implemented, complementary to a screening equipment. With these modifications, a decrease in the content of impurities and the microbiological load of bee-pollen was seen from the first stages, principally with a reduction of the presence of molds and yeasts and in the number of foreign animal origin impurities. The use of the greenhouse solar dryer integrated to the cabin dryer allowed the processing of larger quantities of product with shorter waiting times in storage, reaching a moisture content of about 6% and a water activity lower than 0.6, being appropriate for the conservation of bee-pollen. Additionally, the contents of functional or nutritional compounds were not affected, even observing an increase of up to 25% in phenols content and a non-significant decrease in carotenoids content and antioxidant activity.

Keywords: beekeeping, drying, food processing, food safety

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Authors: Ahmad Kayvani Fard, Yehia Manawi

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Qatar’s primary source of fresh water is through seawater desalination. Amongst the major processes that are commercially available on the market, the most common large scale techniques are Multi-Stage Flash distillation (MSF), Multi Effect distillation (MED), and Reverse Osmosis (RO). Although commonly used, these three processes are highly expensive down to high energy input requirements and high operating costs allied with maintenance and stress induced on the systems in harsh alkaline media. Beside that cost, environmental footprint of these desalination techniques are significant; from damaging marine eco-system, to huge land use, to discharge of tons of GHG and huge carbon footprint. Other less energy consuming techniques based on membrane separation are being sought to reduce both the carbon footprint and operating costs is membrane distillation (MD). Emerged in 1960s, MD is an alternative technology for water desalination attracting more attention since 1980s. MD process involves the evaporation of a hot feed, typically below boiling point of brine at standard conditions, by creating a water vapor pressure difference across the porous, hydrophobic membrane. Main advantages of MD compared to other commercially available technologies (MSF and MED) and specially RO are reduction of membrane and module stress due to absence of trans-membrane pressure, less impact of contaminant fouling on distillate due to transfer of only water vapor, utilization of low grade or waste heat from oil and gas industries to heat up the feed up to required temperature difference across the membrane, superior water quality, and relatively lower capital and operating cost. To achieve the objective of this study, state of the art flat-sheet cross-flow DCMD bench scale unit was designed, commissioned, and tested. The objective of this study is to analyze the characteristics and morphology of the membrane suitable for DCMD through SEM imaging and contact angle measurement and to study the water quality of distillate produced by DCMD bench scale unit. Comparison with available literature data is undertaken where appropriate and laboratory data is used to compare a DCMD distillate quality with that of other desalination techniques and standards. Membrane SEM analysis showed that the PTFE membrane used for the study has contact angle of 127º with highly porous surface supported with less porous and bigger pore size PP membrane. Study on the effect of feed solution (salinity) and temperature on water quality of distillate produced from ICP and IC analysis showed that with any salinity and different feed temperature (up to 70ºC) the electric conductivity of distillate is less than 5 μS/cm with 99.99% salt rejection and proved to be feasible and effective process capable of consistently producing high quality distillate from very high feed salinity solution (i.e. 100000 mg/L TDS) even with substantial quality difference compared to other desalination methods such as RO and MSF.

Keywords: membrane distillation, waste heat, seawater desalination, membrane, freshwater, direct contact membrane distillation

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Authors: M. Shiva Prasad, S. R. Atchuta, T. Vijayaraghavan, S. Sakthivel

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The world is in need of efficient energy conversion technologies which are affordable, accessible, and sustainable with eco-friendly nature. Solar energy is one of the cornerstones for the world’s economic growth because of its abundancy with zero carbon pollution. Among the various solar energy conversion technologies, solar thermal technology has attracted a substantial renewed interest due to its diversity and compatibility in various applications. Solar thermal systems employ concentrators, tracking systems and heat engines for electricity generation which lead to high cost and complexity in comparison with photovoltaics; however, it is compatible with distinct thermal energy storage capability and dispatchable electricity which creates a tremendous attraction. Apart from that, employing cost-effective solar selective receiver tube in a concentrating solar thermal (CST) system improves the energy conversion efficiency and directly reduces the cost of technology. In addition, the development of solar receiver tubes by low cost methods which can offer high optical properties and corrosion resistance in an open-air atmosphere would be beneficial for low and medium temperature applications. In this regard, our work opens up an approach which has the potential to achieve cost-effective energy conversion. We have developed a highly selective tandem absorber coating through a facile wet chemical route by a combination of chemical oxidation, sol-gel, and nanoparticle coating methods. The developed tandem absorber coating has gradient refractive index nature on stainless steel (SS 304) and exhibited high optical properties (α ≤ 0.95 & ε ≤ 0.14). The first absorber layer (Cr-Mn-Fe oxides) developed by controlled oxidation of SS 304 in a chemical bath reactor. A second composite layer of ZrO₂-SiO₂ has been applied on the chemically oxidized substrate by So-gel dip coating method to serve as optical enhancing and corrosion resistant layer. Finally, an antireflective layer (MgF₂) has been deposited on the second layer, to achieve > 95% of absorption. The developed tandem layer exhibited good thermal stability up to 250 °C in open air atmospheric condition and superior corrosion resistance (withstands for > 200h in salt spray test (ASTM B117)). After the successful development of a coating with targeted properties at a laboratory scale, a prototype of the 1 m tube has been demonstrated with excellent uniformity and reproducibility. Moreover, it has been validated under standard laboratory test condition as well as in field condition with a comparison of the commercial receiver tube. The presented strategy can be widely adapted to develop highly selective coatings for a variety of CST applications ranging from hot water, solar desalination, and industrial process heat and power generation. The high-performance, cost-effective medium temperature receiver tube technology has attracted many industries, and recently the technology has been transferred to Indian industry.

Keywords: concentrated solar thermal system, solar selective coating, tandem absorber, ultralow refractive index

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Fei Jia, Xingjian Bai, Xiaowei Zhang, Wenjie Yan, Ruitong Dai, Xingmin Li, Jozef Kokini

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Pseudomonas aeruginosa is a Gram-negative, aerobic, opportunistic human pathogen that is present in the soil, water, and food. This microbe has been recognized as a representative food-borne spoilage bacterium that can lead to many types of infections. Considering the casualties and property loss caused by P. aeruginosa, the development of a rapid and reliable technique for the detection of P. aeruginosa is crucial. The whole-cell aptasensor, an emerging biosensor using aptamer as a capture probe to bind to the whole cell, for food-borne pathogens detection has attracted much attention due to its convenience and high sensitivity. Here, a low-field magnetic resonance imaging (LF-MRI) aptasensor for the rapid detection of P. aeruginosa was developed. The basic detection principle of the magnetic relaxation switch (MRSw) nanosensor lies on the ‘T₂-shortening’ effect of magnetic nanoparticles in NMR measurements. Briefly speaking, the transverse relaxation time (T₂) of neighboring water protons get shortened when magnetic nanoparticles are clustered due to the cross-linking upon the recognition and binding of biological targets, or simply when the concentration of the magnetic nanoparticles increased. Such shortening is related to both the state change (aggregation or dissociation) and the concentration change of magnetic nanoparticles and can be detected using NMR relaxometry or MRI scanners. In this work, two different sizes of magnetic nanoparticles, which are 10 nm (MN₁₀) and 400 nm (MN₄₀₀) in diameter, were first immobilized with anti- P. aeruginosa aptamer through 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC)/N-hydroxysuccinimide (NHS) chemistry separately, to capture and enrich the P. aeruginosa cells. When incubating with the target, a ‘sandwich’ (MN₁₀-bacteria-MN₄₀₀) complex are formed driven by the bonding of MN400 with P. aeruginosa through aptamer recognition, as well as the conjugate aggregation of MN₁₀ on the surface of P. aeruginosa. Due to the different magnetic performance of the MN₁₀ and MN₄₀₀ in the magnetic field caused by their different saturation magnetization, the MN₁₀-bacteria-MN₄₀₀ complex, as well as the unreacted MN₄₀₀ in the solution, can be quickly removed by magnetic separation, and as a result, only unreacted MN₁₀ remain in the solution. The remaining MN₁₀, which are superparamagnetic and stable in low field magnetic field, work as a signal readout for T₂ measurement. Under the optimum condition, the LF-MRI platform provides both image analysis and quantitative detection of P. aeruginosa, with the detection limit as low as 100 cfu/mL. The feasibility and specificity of the aptasensor are demonstrated in detecting real food samples and validated by using plate counting methods. Only two steps and less than 2 hours needed for the detection procedure, this robust aptasensor can detect P. aeruginosa with a wide linear range from 3.1 ×10² cfu/mL to 3.1 ×10⁷ cfu/mL, which is superior to conventional plate counting method and other molecular biology testing assay. Moreover, the aptasensor has a potential to detect other bacteria or toxins by changing suitable aptamers. Considering the excellent accuracy, feasibility, and practicality, the whole-cell aptasensor provides a promising platform for a quick, direct and accurate determination of food-borne pathogens at cell-level.

