Search results for: Hamilton cycle decision problem

Authors: A. S. Lunev, A. A. Larenkov, O. E. Klementyeva, G. E. Kodina

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Background and aims: 68Ga-citrate is one of prospective radiopharmaceutical for PET-imaging of inflammation and infection. 68Ga-citrate is 67Ga-citrate analogue using since 1970s for SPECT-imaging. There's known rebinding reaction occurs past Ga-citrate injection and gallium (similar iron Fe3+) binds with blood transferrin. Then radiolabeled protein complex is delivered to pathological foci (inflammation/infection sites). But excessive gallium bindings with transferrin are cause of slow blood clearance, long accumulation time in foci (24-72 h) and exception of application possibility of the short-lived gallium-68 (T½ = 68 min). Injection of additional chemical agents (e.g. Fe3+ compounds) competing with radioactive gallium to the blood transferrin joining (blocking of its metal binding capacity) is one of the ways to solve formulated problem. This phenomenon can be used for correction of 68Ga-citrate pharmacokinetics for increasing of the blood clearance and accumulation in foci. The aim of real studying is research of effect of stable Fe-citrate on 68Ga-citrate tissue distribution. Materials and methods: 68Ga-citrate without/with extra injection of stable Fe-citrate (III) was injected nonlinear mice with inflammation models (aseptic soft tissue inflammation, lung infection, osteomyelitis). PET/X-RAY Genisys4 (Sofie Bioscience, USA) was used for non-invasive PET imaging (for 30, 60, 120 min past injection 68Ga-citrate) with subsequent reconstruction of imaging and their analysis (value of clearance, distribution volume). Scanning time is 10 min. Results and conclusions: I. v. injection of stable Fe-citrate blocks the metal-binding capability of transferrin serum and allows decreasing gallium-68 radioactivity in blood significantly and increasing accumulation in inflammation (3-5 time). It allows receiving more informative PET-images of inflammation early (for 30-60 min after injection). Pharmacokinetic parameters prove it. Noted there is no statistically significant difference between 68Ga-citrate accumulation for different inflammation model because PET imaging is indication of pathological processes and is not their identification.

Keywords: 68Ga-citrate, Fe-citrate, PET imaging, mice, inflammation, infection

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Authors: Yvonne A. Unrau

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Social work education is a competency-based curriculum that relies mostly on cognitive frameworks and problem-solving models. Absent from the curriculum is knowledge and skills that draw from an embodiment perspective, especially somatic practice methods. Embodiment broadly encompasses the understanding that biological, political, historical, and social factors impact human development via changes to the nervous system. In the past 20 years, research has well-established that unresolved traumatic events, especially during childhood, negatively impacts long-term health and well-being. Furthermore, traumatic stress compromises cognitive processing and activates reflexive action such as ‘fight’ or ‘flight,’ which are the focus of somatic methods. The main objective of this paper is to show how embodiment perspectives and somatic methods can enhance social work practice overall. Using an exploratory approach, the author shares a decade-long journey that involved creating an education-support program for college students who exited the state foster care system. Personal experience, program outcomes and case study narratives revealed that ‘classical’ social work methods were insufficient to fully address the complex needs of college students who were living with complex traumatic stressors. The paper chronicles select case study scenarios and key program development milestones over a 10-year period to show the benefit of incorporating embodiment perspectives in social work practice. The lessons reveal that there is an immediate need for social work curriculum to include embodiment perspectives so that social workers may be equipped to respond competently to their many clients who live with unresolved trauma.

Keywords: social work practice, social work curriculum, embodiment, traumatic stress

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Authors: Xabier Barandiaran, Igone Guerra

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The economic and financial crisis that hit European countries in 2008 revealed the inability of governments to respond unilaterally to the so-called “wicked” problems that affect our societies. Closely linked to this, the increasing disaffection of citizens towards politics has resulted in growing distrust of the citizenry not only in the institutions in general but also in the political system, in particular. Precisely, these two factors provoked the action of the local government of Gipuzkoa (Basque Country) to move from old ways of “doing politics” to a new way of “thinking politics” based on a collaborative approach, in which innovative modes of public decision making are prominent. In this context, in 2015, the initiative Etorkizuna Eraikiz (Building the Future), a contemporary form of networked governance, was launched by the Provincial Government. The paper focuses on the Etorkizuna Eraikiz initiative, a sound commitment from a local government to build jointly with the citizens the future of the territory. This paper will present preliminary results obtained from three different experiences of co-creation developed within Etorkizuna Eraikiz in which the formulation of networked governance is a mandatory pre-requisite. These experiences show how the network building approach among the different agents of the territory as well as the co-creation of public policies is the cornerstone of this challenging mission. Through the analysis of the information and documentation gathered during the four years of Etorkizuna-Eraikiz, and, specifically by delving into the strategy promoted by the initiative, some emerging analytical conclusions resulting from the promotion of this collaborative culture will be presented. For example, some preliminary results have shown a significant positive relationship between shared leadership and the formulation of the public good. In the period 2016-2018, a total of 73 projects were launched and funding by the Provincial Government of Gipuzkoa within the Etorkizuna Eraikiz initiative, that indicates greater engagement of the citizenry in the process of policy-making and therefore improving, somehow, the quality of the public policies. These statements have been supported by the last survey about the perspectives of the citizens toward politics and policies. Some of the more prominent results show us that there is still a high level of distrust in Politics (78,9% of respondents) but a greater trust in institutions such the Political Government of Gipuzkoa (40,8% of respondents declared as “good” the performance of this provincial institution). Regarding the Etorkizuna Eraikiz Initiative, it is being more readily recognized by citizens over this period of time (25,4% of the respondents in June 2018 agreed to know about the initiative giving it a mark of 5,89 ) and thus build trust and a sense of ownership. Although, there is a clear requirement for further research on the linkages between collaborative governance and level of trust, the paper, based on these findings, will provide some managerial and theoretical implications for collaborative governance in the territory.

Keywords: network governance, collaborative governance, public sector innovation, citizen participation, trust

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Authors: John Dorrell, Matthew Ambrosia, Abilash

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This paper employs econometric analysis to quantify the potential profit wind farms can receive by allocating excess wind energy to power bitcoin mining machines. Cryptocurrency mining consumes a substantial amount of electricity worldwide, and wind energy produces a significant amount of energy that is lost because of the intermittent nature of the resource. Supply does not always match consumer demand. By combining the weaknesses of these two technologies, we can improve efficiency and a sustainable path to mine cryptocurrencies. This paper uses historical wind energy from the ERCOT network in Texas and cryptocurrency data from 2000-2021, to create 4-year return on investment projections. Our research model incorporates the price of bitcoin, the price of the miner, the hash rate of the miner relative to the network hash rate, the block reward, the bitcoin transaction fees awarded to the miners, the mining pool fees, the cost of the electricity and the percentage of time the miner will be running to demonstrate that wind farms generate enough excess energy to mine bitcoin profitably. Excess wind energy can be used as a financial battery, which can utilize wasted electricity by changing it into economic energy. The findings of our research determine that wind energy producers can earn profit while not taking away much if any, electricity from the grid. According to our results, Bitcoin mining could give as much as 1347% and 805% return on investment with the starting dates of November 1, 2021, and November 1, 2022, respectively, using wind farm curtailment. This paper is helpful to policymakers and investors in determining efficient and sustainable ways to power our economic future. This paper proposes a practical solution for the problem of crypto mining energy consumption and creates a more sustainable energy future for Bitcoin.

