Search results for: perceptual linear prediction (PLP’s)

Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Alfredo Fortunato, Carmelofrancesco Origlia, Sara Laurita, Rossella Nicoletti

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In the post-pandemic recovery phase of tourism, the role of a Destination Management Organization (DMO) as a coordinated management system of all the elements that make up a destination (attractions, access, marketing, human resources, brand, pricing, etc.) is also becoming relevant for local territories. The objective of a DMO is to maximize the visitor's perception of value and quality while ensuring the competitiveness and sustainability of the destination, as well as the long-term preservation of its natural and cultural assets, and to catalyze benefits for the local economy and residents. In carrying out the multiple functions to which it is called, the DMO can leverage a collective intelligence that comes from the ability to pool information, explicit and tacit knowledge, and relationships of the various stakeholders: policymakers, public managers and officials, entrepreneurs in the tourism supply chain, researchers, data journalists, schools, associations and committees, citizens, etc. The DMO potentially has at its disposal large volumes of data and many of them at low cost, that need to be properly processed to produce value. Based on these assumptions, the paper presents a conceptual framework for building an information system to support the DMO in the intelligent management of a tourist destination tested in an area of southern Italy. The approach adopted is data-informed and consists of four phases: (1) formulation of the knowledge problem (analysis of policy documents and industry reports; focus groups and co-design with stakeholders; definition of information needs and key questions); (2) research and metadatation of relevant sources (reconnaissance of official sources, administrative archives and internal DMO sources); (3) gap analysis and identification of unconventional information sources (evaluation of traditional sources with respect to the level of consistency with information needs, the freshness of information and granularity of data; enrichment of the information base by identifying and studying web sources such as Wikipedia, Google Trends, Booking.com, Tripadvisor, websites of accommodation facilities and online newspapers); (4) definition of the set of indicators and construction of the information base (specific definition of indicators and procedures for data acquisition, transformation, and analysis). The framework derived consists of 6 thematic areas (accommodation supply, cultural heritage, flows, value, sustainability, and enabling factors), each of which is divided into three domains that gather a specific information need to be represented by a scheme of questions to be answered through the analysis of available indicators. The framework is characterized by a high degree of flexibility in the European context, given that it can be customized for each destination by adapting the part related to internal sources. Application to the case study led to the creation of a decision support system that allows: •integration of data from heterogeneous sources, including through the execution of automated web crawling procedures for data ingestion of social and web information; •reading and interpretation of data and metadata through guided navigation paths in the key of digital story-telling; •implementation of complex analysis capabilities through the use of data mining algorithms such as for the prediction of tourist flows.

Keywords: collective intelligence, data framework, destination management, smart tourism

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Authors: Pinzhe Zhao

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This study focuses on predicting university students' cheating tendencies using psychological traits and machine learning techniques. Academic dishonesty is a significant issue that compromises the integrity and fairness of educational institutions. While much research has been dedicated to detecting cheating behaviors after they have occurred, there is limited work on predicting such tendencies before they manifest. The aim of this research is to develop a model that can identify students who are at higher risk of engaging in academic misconduct, allowing for earlier interventions to prevent such behavior. Psychological factors are known to influence students' likelihood of cheating. Research shows that traits such as test anxiety, moral reasoning, self-efficacy, and achievement motivation are strongly linked to academic dishonesty. High levels of anxiety may lead students to cheat as a way to cope with pressure. Those with lower self-efficacy are less confident in their academic abilities, which can push them toward dishonest behaviors to secure better outcomes. Students with weaker moral judgment may also justify cheating more easily, believing it to be less wrong under certain conditions. Achievement motivation also plays a role, as students driven primarily by external rewards, such as grades, are more likely to cheat compared to those motivated by intrinsic learning goals. In this study, data on students’ psychological traits is collected through validated assessments, including scales for anxiety, moral reasoning, self-efficacy, and motivation. Additional data on academic performance, attendance, and engagement in class are also gathered to create a more comprehensive profile. Using machine learning algorithms such as Random Forest, Support Vector Machines (SVM), and Long Short-Term Memory (LSTM) networks, the research builds models that can predict students’ cheating tendencies. These models are trained and evaluated using metrics like accuracy, precision, recall, and F1 scores to ensure they provide reliable predictions. The findings demonstrate that combining psychological traits with machine learning provides a powerful method for identifying students at risk of cheating. This approach allows for early detection and intervention, enabling educational institutions to take proactive steps in promoting academic integrity. The predictive model can be used to inform targeted interventions, such as counseling for students with high test anxiety or workshops aimed at strengthening moral reasoning. By addressing the underlying factors that contribute to cheating behavior, educational institutions can reduce the occurrence of academic dishonesty and foster a culture of integrity. In conclusion, this research contributes to the growing body of literature on predictive analytics in education. It offers a approach by integrating psychological assessments with machine learning to predict cheating tendencies. This method has the potential to significantly improve how academic institutions address academic dishonesty, shifting the focus from punishment after the fact to prevention before it occurs. By identifying high-risk students and providing them with the necessary support, educators can help maintain the fairness and integrity of the academic environment.