Keywords: magnetic resonance imaging, meat spoilage, P. aeruginosa, transverse relaxation time

Procedia PDF Downloads 125

Authors: Sonia Boscenco, Zihan Wang, Euclides José de Mendoça Filho, João Paulo Hoppe, Irina Pokhvisneva, Geoffrey B.C. Hall, Michael J. Meaney, Patricia Pelufo Silveira

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Entropy can be described as a measure of the number of states of a system, and when used in the context of physiological time-based signals, it serves as a measure of complexity. In functional connectivity data, entropy can account for the moment-to-moment variability that is neglected in traditional functional magnetic resonance imaging (fMRI) analyses. While brain fMRI resting state entropy has been associated with some pathological conditions like schizophrenia, no investigations have explored the association between brain entropy measures and individual differences in child behavior in healthy children. We describe a novel exploratory approach to evaluate brain fMRI resting state data in two child cohorts, and MAVAN (N=54, 4.5 years, 48% males) and GUSTO (N = 206, 4.5 years, 48% males) and its associations to child behavior, that can be used in future research in the context of child exposures and long-term health. Following rs-fMRI data pre-processing and Shannon entropy calculation across 32 network regions of interest to acquire 496 unique functional connections, partial correlation coefficient analysis adjusted for sex was performed to identify associations between entropy data and Strengths and Difficulties questionnaire in MAVAN and Child Behavior Checklist domains in GUSTO. Significance was set at p < 0.01, and we found eight significant associations in GUSTO. Negative associations were found between two frontoparietal regions and cerebellar posterior and oppositional defiant problems, (r = -0.212, p = 0.006) and (r = -0.200, p = 0.009). Positive associations were identified between somatic complaints and four default mode connections: salience insula (r = 0.202, p < 0.01), dorsal attention intraparietal sulcus (r = 0.231, p = 0.003), language inferior frontal gyrus (r = 0.207, p = 0.008) and language posterior superior temporal gyrus (r = 0.210, p = 0.008). Positive associations were also found between insula and frontoparietal connection and attention deficit / hyperactivity problems (r = 0.200, p < 0.01), and insula – default mode connection and pervasive developmental problems (r = 0.210, p = 0.007). In MAVAN, ten significant associations were identified. Two positive associations were found = with prosocial scores: the salience prefrontal cortex and dorsal attention connection (r = 0.474, p = 0.005) and the salience supramarginal gyrus and dorsal attention intraparietal sulcus (r = 0.447, p = 0.008). The insula and prefrontal connection were negatively associated with peer problems (r = -0.437, p < 0.01). Conduct problems were negatively associated with six separate connections, the left salience insula and right salience insula (r = -0.449, p = 0.008), left salience insula and right salience supramarginal gyrus (r = -0.512, p = 0.002), the default mode and visual network (r = -0.444, p = 0.009), dorsal attention and language network (r = -0.490, p = 0.003), and default mode and posterior parietal cortex (r = -0.546, p = 0.001). Entropy measures of resting state functional connectivity can be used to identify individual differences in brain function that are correlated with variation in behavioral problems in healthy children. Further studies applying this marker into the context of environmental exposures are warranted.

Keywords: child behaviour, functional connectivity, imaging, Shannon entropy

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Authors: Elina Vroblevska, Toms Ratfelders

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This paper examines the impact of international status-seeking aspirations on great power behavior within the international system. In particular, we seek to test the assumption advanced by the proponents of the Social Identity Theory (SIT) that the inability to achieve social mobilization through joining perceived higher-status social groups (of states) leads great powers to adopt the approach of social competition in which they aim to equal or outdo the dominant group in the area on which its claim to superior status rests. Since the dissolution of the Soviet Union, Russia has struggled to be accepted as a great power by the group of Western states that had created the dominant international system order, while the Soviet states were isolated. While the 1990s and the beginning of the 21st century can be characterized by striving to integrate into the existing order, the second decade has seen a rather sharp turn towards creating a new power center for Russia through the realization of ideas of multipolarity rivalry and uniqueness of the state itself. Increasingly, we have seen the Kremlin striving to collaborate and mobilize groups of states that fall outside of the categories of democracy, multiculturalism, and international order, the way that is perceived by the dominant group, which can be described as the West. Instead, Russia builds its own narrative where it creates an alternative understanding of these values, differentiating from the higher-status social group. The Global South, from a Russian perspective, is the group of states that can still be swayed to create an alternative power center in the international system - one where Russia can assert its status as a great power. This is based on a number of reasons, the most important being that the global north is already highly institutionalized in terms of economy (the EU) and defense (NATO), leaving no room for Russia but to integrate within the existing framework. Second, the difference in values and their interpretation - Russia has been adamant, for the last twenty years, on basing its moral code on traditional values like religion, the heterosexual family model, and moral superiority, which contradict the overall secularism of the Global North. And last, the striking difference in understanding of state governance models - with Russia becoming more autocratic over the course of the last 20 years, it has deliberately created distance between itself and democratic states, entering a “gray area” of alternative understanding of democracy which is more relatable to the global South countries. Using computational text analysis of the excerpts of Vladimir Putin’s speeches delivered from 2000-2022 regarding the areas that fall outside the immediate area of interest of Russia (the Global South), we identify 80 topics that relate to the particular component of the great power status - interest to use force globally. These topics are compared across four temporal frames that capture the periods of more and less permissible Western social boundaries. We find that there exists a negative association between such permissiveness and Putin’s emphasis on the “use of force” topics. This lends further support to the Social Identity Theory and contributes to broadening its applicability to explaining the questions related to great power assertiveness in areas outside of their primary focus regions.

Keywords: Russia, Global South, great power, identity

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Authors: Demet Devrimsel Dogan, Ecem Deniz Kirkpantur, Muharrem Dogan, Ahmet Aykut, Ebru Unal Akoglu, Ozge Ecmel Onur

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Introduction: Median Arcuate Ligament Syndrome (MALS) is a rare cause of chronic abdominal pain due to external compression of the celiac trunk by a fibrous arch that unites diaphragmatic crura on each side of the aortic hiatus. While 10-24% of the population may suffer from compression of celiac trunk, it rarely causes patients to develop symptoms. The typical clinical triad of symptoms includes postprandial epigastric pain, weight loss and vomiting. The diagnosis can be made using thin section multi-detector computed tomography (CT) scans which delineate the ligament and the compressed vessel. The treatment of MALS is aimed at relieving the compression of the celiac artery to restore adequate blood flow through the vessel and neurolysis to address chronic pain. Case: A 68-year-old male presented to our clinic with acute postprandial epigastric pain. This was patients’ first attack, and the pain was the worst pain of his life. The patient did not have any other symptoms like nausea, vomiting, chest pain or dyspnea. In his medical history, the patient has had an ischemic cerebrovascular stroke 5 years ago which he recovered with no sequel, and he was using 75 mg clopidogrel and 100 mg acetylsalicylic acid. He was not using any other medication and did not have a story of cardiovascular disease. His vital signs were stable (BP:113/72 mmHg, Spo2:97, temperature:36.3°C, HR:90/bpm). In his electrocardiogram, there was ST depression in leads II, III and AVF. In his physical examination, there was only epigastric tenderness, other system examinations were normal. Physical examination through his upper gastrointestinal system showed no bleeding. His laboratory results were as follows: creatinine:1.26 mg/dL, AST:42 U/L, ALT:17 U/L, amylase:78 U/L, lipase:26 U/L, troponin:10.3 pg/ml, WBC:28.9 K/uL, Hgb:12.7 gr/dL, Plt:335 K/uL. His serial high-sensitive troponin levels were also within normal limits, his echocardiography showed no segmental wall motion abnormalities, an acute myocardial infarction was excluded. In his abdominal ultrasound, no pathology was founded. Contrast-enhanced abdominal CT and CT angiography reported ‘thickened diaphragmatic cruras are compressing and stenosing truncus celiacus superior, this is likely compatible with MALS’. The patient was consulted to general surgery, and they admitted the patient for laparoscopic ligament release. Results: MALS is a syndrome that causes postprandial pain, nausea and vomiting as its most common symptoms. Affected patients are normally young, slim women between the ages of 30 and 50 who have undergone extensive examinations to find the source of their symptoms. To diagnose MALS, other underlying pathologies should initially be excluded. The gold standard is aortic angiography. Although diagnosis and treatment of MALS are unclear, symptom resolution has been achieved with multiple surgical modalities, including open, laparoscopic or robotic ligament release as well as celiac ganglionectomy, which often requires celiac artery revascularisation.