Keywords: bitcoin, mining, economics, energy

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Authors: Nutcha Taneepanichskul, Helen C. Hailes, Mark Miodownik

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Plastic waste has emerged as a critical global environmental challenge, primarily driven by the prevalent use of conventional plastics derived from petrochemical refining and manufacturing processes in modern packaging. While these plastics serve vital functions, their persistence in the environment post-disposal poses significant threats to ecosystems. Addressing this issue necessitates approaches, one of which involves the development of biodegradable plastics designed to degrade under controlled conditions, such as industrial composting facilities. It is imperative to note that compostable plastics are engineered for degradation within specific environments and are not suited for uncontrolled settings, including natural landscapes and aquatic ecosystems. The full benefits of compostable packaging are realized when subjected to industrial composting, preventing environmental contamination and waste stream pollution. Therefore, effective sorting technologies are essential to enhance composting rates for these materials and diminish the risk of contaminating recycling streams. In this study, it leverage hyperspectral imaging technology (HSI) coupled with advanced machine learning algorithms to accurately identify various types of plastics, encompassing conventional variants like Polyethylene terephthalate (PET), Polypropylene (PP), Low density polyethylene (LDPE), High density polyethylene (HDPE) and biodegradable alternatives such as Polybutylene adipate terephthalate (PBAT), Polylactic acid (PLA), and Polyhydroxyalkanoates (PHA). The dataset is partitioned into three subsets: a training dataset comprising uncontaminated conventional and biodegradable plastics, a validation dataset encompassing contaminated plastics of both types, and a testing dataset featuring real-world packaging items in both pristine and contaminated states. Five distinct machine learning algorithms, namely Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Logistic Regression, and Decision Tree Algorithm, were developed and evaluated for their classification performance. Remarkably, the Logistic Regression and CNN model exhibited the most promising outcomes, achieving a perfect accuracy rate of 100% for the training and validation datasets. Notably, the testing dataset yielded an accuracy exceeding 80%. The successful implementation of this sorting technology within recycling and composting facilities holds the potential to significantly elevate recycling and composting rates. As a result, the envisioned circular economy for plastics can be established, thereby offering a viable solution to mitigate plastic pollution.

Keywords: biodegradable plastics, sorting technology, hyperspectral imaging technology, machine learning algorithms

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Authors: Vladimir Klepikov

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Countries of Central and Southern Europe have a typical feature: oil consumption in the region exceeds own commodity production capacity by far. So crude oil import prevails in the region’s crude oil consumption structure. Transportation using marine and pipeline transport is a common method of the imported oil delivery in the region. For certain refineries, in addition to possible transportation by oil pipelines from seaports, oil is delivered from Russian oil fields. With the view to these specific features and geographic location of the region’s refineries, three ways of imported oil delivery can be singled out: oil delivery by tankers to the port and subsequent transportation by pipeline transport of the port and the refinery; oil delivery by tanker fleet to the port and subsequent transportation by oil trunk pipeline transport; oil delivery from the fields by oil trunk pipelines to refineries. Oil is also delivered by road, internal water, and rail transport. However, the volumes transported this way are negligible in comparison to the three above transportation means. Multimodal oil transportation to refineries using the pipeline and marine transport is one of the biggest cargo flows worldwide. However, in scientific publications this problem is considered mainly for certain modes of transport. Therefore, this study is topical. To elaborate an efficient transportation policy of crude oil supply to Central and Southern Europe, in this paper the geographic concentration of oil refineries was determined and the capacities of the region’s refineries were assessed. The quantitative analysis method is used as a tool. The port infrastructure and the oil trunk pipeline system capacity were assessed in terms of delivery of raw materials to the refineries. The main groups of oil consuming countries were determined. The trends of crude oil production in the region were reviewed. The changes in production capacities and volumes at refineries in the last decade were shown. Based on the revealed refining trends, the scope of possible crude oil supplies to the refineries of the region under review was forecast. The existing transport infrastructure is able to handle the increased oil flow.

Keywords: European region, infrastructure, oil terminal capacity, pipeline capacity, refinery capacity, tanker draft

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Authors: Pranab Kumar Goswami, Elena Gurung

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Small and medium enterprises (SME) are considered as the driving force for the economic growth of a developing country like India. Most of the SMEs are located in residential/non-industrial areas to avoid legal obligations of occupational safety and health (OSH) provisions. This study was conducted in Delhiwith a view to analyze the accidents that occurredduringthe year 2019 & 2020. The objective of the study was to find out the accident prone SMEs in Delhi and major causes of such accidents. Methods: Survey and comprehensive data analysis methods, followed by applying simple statistical techniques, were used for this study. The accident reports for the study period collected from the labour department and police stations were analyzed for the study. The injured workers were interviewed to ascertain safety compliances, training and awareness programs, etc. The study was completed in March2021. Results: It was found that most of the accidents took place in SMEs located in residential/non- industrial areas in Delhi. The accident-prone machines were found to be power presses (42%) and injection moulding machines (37%). Predominantly unsafe machinery or unsafe working conditions and lack of training of worker were observed to be the major causes of accidents in such industries. Conclusions: It was concluded from the study that unsafe machinery/equipment and lack of proper training to the workers were two main reasons for increase in accidents.It was also concluded that the industries located in industrial areas were better placed in terms of workplace compliances. The managements who were running their operations from residential/non-industrial areaswere found to be less aware on health and safety issues. Lack of enforcement by government agencies in such areas has escalated this problem. Adequate training to workers, managing safe & healthy workplace, and sustained enforcement can reduce accidents in such industries.

