Search results for: co-citation networks; keyword co-occurrence network

Authors: Pratima Pokharel

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When sewer overflow due to rainfall in urban areas, this leads to public health risks when an individual is exposed to that contaminated floodwater. Nevertheless, it is still unclear the extent to which the infections pose a risk to public health. This study analyzed reported diarrheal cases by month and age in Bangkok, Thailand. The results showed that the cases are reported higher in the wet season than in the dry season. It was also found that in Bangkok, the probability of infection with diarrheal diseases in the wet season is higher for the age group between 15 to 44. However, the probability of infection is highest for kids under 5 years, but they are not influenced by wet weather. Further, this study introduced a vulnerability that leads to health risks from urban flooding. This study has found some vulnerability variables that contribute to health risks from flooding. Thus, for vulnerability analysis, the study has chosen two variables, economic status, and age, that contribute to health risk. Assuming that the people's economic status depends on the types of houses they are living in, the study shows the spatial distribution of economic status in the vulnerability maps. The vulnerability map result shows that people living in Sukhumvit have low vulnerability to health risks with respect to the types of houses they are living in. In addition, from age the probability of infection of diarrhea was analyzed. Moreover, a field survey was carried out to validate the vulnerability of people. It showed that health vulnerability depends on economic status, income level, and education. The result depicts that people with low income and poor living conditions are more vulnerable to health risks. Further, the study also carried out 1D Hydrodynamic Advection-Dispersion modelling with 2-year rainfall events to simulate the dispersion of fecal coliform concentration in the drainage network as well as 1D/2D Hydrodynamic model to simulate the overland flow. The 1D result represents higher concentrations for dry weather flows and a large dilution of concentration on the commencement of a rainfall event, resulting in a drop of the concentration due to runoff generated after rainfall, whereas the model produced flood depth, flood duration, and fecal coliform concentration maps, which were transferred to ArcGIS to produce hazard and risk maps. In addition, the study also simulates the 5-year and 10-year rainfall simulations to show the variation in health hazards and risks. It was found that even though the hazard coverage is very high with a 10-year rainfall events among three rainfall events, the risk was observed to be the same with a 5-year and 10-year rainfall events.

Keywords: urban flooding, risk, hazard, vulnerability, health risk, framework

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Authors: Feng Yue, Fei Dai

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With the rapid development of urbanization process in China, its environmental protection pressure is severely tested. So, analyzing and optimizing the landscape pattern is an important measure to ease the pressure on the ecological environment. This paper takes Wuhan Urban Development Zone as the research object, and studies its landscape pattern evolution and quantitative optimization strategy. First, remote sensing image data from 1990 to 2015 were interpreted by using Erdas software. Next, the landscape pattern index of landscape level, class level, and patch level was studied based on Fragstats. Then five indicators of ecological environment based on National Environmental Protection Standard of China were selected to evaluate the impact of landscape pattern evolution on the ecological environment. Besides, the cost distance analysis of ArcGIS was applied to simulate wildlife migration thus indirectly measuring the improvement of ecological environment quality. The result shows that the area of land for construction increased 491%. But the bare land, sparse grassland, forest, farmland, water decreased 82%, 47%, 36%, 25% and 11% respectively. They were mainly converted into construction land. On landscape level, the change of landscape index all showed a downward trend. Number of patches (NP), Landscape shape index (LSI), Connection index (CONNECT), Shannon's diversity index (SHDI), Aggregation index (AI) separately decreased by 2778, 25.7, 0.042, 0.6, 29.2%, all of which indicated that the NP, the degree of aggregation and the landscape connectivity declined. On class level, the construction land and forest, CPLAND, TCA, AI and LSI ascended, but the Distribution Statistics Core Area (CORE_AM) decreased. As for farmland, water, sparse grassland, bare land, CPLAND, TCA and DIVISION, the Patch Density (PD) and LSI descended, yet the patch fragmentation and CORE_AM increased. On patch level, patch area, Patch perimeter, Shape index of water, farmland and bare land continued to decline. The three indexes of forest patches increased overall, sparse grassland decreased as a whole, and construction land increased. It is obvious that the urbanization greatly influenced the landscape evolution. Ecological diversity and landscape heterogeneity of ecological patches clearly dropped. The Habitat Quality Index continuously declined by 14%. Therefore, optimization strategy based on greenway network planning is raised for discussion. This paper contributes to the study of landscape pattern evolution in planning and design and to the research on spatial layout of urbanization.

Keywords: landscape pattern, optimization strategy, ArcGIS, Erdas, landscape metrics, landscape architecture

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Authors: Nada Poropat Jeletic, Gordana Hrzica

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Bilingual conversational corpora represent a meaningful and the most comprehensive data source for investigating the genuine contact phenomena in non-monitored bi-lingual speech productions. They can be particularly useful for bilingual research since some features of bilingual interaction can hardly be accessed with more traditional methodologies (e.g., elicitation tasks). The method of language sampling provides the resources for describing language interaction in a bilingual community and/or in bilingual situations (e.g. code-switching, amount of languages used, number of languages used, etc.). To capture these phenomena in genuine communication situations, such sampling should be as close as possible to spontaneous communication. Bilingual spoken corpus design is methodologically demanding. Therefore this paper aims at describing the methodological challenges that apply to the corpus design of the conversational corpus design of the Istrian Istrovenetian-Croatian Bilingual Corpus. Croatian is the first official language of the Croatian-Italian officially bilingual Istria County, while Istrovenetian is a diatopic subvariety of Venetian, a longlasting lingua franca in the Istrian peninsula, the mother tongue of the members of the Italian National Community in Istria and the primary code of informal everyday communication among the Istrian Italophone population. Within the CLARIN infrastructure, TalkBank is being used, as it provides relevant procedures for designing and analyzing bilingual corpora. Furthermore, it allows public availability allows for easy replication of studies and cumulative progress as a research community builds up around the corpus, while the tools developed within the field of corpus linguistics enable easy retrieval and analysis of information. The method of language sampling employed is kept at the level of spontaneous communication, in order to maximise the naturalness of the collected conversational data. All speakers have provided written informed consent in which they agree to be recorded at a random point within the period of one month after signing the consent. Participants are administered a background questionnaire providing information about the socioeconomic status and the exposure and language usage in the participants social networks. Recording data are being transcribed, phonologically adapted within a standard-sized orthographic form, coded and segmented (speech streams are being segmented into communication units based on syntactic criteria) and are being marked following the CHAT transcription system and its associated CLAN suite of programmes within the TalkBank toolkit. The corpus consists of transcribed sound recordings of 36 bilingual speakers, while the target is to publish the whole corpus by the end of 2020, by sampling spontaneous conversations among approximately 100 speakers from all the bilingual areas of Istria for ensuring representativeness (the participants are being recruited across three generations of native bilingual speakers in all the bilingual areas of the peninsula). Conversational corpora are still rare in TalkBank, so the Corpus will contribute to BilingBank as a highly relevant and scientifically reliable resource for an internationally established and active research community. The impact of the research of communities with societal bilingualism will contribute to the growing body of research on bilingualism and multilingualism, especially regarding topics of language dominance, language attrition and loss, interference and code-switching etc.

Keywords: conversational corpora, bilingual corpora, code-switching, language sampling, corpus design methodology

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Authors: Nwamaka Patricia Ibeme, Musa Zakari

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E-learning is made more effective because; it is enable student to students to easily interact, share, and collaborate across time and space with the help of e-governance platform. Zoom and the Microsoft classroom team can invite students from all around the world to join a conversation on a certain subject simultaneously. E-governance may be able to work on problem solving skills, as well as brainstorming and developing ideas. As a result of the shared experiences and knowledge, students are able to express themselves and reflect on their own learning." For students, e-governance facilities provide greater opportunity for students to build critical (higher order) thinking abilities through constructive learning methods. Students' critical thinking abilities may improve with more time spent in an online classroom. Students' inventiveness can be enhanced through the use of computer-based instruction. Discover multimedia tools and produce products in the styles that are easily available through games, Compact Disks, and television. The use of e-learning has increased both teaching and learning quality by combining student autonomy, capacity, and creativity over time in developed countries." Teachers are catalysts for the integration of technology through Information and Communication Technology, and e-learning supports teaching by simplifying access to course content." Creating an Information and Communication Technology class will be much easier if educational institutions provide teachers with the assistance, equipment, and resources they need. The study adopted survey research design. The populations of the study are Students and staff. The study adopted a simple random sampling technique to select a representative population. Both primary and secondary method of data collection was used to obtain the data. A chi-square statistical technique was used to analyze. Finding from the study revealed that e-learning has increase accesses to universities educational by public servants in Nigeria. Public servants in Nigeria have utilized e-learning and Online Distance Learning (ODL) programme to into various degree programmes. Finding also shows that E-learning plays an important role in teaching because it is oriented toward the use of information and communication technologies that have become a part of the everyday life and day-to-day business. E-learning contributes to traditional teaching methods and provides many advantages to society and citizens. The study recommends that the e-learning tools and internet facilities should be upgrade to foster any network challenges in the online facilitation and lecture delivery system.