Keywords: academic dishonesty, cheating prediction, intervention strategies, machine learning, psychological traits, academic integrity

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Authors: M. François, L. Sigot, C. Vallières

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Volatile Organic Compounds (VOCs) are a real health issue, particularly in domestic indoor environments. Among these VOCs, acetaldehyde is frequently monitored in dwellings ‘air, especially due to smoking and spontaneous emissions from the new wall and soil coverings. It is responsible for respiratory complaints and is classified as possibly carcinogenic to humans. Adsorption processes are commonly used to remove VOCs from the air. Metal-Organic Frameworks (MOFs) are a promising type of material for high adsorption performance. These hybrid porous materials composed of metal inorganic clusters and organic ligands are interesting thanks to their high porosity and surface area. The HKUST-1 (also referred to as MOF-199) is a copper-based MOF with the formula [Cu₃(BTC)₂(H₂O)₃]n (BTC = benzene-1,3,5-tricarboxylate) and exhibits unsaturated metal sites that can be attractive sites for adsorption. The objective of this study is to investigate the impact of HKUST-1 pretreatment on acetaldehyde adsorption. Thus, dynamic adsorption experiments were conducted in 1 cm diameter glass column packed with 2 cm MOF bed height. MOF were sieved to 630 µm - 1 mm. The feed gas (Co = 460 ppmv ± 5 ppmv) was obtained by diluting a 1000 ppmv acetaldehyde gas cylinder in air. The gas flow rate was set to 0.7 L/min (to guarantee a suitable linear velocity). Acetaldehyde concentration was monitored online by gas chromatography coupled with a flame ionization detector (GC-FID). Breakthrough curves must allow to understand the interactions between the MOF and the pollutant as well as the impact of the HKUST-1 humidity in the adsorption process. Consequently, different MOF water content conditions were tested, from a dry material with 7 % water content (dark blue color) to water saturated state with approximately 35 % water content (turquoise color). The rough material – without any pretreatment – containing 30 % water serves as a reference. First, conclusions can be drawn from the comparison of the evolution of the ratio of the column outlet concentration (C) on the inlet concentration (Co) as a function of time for different HKUST-1 pretreatments. The shape of the breakthrough curves is significantly different. The saturation of the rough material is slower (20 h to reach saturation) than that of the dried material (2 h). However, the breakthrough time defined for C/Co = 10 % appears earlier in the case of the rough material (0.75 h) compared to the dried HKUST-1 (1.4 h). Another notable difference is the shape of the curve before the breakthrough at 10 %. An abrupt increase of the outlet concentration is observed for the material with the lower humidity in comparison to a smooth increase for the rough material. Thus, the water content plays a significant role on the breakthrough kinetics. This study aims to understand what can explain the shape of the breakthrough curves associated to the pretreatments of HKUST-1 and which mechanisms take place in the adsorption process between the MOF, the pollutant, and the water.