Keywords: SME, accident prevention, cause of accident, unorganised

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Authors: Tansa Nisan Gunerhan

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Dementia comes in different forms, including Alzheimer's disease. The most common dementia diagnosis among elderly individuals is Alzheimer's disease. On average, for patients with Alzheimer’s, life expectancy is around 4-8 years after the diagnosis; however, expectancy can go as high as twenty years or more, depending on the shrinkage of the brain. Normally, along with aging, the brain shrinks at some level but doesn’t lose a vast amount of neurons. However, Alzheimer's patients' neurons are destroyed rapidly; hence problems with loss of memory, communication, and other metabolic activities begin. The toxic changes in the brain affect the stability of the neurons. Beta-amyloid and tau are two proteins that are believed to play a role in the development of Alzheimer's disease through their toxic changes. Beta-amyloid is a protein that is produced in the brain and is normally broken down and removed from the body. However, in people with Alzheimer's disease, the production of beta-amyloid increases, and it begins to accumulate in the brain. These plaques are thought to disrupt communication between nerve cells and may contribute to the death of brain cells. Tau is a protein that helps to stabilize microtubules, which are essential for the transportation of nutrients and other substances within brain cells. In people with Alzheimer's disease, tau becomes abnormal and begins to accumulate inside brain cells, forming neurofibrillary tangles. These tangles disrupt the normal functioning of brain cells and may contribute to their death, forming amyloid plaques which are deposits of a protein called amyloid-beta that build up between nerve cells in the brain. The accumulation of amyloid plaques and neurofibrillary tangles in the brain is thought to contribute to the shrinkage of brain tissue. As the brain shrinks, the size of the brain may decrease, leading to a reduction in brain volume. Brain atrophy in Alzheimer's disease is often accompanied by changes in the structure and function of brain cells and the connections between them, leading to a decline in brain function. These toxic changes that accumulate can cause symptoms such as memory loss, difficulty with thinking and problem-solving, and changes in behavior and personality.

Keywords: Alzheimer, amyloid-beta, brain atrophy, neuron, shrinkage

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Authors: Redhouane Ghernaout, Amira Fredj, Boualem Remini

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Suspended sediment transport is a serious problem worldwide, but it is much more worrying in certain regions of the world, as is the case in the Maghreb and more particularly in Algeria. It continues to take disturbing proportions in Northern Algeria due to the variability of rains in time and in space and constant deterioration of vegetation. Its prediction is essential in order to identify its intensity and define the necessary actions for its reduction. The purpose of this study is to analyze the concentration data of suspended sediment measured at Wadi El-Abtal Hydrometric Station. It also aims to find and highlight regressive power relationships, which can explain the suspended solid flow by the measured liquid flow. The study strives to find models of artificial neural networks linking the flow, month and precipitation parameters with solid flow. The obtained results show that the power function of the solid transport rating curve and the models of artificial neural networks are appropriate methods for analysing and estimating suspended sediment transport in Wadi Mina at Wadi El-Abtal Hydrometric Station. They made it possible to identify in a fairly conclusive manner the model of neural networks with four input parameters: the liquid flow Q, the month and the daily precipitation measured at the representative stations (Frenda 013002 and Ain El-Hadid 013004 ) of the watershed. The model thus obtained makes it possible to estimate the daily solid flows (interpolate and extrapolate) even beyond the period of observation of solid flows (1985/86 to 1999/00), given the availability of the average daily liquid flows and daily precipitation since 1953/1954.

Keywords: suspended sediment, concentration, regression, liquid flow, solid flow, artificial neural network, modeling, mina, algeria

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Authors: Krzysztof Gwozdzinski, Janusz Mazur

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Bory Tucholskie (Tucholskie Forest) is one of the largest pine forest complexes in Poland. It occupies approx. 3,000 square kilometers of Sandr in the Brda and Wda basin and the Tuchola Plain and the Charzykowskie Plain. Since 2010 it has transformed into The Bory Tucholskie Biosphere Reserve, according to the UNESCO decision. The area of the Bory Tucholskie National Park (BTNP), the park area, has been designated in 1996. There is little data on the presence of heavy metals in the Park's lakes. Concentration of heavy metals in the water of 19 lakes in the BTNP was examined. The lakes were divided into two groups: subglacial channel lakes of Struga Siedmiu Jezior (the Seven Lakes Stream) and other lakes. Heavy metals (transition metals) belong to d-block of elements. The part of these metals plays an important role in the function of living organisms as metalloproteins (enzymes, hemoproteins, vitamins, etc.). However, heavy metals are also typical; heavy metals are typical anthropogenic pollutants. Water samples were collected at the deepest points of lakes during spring and during summer stagnation. The analysis of metals was performed in an atomic absorption spectrophotometer Varian Spectra A300/400 in electric atomizer (GTA 96) in graphite cuvette. In the waters of the Seven Lakes Stream (Ostrowite, Zielone, Jelen, Belczak, Glowka, Plesno, Skrzynka, Mielnica) the increase in the concentration of the manganese and iron from outflow to inflow of Charzykowskie lake was found, while the concentration of copper (approx. 4 μg dm⁻³) and cadmium ( < 0.5 μg dm⁻³) was similar in all lakes. The concentration of the lead also varied within 2.1-3.6 μg dm⁻³. The concentration of nickel was approx. 3-fold higher in Ostrowite lake than other lakes of Struga. In turn the waters of the lakes Ostrowite, Jelen and Belczak were rich in zinc. The lowest level of heavy metals was observed in Zielone lake. In the second group of lakes, i.e., Krzywce Wielkie and Krzywce Male the heavy metal concentrations were lower than in the waters of Struga but higher than in oligotrophic lakes, i.e., Nierybno, Gluche, Kociol, Gacno Wielkie, Gacno Mae, Dlugie, Zabionek, and Sosnowek. The concentration of cadmium was below 0.5 μg dm⁻³ in all the studied lakes from this group. In the group of oligotrophic lakes the highest concentrations of metals such as manganese, iron, zinc and nickel in Gacno Male and Gacno Wielkie were observed. The high level of manganese in Sosnowek and Gacno Wielkie lakes was found. The lead level was also high in Nierybno lake and nickel in Gacno Wielkie lake. The lower level of heavy metals was in oligotrophic lakes such as Kociol, Dlugie, Zabionek and α-mesotrophic lake, Krzywce Wielkie. Generally, the level of heavy metals in studied lakes situated in Bory Tucholskie National Park was lower than in other lakes of Bory Tucholskie Biosphere Reserve.