Keywords: E-governance, E-learning, online distance learning, university education public servants, Nigeria

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Authors: Priyanka Bhowmik, Subrata Majumdar, Debprasad Chattopadhyay

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Background: Cervical cancer is the third major cause of cancer in women and the second most frequent cause of cancer related deaths causing 300,000 deaths annually worldwide. Evasion of immune response by Human Papilloma Virus (HPV), the key contributing factor behind cancer and pre-cancerous lesions of the uterine cervix, makes immunotherapy a necessity to treat this disease. Objective: A Heat killed fraction of Mycobacterium indicus pranii (MIP), a non-pathogenic Mycobacterium has been shown to exhibit cytotoxic effects on different cancer cells, including human cervical carcinoma cell line HeLa. However, the underlying mechanisms remain unknown. The aim of this study is to decipher the mechanism of MIP induced HeLa cell death. Methods: The cytotoxicity of Mycobacterium indicus pranii against HeLa cells was evaluated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Apoptosis was detected by annexin V and Propidium iodide (PI) staining. The assessment of reactive oxygen species (ROS) generation and cell cycle analysis were measured by flow cytometry. The expression of apoptosis associated genes was analyzed by real time PCR. Result: MIP could inhibit the proliferation of HeLa cell in a time and dose dependent manner but caused minor damage to normal cells. The induction of apoptosis was confirmed by the cell surface presentation of phosphatidyl serine, DNA fragmentation, and mitochondrial damage. MIP caused very early (as early as 30 minutes) transcriptional activation of p53, followed by a higher activation (32 fold) at 24 hours suggesting prime importance of p53 in MIP-induced apoptosis in HeLa cell. The up regulation of p53 dependent pro-apoptotic genes Bax, Bak, PUMA, and Noxa followed a lag phase that was required for the transcriptional p53 program. MIP also caused the transcriptional up regulation of Toll like receptor 2 and 4 after 30 minutes of MIP treatment suggesting recognition of MIP by toll like receptors. Moreover, MIP caused the inhibition of expression of HPV anti apoptotic gene E6, which is known to interfere with p53/PUMA/Bax apoptotic cascade. This inhibition might have played a role in transcriptional up regulation of PUMA and subsequently apoptosis. ROS was generated transiently which was concomitant with the highest transcription activation of p53 suggesting a plausible feedback loop network of p53 and ROS in the apoptosis of HeLa cells. Scavenger of ROS, such as N-acetyl-L-cysteine, decreased apoptosis suggesting ROS is an important effector of MIP induced apoptosis. Conclusion: Taken together, MIP possesses full potential to be a novel therapeutic agent in the clinical treatment of cervical cancer.

Keywords: cancer, mycobacterium, immunity, immunotherapy.

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Authors: Vahid Bairami Rad

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The intelligentization of agricultural fields can control the temperature, humidity, and variables affecting the growth of agricultural products online and on a mobile phone or computer. Smarting agricultural fields and gardens is one of the best and best ways to optimize agricultural equipment and has a 100 percent direct effect on the growth of plants and agricultural products and farms. Smart farms are the topic that we are going to discuss today, the Internet of Things and artificial intelligence. Agriculture is becoming smarter every day. From large industrial operations to individuals growing organic produce locally, technology is at the forefront of reducing costs, improving results and ensuring optimal delivery to market. A key element to having a smart agriculture is the use of useful data. Modern farmers have more tools to collect intelligent data than in previous years. Data related to soil chemistry also allows people to make informed decisions about fertilizing farmland. Moisture meter sensors and accurate irrigation controllers have made the irrigation processes to be optimized and at the same time reduce the cost of water consumption. Drones can apply pesticides precisely on the desired point. Automated harvesting machines navigate crop fields based on position and capacity sensors. The list goes on. Almost any process related to agriculture can use sensors that collect data to optimize existing processes and make informed decisions. The Internet of Things (IoT) is at the center of this great transformation. Internet of Things hardware has grown and developed rapidly to provide low-cost sensors for people's needs. These sensors are embedded in IoT devices with a battery and can be evaluated over the years and have access to a low-power and cost-effective mobile network. IoT device management platforms have also evolved rapidly and can now be used securely and manage existing devices at scale. IoT cloud services also provide a set of application enablement services that can be easily used by developers and allow them to build application business logic. Focus on yourself. These development processes have created powerful and new applications in the field of Internet of Things, and these programs can be used in various industries such as agriculture and building smart farms. But the question is, what makes today's farms truly smart farms? Let us put this question in another way. When will the technologies associated with smart farms reach the point where the range of intelligence they provide can exceed the intelligence of experienced and professional farmers?

Keywords: food security, IoT automation, wireless communication, hybrid lifestyle, arduino Uno

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Authors: Maddalena Arigoni, Maria Luisa Ratto, Raffaele A. Calogero, Luca Alessandri

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The presence of tumor heterogeneity, where distinct cancer cells exhibit diverse morphological and phenotypic profiles, including gene expression, metabolism, and proliferation, poses challenges for molecular prognostic markers and patient classification for targeted therapies. Understanding the causes and progression of cancer requires research efforts aimed at characterizing heterogeneity, which can be facilitated by evolving single-cell sequencing technologies. However, analyzing single-cell data necessitates computational methods that often lack objective validation. Therefore, the establishment of benchmarking datasets is necessary to provide a controlled environment for validating bioinformatics tools in the field of single-cell oncology. Benchmarking bioinformatics tools for single-cell experiments can be costly due to the high expense involved. Therefore, datasets used for benchmarking are typically sourced from publicly available experiments, which often lack a comprehensive cell annotation. This limitation can affect the accuracy and effectiveness of such experiments as benchmarking tools. To address this issue, we introduce omics benchmark experiments designed to evaluate bioinformatics tools to depict the heterogeneity in single-cell tumor experiments. We conducted single-cell RNA sequencing on six lung cancer tumor cell lines that display resistant clones upon treatment of EGFR mutated tumors and are characterized by driver genes, namely ROS1, ALK, HER2, MET, KRAS, and BRAF. These driver genes are associated with downstream networks controlled by EGFR mutations, such as JAK-STAT, PI3K-AKT-mTOR, and MEK-ERK. The experiment also featured an EGFR-mutated cell line. Using 10XGenomics platform with cellplex technology, we analyzed the seven cell lines together with a pseudo-immunological microenvironment consisting of PBMC cells labeled with the Biolegend TotalSeq™-B Human Universal Cocktail (CITEseq). This technology allowed for independent labeling of each cell line and single-cell analysis of the pooled seven cell lines and the pseudo-microenvironment. The data generated from the aforementioned experiments are available as part of an online tool, which allows users to define cell heterogeneity and generates count tables as an output. The tool provides the cell line derivation for each cell and cell annotations for the pseudo-microenvironment based on CITEseq data by an experienced immunologist. Additionally, we created a range of pseudo-tumor tissues using different ratios of the aforementioned cells embedded in matrigel. These tissues were analyzed using 10XGenomics (FFPE samples) and Curio Bioscience (fresh frozen samples) platforms for spatial transcriptomics, further expanding the scope of our benchmark experiments. The benchmark experiments we conducted provide a unique opportunity to evaluate the performance of bioinformatics tools for detecting and characterizing tumor heterogeneity at the single-cell level. Overall, our experiments provide a controlled and standardized environment for assessing the accuracy and robustness of bioinformatics tools for studying tumor heterogeneity at the single-cell level, which can ultimately lead to more precise and effective cancer diagnosis and treatment.