Keywords: acetaldehyde, dynamic adsorption, HKUST-1, pretreatment influence

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Authors: L. C. Nwosu, C. O. Adedire, M. O. Ashamo, E. O. Ogunwolu

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The maize weevil, Sitophilus zeamais Motschulsky is a notorious pest of stored maize (Zea mays L.). The development of resistant maize varieties to manage weevils is a major breeding objective. The study investigated the parameters and mechanisms that confer resistance on a maize variety to S. zeamais infestation using twenty elite maize varieties. Detailed morphological, physical and chemical studies were conducted on whole-maize grain and the grain pericarp. Resistance was assessed at 33, 56, and 90 days post infestation using weevil mortality rate, weevil survival rate, percent grain damage, percent grain weight loss, weight of grain powder, oviposition rate and index of susceptibility as indices rated on a scale developed by the present study and on Dobie’s modified scale. Linear regression models that can predict maize grain damage in relation to the duration of storage were developed and applied. The resistant varieties identified particularly 2000 SYNEE-WSTR and TZBRELD3C5 with very high degree of resistance should be used singly or best in an integrated pest management system for the control of S. zeamais infestation in stored maize. Though increases in the physical properties of grain hardness, weight, length, and width increased varietal resistance, it was found that the bases of resistance were increased chemical attributes of phenolic acid, trypsin inhibitor and crude fibre while the bases of susceptibility were increased protein, starch, magnesium, calcium, sodium, phosphorus, manganese, iron, cobalt and zinc, the role of potassium requiring further investigation. Characters that conferred resistance on the test varieties were found distributed in the pericarp and the endosperm of the grains. Increases in grain phenolic acid, crude fibre, and trypsin inhibitor adversely and significantly affected the bionomics of the weevil on further assessment. The flat side of a maize grain at the point of penetration was significantly preferred by the weevil. Why the south area of the flattened side of a maize grain was significantly preferred by the weevil is clearly unknown, even though grain-face-type seemed to be a contributor in the study. The preference shown to the south area of the grain flat side has implications for seed viability. The study identified antibiosis, preference, antixenosis, and host evasion as the mechanisms of maize post harvest resistance to Sitophilus zeamais infestation.

Keywords: maize weevil, resistant, parameters, mechanisms, preference

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Authors: Beatriz González-rodrigo, Diego Hidalgo-leiva, Omar Flores, Claudia Germoso, Maribel Jiménez-martínez, Laura Navas-sánchez, Belén Orta, Nicola Tarque, Orlando Hernández- Rubio, Miguel Marchamalo, Juan Gregorio Rejas, Belén Benito-oterino

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Cities facing seismic hazard necessitate detailed risk assessments for effective urban planning and vulnerability identification, ensuring the safety and sustainability of urban infrastructure. Comprehensive studies involving seismic hazard, vulnerability, and exposure evaluations are pivotal for estimating potential losses and guiding proactive measures against seismic events. However, broad-scale traditional risk studies limit consideration of specific local threats and identify vulnerable housing within a structural typology. Achieving precise results at neighbourhood levels demands higher resolution seismic hazard exposure, and vulnerability studies. This research aims to bolster sustainability and safety against seismic disasters in three Central American and Caribbean capitals. It integrates geospatial techniques and artificial intelligence into seismic risk studies, proposing cost-effective methods for exposure data collection and damage prediction. The methodology relies on prior seismic threat studies in pilot zones, utilizing existing exposure and vulnerability data in the region. Emphasizing detailed building attributes enables the consideration of behaviour modifiers affecting seismic response. The approach aims to generate detailed risk scenarios, facilitating prioritization of preventive actions pre-, during, and post-seismic events, enhancing decision-making certainty. Detailed risk scenarios necessitate substantial investment in fieldwork, training, research, and methodology development. Regional cooperation becomes crucial given similar seismic threats, urban planning, and construction systems among involved countries. The outcomes hold significance for emergency planning and national and regional construction regulations. The success of this methodology depends on cooperation, investment, and innovative approaches, offering insights and lessons applicable to regions facing moderate seismic threats with vulnerable constructions. Thus, this framework aims to fortify resilience in seismic-prone areas and serves as a reference for global urban planning and disaster management strategies. In conclusion, this research proposes a comprehensive framework for seismic risk assessment in high-risk urban areas, emphasizing detailed studies at finer resolutions for precise vulnerability evaluations. The approach integrates regional cooperation, geospatial technologies, and adaptive fragility curve adjustments to enhance risk assessment accuracy, guiding effective mitigation strategies and emergency management plans.