Keywords: differential diagnosis, epigastric pain, median arcuate ligament syndrome, celiac trunk

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Authors: Priyanka Jain, Ashish K. Sharma, Esha Shukla, K. J. Mukherjee

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We propose a paradigm shift in our approach to design improved platforms for recombinant protein production, by addressing system level issues rather than the individual steps associated with recombinant protein synthesis like transcription, translation, etc. We demonstrate that by controlling and modulating the cellular stress response (CSR), which is responsible for feedback control of protein synthesis, we can generate hyper-producing strains. We did transcriptomic profiling of post-induction cultures, expressing different types of protein, to analyze the nature of this cellular stress response. We found significant down-regulation of substrate utilization, translation, and energy metabolism genes due to generation CSR inside the host cell. However, transcription profiling has also shown that many genes are up-regulated post induction and their role in modulating the CSR is unclear. We hypothesized that these up-regulated genes trigger signaling pathways, generating the CSR and concomitantly reduce the recombinant protein yield. To test this hypothesis, we knocked out the up-regulated genes, which did not have any downstream regulatees, and analyzed their impact on cellular health and recombinant protein expression. Two model proteins i.e., GFP and L-Asparaginase were chosen for this analysis. We observed a significant improvement in expression levels, with some knock-outs showing more than 7-fold higher expression compared to control. The 10 best single knock-outs were chosen to make 45 combinations of all possible double knock-outs. A further increase in expression was observed in some of these double knock- outs with GFP levels being highest in a double knock-out ΔyhbC + ΔelaA. However, for L-Asparaginase which is a secretory protein, the best results were obtained using a combination of ΔelaA+ΔcysW knock-outs. We then tested all the knock outs for their ability to enhance the expression of a 'difficult-to-express' protein. The Rubella virus E1 protein was chosen and tagged with sfGFP at the C-terminal using a linker peptide for easy online monitoring of expression of this fusion protein. Interestingly, the highest increase in Rubella-sGFP levels was obtained in the same double knock-out ΔelaA + ΔcysW (5.6 fold increase in expression yield compared to the control) which gave the highest expression for L-Asparaginase. However, for sfGFP alone, the ΔyhbC+ΔmarR knock-out gave the highest level of expression. These results indicate that there is a fair degree of commonality in the nature of the CSR generated by the induction of different proteins. Transcriptomic profiling of the double knock out showed that many genes associated with the translational machinery and energy biosynthesis did not get down-regulated post induction, unlike the control where these genes were significantly down-regulated. This confirmed our hypothesis of these genes playing an important role in the generation of the CSR and allowed us to design a strategy for making better expression hosts by simply knocking out key genes. This strategy is radically superior to the previous approach of individually up-regulating critical genes since it blocks the mounting of the CSR thus preventing the down-regulation of a very large number of genes responsible for sustaining the flux through the recombinant protein production pathway.

Keywords: cellular stress response, GFP, knock-outs, up-regulated genes

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Authors: Sandra Regina Cavalcante, Rodolfo A. G. Vilela

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Introduction: Work accidents and occupational diseases are a big problem for public health around the world and the main health problem of workers with high social and economic costs. Brazil has shown progress over the last years, with the development of the regulatory system to improve safety and quality of life in the workplace. However, the situation is far from acceptable, because the occurrences remain high and there is a great gap between legislation and reality, generated by the low level of voluntary compliance with the law. Brazilian laws provide procedural legal instruments for both, to compensate the damage caused to the worker's health and to prevent future injuries. In the Judiciary, the prevention idea is in the collective action, effected through Brazilian Class Actions. Inhibitory guardianships may impose both, improvements to the working environment, as well as determine the interruption of activity or a ban on the machine that put workers at risk. Both the Labor Prosecution and trade unions have to stand to promote this type of action, providing payment of compensation for collective moral damage. Objectives: To verify how class actions (known as ‘public civil actions’), regulated in Brazilian legal system to protect diffuse, collective and homogeneous rights, are being used to protect workers' health and safety. Methods: The author identified and evaluated decisions of Brazilian Superior Court of Labor involving collective actions and work accidents. The timeframe chosen was December 2015. The online jurisprudence database was consulted in page available for public consultation on the court website. The categorization of the data was made considering the result (court application was rejected or accepted), the request type, the amount of compensation and the author of the cause, besides knowing the reasoning used by the judges. Results: The High Court issued 21,948 decisions in December 2015, with 1448 judgments (6.6%) about work accidents and only 20 (0.09%) on collective action. After analyzing these 20 decisions, it was found that the judgments granted compensation for collective moral damage (85%) and/or obligation to make, that is, changes to improve prevention and safety (71%). The processes have been filed mainly by the Labor Prosecutor (83%), and also appeared lawsuits filed by unions (17%). The compensation for collective moral damage had average of 250,000 reais (about US$65,000), but it should be noted that there is a great range of values found, also are several situations repaired by this compensation. This is the last instance resource for this kind of lawsuit and all decisions were well founded and received partially the request made for working environment protection. Conclusions: When triggered, the labor court system provides the requested collective protection in class action. The values of convictions arbitrated in collective actions are significant and indicate that it creates social and economic repercussions, stimulating employers to improve the working environment conditions of their companies. It is necessary to intensify the use of collective actions, however, because they are more efficient for prevention than reparatory individual lawsuits, but it has been underutilized, mainly by Unions.

Keywords: Brazilian Class Action, collective action, work accident penalization, workplace accident prevention, workplace protection law

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Authors: Pierobon Enrico, Missiaggia Marta, Castelluzzo Michele, Tommasino Francesco, Ricci Leonardo, Scifoni Emanuele, Vincezo Monaco, Boscardin Maurizio, La Tessa Chiara

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Clinical outcomes collected over the past three decades have suggested that ion therapy has the potential to be a treatment modality superior to conventional radiation for several types of cancer, including recurrences, as well as for other diseases. Although the results have been encouraging, numerous treatment uncertainties remain a major obstacle to the full exploitation of particle radiotherapy. To overcome therapy uncertainties optimizing treatment outcome, the best possible radiation quality description is of paramount importance linking radiation physical dose to biological effects. Microdosimetry was developed as a tool to improve the description of radiation quality. By recording the energy deposition at the micrometric scale (the typical size of a cell nucleus), this approach takes into account the non-deterministic nature of atomic and nuclear processes and creates a direct link between the dose deposited by radiation and the biological effect induced. Microdosimeters measure the spectrum of lineal energy y, defined as the energy deposition in the detector divided by most probable track length travelled by radiation. The latter is provided by the so-called “Mean Chord Length” (MCL) approximation, and it is related to the detector geometry. To improve the characterization of the radiation field quality, we define a new quantity replacing the MCL with the actual particle track length inside the microdosimeter. In order to measure this new quantity, we propose a two-stage detector consisting of a commercial Tissue Equivalent Proportional Counter (TEPC) and 4 layers of Low Gain Avalanche Detectors (LGADs) strips. The TEPC detector records the energy deposition in a region equivalent to 2 um of tissue, while the LGADs are very suitable for particle tracking because of the thickness thinnable down to tens of micrometers and fast response to ionizing radiation. The concept of HDM has been investigated and validated with Monte Carlo simulations. Currently, a dedicated readout is under development. This two stages detector will require two different systems to join complementary information for each event: energy deposition in the TEPC and respective track length recorded by LGADs tracker. This challenge is being addressed by implementing SoC (System on Chip) technology, relying on Field Programmable Gated Arrays (FPGAs) based on the Zynq architecture. TEPC readout consists of three different signal amplification legs and is carried out thanks to 3 ADCs mounted on a FPGA board. LGADs activated strip signal is processed thanks to dedicated chips, and finally, the activated strip is stored relying again on FPGA-based solutions. In this work, we will provide a detailed description of HDM geometry and the SoC solutions that we are implementing for the readout.