Keywords: single cell omics, benchmark, spatial transcriptomics, CITEseq

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Authors: A. Newman-Tancredi, R. Depoortère, P. Gruca, E. Litwa, M. Lason, M. Papp

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The N-methyl-D-aspartic acid (NMDA) receptor antagonist, ketamine, can elicit rapid-acting antidepressant (RAAD) effects in treatment-resistant patients, but it requires parenteral co-administration with a classical antidepressant under medical supervision. In addition, ketamine can also produce serious side effects that limit its long-term use, and there is much interest in identifying RAADs based on ketamine’s mechanism of action but with safer profiles. Ketamine elicits GABAergic interneuron inhibition, glutamatergic neuron stimulation, and, notably, activation of serotonin 5-HT1A receptors in the prefrontal cortex (PFC). Direct activation of the latter receptor subpopulation with selective ‘biased agonists’ may therefore be a promising strategy to identify novel RAADs and, consistent with this hypothesis, the prototypical cortical biased agonist, NLX-101, exhibited robust RAAD-like activity in the chronic mild stress model of depression (CMS). The present study compared the effects of a novel, selective 5-HT1A receptor-biased agonist, NLX-204, with those of ketamine and NLX-101. Materials and methods: CMS procedure was conducted on Wistar rats; drugs were administered either intraperitoneally (i.p.) or by bilateral intracortical microinjection. Ketamine: 10 mg/kg i.p. or 10 µg/side in PFC; NLX-204 and NLX-101: 0.08 and 0.16 mg/kg i.p. or 16 µg/side in PFC. In addition, interaction studies were carried out with systemic NLX-204 or NLX-101 (each at 0.16 mg/kg i.p.) in combination with intracortical WAY-100635 (selective 5-HT1A receptor antagonist; 2 µg/side) or muscimol (GABA-A receptor agonist, 12.5 ng/side). Anhedonia was assessed by CMS-induced decrease in sucrose solution consumption; anxiety-like behavior was assessed using the Elevated Plus Maze (EPM), and cognitive impairment was assessed by the Novel Object Recognition (NOR) test. Results: A single administration of NLX-204 was sufficient to reverse the CMS-induced deficit in sucrose consumption, similarly to ketamine and NLX-101. NLX-204 also reduced CMS-induced anxiety in the EPM and abolished CMS-induced NOR deficits. These effects were maintained (EPM and NOR) or enhanced (sucrose consumption) over a subsequent 2-week period of treatment. The anti-anhedonic response of the drugs was also maintained for several weeks Following treatment discontinuation, suggesting that they had sustained effects on neuronal networks. A single PFC administration of NLX-204 reversed deficient sucrose consumption, similarly to ketamine and NLX-101. Moreover, the anti-anhedonic activities of systemic NLX-204 and NLX 101 were abolished by coadministration with intracortical WAY-100635 or muscimol. Conclusions: (i) The antidepressant-like activity of NLX-204 in the rat CMS model was as rapid as that of ketamine or NLX-101, supporting targeting cortical 5-HT1A receptors with selective, biased agonists to achieve RAAD effects. (ii)The anti-anhedonic activity of systemic NLX-204 was mimicked by local administration of the compound in the PFC, confirming the involvement of cortical circuits in its RAAD-like effects. (iii) Notably, the effects of systemic NLX-204 and NLX-101 were abolished by PFC administration of muscimol, indicating that they act by (indirectly) eliciting a reduction in cortical GABAergic neurotransmission. This is consistent with ketamine’s mechanism of action and suggests that there are converging NMDA and 5-HT1A receptor signaling cascades in PFC underlying the RAAD-like activities of ketamine and NLX-204. Acknowledgements: The study was financially supported by NCN grant no. 2019/35/B/NZ7/00787.

Keywords: depression, ketamine, serotonin, 5-HT1A receptor, chronic mild stress

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Authors: Jamuna Loganath

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Education is the key to the development of any individual’s personality. Today’s students will be tomorrow’s citizens of the global society. The education of the student is the edifice on which his/her future will be built. Schools therefore should provide an all-round development of students so as to foster a healthy society. The behaviors and the attitude of the students in school play an essential role for the success of the education process. Frequent reports of misbehaviors such as clowning, harassing classmates, verbal insults are becoming common in schools today. If this issue is left unattended, it may develop a negative attitude and increase the delinquent behavior. So, the need of the hour is to find a solution to this problem. To solve this issue, it is important to monitor the students’ behaviors in school and give necessary feedback and mentor them to develop a positive attitude and help them to become a successful grownup. Nevertheless, measuring students’ behavior and attitude is extremely challenging. None of the present technology has proven to be effective in this measurement process because actions, reactions, interactions, response of the students are rarely used in the course of the data due to complexity. The purpose of this proposal is to recommend an effective supervising system after carrying out a feasibility study by measuring the behavior of the Students. This can be achieved by equipping schools with CCTV cameras. These CCTV cameras installed in various schools of the world capture the facial expressions and interactions of the students inside and outside their classroom. The real time raw videos captured from the CCTV can be uploaded to the cloud with the help of a network. The video feeds get scooped into various nodes in the same rack or on the different racks in the same cluster in Hadoop HDFS. The video feeds are converted into small frames and analyzed using various Pattern recognition algorithms and MapReduce algorithm. Then, the video frames are compared with the bench marking database (good behavior). When misbehavior is detected, an alert message can be sent to the counseling department which helps them in mentoring the students. This will help in improving the effectiveness of the education process. As Video feeds come from multiple geographical areas (schools from different parts of the world), BIG DATA helps in real time analysis as it analyzes computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. It also analyzes data that can’t be analyzed by traditional software applications such as RDBMS, OODBMS. It has also proven successful in handling human reactions with ease. Therefore, BIG DATA could certainly play a vital role in handling this issue. Thus, effectiveness of the education process can be enhanced with the help of video analytics using the latest BIG DATA technology.

Keywords: big data, cloud, CCTV, education process

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

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

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

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Authors: Ruwani N. Nugara, Masashi Inafuku, Kensaku Takara, Hironori Iwasaki, Hirosuke Oku

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Pteryxin from the partially purified hexane phase (HP) of Peucedanum japonicum Thunb (PJT) was identified as the active compound related to anti-obesity. Thus, in this study we investigated the mechanisms related to anti-obesity activity in-vitro. The HP was fractionated, and effect on the triglyceride (TG) content was evaluated in 3T3-L1 and HepG2 cells. Comprehensive spectroscopic analyses were used to identify the structure of the active compound. The dose dependent effect of active constituent on the TG content, and the gene expressions related to adipogenesis, fatty acid catabolism, energy expenditure, lipolysis and lipogenesis (20 μg/mL) were examined in-vitro. Furthermore, higher dosage of pteryxin (50μg/mL) was tested against 20μg/mL in 3T3-L1 adipocytes. The mRNA were subjected to SOLiD next generation sequencer and the obtained data were analyzed by Ingenuity Pathway Analysis (IPA). The active constituent was identified as pteryxin, a known compound in PJT. However, its biological activities against obesity have not been reported previously. Pteryxin dose dependently suppressed TG content in both 3T3-L1 adipocytes and HepG2 hepatocytes (P < 0.05). Sterol regulatory element-binding protein-1 (SREBP1 c), Fatty acid synthase (FASN), and acetyl-CoA carboxylase-1 (ACC1) were downregulated in pteryxin-treated adipocytes (by 18.0, 36.1 and 38.2%; P < 0.05, respectively) and hepatocytes (by 72.3, 62.9 and 38.8%, respectively; P < 0.05) indicating its suppressive effects on fatty acid synthesis. The hormone-sensitive lipase (HSL), a lipid catabolising gene was upregulated (by 15.1%; P < 0.05) in pteryxin-treated adipocytes suggesting improved lipolysis. Concordantly, the adipocyte size marker gene, paternally expressed gene1/mesoderm specific transcript (MEST) was downregulated (by 42.8%; P < 0.05), further accelerating the lipolytic activity. The upregulated trend of uncoupling protein 2 (UCP2; by 77.5%; P < 0.05) reflected the improved energy expenditure due to pteryxin. The 50μg/mL dosage of pteryxin completely suppressed PPARγ, MEST, SREBP 1C, HSL, Adiponectin, Fatty Acid Binding Protein (FABP) 4, and UCP’s in 3T3-L1 adipocytes. The IPA suggested that pteryxin at 20μg/mL and 50μg/mL suppress obesity in two different pathways, whereas the WNT signaling pathway play a key role in the higher dose of pteryxin in preadipocyte stage. Pteryxin in PJT play the key role in regulating lipid metabolism related gene network and improving energy production in vitro. Thus, the results suggests pteryxin as a new natural compound to be used as an anti-obesity drug in pharmaceutical industry.