Keywords: assessment, behaviour modifiers, emergency management, mitigation strategies, resilience, vulnerability

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Authors: Luisa Villani

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The proposal aims to express concerns about the connection between mind, body, society, and environment in the Flyers’ dance, a very well-known rotatory dance in Mexico, to create meanings and to make the apprehension of the world possible. The interaction among the brain, mind, body, and environment, and the intersubjective relation among them, means the world creates and recreates a social interaction. The purpose of this methodology, based on the embodied cognition theory, which was named “A Performance-Embodied Theory” is to find the principles and patterns that organize the culture and the rules of the apprehension of the environment by Totonac people while the dance is being performed. The analysis started by questioning how anthropologists can interpret how Totonacs transform their unconscious knowledge into conscious knowledge and how the scheme formation of imagination and their collective imagery is understood in the context of public-facing rituals, such as Flyers’ dance. The problem is that most of the time, researchers interpret elements in a separate way and not as a complex ritual dancing whole, which is the original contribution of this study. This theory, which accepts the fact that people are body-mind agents, wants to interpret the dance as a whole, where the different elements are joined to an integral interpretation. To understand incorporation, data was recollected in prolonged periods of fieldwork, with participant observation and linguistic and extralinguistic data analysis. Laban’s notation for the description and analysis of gestures and movements in the space was first used, but it was later transformed and gone beyond this method, which is still a linear and compositional one. Performance in a ritual is the actualization of a potential complex of meanings or cognitive domains among many others in a culture: one potential dimension becomes probable and then real because of the activation of specific meanings in a context. It can only be thought what language permits thinking, and the lexicon that is used depends on the individual culture. Only some parts of this knowledge can be activated at once, and these parts of knowledge are connected. Only in this way, the world can be understood. It can be recognized that as languages geometrize the physical world thanks to the body, also ritual does. In conclusion, the ritual behaves as an embodied grammar or a text in movement, which, depending on the ritual phases and the words and sentences pronounced in the ritual, activates bits of encyclopedic knowledge that people have about the world. Gestures are not given by the performer but emerge from the intentional perception in which gestures are “understood” by the audio-spectator in an inter-corporeal way. The impact of this study regards the possibility not only to disseminate knowledge effectively but also to generate a balance between different parts of the world where knowledge is shared, rather than being received by academic institutions alone. This knowledge can be exchanged, so indigenous communities and academies could be together as part of the activation and the sharing of this knowledge with the world.

Keywords: dance, flyers, performance, embodied, cognition

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Authors: Bharti Singh, Shri K. Singh

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Child malnutrition is a multifaceted issue that transcends geographical boundaries. Malnutrition not only stunts physical growth but also leads to a spectrum of morbidities and child mortality. It is one of the leading causes of death (~50 %) among children under age five. Despite economic progress and advancements in healthcare, child malnutrition remains a formidable challenge for India. The objective is to investigate the impact of women's empowerment on child nutrition outcomes in India from 2006 to 2021. A composite index of women's empowerment was constructed using Confirmatory Factor Analysis (CFA), a rigorous technique that validates the measurement model by assessing how well-observed variables represent latent constructs. This approach ensures the reliability and validity of the empowerment index. Secondly, kernel density plots were utilised to visualise the distribution of key nutritional indicators, such as stunting, wasting, and overweight. These plots offer insights into the shape and spread of data distributions, aiding in understanding the prevalence and severity of malnutrition. Thirdly, linear polynomial graphs were employed to analyse how nutritional parameters evolved with the child's age. This technique enables the visualisation of trends and patterns over time, allowing for a deeper understanding of nutritional dynamics during different stages of childhood. Lastly, multilevel analysis was conducted to identify vulnerable levels, including State-level, PSU-level, and household-level factors impacting undernutrition. This approach accounts for hierarchical data structures and allows for the examination of factors at multiple levels, providing a comprehensive understanding of the determinants of child malnutrition. Overall, the utilisation of these statistical methodologies enhances the transparency and replicability of the study by providing clear and robust analytical frameworks for data analysis and interpretation. Our study reveals that NFHS-4 and NFHS-5 exhibit an equal density of severely stunted cases. NFHS-5 indicates a limited decline in wasting among children aged five, while the density of severely wasted children remains consistent across NFHS-3, 4, and 5. In 2019-21, women with higher empowerment had a lower risk of their children being undernourished (Regression coefficient= -0.10***; Confidence Interval [-0.18, -0.04]). Gender dynamics also play a significant role, with male children exhibiting a higher susceptibility to undernourishment. Multilevel analysis suggests household-level vulnerability (intra-class correlation=0.21), highlighting the need to address child undernutrition at the household level.