Keywords: Bory Tucholskie Biosphere Reserve, Bory Tucholskie National Park, heavy metals, lakes

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Authors: David Abrahams

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In October 2016 South Africa deposited its ‘instrument of withdrawal’ from the Rome Statute of the International Criminal Court, with the Secretary-General of the United Nations. The Rome Statute is the founding document of the treaty-based International Criminal Court (ICC). The ICC has jurisdiction to hear cases where crimes against humanity, war crimes and genocide have been committed, on the basis of individual criminal responsibility. It is therefore not surprising that one of the ICCs mandates is to ensure that the sufferings, due to gross human rights violations towards the civilian population is, in principle, brought to an end by punishing those individuals responsible, thus providing justice to the victims. The ICC is unable to effectively fulfill its mandate and thus depends, in part on the willingness of states to assist the Court in its functions. This requires states to ratify the Statute and to domesticate its provisions, depending on whether it is a monist or dualist state. South Africa ratified the Statute in November 2000, and domesticated the Statute in 2002 by virtue of the Implementation of the Rome Statute of the International Criminal Court Act 27 of 2002. South Africa thus remains under an obligation to cooperate with the ICC until the final date of withdrawal, which is October 2017. An AU Summit was hosted by South Africa during June 2015. Omar Al-Bashir, whom the prosecutor of the ICC has indicted on two separate occasions, was invited to the summit. South Africa made an agreement with the AU that it will honour its obligations in terms of its Diplomatic and Immunities Privileges Act of 2001, by granting immunity to all heads of state, including that of Sudan. This decision by South Africa has raised a plethora of questions regarding the status and hierarchy of international laws versus regional laws versus domestic laws. In particular, this paper explores whether a state’s international law treaty obligations may be suspended in favour of, firstly, regional peace (thus safeguarding the security of the civilian population against further atrocities and other gross violations of human rights), and secondly, head of state immunity. This paper also reflects on the effectiveness of the trias politca in South Africa in relation the manner in which South African courts have confirmed South Africa’s failure in fulfilling its obligations in terms of the Rome Statute. A secondary question which will also be explored, is whether the Rome Statute is currently an effective tool in dealing with gross violations of human rights, particularly in a regional African context, given the desire by a number of African states currently party to the Statute, to engage in a mass exodus from the Statute. Finally, the paper concludes with a proposal that there can be no justice for victims of gross human rights violations unless states are serious in playing an instrumental role in bringing an end to impunity in Africa, and that withdrawing from the ICC without an alternative, effective system in place, will simply perpetuate impunity.

Keywords: African Union, diplomatic immunity, impunity, international criminal court, South Africa

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Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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Authors: Arpita Mondal, Aurobinda Routray, Sreeraj Puravankara, Rajashree Biswas

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The most difficult part of designing a battery management system (BMS) is battery modeling. A good battery model can capture the dynamics which helps in energy management, by accurate model-based state estimation algorithms. So far the most suitable and fruitful model is the equivalent circuit model (ECM). However, in real-time applications, the model parameters are time-varying, changes with current, temperature, state of charge (SOC), and aging of the battery and this make a great impact on the performance of the model. Therefore, to increase the equivalent circuit model performance, the parameter estimation has been carried out in the frequency domain. The battery is a very complex system, which is associated with various chemical reactions and heat generation. Therefore, it’s very difficult to select the optimal model structure. As we know, if the model order is increased, the model accuracy will be improved automatically. However, the higher order model will face the tendency of over-parameterization and unfavorable prediction capability, while the model complexity will increase enormously. In the time domain, it becomes difficult to solve higher order differential equations as the model order increases. This problem can be resolved by frequency domain analysis, where the overall computational problems due to ill-conditioning reduce. In the frequency domain, several dominating frequencies can be found in the input as well as output data. The selective frequency domain estimation has been carried out, first by estimating the frequencies of the input and output by subspace decomposition, then by choosing the specific bands from the most dominating to the least, while carrying out the least-square, recursive least square and Kalman Filter based parameter estimation. In this paper, a second order battery model consisting of three resistors, two capacitors, and one SOC controlled voltage source has been chosen. For model identification and validation hybrid pulse power characterization (HPPC) tests have been carried out on a 2.6 Ah LiFePO₄ battery.

Keywords: equivalent circuit model, frequency estimation, parameter estimation, subspace decomposition

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Authors: Yuzhen Hu, Sirui Wang

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As a training base for intellectual talents, universities have a large number of students. Teaching is a primary activity in universities, and during the teaching process, a large number of people gather both inside and outside the teaching buildings, posing a strong risk of close contact. The class schedule is the fundamental basis for teaching activities in universities and plays a crucial role in the management of teaching order. Different class schedules can lead to varying degrees of indoor gatherings and trajectories of class attendees. In recent years, highly contagious diseases have frequently occurred worldwide, and how to reduce the risk of infection has always been a hot issue related to public safety. "Reducing gatherings" is one of the core measures in epidemic prevention and control, and it can be controlled through scientific scheduling in specific environments. Therefore, the scientific prevention and control goal can be achieved by considering the reduction of the risk of excessive gathering of people during the course schedule arrangement. Firstly, we address the issue of personnel gathering in various pathways on campus, with the goal of minimizing congestion and maximizing teaching effectiveness, establishing a nonlinear mathematical model. Next, we design an improved genetic algorithm, incorporating real-time evacuation operations based on tracking search and multidimensional positive gradient cross-mutation operations, considering the characteristics of outdoor crowd evacuation. Finally, we apply undergraduate course data from a university in Harbin to conduct a case study. It compares and analyzes the effects of algorithm improvement and optimization of gathering situations and explores the impact of path blocking on the degree of gathering of individuals on other pathways.

Keywords: the university timetabling problem, risk prevention, genetic algorithm, risk control

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Authors: G. Judakova, M. Bause

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The ability to model and simulate numerically natural gas flow in pipelines has become of high importance for the design of pipeline systems. The understanding of the formation of hydrate particles and their dynamical behavior is of particular interest, since these processes govern the operation properties of the systems and are responsible for system failures by clogging of the pipelines under certain conditions. Mathematically, natural gas flow can be described by multiphase flow models. Using the two-fluid modeling approach, the gas phase is modeled by the compressible Euler equations and the particle phase is modeled by the pressureless Euler equations. The numerical simulation of compressible multiphase flows is an important research topic. It is well known that for nonlinear fluxes, even for smooth initial data, discontinuities in the solution are likely to occur in finite time. They are called shock waves or contact discontinuities. For hyperbolic and singularly perturbed parabolic equations the standard application of the Galerkin finite element method (FEM) leads to spurious oscillations (e.g. Gibb's phenomenon). In our approach, we use stabilized FEM, the streamline upwind Petrov-Galerkin (SUPG) method, where artificial diffusion acting only in the direction of the streamlines and using a special treatment of the boundary conditions in inviscid convective terms, is added. Numerical experiments show that the numerical solution obtained and stabilized by SUPG captures discontinuities or steep gradients of the exact solution in layers. However, within this layer the approximate solution may still exhibit overshoots or undershoots. To suitably reduce these artifacts we add a discontinuity capturing or shock capturing term. The performance properties of our numerical scheme are illustrated for two-phase flow problem.