Keywords: obesity, peucedanum japonicum thunb, pteryxin, food science

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Authors: Rafael do Amaral Teodoro, Leandro Augusto da Silva

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Originated from graphite, graphene is a two-dimensional (2D) material that promises to revolutionize technology in many different areas, such as energy, telecommunications, civil construction, aviation, textile, and medicine. This is possible because its structure, formed by carbon bonds, provides desirable optical, thermal, and mechanical characteristics that are interesting to multiple areas of the market. Thus, several research and development centers are studying different manufacturing methods and material applications of graphene, which are often compromised by the scarcity of more agile and accurate methodologies to characterize the material – that is to determine its composition, shape, size, and the number of layers and crystals. To engage in this search, this study proposes a computational methodology that applies deep learning to identify graphene oxide crystals in order to characterize samples by crystal sizes. To achieve this, a fully convolutional neural network called U-net has been trained to segment SEM graphene oxide images. The segmentation generated by the U-net is fine-tuned with a standard deviation technique by classes, which allows crystals to be distinguished with different labels through an object delimitation algorithm. As a next step, the characteristics of the position, area, perimeter, and lateral measures of each detected crystal are extracted from the images. This information generates a database with the dimensions of the crystals that compose the samples. Finally, graphs are automatically created showing the frequency distributions by area size and perimeter of the crystals. This methodological process resulted in a high capacity of segmentation of graphene oxide crystals, presenting accuracy and F-score equal to 95% and 94%, respectively, over the test set. Such performance demonstrates a high generalization capacity of the method in crystal segmentation, since its performance considers significant changes in image extraction quality. The measurement of non-overlapping crystals presented an average error of 6% for the different measurement metrics, thus suggesting that the model provides a high-performance measurement for non-overlapping segmentations. For overlapping crystals, however, a limitation of the model was identified. To overcome this limitation, it is important to ensure that the samples to be analyzed are properly prepared. This will minimize crystal overlap in the SEM image acquisition and guarantee a lower error in the measurements without greater efforts for data handling. All in all, the method developed is a time optimizer with a high measurement value, considering that it is capable of measuring hundreds of graphene oxide crystals in seconds, saving weeks of manual work.

Keywords: characterization, graphene oxide, nanomaterials, U-net, deep learning

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Authors: Laurie Dempsey

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Relationships are considered to be beneficial for emotional wellbeing, happiness and physical health. However, they are also complicated: individuals engage in a multitude of complex and volatile relationships during their lifetime, where the change to or ending of these dynamics can be deeply disruptive. As the internet is further integrated into everyday life and relationships are increasingly mediated, Media Studies’ and Sociology’s research interests intersect and converge. This study longitudinally explores how relationship change over time corresponds with the developing UK technological landscape between 2005-2018. Since the early 2000s, the use of computer-mediated communication (CMC) in the UK has dramatically reshaped interaction. Its use has compelled individuals to renegotiate how they consider their relationships: some argue it has allowed for vast networks to be accumulated and strengthened; others contend that it has eradicated the core values and norms associated with communication, damaging relationships. This research collaborated with UK media regulator Ofcom, utilising the longitudinal dataset from their Adult Media Lives study to explore how relationships and CMC use developed over time. This is a unique qualitative dataset covering 2005-2018, where the same 18 participants partook in annual in-home filmed depth interviews. The interviews’ raw video footage was examined year-on-year to consider how the same people changed their reported behaviour and outlooks towards their relationships, and how this coincided with CMC featuring more prominently in their everyday lives. Each interview was transcribed, thematically analysed and coded using NVivo 11 software. This study allowed for a comprehensive exploration into these individuals’ changing relationships over time, as participants grew older, experienced marriages or divorces, conceived and raised children, or lost loved ones. It found that as technology developed between 2005-2018, everyday CMC use was increasingly normalised and incorporated into relationship maintenance. It played a crucial role in altering relationship dynamics, even factoring in the breakdown of several ties. Three key relationships were identified as being shaped by CMC use: parent-child; extended family; and friendships. Over the years there were substantial instances of relationship conflict: for parents renegotiating their dynamic with their child as they tried to both restrict and encourage their child’s technology use; for estranged family members ‘forced’ together in the online sphere; and for friendships compelled to publicly display their relationship on social media, for fear of social exclusion. However, it was also evident that CMC acted as a crucial lifeline for these participants, providing opportunities to strengthen and maintain their bonds via previously unachievable means, both over time and distance. A longitudinal study of this length and nature utilising the same participants does not currently exist, thus provides crucial insight into how and why relationship dynamics alter over time. This unique and topical piece of research draws together Sociology and Media Studies, illustrating how the UK’s changing technological landscape can reshape one of the most basic human compulsions. This collaboration with Ofcom allows for insight that can be utilised in both academia and policymaking alike, making this research relevant and impactful across a range of academic fields and industries.

Keywords: computer mediated communication, longitudinal research, personal relationships, qualitative data

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Authors: Tanmaya Pradhan, K. Midhun, M. Joy Thomas

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Increasing the shelf life and improving the quality are important objectives for the success of packaged liquid food industry. One of the methods by which this can be achieved is by deactivating the micro-organisms present in the liquid food through pasteurization. Pasteurization is done by heating, but some serious disadvantages such as the reduction in food quality, flavour, taste, colour, etc. were observed because of heat treatment, which leads to the development of newer methods instead of pasteurization such as treatment using UV radiation, high pressure, nuclear irradiation, pulsed electric field, etc. In recent years the use of the pulsed electric field (PEF) for inactivation of the microbial content in the food is gaining popularity. PEF uses a very high electric field for a short time for the inactivation of microorganisms, for which we require a high voltage pulsed power source. Pulsed power sources used for PEF treatments are usually in the range of 5kV to 50kV. Different pulse shapes are used, such as exponentially decaying and square wave pulses. Exponentially decaying pulses are generated by high power switches with only turn-on capacity and, therefore, discharge the total energy stored in the capacitor bank. These pulses have a sudden onset and, therefore, a high rate of rising but have a very slow decay, which yields extra heat, which is ineffective in microbial inactivation. Square pulses can be produced by an incomplete discharge of a capacitor with the help of a switch having both on/off control or by using a pulse forming network. In this work, a pulsed power-based system is designed with the help of high voltage capacitors and solid-state switches (IGBT) for the inactivation of pathogenic micro-organism in liquid food such as fruit juices. The high voltage generator is based on the Marx generator topology, which can produce variable amplitude, frequency, and pulse width according to the requirements. Liquid food is treated in a chamber where pulsed electric field is produced between stainless steel electrodes using the pulsed output voltage of the supply. Preliminary bacterial inactivation tests were performed by subjecting orange juice inoculated with Escherichia Coli bacteria. With the help of the developed pulsed power source and the chamber, the inoculated orange has been PEF treated. The voltage was varied to get a peak electric field up to 15kV/cm. For a total treatment time of 200µs, a 30% reduction in the bacterial count has been observed. The detailed results and analysis will be presented in the final paper.