Keywords: particle tracking, ion therapy, low gain avalanche diode, tissue equivalent proportional counter, microdosimetry

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Authors: Lachin Mikjtarnejad, Mohsen Farzaneh

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Various microbes, such as fungi and bacteria species, are naturally found in the fruit microbiota, and some of them act as a pathogen and result in fruit rot. Among non-pathogenic microbes, yeasts (single-celled microorganisms belonging to the fungi kingdom) can colonize fruit tissues and interact with them without causing any damage to them. Although yeasts are part of the plant microbiota, there is little information about their interactions with plants in comparison with bacteria and filamentous fungi. According to several existing studies, some yeasts can colonize different plant species and have the biological control ability to suppress some of the plant pathogens. It means those specific yeast-colonized plants are more resistant to some plant pathogens. The major objective of the present investigation is to isolate yeast strains from apple fruit and screen their ability to control Penicillium expansum, the causal agent of blue mold of fruits. In the present study, psychrotrophic and epiphytic yeasts were isolated from apple fruits that were stored at low temperatures (0–1°C). Totally, 42 yeast isolates were obtained and identified by molecular analysis based on genomic sequences of the D1/D2 and ITS1/ITS4 regions of their rDNA. All isolated yeasts were primarily screened by' in vitro dual culture assay against P. expansum by measuring the fungus' relative growth inhibition after 10 days of incubation. The results showed that the mycelial growth of P. expansum was reduced between 41–53% when challenged by promising yeast strains. The isolates with the strongest antagonistic activity belonged to Metschnikowia pulcherrima A13, Rhodotorula mucilaginosa A41, Leucosporidium Scottii A26, Aureobasidium pullulans A19, Pichia guilliermondii A32, Cryptococcus flavescents A25, and Pichia kluyveri A40. The results of seven superior isolates to inhibit blue mold decay on fruit showed that isolates A. pullulans A19, L. scottii A26, and Pi. guilliermondii A32 could significantly reduce the fruit rot and decay with 26 mm, 22 mm and 20 mm zone diameter, respectively, compared to the control sample with 43 mm. Our results show Pi. guilliermondii strain A13 was the most effective yeast isolates in inhibiting P. expansum on apple fruits. In addition, various biological control mechanisms of promising biological isolates against blue mold have been evaluated to date, including competition for nutrients and space, production of volatile metabolites, reduction of spore germination, production of siderophores and production of extracellular lytic enzymes such as chitinase and β-1,3-glucanase. However, the competition for nutrients and the ability to inhibit P. expansum spore growth have been introduced as the prevailing mechanisms among them. Accordingly, in our study, isolates A13, A41, A40, A25, A32, A19 and A26 inhibited the germination of P. expansum, whereas isolates A13 and A19 were the strongest inhibitors of P. expansum mycelia growth, causing 89.13% and 81.75 % reduction in the mycelial surface, respectively. All the promising isolates produced chitinase and β-1,3-glucanase after 3, 5 and 7 days of cultivation. Finally, based on our findings, we are proposing that, Pi. guilliermondiias as an effective biocontrol agent and alternative to chemical fungicides to control the blue mold of apple fruit.

Keywords: yeast, yeast enzymes, biocontrol, post harvest diseases

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Authors: Hilal T. Sasmazel, Seda Surucu

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Skin tissue engineering is a promising field for the treatment of skin defects using scaffolds. This approach involves the use of living cells and biomaterials to restore, maintain, or regenerate tissues and organs in the body by providing; (i) larger surface area for cell attachment, (ii) proper porosity for cell colonization and cell to cell interaction, and (iii) 3-dimensionality at macroscopic scale. Recent studies on this area mainly focus on fabrication of scaffolds that can closely mimic the natural extracellular matrix (ECM) for creation of tissue specific niche-like environment at the subcellular scale. Scaffolds designed as ECM-like architectures incorporating into the host with minimal scarring/pain and facilitate angiogenesis. This study is related to combining of synthetic PCL and natural chitosan polymers to form 3D PCL/Chitosan core-shell structures for skin tissue engineering applications. Amongst the polymers used in tissue engineering, natural polymer chitosan and synthetic polymer poly(ε-caprolactone) (PCL) are widely preferred in the literature. Chitosan has been among researchers for a very long time because of its superior biocompatibility and structural resemblance to the glycosaminoglycan of bone tissue. However, the low mechanical flexibility and limited biodegradability properties reveals the necessity of using this polymer in a composite structure. On the other hand, PCL is a versatile polymer due to its low melting point (60°C), ease of processability, degradability with non-enzymatic processes (hydrolysis) and good mechanical properties. Nevertheless, there are also several disadvantages of PCL such as its hydrophobic structure, limited bio-interaction and susceptibility to bacterial biodegradation. Therefore, it became crucial to use both of these polymers together as a hybrid material in order to overcome the disadvantages of both polymers and combine advantages of those. The scaffolds here were fabricated by using electrospinning technique and the characterizations of the samples were done by contact angle (CA) measurements, scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-Ray Photoelectron spectroscopy (XPS). Additionally, gas permeability test, mechanical test, thickness measurement and PBS absorption and shrinkage tests were performed for all type of scaffolds (PCL, chitosan and PCL/chitosan core-shell). By using ImageJ launcher software program (USA) from SEM photographs the average inter-fiber diameter values were calculated as 0.717±0.198 µm for PCL, 0.660±0.070 µm for chitosan and 0.412±0.339 µm for PCL/chitosan core-shell structures. Additionally, the average inter-fiber pore size values exhibited decrease of 66.91% and 61.90% for the PCL and chitosan structures respectively, compare to PCL/chitosan core-shell structures. TEM images proved that homogenous and continuous bead free core-shell fibers were obtained. XPS analysis of the PCL/chitosan core-shell structures exhibited the characteristic peaks of PCL and chitosan polymers. Measured average gas permeability value of produced PCL/chitosan core-shell structure was determined 2315±3.4 g.m-2.day-1. In the future, cell-material interactions of those developed PCL/chitosan core-shell structures will be carried out with L929 ATCC CCL-1 mouse fibroblast cell line. Standard MTT assay and microscopic imaging methods will be used for the investigation of the cell attachment, proliferation and growth capacities of the developed materials.