Keywords: child nutrition, India, NFHS, women’s empowerment

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Authors: Martyna Chotomska, Aleksandra Studzinska, Marta Lisowska, Justyna Szubert, Aleksandra Tabis, Jacek Bania, Arkadiusz Miazek

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Objectives: Assessing antigen-specific T cell responses is of utmost importance for the pre-clinical testing of prototype vaccines against intracellular pathogens and tumor antigens. Mainly two types of in vitro assays are used for this purpose 1) enzyme-linked immunospot (ELISpot) and 2) intracellular cytokine staining (ICS). Both are time-consuming, relatively expensive, and require manual dexterity. Here, we assess if a straightforward detection of luciferase activity in blood samples of transgenic reporter mice expressing a secreted Lucia luciferase under the transcriptional control of IFN-γ promoter parallels the sensitivity of IFNγ ELISpot assay. Methods: IFN-γ-LUCIA mouse strain carrying multiple copies of Lucia luciferase transgene under the transcriptional control of IFNγ minimal promoter were generated by pronuclear injection of linear DNA. The specificity of transgene expression and mobilization was assessed in vitro using transgenic splenocytes exposed to various mitogens. The IFN-γ-LUCIA mice were immunized with 50mg of ovalbumin (OVA) emulsified in incomplete Freund’s adjuvant three times every two weeks by subcutaneous injections. Blood samples were collected before and five days after each immunization. Luciferase activity was assessed in blood serum. Peripheral blood mononuclear cells were separated and assessed for frequencies of OVA-specific IFNγ-secreting T cells. Results: We show that in vitro cultured splenocytes of IFN-γ-LUCIA mice respond by 2 and 3 fold increase in secreted luciferase activity to T cell mitogens concanavalin A and phorbol myristate acetate, respectively but fail to respond to B cell-stimulating E.coli lipopolysaccharide. Immunization of IFN-γ-LUCIA mice with OVA leads to over 4 fold increase in luciferase activity in blood serum five days post-immunization with a barely detectable increase in OVA-specific, IFNγ-secreting T cells by ELISpot. Second and third immunizations, further increase the luciferase activity and coincidently also increase the frequencies of OVA-specific T cells by ELISpot. Conclusions: We conclude that minimally invasive monitoring of luciferase secretions in blood serum of IFN-γ-LUCIA mice constitutes a sensitive method for evaluating primary and memory Th1 responses to protein antigens. As such, this method may complement existing methods for rapid immunogenicity assessment of prototype vaccines.

Keywords: ELISpot, immunogenicity, interferon-gamma, reporter mice, vaccines

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Authors: Fadi Al Khatib, Raouf Mbarki, Malek Adouni