Keywords: Escherichia coli bacteria, high voltage generator, microbial inactivation, pulsed electric field, pulsed forming line, solid-state switch

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Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Within agent-based modeling, opinion dynamics is the field that focuses on modeling people's opinions. In this prolific field, most of the literature is dedicated to the exploration of the two 'degrees of freedom' and how they impact the model’s properties (e.g., the average final opinion, the number of final clusters, etc.). These degrees of freedom are (1) the interaction rule, which determines how agents update their own opinion, and (2) the network topology, which defines the possible interaction among agents. In this work, we show that the third degree of freedom exists. This can be used to change a model's output up to 100% of its initial value or to transform two models (both from the literature) into each other. Since opinion dynamics models are representations of the real world, it is fundamental to understand how people’s opinions can be measured. Even for abstract models (i.e., not intended for the fitting of real-world data), it is important to understand if the way of numerically representing opinions is unique; and, if this is not the case, how the model dynamics would change by using different representations. The process of measuring opinions is non-trivial as it requires transforming real-world opinion (e.g., supporting most of the liberal ideals) to a number. Such a process is usually not discussed in opinion dynamics literature, but it has been intensively studied in a subfield of psychology called psychometrics. In psychometrics, opinion scales can be converted into each other, similarly to how meters can be converted to feet. Indeed, psychometrics routinely uses both linear and non-linear transformations of opinion scales. Here, we analyze how this transformation affects opinion dynamics models. We analyze this effect by using mathematical modeling and then validating our analysis with agent-based simulations. Firstly, we study the case of perfect scales. In this way, we show that scale transformations affect the model’s dynamics up to a qualitative level. This means that if two researchers use the same opinion dynamics model and even the same dataset, they could make totally different predictions just because they followed different renormalization processes. A similar situation appears if two different scales are used to measure opinions even on the same population. This effect may be as strong as providing an uncertainty of 100% on the simulation’s output (i.e., all results are possible). Still, by using perfect scales, we show that scales transformations can be used to perfectly transform one model to another. We test this using two models from the standard literature. Finally, we test the effect of scale transformation in the case of finite precision using a 7-points Likert scale. In this way, we show how a relatively small-scale transformation introduces both changes at the qualitative level (i.e., the most shared opinion at the end of the simulation) and in the number of opinion clusters. Thus, scale transformation appears to be a third degree of freedom of opinion dynamics models. This result deeply impacts both theoretical research on models' properties and on the application of models on real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

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Authors: Claire Norman-Maillet

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Insider fraud, including its various synonyms such as occupational, employee or internal fraud, is a major financial crime threat whereby an employee defrauds (or attempts to defraud) their current, prospective, or past employer. ‘Employee’ covers anyone employed by the company, including contractors, directors, and part time staff; they may be a solo bad actor or working in collusion with others, whether internal or external. Insider fraud is even more of a concern given the impacts of the Coronavirus pandemic, which has generated multiple opportunities to commit insider fraud. Insider fraud is something that is not necessarily thought of as a significant financial crime threat; the focus of most academics and practitioners has historically been on that of ‘external fraud’ against businesses or entities where an individual or group has no professional ties. Without the face-to-face, ‘over the shoulder’ capabilities of staff being able to keep an eye on their employees, there is a heightened reliance on trust and transparency. With this, naturally, comes an increased risk of insider fraud perpetration. The objective of the research is to better understand how companies are impacted by insider fraud, and therefore how to stop it. This research will make both an original contribution and stimulate debate within the financial crime field. The financial crime landscape is never static – criminals are always creating new ways to perpetrate financial crime, and new legislation and regulations are implemented as attempts to strengthen controls, in addition to businesses doing what they can internally to detect and prevent it. By focusing on insider fraud specifically, the research will be more specific and will be of greater use to those in the field. To achieve the aims of the research, semi-structured interviews were conducted with 22 individuals who either work in financial services and deal with insider fraud or work within insider fraud perpetration in a recruitment or advisory capacity. This was to enable the sourcing of information from a wide range of individuals in a setting where they were able to elaborate on their answers. The principal recruitment strategy was engaging with the researcher’s network on LinkedIn. The interviews were then transcribed and analysed thematically. Main findings in the research suggest that insider fraud has been ignored owing to the denial of accepting the possibility that colleagues would defraud their employer. Whilst Coronavirus has led to a significant rise in insider fraud, this type of crime has been a major risk to businesses since their inception, however have never been given the financial or strategic backing required to be mitigated, until it's too late. Furthermore, Coronavirus should have led to companies tightening their access rights, controls and policies to mitigate the insider fraud risk. However, in most cases this has not happened. The research concludes that insider fraud needs to be given a platform upon which to be recognised as a threat to any company and given the same level of weighting and attention by Executive Committees and Boards as other types of economic crime.

Keywords: fraud, insider fraud, economic crime, coronavirus, Covid-19

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Authors: Kedar J. Mahadeshwar

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Concept introduction: This paper talks about how an innovative cloud based analytics enabled solution that could address a major industry challenge that is approaching all of us globally faster than what one would think. The world of supply chain for drugs and devices is changing today at a rapid speed. In the US, the Drug Supply Chain Security Act (DSCSA) is a new law for Tracing, Verification and Serialization phasing in starting Jan 1, 2015 for manufacturers, repackagers, wholesalers and pharmacies / clinics. Similarly we are seeing pressures building up in Europe, China and many countries that would require an absolute traceability of every drug and device end to end. Companies (both manufacturers and distributors) can use this opportunity not only to be compliant but to differentiate themselves over competition. And moreover a country such as UAE can be the leader in coming up with a global solution that brings innovation in this industry. Problem definition and timing: The problem of counterfeit drug market, recognized by FDA, causes billions of dollars loss every year. Even in UAE, the concerns over prevalence of counterfeit drugs, which enter through ports such as Dubai remains a big concern, as per UAE pharma and healthcare report, Q1 2015. Distribution of drugs and devices involves multiple processes and systems that do not talk to each other. Consumer confidence is at risk due to this lack of traceability and any leading provider is at risk of losing its reputation. Globally there is an increasing pressure by government and regulatory bodies to trace serial numbers and lot numbers of every drug and medical devices throughout a supply chain. Though many of large corporations use some form of ERP (enterprise resource planning) software, it is far from having a capability to trace a lot and serial number beyond the enterprise and making this information easily available real time. Solution: The solution here talks about a service provider that allows all subscribers to take advantage of this service. The solution allows a service provider regardless of its physical location, to host this cloud based traceability and analytics solution of millions of distribution transactions that capture lots of each drug and device. The solution platform will capture a movement of every medical device and drug end to end from its manufacturer to a hospital or a doctor through a series of distributor or retail network. The platform also provides advanced analytics solution to do some intelligent reporting online. Why Dubai? Opportunity exists with huge investment done in Dubai healthcare city also with using technology and infrastructure to attract more FDI to provide such a service. UAE and countries similar will be facing this pressure from regulators globally in near future. But more interestingly, Dubai can attract such innovators/companies to run and host such a cloud based solution and become a hub of such traceability globally.

Keywords: cloud, pharmaceutical, supply chain, tracking

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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: Neha Pranav Kolhe, Harithapriya Vijaye, Arushi Kamle

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The economic growth engines are urban regions. As the economy expands, so does the need for peace and quiet, and noise pollution is one of the important social and environmental issue. Health and wellbeing are at risk from environmental noise pollution. Because of urbanisation, population growth, and the consequent rise in the usage of increasingly potent, diverse, and highly mobile sources of noise, it is now more severe and pervasive than ever before, and it will only become worse. Additionally, it will expand as long as there is an increase in air, train, and highway traffic, which continue to be the main contributors of noise pollution. The current study will be conducted in two zones of class I city of central India (population range: 1 million–4 million). Total 56 measuring points were chosen to assess noise pollution. The first objective evaluates the noise pollution in various urban habitats determined as formal and informal settlement. It identifies the comparison of noise pollution within the settlements using T- Test analysis. The second objective assess the noise pollution in silent zones (as stated in Central Pollution Control Board) in a hierarchical way. It also assesses the noise pollution in the settlements and compares with prescribed permissible limits using class I sound level equipment. As appropriate indices, equivalent noise level on the (A) frequency weighting network, minimum sound pressure level and maximum sound pressure level were computed. The survey is conducted for a period of 1 week. Arc GIS is used to plot and map the temporal and spatial variability in urban settings. It is discovered that noise levels at most stations, particularly at heavily trafficked crossroads and subway stations, were significantly different and higher than acceptable limits and squares. The study highlights the vulnerable areas that should be considered while city planning. The study demands area level planning while preparing a development plan. It also demands attention to noise pollution from the perspective of residential and silent zones. The city planning in urban areas neglects the noise pollution assessment at city level. This contributes to that, irrespective of noise pollution guidelines, the ground reality is far away from its applicability. The result produces incompatible land use on a neighbourhood scale with respect to noise pollution. The study's final results will be useful to policymakers, architects and administrators in developing countries. This will be useful for noise pollution in urban habitat governance by efficient decision making and policy formulation to increase the profitability of these systems.