Keywords: two-phase flow, gas-particle mixture, inviscid two-fluid model, euler equation, finite element method, streamline upwind petrov-galerkin, shock capturing

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Authors: Sonia Barbouchi, Meriem Samcha

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Scale deposition during water injection into aquifer of oil reservoirs is a serious problem experienced in the oil production industry. One of the primary causes of scale formation and injection well plugging is mixing two waters which are incompatible. Considered individually, the waters may be quite stable at system conditions and present no scale problems. However, once they are mixed, reactions between ions dissolved in the individual waters may form insoluble products. The purpose of this study is to identify the causes of well plugging in a southern Tunisian oilfield, where fresh water has been injected into the producing wells to counteract the salinity of the formation waters and inhibit the deposition of halite. X-ray diffraction (XRD) mineralogical analysis has been carried out on scale samples collected from the blocked well. Two samples collected from both formation water and injected water were analysed using inductively coupled plasma atomic emission spectroscopy, ion chromatography and other standard laboratory techniques. The results of complete waters analysis were the typical input parameters, to determine scaling tendency. Saturation indices values related to CaCO3, CaSO4, BaSO4 and SrSO4 scales were calculated for the water mixtures at different share, under various conditions of temperature, using a computerized scale prediction model. The compatibility study results showed that mixing the two waters tends to increase the probability of barite deposition. XRD analysis confirmed the compatibility study results, since it proved that the analysed deposits consisted predominantly of barite with minor galena. At the studied temperatures conditions, the tendency for barite scale is significantly increasing with the increase of fresh water share in the mixture. The future scale inhibition and removal strategies to be implemented in the concerned oilfield are being derived in a large part from the results of the present study.

Keywords: compatibility study, produced water, scaling, water injection

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Authors: Yuan-Jye Tseng, Jia-Shu Li

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To design a product with the given product requirement and design objective, there can be alternative ways to propose the detailed design specifications of the product. In the design modeling stage, alternative design cases with detailed specifications can be modeled to fulfill the product requirement and design objective. Therefore, in the design evaluation stage, it is required to perform an evaluation of the alternative design cases for deciding the final design. The purpose of this research is to develop a product evaluation model for evaluating the alternative design cases by integrated evaluating the criteria of functional design, Kansei design, and design for supply chain. The criteria in the functional design group include primary function, expansion function, improved function, and new function. The criteria in the Kansei group include geometric shape, dimension, surface finish, and layout. The criteria in the design for supply chain group include material, manufacturing process, assembly, and supply chain operation. From the point of view of value and cost, the criteria in the functional design group and Kansei design group represent the design value of the product. The criteria in the design for supply chain group represent the supply chain and manufacturing cost of the product. It is required to evaluate the design value and the supply chain cost to determine the final design. For the purpose of evaluating the criteria in the three criteria groups, a fuzzy analytic network process (FANP) method is presented to evaluate a weighted index by calculating the total relational values among the three groups. A method using the technique for order preference by similarity to ideal solution (TOPSIS) is used to compare and rank the design alternative cases according to the weighted index using the total relational values of the criteria. The final decision of a design case can be determined by using the ordered ranking. For example, the design case with the top ranking can be selected as the final design case. Based on the criteria in the evaluation, the design objective can be achieved with a combined and weighted effect of the design value and manufacturing cost. An example product is demonstrated and illustrated in the presentation. It shows that the design evaluation model is useful for integrated evaluation of functional design, Kansei design, and design for supply chain to determine the best design case and achieve the design objective.

Keywords: design for supply chain, design evaluation, functional design, Kansei design, fuzzy analytic network process, technique for order preference by similarity to ideal solution

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Authors: Hamed Delrobai Ghoochan Atigh

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Androgenic alopecia (AGA) is a common form of hair loss, impacting approximately 50% of females, which leads to reduced self-esteem and quality of life. It causes progressive follicular miniaturization in genetically predisposed individuals. Mesotherapy -- a minimally invasive procedure, topical 2% minoxidil, and oral finasteride have emerged as popular treatment options in the realm of cosmetics. However, the efficacy of mesotherapy compared to other options remains unclear. This study aims to assess the effectiveness of mesotherapy when it is added to topical 2% minoxidil treatment on female androgenic alopecia. Mesotherapy, also known as intradermotherapy, is a technique that entails administering multiple intradermal injections of a carefully composed mixture of compounds in low doses, applied at various points in close proximity to or directly over the affected areas. This study involves a randomized controlled trial with 100 female participants diagnosed with androgenic alopecia. The subjects were randomly assigned to two groups: Group A used topical 2% minoxidil twice daily and took Finastride oral tablet. For Group B, 10 mesotherapy sessions were added to the prior treatment. The injections were administered every week in the first month of treatment, every two weeks in the second month, and after that the injections were applied monthly for four consecutive months. The response assessment was made at baseline, the 4th session, and finally after 6 months when the treatment was complete. Clinical photographs, 7-point Likert scale patient self-evaluation, and 7-point Likert scale assessment tool were used to measure the effectiveness of the treatment. During this evaluation, a significant and visible improvement in hair density and thickness was observed. The study demonstrated a significant increase in treatment efficacy in Group B compared to Group A post-treatment, with no adverse effects. Based on the findings, it appears that mesotherapy offers a significant improvement in female AGA over minoxidil. Hair loss was stopped in Group B after one month and improvement in density and thickness of hair was observed after the third month. The findings from this study provide valuable insights into the efficacy of mesotherapy in treating female androgenic alopecia. Our evaluation offers a detailed assessment of hair growth parameters, enabling a better understanding of the treatments' effectiveness. The potential of this promising technique is significantly enhanced when carried out in a medical facility, guided by appropriate indications and skillful execution. An interesting observation in our study is that in areas where the hair had turned grey, the newly regrown hair does not retain its original grey color; instead, it becomes darker. The results contribute to evidence-based decision-making in dermatological practice and offer different insights into the treatment of female pattern hair loss.

Keywords: androgenic alopecia, female hair loss, mesotherapy, topical 2% minoxidil

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Authors: Hanan Eltayeb, Reem Al Refaie

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To be able to connect and relate to shows spoken in a foreign language, advanced learners must understand not only linguistics inferences but also cultural, metacognitive, and pragmatic connotations in colloquial Egyptian TV series. These connotations are needed to both understand the different facets of the dramas put before them, and they’re also consistently grown and formulated through watching these shows. The inferences have become a staple in the Egyptian colloquial culture over the years, making their way into day-to-day conversations as Egyptians use them to speak, relate, joke, and connect with each other, without having known one another from previous times. As for advanced learners, they need to understand these inferences not only to watch these shows, but also to be able to converse with Egyptians on a level that surpasses the formal, or standard. When faced with some of the somewhat recent shows on the Egyptian screens, learners faced challenges in understanding pragmatics, cultural, and religious background of the target language and consequently not able to interact effectively with a native speaker in real-life situations. This study aims to enhance the linguistic and cultural proficiency of learners through studying two genres of TV Colloquial Egyptian series. Study samples derived from two recent comedian and social Egyptian series ('The Seventh Neighbor' سابع جار, and 'Nelly and Sherihan' نيللي و شريهان). When learners watch such series, they are usually faced with a problem understanding inferences that have to do with social, religious, and political events that are addressed in the series. Using discourse analysis of the sematic, semantic, pragmatic, cultural, and linguistic characteristics of the target language, some major deductions were highlighted and repeated, showing a pattern in both. The research paper concludes that there are many sets of lingual and para-lingual phrases, idioms, and proverbs to be acquired and used effectively by teaching these series. The strategies adopted in the study can be applied to different types of media, like movies, TV shows, and even cartoons, to enhance student proficiency.