Keywords: chitosan, coaxial electrospinning, core-shell, PCL, tissue scaffold

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Authors: Z. Gharaee

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Recognizing actions performed by others is important in our daily lives since it is necessary for communicating with others in a proper way. We perceive an action by observing the kinematics of motions involved in the performance. We use our experience and concepts to make a correct recognition of the actions. Although building the action concepts is a life-long process, which is repeated throughout life, we are very efficient in applying our learned concepts in analyzing motions and recognizing actions. Experiments on the subjects observing the actions performed by an actor show that an action is recognized after only about two hundred milliseconds of observation. In this study, hierarchical action recognition architecture is proposed by using growing grid layers. The first-layer growing grid receives the pre-processed data of consecutive 3D postures of joint positions and applies some heuristics during the growth phase to allocate areas of the map by inserting new neurons. As a result of training the first-layer growing grid, action pattern vectors are generated by connecting the elicited activations of the learned map. The ordered vector representation layer receives action pattern vectors to create time-invariant vectors of key elicited activations. Time-invariant vectors are sent to second-layer growing grid for categorization. This grid creates the clusters representing the actions. Finally, one-layer neural network developed by a delta rule labels the action categories in the last layer. System performance has been evaluated in an experiment with the publicly available MSR-Action3D dataset. There are actions performed by using different parts of human body: Hand Clap, Two Hands Wave, Side Boxing, Bend, Forward Kick, Side Kick, Jogging, Tennis Serve, Golf Swing, Pick Up and Throw. The growing grid architecture was trained by applying several random selections of generalization test data fed to the system during on average 100 epochs for each training of the first-layer growing grid and around 75 epochs for each training of the second-layer growing grid. The average generalization test accuracy is 92.6%. A comparison analysis between the performance of growing grid architecture and self-organizing map (SOM) architecture in terms of accuracy and learning speed show that the growing grid architecture is superior to the SOM architecture in action recognition task. The SOM architecture completes learning the same dataset of actions in around 150 epochs for each training of the first-layer SOM while it takes 1200 epochs for each training of the second-layer SOM and it achieves the average recognition accuracy of 90% for generalization test data. In summary, using the growing grid network preserves the fundamental features of SOMs, such as topographic organization of neurons, lateral interactions, the abilities of unsupervised learning and representing high dimensional input space in the lower dimensional maps. The architecture also benefits from an automatic size setting mechanism resulting in higher flexibility and robustness. Moreover, by utilizing growing grids the system automatically obtains a prior knowledge of input space during the growth phase and applies this information to expand the map by inserting new neurons wherever there is high representational demand.

Keywords: action recognition, growing grid, hierarchical architecture, neural networks, system performance

Procedia PDF Downloads 133

Authors: Pedro P. Drumond, James E. Ball, Priscilla M. Moura, Márcia M. L. P. Coelho

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In recent decades, On-site Stormwater Detention (OSD) systems have been implemented in many cities around the world. In Brazil, urban drainage source control policies were created in the 1990’s and were mainly based on OSD. The concept of this technique is to promote the detention of additional stormwater runoff caused by impervious areas, in order to maintain pre-urbanization peak flow levels. In Australia OSD, was first adopted in the early 1980’s by the Ku-ring-gai Council in Sydney’s northern suburbs and Wollongong City Council. Many papers on the topic were published at that time. However, source control techniques related to stormwater quality have become to the forefront and OSD has been relegated to the background. In order to evaluate the effectiveness of the current regulations regarding OSD, the existing policies were compared in Australian cities, a country considered experienced in the use of this technique, and in Brazilian cities where OSD adoption has been increasing. The cities selected for analysis were Wollongong and Belo Horizonte, the first municipalities to adopt OSD in their respective countries, and Sydney and Porto Alegre, cities where these policies are local references. The Australian and Brazilian cities are located in Southern Hemisphere of the planet and similar rainfall intensities can be observed, especially in storm bursts greater than 15 minutes. Regarding technical criteria, Brazilian cities have a site-based approach, analyzing only on-site system drainage. This approach is criticized for not evaluating impacts on urban drainage systems and in rare cases may cause the increase of peak flows downstream. The city of Wollongong and most of the Sydney Councils adopted a catchment-based approach, requiring the use of Permissible Site Discharge (PSD) and Site Storage Requirements (SSR) values based on analysis of entire catchments via hydrograph-producing computer models. Based on the premise that OSD should be designed to dampen storms of 100 years Average Recurrence Interval (ARI) storm, the values of PSD and SSR in these four municipalities were compared. In general, Brazilian cities presented low values of PSD and high values of SSR. This can be explained by site-based approach and the low runoff coefficient value adopted for pre-development conditions. The results clearly show the differences between approaches and methodologies adopted in OSD designs among Brazilian and Australian municipalities, especially with regard to PSD values, being on opposite sides of the scale. However, lack of research regarding the real performance of constructed OSD does not allow for determining which is best. It is necessary to investigate OSD performance in a real situation, assessing the damping provided throughout its useful life, maintenance issues, debris blockage problems and the parameters related to rain-flow methods. Acknowledgments: The authors wish to thank CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico (Chamada Universal – MCTI/CNPq Nº 14/2014), FAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerais, and CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior for their financial support.

Keywords: on-site stormwater detention, source control, stormwater, urban drainage

Procedia PDF Downloads 158

Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Kaushikk Iyer, Richard M Hall, David Keeling

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Hardware-in-the-loop (HIL) simulation is an advanced technique for developing and testing complex real-time control systems. This paper presents the benefits of HIL simulation and how it can be implemented and used effectively to develop, test, and validate advanced control algorithms used in a spinal joint Wear simulator for the Tribological testing of spinal disc prostheses. spinal wear simulator is technologically the most advanced machine currently employed For the in-vitro testing of newly developed spinal Discimplants. However, the existing control techniques, such as a simple position control Does not allow the simulator to test non-sinusoidal waveforms. Thus, there is a need for better and advanced control methods that can be developed and tested Rigorouslybut safely before deploying it into the real simulator. A benchtop HILsetupis was created for experimentation, controller verification, and validation purposes, allowing different control strategies to be tested rapidly in a safe environment. The HIL simulation aspect in this setup attempts to replicate similar spinal motion and loading conditions. The spinal joint wear simulator containsa four-Barlinkpowered by electromechanical actuators. LabVIEW software is used to design a kinematic model of the spinal wear Simulator to Validatehow each link contributes towards the final motion of the implant under test. As a result, the implant articulates with an angular motion specified in the international standards, ISO-18192-1, that define fixed, simplified, and sinusoid motion and load profiles for wear testing of cervical disc implants. Using a PID controller, a velocity-based position control algorithm was developed to interface with the benchtop setup that performs HIL simulation. In addition to PID, a fuzzy logic controller (FLC) was also developed that acts as a supervisory controller. FLC provides intelligence to the PID controller by By automatically tuning the controller for profiles that vary in amplitude, shape, and frequency. This combination of the fuzzy-PID controller is novel to the wear testing application for spinal simulators and demonstrated superior performance against PIDwhen tested for a spectrum of frequency. Kaushikk Iyer is a Ph.D. Student at the University of Leeds and an employee at Key Engineering Solutions, Leeds, United Kingdom, (e-mail: [email protected], phone: +44 740 541 5502). Richard M Hall is with the University of Leeds, the United Kingdom as a professor in the Mechanical Engineering Department (e-mail: [email protected]). David Keeling is the managing director of Key Engineering Solutions, Leeds, United Kingdom (e-mail: [email protected]). Results obtained are successfully validated against the load and motion tolerances specified by the ISO18192-1 standard and fall within limits, that is, ±0.5° at the maxima and minima of the motion and ±2 % of the complete cycle for phasing. The simulation results prove the efficacy of the test setup using HIL simulation to verify and validate the accuracy and robustness of the prospective controller before its deployment into the spinal wear simulator. This method of testing controllers enables a wide range of possibilities to test advanced control algorithms that can potentially test even profiles of patients performing various dailyliving activities.