Keywords: noise pollution, formal settlements, informal settlements, built environment, silent zone, residential area

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Authors: F. Tang, S. Boskovich, A. Raheja, Z. Aliyazicioglu, S. Bhandari, N. Tsuchiya

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Calpoly Autonomous Transportation Experience (CATE) is a driverless vehicle that we are developing to provide safe, accessible, and efficient transportation of passengers throughout the Cal Poly Pomona campus for events such as orientation tours. Unlike the other self-driving vehicles that are usually developed to operate with other vehicles and reside only on the road networks, CATE will operate exclusively on walk-paths of the campus (potentially narrow passages) with pedestrians traveling from multiple locations. Safety becomes paramount as CATE operates within the same environment as pedestrians. As driverless vehicles assume greater roles in today’s transportation, this project will contribute to autonomous driving with pedestrian traffic in a highly dynamic environment. The CATE project requires significant interdisciplinary work. Researchers from mechanical engineering, electrical engineering and computer science are working together to attack the problem from different perspectives (hardware, software and system). In this abstract, we describe the software aspects of the project, with a focus on the requirements and the major components. CATE shall provide a GUI interface for the average user to interact with the car and access its available functionalities, such as selecting a destination from any origin on campus. We have developed an interface that provides an aerial view of the campus map, the current car location, routes, and the goal location. Users can interact with CATE through audio or manual inputs. CATE shall plan routes from the origin to the selected destination for the vehicle to travel. We will use an existing aerial map for the campus and convert it to a spatial graph configuration where the vertices represent the landmarks and edges represent paths that the car should follow with some designated behaviors (such as stay on the right side of the lane or follow an edge). Graph search algorithms such as A* will be implemented as the default path planning algorithm. D* Lite will be explored to efficiently recompute the path when there are any changes to the map. CATE shall avoid any static obstacles and walking pedestrians within some safe distance. Unlike traveling along traditional roadways, CATE’s route directly coexists with pedestrians. To ensure the safety of the pedestrians, we will use sensor fusion techniques that combine data from both lidar and stereo vision for obstacle avoidance while also allowing CATE to operate along its intended route. We will also build prediction models for pedestrian traffic patterns. CATE shall improve its location and work under a GPS-denied situation. CATE relies on its GPS to give its current location, which has a precision of a few meters. We have implemented an Unscented Kalman Filter (UKF) that allows the fusion of data from multiple sensors (such as GPS, IMU, odometry) in order to increase the confidence of localization. We also noticed that GPS signals can easily get degraded or blocked on campus due to high-rise buildings or trees. UKF can also help here to generate a better state estimate. In summary, CATE will provide on-campus transportation experience that coexists with dynamic pedestrian traffic. In future work, we will extend it to multi-vehicle scenarios.

Keywords: driverless vehicle, path planning, sensor fusion, state estimate

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Authors: Bagam Venkateswarlu

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NMDC Limited, Indian multinational mining company operates under administrative control of Ministry of Steel, Government of India. This study is undertaken to evaluate how sustainable mining practiced by the company fulfils the provisions of Indian Constitution to secure to its citizen – justice, equality of status and opportunity, promoting social, economic, political, and religious wellbeing. The Constitution of India lays down a road map as to how the goal of being a “Welfare State” shall be achieved. The vision of sustainable mining being practiced is oriented along the constitutional responsibilities on Indian Citizens and the Corporate World. This qualitative study shall be backed by quantitative studies of National Mineral Development Corporation performances in various domains of sustainable mining and ESG, that is, environment, social and governance parameters. For example, Five Star Rating of mine is a comprehensive evaluation system introduced by Ministry of Mines, Govt. of India is one of the methodologies. Corporate Social Responsibilities is one of the thrust areas for securing social well-being. Green energy initiatives in and around the mines has given the title of “Eco-Friendly Miner” to NMDC Limited. While operating fully mechanized large scale iron ore mine (18.8 million tonne per annum capacity) in Bacheli, Chhattisgarh, M/s NMDC Limited caters to the needs of mineral security of State of Chhattisgarh and Indian Union. It preserves forest, wild-life, and environment heritage of richly endowed State of Chhattisgarh. In the remote and far-flung interiors of Chhattisgarh, NMDC empowers the local population by providing world class educational & medical facilities, transportation network, drinking water facilities, irrigational agricultural supports, employment opportunities, establishing religious harmony. All this ultimately results in empowered, educated, and improved awareness in population. Thus, the basic tenets of constitution of India- secularism, democracy, welfare for all, socialism, humanism, decentralization, liberalism, mixed economy, and non-violence is fulfilled. Constitution declares India as a welfare state – for the people, of the people and by the people. The sustainable mining practices by NMDC are in line with the objective. Thus, the purpose of study is fully met with. The potential benefit of the study includes replicating this model in existing or new establishments in various parts of country – especially in the under-privileged interiors and far-flung areas which are yet to see the lights of development.

Keywords: ESG values, Indian constitution, NMDC limited, sustainable mining, CSR, green energy

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Authors: Roland F. Karthaus, Rachel S. O'Brien

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Over the past decade, the authors have undertaken applied research aimed at enabling transformation within the prison service to improve conditions and outcomes for those living, working and visiting in prisons in the UK and the communities they serve. The research has taken place against a context of reducing resources and public discontent at increasing levels of violence, deteriorating conditions and persistently high levels of re-offending. Top-down governmental policies have mainly been ineffectual and in some cases counter-productive. The prison service is characterised by hierarchical organisation, and the research has applied design thinking at multiple levels to challenge and precipitate change: top-down, middle-out and bottom-up. The research employs three distinct but related approaches, system design (top-down): working at the national policy level to analyse the changing policy context, identifying opportunities and challenges; engaging with the Ministry of Justice commissioners and sector organisations to facilitate debate, introducing new evidence and provoking creative thinking, place-based design (middle-out): working with individual prison establishments as pilots to illustrate and test the potential for local empowerment, creative change, and improved architecture within place-specific contexts and organisational hierarchies, everyday design (bottom-up): working with individuals in the system to explore the potential for localised, significant, demonstrator changes; including collaborative design, capacity building and empowerment in skills, employment, communication, training, and other activities. The research spans a series of projects, through which the methodological approach has developed responsively. The projects include a place-based model for the re-purposing of Ministry of Justice land assets for the purposes of rehabilitation; an evidence-based guide to improve prison design for health and well-being; capacity-based employment, skills and self-build project as a template for future open prisons. The overarching research has enabled knowledge to be developed and disseminated through policy and academic networks. Whilst the research remains live and continuing; key findings are emerging as a basis for a new methodological approach to effecting change in the UK prison service. An interdisciplinary approach is necessary to overcome the barriers between distinct areas of the prison service. Sometimes referred to as total environments, prisons encompass entire social and physical environments which themselves are orchestrated by institutional arms of government, resulting in complex systems that cannot be meaningfully engaged through narrow disciplinary lenses. A scalar approach is necessary to connect strategic policies with individual experiences and potential, through the medium of individual prison establishments, operating as discrete entities within the system. A reflexive process is necessary to connect research with action in a responsive mode, learning to adapt as the system itself is changing. The role of individuals in the system, their latent knowledge and experience and their ability to engage and become agents of change are essential. Whilst the specific characteristics of the UK prison system are unique, the approach is internationally applicable.