Keywords: Egyptian series, culture, linguistic competence, pragmatics, semantics, social

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Authors: Osama Ahmed Ibrahim Masoud, Mohamed Ibrahim Mohamed Abdelhadi, Ahmed Mohamed Seddik Hassan

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The problem of study focuses on thermal comfort realization in a residential building during hot and dry climate periods consumes a major electrical energy for air conditioning operation. Thermal comfort realization in a residential building during such climate becomes more difficult regarding the phenomena of climate change, and the use of building and construction materials which have the feature of heat conduction as (bricks-reinforced concrete) and the global energy crises. For that, this study aims to how to realize internal thermal comfort through how to make the best use of building services (temporarily used service spaces) for reducing the electrical energy transfer and saving self-shading. In addition, the possibility of reduction traditional energy (fossil fuel) consumed in cooling through the use of building services for reducing the internal thermal comfort and the relationship between them. This study is based on measuring the consumed electrical energy rate in cooling (by using Design-Builder program) for a residential building (the place of study is: Egypt- Suez Canal- Suez City), this design model has lots of alternatives designs for the place of building services (center of building- the eastern front- southeastern front- the southern front- the south-west front, the western front). The building services are placed on the fronts with different rates for determining the best rate on fronts which realizes thermal comfort with the lowest of energy consumption used in cooling. Findings of the study indicate to that the best position for building services is on the west front then the south-west front, and the more the building services increase, the more energy consumption used in cooling of residential building decreases. Recommendations indicate to the need to study the building services positions in the new projects progress to select the best alternatives to realize ‘Energy conservation’ used in cooling or heating into the buildings in general, residential buildings particularly.

Keywords: residential buildings, energy conservation, thermal comfort, building services, temporary used service spaces, DesignBuilder

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Authors: Stefan Fuchs

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Against the backdrop of the proliferation of shopping malls in Japan during the last two decades, this paper presents the results of an ethnography conducted at a recently built suburban shopping mall in Western Tokyo. Through the analysis of the lived experiences of local residents, mall customers and the mall management this paper evaluates the benefits and disadvantages of the Business Improvement District (BID) model, which was implemented as urban redevelopment strategy in the area surrounding the shopping mall. The results of this research project show that while the BID model has in some respects contributed to the economic prosperity and to the perceived convenience of the area, it has led to gentrification and the redevelopment shows some deficiencies with regard to the inclusion of the elderly population as well as to the democratization of the decision-making process within the area. In Japan, shopping malls have been steadily growing both in size and number since a series of deregulation policies was introduced in the year 2000 in an attempt to push the domestic economy and to rejuvenate urban landscapes. Shopping malls have thereby become defining spaces of the built environment and are arguably important places of social interaction. Notwithstanding the vital role they play as factors of urban transformation, they have been somewhat overlooked in the research on Japan; especially with respect to their meaning for people’s everyday lives. By examining the ways, people make use of space in a shopping mall the research project presented in this paper addresses this gap in the research. Moreover, the research site of this research project is one of the few BIDs of Japan and the results presented in this paper can give indication on the scope of the future applicability of this urban redevelopment model. The data presented in this research was collected during a nine-months ethnographic fieldwork in and around the shopping mall. This ethnography includes semi-structured interviews with ten key informants as well as direct and participant observations examining the lived experiences and perceptions of people living, shopping or working at the shopping mall. The analysis of the collected data focused on recurring themes aiming at ultimately capturing different perspectives on the same aspects. In this manner, the research project documents the social agency of different groups within one communal network. The analysis of the perceptions towards the urban redevelopment around the shopping mall has shown that mainly the mall customers and large businesses benefit from the BID redevelopment model. While local residents benefit to some extent from their neighbourhood becoming more convenient for shopping they perceive themselves as being disadvantaged by changing demographics due to rising living expenses, the general noise level and the prioritisation of a certain customer segment or age group at the shopping mall. Although the shopping mall examined in this research project is just an example, the findings suggest that in future urban redevelopment politics have to provide incentives for landowners and developing companies to think of other ways of transforming underdeveloped areas.

Keywords: business improvement district, ethnography, shopping mall, urban redevelopment

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Authors: Tomohiko Utsuki, Kyoka Sato

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In emergency medicine, it is recognized that brain resuscitation is very important for the reduction of mortality rate and neurological sequelae. Especially, the control of brain temperature (BT), intracranial pressure (ICP), and cerebral blood flow (CBF) are most required for stabilizing brain’s physiological state in the treatment for such as brain injury, stroke, and encephalopathy. However, the manual control of BT, ICP, and CBF frequently requires the decision and operation of medical staff, relevant to medication and the setting of therapeutic apparatus. Thus, the integration and the automation of the control of those is very effective for not only improving therapeutic effect but also reducing staff burden and medical cost. For realizing such integration and automation, a mathematical model of brain physiological state is necessary as the controlled object in simulations, because the performance test of a prototype of the control system using patients is not ethically allowed. A model of cerebral blood circulation has already been constructed, which is the most basic part of brain physiological state. Also, a migration model of extracellular fluid in brain has been constructed, however the condition that the total volume of intracranial cavity is almost changeless due to the hardness of cranial bone has not been considered in that model. Therefore, in this research, the dynamic migration model of extracellular fluid in brain was constructed on the consideration of the changelessness of intracranial cavity’s total volume. This model is connectable to the cerebral blood circulation model. The constructed model consists of fourteen compartments, twelve of which corresponds to perfused area of bilateral anterior, middle and posterior cerebral arteries, the others corresponds to cerebral ventricles and subarachnoid space. This model enable to calculate the migration of tissue fluid from capillaries to gray matter and white matter, the flow of tissue fluid between compartments, the production and absorption of cerebrospinal fluid at choroid plexus and arachnoid granulation, and the production of metabolic water. Further, the volume, the colloid concentration, and the tissue pressure of/in each compartment are also calculable by solving 40-dimensional non-linear simultaneous differential equations. In this research, the obtained model was analyzed for its validation under the four condition of a normal adult, an adult with higher cerebral capillary pressure, an adult with lower cerebral capillary pressure, and an adult with lower colloid concentration in cerebral capillary. In the result, calculated fluid flow, tissue volume, colloid concentration, and tissue pressure were all converged to suitable value for the set condition within 60 minutes at a maximum. Also, because these results were not conflict with prior knowledge, it is certain that the model can enough represent physiological state of brain under such limited conditions at least. One of next challenges is to integrate this model and the already constructed cerebral blood circulation model. This modification enable to simulate CBF and ICP more precisely due to calculating the effect of blood pressure change to extracellular fluid migration and that of ICP change to CBF.