Keywords: Fuzzy-PID controller, hardware-in-the-loop (HIL), real-time simulation, spinal wear simulator

Procedia PDF Downloads 145

Authors: Kamolvara Sirisuksakulchai, Soamwadee Chaianansutcharit, Kazunori Sato

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Solid Oxide Fuel Cells (SOFCs) have been considered as one of the most efficient large unit power generators for household and industrial applications. The efficiency of an electronic cell depends mainly on the electrochemical reactions in the anode. The development of anode materials has been intensely studied to achieve higher kinetic rates of redox reactions and lower internal resistance. Recent studies have introduced an efficient cermet (ceramic-metallic) material for its ability in fuel oxidation and oxide conduction. This could expand the reactive site, also known as the triple-phase boundary (TPB), thus increasing the overall performance. In this study, a bimetallic catalyst Ni₀.₇₅Co₀.₂₅Oₓ was combined with Gd₀.₁Ce₀.₉O₁.₉₅ (GDC) to be used as a cermet anode (NiCo-GDC) for an anode-supported type SOFC. The synthesis of Ni₀.₇₅Co₀.₂₅Oₓ was carried out by ball milling NiO and Co3O4 powders in ethanol and calcined at 1000 °C. The Gd₀.₁Ce₀.₉O₁.₉₅ was prepared by a urea co-precipitation method. Precursors of Gd(NO₃)₃·6H₂O and Ce(NO₃)₃·6H₂O were dissolved in distilled water with the addition of urea and were heated subsequently. The heated mixture product was filtered and rinsed thoroughly, then dried and calcined at 800 °C and 1500 °C, respectively. The two powders were combined followed by pelletization and sintering at 1100 °C to form an anode support layer. The fabrications of an electrolyte layer and cathode layer were conducted. The electrochemical performance in H₂ was measured from 800 °C to 600 °C while for CH₄ was from 750 °C to 600 °C. The maximum power density at 750 °C in H₂ was 13% higher than in CH₄. The difference in performance was due to higher polarization resistances confirmed by the impedance spectra. According to the standard enthalpy, the dissociation energy of C-H bonds in CH₄ is slightly higher than the H-H bond H₂. The dissociation of CH₄ could be the cause of resistance within the anode material. The results from lower temperatures showed a descending trend of power density in relevance to the increased polarization resistance. This was due to lowering conductivity when the temperature decreases. The long-term stability was measured at 750 °C in CH₄ monitoring at 12-hour intervals. The maximum power density tends to increase gradually with time while the resistances were maintained. This suggests the enhanced stability from charge transfer activities in doped ceria due to the transition of Ce⁴⁺ ↔ Ce³⁺ at low oxygen partial pressure and high-temperature atmosphere. However, the power density started to drop after 60 h, and the cell potential also dropped from 0.3249 V to 0.2850 V. These phenomena was confirmed by a shifted impedance spectra indicating a higher ohmic resistance. The observation by FESEM and EDX-mapping suggests the degradation due to mass transport of ions in the electrolyte while the anode microstructure was still maintained. In summary, the electrochemical test and stability test for 60 h was achieved by NiCo-GDC cermet anode. Coke deposition was not detected after operation in CH₄, hence this confirms the superior properties of the bimetallic cermet anode over typical Ni-GDC.

Keywords: bimetallic catalyst, ceria-based SOFCs, methane oxidation, solid oxide fuel cell

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Authors: B. S. Premalatha, Kausalya Sahani

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Background: Glomus jugulare tumors arise within the jugular foramen and are commonly seen in females particularly on the left side. Surgical excision of the tumor may cause lower cranial nerve deficits. Cranial nerve involvement produces hoarseness of voice, slurred speech, and dysphagia along with other physical symptoms, thereby affecting the quality of life of individuals. Though oncological clearance is mainly emphasized on while treating these individuals, little importance is given to their communication, voice and swallowing problems, which play a crucial part in daily functioning. Objective: To examine the functions of voice, speech and swallowing outcomes of the subjects, following excision of glomus jugulare tumor. Methods: Two female subjects aged 56 and 62 years had come with a complaint of change in voice, inability to swallow and reduced clarity of speech following surgery for left glomus jugulare tumor were participants of the study. Their surgical information revealed multiple cranial nerve palsies involving the left facial, left superior and recurrent branches of the vagus nerve, left pharyngeal, left soft palate, left hypoglossal and vestibular nerves. Functional outcomes of voice, speech and swallowing were evaluated by perceptual and objective assessment procedures. Assessment included the examination of oral structures and functions, dysarthria by Frenchey dysarthria assessment, cranial nerve functions and swallowing functions. MDVP and Dr. Speech software were used to evaluate acoustic parameters of voice and quality of voice respectively. Results: The study revealed that both the subjects, subsequent to excision of glomus jugulare tumor, showed a varied picture of affected oral structure and functions, articulation, voice and swallowing functions. The cranial nerve assessment showed impairment of the vagus, hypoglossal, facial and glossopharyngeal nerves. Voice examination indicated vocal cord paralysis associated with breathy quality of voice, weak voluntary cough, reduced pitch and loudness range, and poor respiratory support. Perturbation parameters as jitter, shimmer were affected along with s/z ratio indicative of voice fold pathology. Reduced MPD(Maximum Phonation Duration) of vowels indicated that disturbed coordination between respiratory and laryngeal systems. Hypernasality was found to be a prominent feature which reduced speech intelligibility. Imprecise articulation was seen in both the subjects as the hypoglossal nerve was affected following surgery. Injury to vagus, hypoglossal, gloss pharyngeal and facial nerves disturbed the function of swallowing. All the phases of swallow were affected. Aspiration was observed before and during the swallow, confirming the oropharyngeal dysphagia. All the subsystems were affected as per Frenchey Dysarthria Assessment signifying the diagnosis of flaccid dysarthria. Conclusion: There is an observable communication and swallowing difficulty seen following excision of glomus jugulare tumor. Even with complete resection, extensive rehabilitation may be necessary due to significant lower cranial nerve dysfunction. The finding of the present study stresses the need for involvement of as speech and swallowing therapist for pre-operative counseling and assessment of functional outcomes.

Keywords: functional outcome, glomus jugulare tumor excision, multiple cranial nerve impairment, speech and swallowing

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Authors: Chen Jiang, Eric Jordan, Maurice Gell, Balakrishnan Nair

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Nuclear fusion, one of the most promising options for reliably generating large amounts of carbon-free energy in the future, has seen a plethora of ground-breaking technological advances in recent years. An efficient and durable “breeding blanket”, needed to ensure a reactor’s self-sufficiency by maintaining the optimal coolant temperature as well as by minimizing radiation dosage behind the blanket, still remains a technological challenge for the various reactor designs for commercial fusion power plants. A relatively new dual-coolant lead-lithium (DCLL) breeder design has exhibited great potential for high-temperature (>700oC), high-thermal-efficiency (>40%) fusion reactor operation. However, the structural material, namely reduced activation ferritic-martensitic (RAFM) steel, is not chemically stable in contact with molten Pb-17%Li coolant. Thus, to utilize this new promising reactor design, the demand for effective corrosion-resistant coatings on RAFM steels represents a pressing need. Solution Spray Technologies LLC (SST) is developing a double-layer ceramic coating design to address the corrosion protection of RAFM steels, using a novel solution and solution/suspension plasma spray technology through a US Department of Energy-funded project. Plasma spray is a coating deposition method widely used in many energy applications. Novel derivatives of the conventional powder plasma spray process, known as the solution-precursor and solution/suspension-hybrid plasma spray process, are powerful methods to fabricate thin, dense ceramic coatings with complex compositions necessary for the corrosion protection in DCLL breeders. These processes can be used to produce ultra-fine molten splats and to allow fine adjustment of coating chemistry. Thin, dense ceramic coatings with chosen chemistry for superior chemical stability in molten Pb-Li, low activation properties, and good radiation tolerance, is ideal for corrosion-protection of RAFM steels. A key challenge is to accommodate its CTE mismatch with the RAFM substrate through the selection and incorporation of appropriate bond layers, thus allowing for enhanced coating durability and robustness. Systematic process optimization is being used to define the optimal plasma spray conditions for both the topcoat and bond-layer, and X-ray diffraction and SEM-EDS are applied to successfully validate the chemistry and phase composition of the coatings. The plasma-sprayed double-layer corrosion resistant coatings were also deposited onto simulated RAFM steel substrates, which are being tested separately under thermal cycling, high-temperature moist air oxidation as well as molten Pb-Li capsule corrosion conditions. Results from this testing on coated samples, and comparisons with bare RAFM reference samples will be presented and conclusions will be presented assessing the viability of the new ceramic coatings to be viable corrosion prevention systems for DCLL breeders in commercial nuclear fusion reactors.