Keywords: architecture, design, policy, prison, system, transformation

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Authors: S. I. Mwasha, Z. Robinson, M. Musgrave

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Communities, especially in the global south, have been reported to have low adaptive capacity to cope with climate change impacts. As an attempt to improve adaptive capacity, most studies have focused on understanding the access of the household resources which can contribute to resilience against changes. However, little attention has been shown in uncovering how the household resources could be used and their implications to resilience against weather related shocks. By using a case study qualitative study, this project analyzed the trends in livelihoods practices and their implication to social equity. The study was done in three different villages within Kilimanjaro region. Each in different agro ecological zone. Two focus group discussions in two agro-ecological zones were done, one for women and another one for men except in the third zone where focus group participant were combined together (due to unforeseen circumstances). In the focus group discussion, several participatory rural appraisal tools were used to understand trend in crops and animal production and the use in which it is made: climate trends, soil fertility, trees and other livelihoods resources. Data were analyzed using thematic network analysis. Using an amalgam of magnitude (to note weather comments made were positive or negative) and descriptive coding (to note the topic), six basic themes were identified under social equity: individual ownership, family ownership, love and respect, women no education, women access to education as well as women access to loans. The results implied that despite mum and dad in the family providing labor in the agro pastoral activities, there were separations on who own what, as well as individual obligations in the family. Dad owned mostly income creating crops and mum, food crops. therefore, men controlled the economy which made some of them become arrogant and spend money to meet their interests sometimes not taking care of the family. Separation in ownership was reported to contribute to conflicts in the household as well as causing controversy on the use income is spent. Men were reported to use income to promote matriarchy system. However, as women were capacitated through access to education and loans they become closer to their husband and get access to own and plan the income together for the interest of the family. Joint ownership and planning on the household resources were reported to be important if families have to better adapt to climate change. The aim of this study is not to show women empowerment and joint ownership and planning as only remedy for low adaptive capacity. There is the need to understand other practices that either directly or indirectly impacts environmental integrity, food security and economic development for household resilience against changing climate.

Keywords: adaptive capacity, climate change, resilience, women empowerment

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Authors: Selin Top, Raul Marcos, M. Sinan Bilgili

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Although there have been several studies related to collection, temporary storage, handling and disposal of solid wastes generated by hospitals, there are only a few studies related to liquid wastes generated by hospitals or hospital wastewaters. There is an important amount of water consumptions in hospitals. While minimum domestic water consumption per person is 100 L/day, water consumption per bed in hospitals is generally ranged between 400-1200 L. This high amount of consumption causes high amount of wastewater. The quantity of wastewater produced in a hospital depends on different factors: bed numbers, hospital age, accessibility to water, general services present inside the structure (kitchen, laundry, laboratory, diagnosis, radiology, and air conditioning), number and type of wards and units, institution management policies and awareness in managing the structure in safeguarding the environment, climate and cultural and geographic factors. In our country, characterization of hospital wastewaters conducted by classical parameters in a very few studies. However, as mentioned above, this type of wastewaters may contain different compounds than domestic wastewaters. Hospital Wastewater (HWW) is wastewater generated from all activities of the hospital, medical and non medical. Nowadays, hospitals are considered as one of the biggest sources of wastewater along with urban sources, agricultural effluents and industrial sources. As a health-care waste, hospital wastewater has the same quality as municipal wastewater, but may also potentially contain various hazardous components due to using disinfectants, pharmaceuticals, radionuclides and solvents making not suitable the connection of hospital wastewater to the municipal sewage network. These characteristics may represent a serious health hazard and children, adults and animals all have the potential to come into contact with this water. Therefore, the treatment of hospital wastewater is an important current interest point to focus on. This paper aims to approach on the investigation of hospital wastewater treatment by membrane systems. This study aim is to determined hospital wastewater’s characterization and also evaluates the efficiency of hospital wastewater treatment by high pressure filtration systems such as ultrafiltration (UF). Hospital wastewater samples were taken directly from sewage system from Şişli Etfal Training and Research Hospital, located in the district of Şişli, in the European part of Istanbul. The hospital is a 784 bed tertiary care center with a daily outpatient department of 3850 patients. Ultrafiltration membrane is used as an experimental treatment and the influence of the pressure exerted on the membranes was examined, ranging from 1 to 3 bar. The permeate flux across the membrane was observed to define the flooding membrane points. The global COD and BOD5 removal efficiencies were 54% and 75% respectively for ultrafiltration, all the SST removal efficiencies were above 90% and a successful removal of the pathological bacteria measured was achieved.

Keywords: hospital wastewater, membrane, ultrafiltration, treatment

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Authors: Bhavana Gulaty, Arshia Chaudhri

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Great civic projects contribute integrally to a city, and every city undergoes a recurring cycle of urban transformations and regeneration by their insertion. The M.I.C.E. (Meetings, Incentives, Convention and Exhibitions) industry is the forbearer of one category of such catalytic civic projects. Through a specific focus on M.I.C.E. destinations, this paper illustrates the multifarious dimensions that urban catalysts impact the city on S.P.U.R. (Seed. Profile. Urbane. Reflections), the theoretical framework of this paper aims to unearth these dimensions in the realm of the COEX (Convention & Exhibition) biosphere. The ‘COEX Biosphere’ is the filter of such catalysts being ecosystems unto themselves. Like a ripple in water, the impact of these strategic interventions focusing on art, culture, trade, and promotion expands right from the trigger; the immediate context to the region and subsequently impacts the global scale. These ripples are known to bring about significant economic, social, and political and network changes. The COEX inventory in the Asian context has one such prominent addition; the proposed India International Convention and Exhibition Centre (IICC) at New Delhi. It is envisioned to be the largest facility in Asia currently and would position India on the global M.I.C.E map. With the first phase of the project scheduled to open for use in the end of 2019, this flagship project of the Government of India is projected to cater to a peak daily footfall of 3,20,000 visitors and estimated to generate 5,00,000 jobs. While the economic benefits are yet to manifest in real time and ‘Good design is good business’ holds true, for the urban transformation to be meaningful, the benefits have to go beyond just a balance sheet for the city’s exchequer. This aspect has been found relatively unexplored in research on these developments. The methodology for investigation will comprise of two steps. The first will be establishing an inventory of the global success stories and associated benefits of COEX projects over the past decade. The rationale for capping the timeframe is the significant paradigm shift that has been observed in their recent conceptualization; for instance ‘Innovation Districts’ conceptualised in the city of Albuquerque that converges into the global economy. The second step would entail a comparative benchmarking of the projected transformations by IICC through a toolkit of parameters. This is posited to yield a matrix that can form the test bed for mapping the catalytic trajectory for projects in the pipeline globally. As a ready reckoner, it purports to be a catalyst to substantiate decision making in the planning stage itself for future projects in similar contexts.

Keywords: catalysts, COEX, M.I.C.E., urban transformations

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Authors: Shayla He

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Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

Procedia PDF Downloads 96

Authors: Alan Johnson

Abstract:

This paper focuses on modern pilgrimage narratives about sites affiliated with Indian religious expressions located both within and outside India. The paper uses a multidisciplinary approach to examine poetry, personal essays, and online attestations of pilgrimage to illustrate how non-religious ideas coexist with outwardly religious ones, exemplifying a characteristically Indian form of syncretism that pre-dates Western ideas of pluralism. The paper argues that the syncretism on display in these modern creative works refutes the current exclusionary vision of India as a primordially Hindu-nationalist realm. A crucial premise of this argument is that the narrative’s intrinsic heteroglossia, so evident in India’s historically rich variety of stories and symbols, belies this reactionary version of Hindu nationalism. Equally important to this argument, therefore, is the vibrancy of Hindu sites outside India, such as the Batu Caves temple complex in Kuala Lumpur, Malaysia. The literary texts examined in this paper include, first, Arun Kolatkar’s famous 1976 collection of poems, titled Jejuri, about a visit to the pilgrimage site of the same name in Maharashtra. Here, the modern, secularized visitor from Bombay (Mumbai) contemplates the effect of the temple complex on himself and on the other, more worshipful visitors. Kolatkar’s modernist poems reflect the narrator’s typically modern-Indian ambivalence for holy ruins, for although they do not evoke a conventionally religious feeling in him, they nevertheless possess an aura of timelessness that questions the narrator’s time-conscious sensibility. The paper bookends Kolatkar’s Jejuri with considerations of an early-twentieth-century text, online accounts by visitors to the Batu Caves, and a recent, more conventional Hindu account of pilgrimage. For example, the pioneering graphic artist Mukul Chandra Dey published in 1917, My Pilgrimages to Ajanta and Bagh, in which he devotes an entire chapter to the life of the Buddha as a means of illustrating the layering of stories that is a characteristic feature of sacred sites in India. In a different but still syncretic register, Jawaharlal Nehru, India’s first prime minister, and a committed secularist proffers India’s ancient pilgrimage network as a template for national unity in his classic 1946 autobiography The Discovery of India. Narrative is the perfect vehicle for highlighting this layering of sensibilities, for a single text can juxtapose the pilgrim-narrator’s description with that of a far older pilgrimage, a juxtaposition that establishes an imaginative connection between otherwise distanced actors, and between them and the reader.