Keywords: dynamic model, cerebral extracellular migration, brain resuscitation, automatic control

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Authors: Fuyuan Ma, Yuhan Wang, Junhe Zhang, Ying Wang

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Identifying the sources of information dissemination is a pivotal task in the study of collective behaviors in networks, enabling us to discern and intercept the critical pathways through which information propagates from its origins. This allows for the control of the information’s dissemination impact in its early stages. Numerous methods for source detection rely on pre-existing, underlying propagation models as prior knowledge. Current models that eschew prior knowledge attempt to harness label propagation algorithms to model the statistical characteristics of propagation states or employ Graph Neural Networks (GNNs) for deep reverse modeling of the diffusion process. These approaches are either deficient in modeling the propagation patterns of information or are constrained by the over-smoothing problem inherent in GNNs, which limits the stacking of sufficient model depth to excavate global propagation patterns. Consequently, we introduce the ODESI model. Initially, the model employs a label propagation algorithm to delineate the distribution density of infected states within a graph structure and extends the representation of infected states from integers to state vectors, which serve as the initial states of nodes. Subsequently, the model constructs a deep architecture based on GNNs-coupled Ordinary Differential Equations (ODEs) to model the global propagation patterns of continuous propagation processes. Addressing the challenges associated with solving ODEs on graphs, we approximate the analytical solutions to reduce computational costs. Finally, we conduct simulation experiments on two real-world social network datasets, and the results affirm the efficacy of our proposed ODESI model in source identification tasks.

Keywords: source identification, ordinary differential equations, label propagation, complex networks

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Authors: Marius Gavrilescu, Sabina-Adriana Floria, Florin Leon, Silvia Curteanu, Costel Anton

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Natural sciences provide a wide range of experimental data whose related problems require study and modeling beyond the capabilities of conventional methodologies. Such problems have solution spaces whose complexity and high dimensionality require correspondingly complex regression methods for proper characterization. In this context, we propose an optimization method which consists in a hybrid dual optimizer setup: a global optimizer based on a modified variant of the popular Imperialist Competitive Algorithm (ICA), and a local optimizer based on a gradient descent approach. The ICA is modified such that intermediate solution populations are more quickly and efficiently pruned of low-fitness individuals by appropriately altering the assimilation, revolution and competition phases, which, combined with an initialization strategy based on low-discrepancy sampling, allows for a more effective exploration of the corresponding solution space. Subsequently, gradient-based optimization is used locally to seek the optimal solution in the neighborhoods of the solutions found through the modified ICA. We use this combined approach to find the optimal configuration and weights of a fully-connected neural network, resulting in regression models used to characterize the process of obtained bricks using silicon-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. Thus, the purpose of our approach is to determine by simulation the working conditions, including the manufacturing mix recipe with the addition of different materials, to minimize the emissions represented by CO and CH4. Our approach determines regression models which perform significantly better than those found using the traditional ICA for the aforementioned problem, resulting in better convergence and a substantially lower error.

Keywords: optimization, biologically inspired algorithm, regression models, bricks, emissions

Procedia PDF Downloads 78

Authors: Yimei Huang, Harvey Lui, Jianhua Zhao, Zhenguo Wu, Haishan Zeng

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Conventional laser treatment of skin diseases and cosmetic surgery is based on the principle of one-photon absorption selective photothermolysis which relies strongly on the difference in the light absorption between the therapeutic target and its surrounding tissue. However, when the difference in one-photon absorption is not sufficient, collateral damage would occur due to indiscriminate and nonspecific tissue heating. To overcome this problem, we developed a spatially selective photothermolysis method based on multiphoton absorption in which the heat generation is restricted to the focal point of a tightly focused near-infrared femtosecond laser beam aligned with the target of interest. A multimodal optical microscope with co-registered reflectance confocal imaging (RCM), two-photon fluorescence imaging (TPF), and second harmonic generation imaging (SHG) capabilities was used to perform and monitor the spatially selective photothermolysis. Skin samples excised from the shaved backs of euthanized NODSCID mice were used in this study. Treatments were performed by focusing and scaning the laser beam in the dermis with a 50µm×50µm target area. Treatment power levels of 200 mW to 400 mW and modulated pulse trains of different duration and period were experimented. Different treatment parameters achieved different degrees of spatial confinement of tissue alterations as visualized by 3-D RCM/TPF/SHG imaging. At 200 mW power level, 0.1 s pulse train duration, 4.1 s pulse train period, the tissue damage was found to be restricted precisely to the 50µm×50µm×10µm volume, where the laser focus spot had scanned through. The overlying epidermis/dermis tissue and the underneath dermis tissue were intact although there was light passing through these regions.

Keywords: multiphoton absorption photothermolysis, reflectance confocal microscopy, second harmonic generation microscopy, spatially selective photothermolysis, two-photon fluorescence microscopy

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Authors: Jean Paul Hategekimana, Josiane Irakoze, Eugene Niyonzima, Annick Ndekezi

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Cassava (Manihot esculenta Crantz) is a root crop comprising an anti-nutritive factor known as cyanide. The compound can be removed by numerous processing methods such as boiling, fermentation, blanching, and sun drying to avoid the possibility of cyanide poisoning. Inappropriate processing mean can lead to disease and death. Cassava-based dishes are consumed in different ways, where cassava is cultivated according to their culture and preference. However, they have been shown to be unsafe based on high cyanide levels. The current study targeted to resolve the problem of high cyanide in cassava consumed in Rwanda. This study was conducted to determine the effect of slicing, blanching, and soaking time to reduce the fermentation duration of cassava for hydrogen cyanide (HCN) in mg/g removal. Cassava was sliced into three different portions (1cm, 2cm, and 5cm). The first portions were naturally fermented for seven days, where each portion was removed every 24 hours from soaking tanks and then oven dried at a temperature of 60°C and then milled to obtain naturally fermented cassava flours. Other portions of 1cm, 2cm, and 5cm were blanched for 2, 5, 10 min, respectively, and each similarly dried at 60°C and milled to produce blanched cassava flour. Other blanched portions were used to follow the previous fermentation steps. The last portions, which formed the control, were simply chopped. Cyanide content and starch content in mg/100g were investigated. According to the conducted analysis on different cassava treatments for detoxification, found that usual fermentation can be used, but for sliced portions aimed to size reduction for the easy hydrogen cyanide diffuse out and it takes four days to complete fermentation, which has reduced at 94.44% with significantly different (p<0.05)of total hydrogen cyanide contained in cassava to safe level of consumption, and what is recommended as more effective is to apply blanching combined with fermentation due to the fact that, it takes three days to complete hydrogen cyanide removal at 95.56% on significantly different (p<0.05) of reduction to the safe level of consumption.