Keywords: breeding blanket, corrosion protection, coating, plasma spray

Procedia PDF Downloads 281

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Mikaela Kutrolli, Noah S. Pereira, Vanessa Scanlon, Mohamadmahdi Samandari, Ali Tamayol

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Bone tissue engineering has drawn significant attention and various biomaterials have been tested. Polymers such as polycaprolactone (PCL) offer excellent biocompatibility, reasonable mechanical properties, and biodegradability. However, PCL scaffolds suffer a critical drawback: a lack of micro/mesoporosity, affecting cell attachment, tissue integration, and mineralization. It also results in a slow degradation rate. While 3D-printing has addressed the issue of macroporosity through CAD-guided fabrication, PCL scaffolds still exhibit poor smaller-scale porosity. To overcome this, we generated composites of PCL, hydroxyapatite (HA), and powdered sucrose (PS). The latter serves as a sacrificial material to generate porous particles after sucrose dissolution. Additionally, we have incorporated dexamethasone (DEX) to boost the PCL osteogenic properties. The resulting scaffolds maintain controlled macroporosity from the lattice print structure but also develop micro/mesoporosity within PCL fibers when exposed to aqueous environments. The study involved mixing PS into solvent-dissolved PCL in different weight ratios of PS to PCL (70:30, 50:50, and 30:70 wt%). The resulting composite was used for 3D printing of scaffolds at room temperature. Printability was optimized by adjusting pressure, speed, and layer height through filament collapse and fusion test. Enzymatic degradation, porogen leaching, and DEX release profiles were characterized. Physical properties were assessed using wettability, SEM, and micro-CT to quantify the porosity (percentage, pore size, and interconnectivity). Raman spectroscopy was used to verify the absence of sugar after leaching. Mechanical characteristics were evaluated via compression testing before and after porogen leaching. Bone marrow stromal cells (BMSCs) behavior in the printed scaffolds was studied by assessing viability, metabolic activity, osteo-differentiation, and mineralization. The scaffolds with a 70% sugar concentration exhibited superior printability and reached the highest porosity of 80%, but performed poorly during mechanical testing. A 50% PS concentration demonstrated a 70% porosity, with an average pore size of 25 µm, favoring cell attachment. No trace of sucrose was found in Raman after leaching the sugar for 8 hours. Water contact angle results show improved hydrophilicity as the sugar concentration increased, making the scaffolds more conductive to cell adhesion. The behavior of bone marrow stromal cells (BMSCs) showed positive viability and proliferation results with an increasing trend of mineralization and osteo-differentiation as the sucrose concentration increased. The addition of HA and DEX also promoted mineralization and osteo-differentiation in the cultures. The integration of PS as porogen at a concentration of 50%wt within PCL scaffolds presents a promising approach to address the poor cell attachment and tissue integration issues of PCL in bone tissue engineering. The method allows for the fabrication of scaffolds with tunable porosity and mechanical properties, suitable for various applications. The addition of HA and DEX further enhanced the scaffolds. Future studies will apply the scaffolds in an in-vivo model to thoroughly investigate their performance.

Keywords: bone, PCL, 3D printing, tissue engineering

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Muhammad Alhada Fuadilah Habib, Ayla Karina Budita, Cut Rizka Al Usrah, Mukhammad Fatkhullah, Kanita Khoirun Nisa, Siti Muslihatul Mukaromah

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In this contemporary era, the term of development often emphasised merely on the economic growth aspect. Development of a program often considered as superior by the government, in fact, it often raises various problems. The problems occur because the development policies determined by the government tend to favor private entrepreneurs and impose on the oppression toward the community. The development promised to prosper the community's life, turn out in fact of harming the community, threatening the survival of the community and damaging the ecosystem of nature where the community hangs their life to it. Nowadays many natural resources should be used for the community’s life prosperity. However, the prosperity is conquered by the private entrepreneurs that are regulated through the free market mechanism and wrapped in democratization. This condition actually is a form of neoliberalism that builds new administration order system which is far from the meaning of the word democracy. The government should play more role in protecting community's life and prosperity, but in fact, the government sides with the private entrepreneurs for the sake of the economic benefits regardless of other aspects of the community’s life. This unjustified condition presents a wide range of social movements from the community in response to the neoliberalis policy that actually eliminates the doctrine of community sovereignty. Social movements performed by Yogyakarta south coastal area community, as the focus of the discussion in this paper, is one of the community’s response toward the government policies related to the construction of the ferruginous sand quarry which is tend to favor on private entrepreneurs and highly prejudicing or even threatening the survival of Yogyakarta south coastal area community. The data collection in this study uses qualitative research methods with in-depth interview data collection techniques and purposive informant determination techniques. This method was chosen in order to obtain the insightful data and detailed information to uncover the injustice policies committed by the government-private entrepreneurs toward Yogyakarta south coastal area community. The brief results of this study show that the conflicts between the community and government-private entrepreneurs occurred because of the differences of interests and paradigm of natural resource management. The resistance movements done by the community to fight back the government-private entrepreneurs was conducted by forming an organization called Paguyupan Petani Lahan Pantai Kulon Progo (PPLP-KP). This organization do the resistances through two ways; firstly, quiet action done through various actions such as; refusing against the socialization, performing discussion to deliberate their argument with the government-private entrepreneurs, complaining the problems to the central government, creating banners or billboards which contain the writing of rejection, performing pray rituals to invoke the justice from the God, as well as instill the resistance ideology to their young generation. Secondly, the rough action also is done through various actions such as; doing roadblocks, conducting rallies, as well as doing clash with the government apparatus. In case the resistances done by the community are seen from the pattern. Actually, the resistances are reaction toward the aggression carried out by the government-private entrepreneurs.

Keywords: community resistance, conflict, ferruginous sand quarry construction, social movement

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Authors: Sagar Saroha, Sawan S. Sinha, Sunil Lakshmipathy

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Reynolds averaged Navier-Stokes (RANS) model is the popular computational tool for prediction of turbulent flows. Being computationally less expensive as compared to direct numerical simulation (DNS), RANS has received wide acceptance in industry and research community as well. However, for high Reynolds number flows, the traditional RANS approach based on the Boussinesq hypothesis is incapacitated to capture all the essential flow characteristics, and thus, its performance is restricted in high Reynolds number flows of practical interest. RANS performance turns out to be inadequate in regimes like flow over curved surfaces, flows with rapid changes in the mean strain rate, duct flows involving secondary streamlines and three-dimensional separated flows. In the recent decade, partially averaged Navier-Stokes (PANS) methodology has gained acceptability among seamless bridging methods of turbulence- placed between DNS and RANS. PANS methodology, being a scale resolving bridging method, is inherently more suitable than RANS for simulating turbulent flows. The superior ability of PANS method has been demonstrated for some cases like swirling flows, high-speed mixing environment, and high Reynolds number turbulent flows. In our work, we intend to evaluate PANS in case of separated turbulent flows past bluff bodies -which is of broad aerodynamic research and industrial application. PANS equations, being derived from base RANS, continue to inherit the inadequacies from the parent RANS model based on linear eddy-viscosity model (LEVM) closure. To enhance PANS’ capabilities for simulating separated flows, the shortcomings of the LEVM closure need to be addressed. Inabilities of the LEVMs have inspired the development of non-linear eddy viscosity models (NLEVM). To explore the potential improvement in PANS performance, in our study we evaluate the PANS behavior in conjugation with NLEVM. Our work can be categorized into three significant steps: (i) Extraction of PANS version of NLEVM from RANS model, (ii) testing the model in the homogeneous turbulence environment and (iii) application and evaluation of the model in the canonical case of separated non-homogeneous flow field (flow past prismatic bodies and bodies of revolution at high Reynolds number). PANS version of NLEVM shall be derived and implemented in OpenFOAM -an open source solver. Homogeneous flows evaluation will comprise the study of the influence of the PANS’ filter-width control parameter on the turbulent stresses; the homogeneous analysis performed over typical velocity fields and asymptotic analysis of Reynolds stress tensor. Non-homogeneous flow case will include the study of mean integrated quantities and various instantaneous flow field features including wake structures. Performance of PANS + NLEVM shall be compared against the LEVM based PANS and LEVM based RANS. This assessment will contribute to significant improvement of the predictive ability of the computational fluid dynamics (CFD) tools in massively separated turbulent flows past bluff bodies.