Keywords: India, literature, narrative, syncretism

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Authors: Elisa Esposito, Johannes C. Jansen, Loredana Dellamuzia, Ugo Moretti, Lidietta Giorno

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The reduction of CO₂ emission into the atmosphere as a result of human activity is one of the most important environmental challenges to face in the next decennia. Emission of CO₂, related to the use of fossil fuels, is believed to be one of the main causes of global warming and climate change. In this scenario, the production of biomethane from organic waste, as a renewable energy source, is one of the most promising strategies to reduce fossil fuel consumption and greenhouse gas emission. Unfortunately, biogas upgrading still produces the greenhouse gas CO₂ as a waste product. Therefore, this work presents a case study on biogas upgrading, aimed at the simultaneous purification of methane and CO₂ via different steps, including CO₂/methane separation by polymeric membranes. The original objective of the project was the biogas upgrading to distribution grid quality methane, but the innovative aspect of this case study is the further purification of the captured CO₂, transforming it from a useless by-product to a pure gas with food-grade quality, suitable for commercial application in the food and beverage industry. The study was performed on a pilot plant constructed by Tecno Project Industriale Srl (TPI) Italy. This is a model of one of the largest biogas production and purification plants. The full-scale anaerobic digestion plant (Montello Spa, North Italy), has a digestive capacity of 400.000 ton of biomass/year and can treat 6.250 m3/hour of biogas from FORSU (organic fraction of solid urban waste). The entire upgrading process consists of a number of purifications steps: 1. Dehydration of the raw biogas by condensation. 2. Removal of trace impurities such as H₂S via absorption. 3.Separation of CO₂ and methane via a membrane separation process. 4. Removal of trace impurities from CO₂. The gas separation with polymeric membranes guarantees complete simultaneous removal of microorganisms. The chemical purity of the different process streams was analysed by a certified laboratory and was compared with the guidelines of the European Industrial Gases Association and the International Society of Beverage Technologists (EIGA/ISBT) for CO₂ used in the food industry. The microbiological purity was compared with the limit values defined in the European Collaborative Action. With a purity of 96-99 vol%, the purified methane respects the legal requirements for the household network. At the same time, the CO₂ reaches a purity of > 98.1% before, and 99.9% after the final distillation process. According to the EIGA/ISBT guidelines, the CO₂ proves to be chemically and microbiologically sufficiently pure to be suitable for food-grade applications.

Keywords: biogas, CO₂ separation, CO2 utilization, CO₂ food grade

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Authors: M. Kowalik, J. Masternak, K. Kazimierczuk, O. V. Khavryuchenko, B. Kupcewicz, B. Barszcz

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Recently, the growing interest of chemists in metal-organic coordination polymers (MOCPs) is primarily derived from their intriguing structures and potential applications in catalysis, gas storage, molecular sensing, ion exchanges, nonlinear optics, luminescence, etc. Currently, we are devoting considerable effort to finding the proper method of synthesizing new coordination polymers containing S- or N-heteroaromatic carboxylates as linkers and characterizing the obtained Pb(II) compounds according to their structural diversity, luminescence, and thermal properties. The choice of Pb(II) as the central ion of MOCPs was motivated by several reasons mentioned in the literature: i) a large ionic radius allowing for a wide range of coordination numbers, ii) the stereoactivity of the 6s2 lone electron pair leading to a hemidirected or holodirected geometry, iii) a flexible coordination environment, and iv) the possibility to form secondary bonds and unusual non-covalent interactions, such as classic hydrogen bonds and π···π stacking interactions, as well as nonconventional hydrogen bonds and rarely reported tetrel bonds, Pb(lone pair)···π interactions, C–H···Pb agostic-type interactions or hydrogen bonds, and chelate ring stacking interactions. Moreover, the construction of coordination polymers requires the selection of proper ligands acting as linkers, because we are looking for materials exhibiting different network topologies and fluorescence properties, which point to potential applications. The reaction of Pb(NO₃)₂ with 1H-pyrrole-2-carboxylic acid (2prCOOH) leads to the formation of a new four-nuclear Pb(II) polymer, [Pb4(2prCOO)₈(H₂O)]ₙ, which has been characterized by CHN, FT-IR, TG, PL and single-crystal X-ray diffraction methods. In view of the primary Pb–O bonds, Pb1 and Pb2 show hemidirected pentagonal pyramidal geometries, while Pb2 and Pb4 display hemidirected octahedral geometries. The topology of the strongest Pb–O bonds was determined as the (4·8²) fes topology. Taking the secondary Pb–O bonds into account, the coordination number of Pb centres increased, Pb1 exhibited a hemidirected monocapped pentagonal pyramidal geometry, Pb2 and Pb4 exhibited a holodirected tricapped trigonal prismatic geometry, and Pb3 exhibited a holodirected bicapped trigonal prismatic geometry. Moreover, the Pb(II) lone pair stereoactivity was confirmed by DFT calculations. The 2D structure was expanded into 3D by the existence of non-covalent O/C–H···π and Pb···π interactions, which was confirmed by the Hirshfeld surface analysis. The above mentioned interactions improve the rigidity of the structure and facilitate the charge and energy transfer between metal centres, making the polymer a promising luminescent compound.

Keywords: coordination polymers, fluorescence properties, lead(II), lone electron pair stereoactivity, non-covalent interactions

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Authors: Liudmyla Vesper

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The problems of modern education are large-scale and diverse. The aspirations of parents, teachers, and experts converge - everyone interested in growing up a generation of whole, well-educated persons. Both the family and society are expected in the future generation to be self-sufficient, desirable in the labor market, and capable of lifelong learning. Today's children have a powerful potential that is difficult to realize in the conditions of traditional school approaches. Focusing on STEM education in practice often ends with the simple use of computers and gadgets during class. "Science", "technology", "engineering" and "mathematics" are difficult to combine within school and university curricula, which have not changed much during the last 10 years. Solving the problems of modern education largely depends on teachers - innovators, teachers - practitioners who develop and implement effective educational methods and programs. Teachers who propose innovative pedagogical practices that allow students to master large-scale knowledge and apply it to the practical plane. Effective education considers the creation of stable neural structures during the learning process, which allow to preserve and increase knowledge throughout life. The author proposed a method of integrated lessons – cases based on the maths patterns for forming a holistic perception of the world. This method and program are scientifically substantiated and have more than 15 years of practical application experience in school and student classrooms. The first results of the practical application of the author's methodology and curriculum were announced at the International Conference "Teaching and Learning Strategies to Promote Elementary School Success", 2006, April 22-23, Yerevan, Armenia, IREX-administered 2004-2006 Multiple Component Education Project. This program is based on the concept of interdisciplinary connections and its implementation in the process of continuous learning. This allows students to save and increase knowledge throughout life according to a single pattern. The pattern principle stores information on different subjects according to one scheme (pattern), using long-term memory. This is how neural structures are created. The author also admits that a similar method can be successfully applied to the training of artificial intelligence neural networks. However, this assumption requires further research and verification. The educational method and program proposed by the author meet the modern requirements for education, which involves mastering various areas of knowledge, starting from an early age. This approach makes it possible to involve the child's cognitive potential as much as possible and direct it to the preservation and development of individual talents. According to the methodology, at the early stages of learning students understand the connection between school subjects (so-called "sciences" and "humanities") and in real life, apply the knowledge gained in practice. This approach allows students to realize their natural creative abilities and talents, which makes it easier to navigate professional choices and find their place in life.

Keywords: science education, maths education, AI, neuroplasticity, innovative education problem, creativity development, modern education problem

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