Keywords: cassava, cyanide, blanching, drying, fermentation

Procedia PDF Downloads 61

Authors: Eashwar V. Somasundaram, Raoul R. Wadhwa, Jacob G. Scott

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The use of radiomics in measuring geometric properties of tumor images such as size, surface area, and volume has been invaluable in assessing cancer diagnosis, treatment, and prognosis. In addition to analyzing geometric properties, radiomics would benefit from measuring topological properties using persistent homology. Intuitively, features uncovered by persistent homology may correlate to tumor structural features. One example is necrotic cavities (corresponding to 2D topological features), which are markers of very aggressive tumors. We develop a data pipeline in R that clusters tumors images based on persistent homology is used to identify meaningful clinical distinctions between tumors and possibly new relationships not captured by established clinical categorizations. A preliminary analysis was performed on 16 Magnetic Resonance Imaging (MRI) breast tissue segments downloaded from the 'Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis' (I-SPY TRIAL or ISPY1) collection in The Cancer Imaging Archive. Each segment represents a patient’s breast tumor prior to treatment. The ISPY1 dataset also provided the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status data. A persistent homology matrix up to 2-dimensional features was calculated for each of the MRI segmentation. Wasserstein distances were then calculated between all pairwise tumor image persistent homology matrices to create a distance matrix for each feature dimension. Since Wasserstein distances were calculated for 0, 1, and 2-dimensional features, three hierarchal clusters were constructed. The adjusted Rand Index was used to see how well the clusters corresponded to the ER/PR/HER2 status of the tumors. Triple-negative cancers (negative status for all three receptors) significantly clustered together in the 2-dimensional features dendrogram (Adjusted Rand Index of .35, p = .031). It is known that having a triple-negative breast tumor is associated with aggressive tumor growth and poor prognosis when compared to non-triple negative breast tumors. The aggressive tumor growth associated with triple-negative tumors may have a unique structure in an MRI segmentation, which persistent homology is able to identify. This preliminary analysis shows promising results in the use of persistent homology on tumor imaging to assess the severity of breast tumors. The next step is to apply this pipeline to other tumor segment images from The Cancer Imaging Archive at different sites such as the lung, kidney, and brain. In addition, whether other clinical parameters, such as overall survival, tumor stage, and tumor genotype data are captured well in persistent homology clusters will be assessed. If analyzing tumor MRI segments using persistent homology consistently identifies clinical relationships, this could enable clinicians to use persistent homology data as a noninvasive way to inform clinical decision making in oncology.

Keywords: cancer biology, oncology, persistent homology, radiomics, topological data analysis, tumor imaging

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Authors: Se-Mi Lim, Won-Jae Jung, Jin-Sup Kim, Jun-Seok Park, Hyung-Il Chae

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This paper presents a current-mode vertical hall device (VHD) structure using metal layers in a CMOS process. The proposed metal layer based vertical hall device (MLVHD) utilizes vertical connection among metal layers (from M1 to the top metal) to facilitate hall effect. The vertical metal structure unit flows a bias current Ibias from top to bottom, and an external magnetic field changes the current distribution by Lorentz force. The asymmetric current distribution can be detected by two differential-mode current outputs on each side at the bottom (M1), and each output sinks Ibias/2 ± Ihall. A single vertical metal structure generates only a small amount of hall effect of Ihall due to the short length from M1 to the top metal as well as the low conductivity of the metal, and a series connection between thousands of vertical structure units can solve the problem by providing NxIhall. The series connection between two units is another vertical metal structure flowing current in the opposite direction, and generates negative hall effect. To mitigate the negative hall effect from the series connection, the differential current outputs at the bottom (M1) from one unit merges on the top metal level of the other unit. The proposed MLVHD is simulated in a 3-dimensional model simulator in COMSOL Multiphysics, with 0.35 μm CMOS process parameters. The simulated MLVHD unit size is (W) 10 μm × (L) 6 μm × (D) 10 μm. In this paper, we use an MLVHD with 10 units; the overall hall device size is (W) 10 μm × (L)78 μm × (D) 10 μm. The COMSOL simulation result is as following: the maximum hall current is approximately 2 μA with a 12 μA bias current and 100mT magnetic field; This work was supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIP) (No.R7117-16-0165, Development of Hall Effect Semiconductor for Smart Car and Device).

Keywords: CMOS, vertical hall device, current mode, COMSOL

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Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

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Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

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Authors: Debalke Dale, Bezabh Geneta, Yohannes Amene, Yordanos Bergene, Mohammed Yimam

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Background: A drug therapy problem (DTP) is an event or circumstance that involves drug therapies that actually or potentially interfere with the desired outcome and requires professional judgment to resolve. Heart failure is an emerging worldwide threat whose prevalence and health loss burden constantly increase, especially in the young and in low-to-middle-income countries. There is a lack of population-based incidence and prevalence of heart failure (HF) studies in sub-Saharan African countries, including Ethiopia. Objective: The aim of this study was designed to assess drug therapy problems and associated factors among patients with HF in the medical ward of Arba Minch General Hospital(AGH), Ethiopia, from June 5 to August 20, 2022. Methods: A retrospective cross-sectional study was conducted among 180 patients with HF who were admitted to the medical ward of AGH. Data were collected from patients' cards by using questionnaires. The data were categorized and analyzed by using SPSS version 25.0 software, and data were presented in tables and words based on the nature of the data. Result: Out of the total, 85 (57.6%) were females, and 113 (75.3%) patients were aged over fifty years. Of the 150 study participants, 86 (57.3%) patients had at least one DTP identified, and a total of 116 DTPs were identified, which is 0.77 DTPs per patient. The most common types of DTP were unnecessary drug therapy (32%), followed by the need for additional drug therapy (36%), and dose too low (15%). Patients who used polypharmacy were 5.86 (AOR) times more likely to develop DTPs than those who did not (95% CI = 1.625–16.536, P = 0.005), and patients with more co-morbid conditions developed 3.68 (AOR) times more DTPs than those who had fewer co-morbidities (95% CI = 1.28–10.5, P = 0.015). Conclusion: The results of this study indicated that drug therapy problems were common among medical ward patients with heart failure. These problems are adversely affecting the treatment outcomes of patients, so it requires the special attention of healthcare professionals to optimize them.

Keywords: heart failure, drug therapy problems, Arba Minch general hospital, Ethiopia

Procedia PDF Downloads 100