Keywords: bridging methods of turbulence, high Re-CFD, non-linear PANS, separated turbulent flows

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Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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Authors: Elena Cangelosi, Wayne Beyea

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This research expands the resilience planning literature by exploring the barriers and enablers to climate and health adaptation planning for small urban, coastal Great Lakes communities. With funding from the United States Centers for Disease Control and Prevention (CDC) Climate Ready City and States Initiative, this research took place during a 3-year pilot intervention project which integrates urban planning and public health. The project used the CDC’s Building Resilience Against Climate Effects (BRACE) framework to prevent or reduce the human health impacts from climate change in Marquette County, Michigan. Using a deliberation with the analysis planning process, interviews, focus groups, and community meetings with over 25 stakeholder groups and over 100 participants identified the area’s climate-related health concerns and adaptation interventions to address those concerns. Marquette County, on the shores of Lake Superior, the largest of the Great Lakes, was selected for the project based on their existing adaptive capacity and proactive approach to climate adaptation planning. With Marquette County as the context, this study fills a gap in the adaptation literature, which currently heavily emphasizes large-urban or agriculturally-based rural areas, and largely neglects small urban areas. This research builds on the qualitative case-study, survey, and interview approach established by previous researchers on contextual barriers and enablers for adaptation planning. This research uses a case study approach, including surveys and interviews of public officials, to identify the barriers and enablers for climate and health adaptation planning for small-urban areas within a large, non-agricultural, Great Lakes county. The researchers hypothesize that the barriers and enablers will, in some cases, overlap those found in other contexts, but in many cases, will be unique to a rural setting. The study reveals that funding, staff capacity, and communication across a large, rural geography act as the main barriers, while strong networks and collaboration, interested leaders, and community interest through a strong human-land connection act as the primary enablers. Challenges unique to rural areas are revealed, including weak opportunities for grant funding, large geographical distances, communication challenges with an aging and remote population, and the out-migration of education residents. Enablers that may be unique to rural contexts include strong collaborative relationships across jurisdictions for regional work and strong connections between residents and the land. As the factors that enable and prevent climate change planning are highly contextual, understanding, and appropriately addressing the unique factors at play for small-urban communities is key for effective planning in those areas. By identifying and addressing the barriers and enablers to climate and health adaptation planning for small-urban, coastal areas, this study can help Great Lakes communities appropriately build resilience to the adverse impacts of climate change. In addition, this research expands the breadth of research and understanding of the challenges and opportunities planners confront in the face of climate change.

Keywords: climate adaptation and resilience, climate change adaptation, climate change and urban resilience, governance and urban resilience

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Authors: Islam Sherif, Ahmed Ashour, Ahmed Hassan, Hatem Osman

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Anterior Cruciate Ligament (ACL) injuries are common among athletes and individuals participating in sports with sudden stops, pivots, and changes in direction. Arthroscopic surgery is the gold standard for ACL reconstruction, aiming to restore knee stability and function. Recent years have witnessed significant advancements in arthroscopic surgery techniques, graft materials, and technological innovations, revolutionizing the field of ACL reconstruction. This presentation delves into the latest advancements in arthroscopic surgery techniques for ACL reconstruction and their potential impact on patient outcomes. Traditionally, autografts from the patellar tendon, hamstring tendon, or quadriceps tendon have been commonly used for ACL reconstruction. However, recent studies have explored the use of allografts, synthetic scaffolds, and tissue-engineered grafts as viable alternatives. This abstract evaluates the benefits and potential drawbacks of each graft type, considering factors such as graft incorporation, strength, and risk of graft failure. Moreover, the application of augmented reality (AR) and virtual reality (VR) technologies in surgical planning and intraoperative navigation has gained traction. AR and VR platforms provide surgeons with detailed 3D anatomical reconstructions of the knee joint, enhancing preoperative visualization and aiding in graft tunnel placement during surgery. We discuss the integration of AR and VR in arthroscopic ACL reconstruction procedures, evaluating their accuracy, cost-effectiveness, and overall impact on surgical outcomes. Beyond graft selection and surgical navigation, patient-specific planning has gained attention in recent research. Advanced imaging techniques, such as MRI-based personalized planning, enable surgeons to tailor ACL reconstruction procedures to each patient's unique anatomy. By accounting for individual variations in the femoral and tibial insertion sites, this personalized approach aims to optimize graft placement and potentially improve postoperative knee kinematics and stability. Furthermore, rehabilitation and postoperative care play a crucial role in the success of ACL reconstruction. This abstract explores novel rehabilitation protocols, emphasizing early mobilization, neuromuscular training, and accelerated recovery strategies. Integrating technology, such as wearable sensors and mobile applications, into postoperative care can facilitate remote monitoring and timely intervention, contributing to enhanced rehabilitation outcomes. In conclusion, this presentation provides an overview of the cutting-edge advancements in arthroscopic surgery techniques for ACL reconstruction. By embracing innovative graft materials, augmented reality, patient-specific planning, and technology-driven rehabilitation, orthopedic surgeons and sports medicine specialists can achieve superior outcomes in ACL injury management. These developments hold great promise for improving the functional outcomes and long-term success rates of ACL reconstruction, benefitting athletes and patients alike.

Keywords: arthroscopic surgery, ACL, autograft, allograft, graft materials, ACL reconstruction, synthetic scaffolds, tissue-engineered graft, virtual reality, augmented reality, surgical planning, intra-operative navigation

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Authors: L. Abubakar, B. M. Sokoto, I. U. Mohammed, M. S. Na’allah, A. Mohammad, A. N. Garba, T. S. Bubuche

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Onion (Allium cepa var. cepa L.), is the most important species of the Allium group belonging to family Alliaceae and genus Allium. It can be regarded as the single important vegetable species in the world after tomatoes. Despite the similarities, which bring the species together, the genus is a strikingly diverse one, with more than five hundred species, which are perennial and mostly bulbous plants. Out of these, only seven species are in cultivation, and five are the most important species of the cultivated Allium. However, Allium cepa (onion) and Allium sativum (Garlic) are the two major cultivated species grown all over the world of which the onion crop is the most important. Heritability defined as the proportion of the observed total variability that is genetic, and its estimates from variance components give more useful information of genotypic variation from the total phenotypic differences and environmental effects on the individuals or families. It therefore guide the breeder with respect to the ease with which selection of traits can be carried out. Heritability estimates guide the breeder with respect to ease of selection of traits while correlations suggest how selection among characters can be practiced. Correlations explain relationship between characters and suggest how selection among characters can be practiced in breeding programmes. Highly significant correlations have been reported, between yield, maturity, rings/bulb and storage loss in onions. Similarly significant positive correlation exists between total bulb yield and plant height, leaf number/plant, bulb diameter and bulb yield/plant. Moderate positive correlations have been observed between maturity date and yield, dry matter content was highly correlated with soluble solids, and higher correlations were also observed between storage loss and soluble solids. The objective of the study is to determine heritability estimates and correlations for characters among onion cultivars of North Western Nigeria. This is envisaged will assist in the breeding of superior onion cultivars within the zone. Thirteen onion cultivars were collected during an expedition covering north western Nigeria and Southern part of Niger Republic during 2013, which are areas noted for onion production. The cultivars were evaluated at two locations; Sokoto, in Sokoto State and Jega in Kebbi State all in Nigeria during the 2013/14 onion season (dry season) under irrigation. Combined analysis of the results revealed fresh bulb yield is highly significantly positively correlated with bulb height and cured bulb yield, and significant positive correlation with plant height and bulb diameter. It also recorded significant negative correlation with mean No. of leaves/plant and non significant negative correlation with bolting %. Cured bulb yield (marketable yield) had highly significant positive correlation with mean bulb weight and fresh bulb yield/ha, with significant positive correlation with bulb height. It also recorded highly significant negative correlation with No. of leaves/plant and significant negative correlation with bolting % and non significant positive correlation with plant height and non significant negative correlation with bulb diameter. High broad sense heritability estimates were recorded for plant height, fresh bulb yield, number of leaves/plant, bolting % and cured bulb yield. Medium to low broad sense heritabilities were also observed for mean bulb weight, plant height and bulb diameter.

Keywords: correlation, heritability, onions, North Western Nigeria

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