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In various sport and recreational activities, the patellofemoral joint undergoes large forces and moments while accommodating the significant knee joint movement. In doing so, this joint is commonly the source of anterior knee pain related to instability in normal patellar tracking and excessive pressure syndrome. One well-observed explanation of the instability of the normal patellar tracking is the patellofemoral ligaments and patellar tendon damage. Improved knowledge of the damage mechanism mediating ligaments and tendon injuries can be a great help not only in rehabilitation and prevention procedures but also in the design of better reconstruction systems in the management of knee joint disorders. This damage mechanism, specifically due to excessive mechanical loading, has been linked to the micro level of the fibred structure precisely to the tropocollagen molecules and their connection density. We argue defining a clear frame starting from the bottom (micro level) to up (macro level) in the hierarchies of the soft tissue may elucidate the essential underpinning on the state of the ligaments damage. To do so, in this study a multiscale fibril reinforced hyper elastoplastic Finite Element model that accounts for the synergy between molecular and continuum syntheses was developed to determine the short-term stresses/strains patellofemoral ligaments and tendon response. The plasticity of the proposed model is associated only with the uniaxial deformation of the collagen fibril. The yield strength of the fibril is a function of the cross-link density between tropocollagen molecules, defined here by a density function. This function obtained through a Coarse-graining procedure linking nanoscale collagen features and the tissue level materials properties using molecular dynamics simulations. The hierarchies of the soft tissues were implemented using the rule of mixtures. Thereafter, the model was calibrated using a statistical calibration procedure. The model then implemented into a real structure of patellofemoral ligaments and patellar tendon (OpenKnee) and simulated under realistic loading conditions. With the calibrated material parameters the calculated axial stress lies well with the experimental measurement with a coefficient of determination (R2) equal to 0.91 and 0.92 for the patellofemoral ligaments and the patellar tendon respectively. The ‘best’ prediction of the yielding strength and strain as compared with the reported experimental data yielded when the cross-link density between the tropocollagen molecule of the fibril equal to 5.5 ± 0.5 (patellofemoral ligaments) and 12 (patellar tendon). Damage initiation of the patellofemoral ligaments was located at the femoral insertions while the damage of the patellar tendon happened in the middle of the structure. These predicted finding showed a meaningful correlation between the cross-link density of the tropocollagen molecules and the stiffness of the connective tissues of the extensor mechanism. Also, damage initiation and propagation were documented with this model, which were in satisfactory agreement with earlier observation. To the best of our knowledge, this is the first attempt to model ligaments from the bottom up, predicted depending to the tropocollagen cross-link density. This approach appears more meaningful towards a realistic simulation of a damaging process or repair attempt compared with certain published studies.

Keywords: tropocollagen, multiscale model, fibrils, knee ligaments

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Authors: Naresh Kumar, Radhika Sharma, A. K. Singh

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Granites from Khanak and Devsar areas, a part of Malani Igneous Suite (MIS) were investigated for their geochemical characteristics to understand the petrogenetic aspect of the research area. Neoproterozoic rocks of MIS are well exposed in Jhunjhunu, Jodhpur, Pali, Barmer, Jalor, Jaisalmer districts of Rajasthan and Bhiwani district of Haryana and also occur at Kirana hills of Pakistan. The MIS predominantly consists of acidic volcanic with acidic plutonic (granite of various types), mafic volcanic, mafic intrusive and minor amount of pyroclasts. Based on the field and petrographical studies, 28 samples were selected and analyzed for geochemical analysis of major, trace and rare earth elements at the Wadia Institute of Himalayan Geology, Dehradun by X-Ray Fluorescence Spectrometer (XRF) and ICP-MS (Inductively Coupled Plasma- Mass Spectrometry). Granites from the studied areas are categorized as grey, green and pink. Khanak granites consist of quartz, k-feldspar, plagioclase, and biotite as essential minerals and hematite, zircon, annite, monazite & rutile as accessory minerals. In Devsar granites, plagioclase is replaced by perthite and occurs as dominantly. Geochemically, granites from Khanak and Devsar areas exhibit typical A-type granites characteristics with their enrichment in SiO2, Na2O+K2O, Fe/Mg, Rb, Zr, Y, Th, U, REE (except Eu) and significant depletion in MgO, CaO, Sr, P, Ti, Ni, Cr, V and Eu suggested about A-type affinities in Northwestern Peninsular India. The amount of heat production (HP) in green and grey granites of Devsar area varies upto 9.68 & 11.70 μWm-3 and total heat generation unit (HGU) i.e. 23.04 & 27.86 respectively. Pink granites of Khanak area display a higher enrichment of HP (16.53 μWm-3) and HGU (39.37) than the granites from Devsar area. Overall, they have much higher values of HP and HGU than the average value of continental crust (3.8 HGU), which imply a possible linear relationship among the surface heat flow and crustal heat generation in the rocks of MIS. Chondrite-normalized REE patterns show enriched LREE, moderate to strong negative Eu anomalies and more or less flat heavy REE. In primitive mantle-normalized multi-element variation diagrams, the granites show pronounced depletions in the high-field-strength elements (HFSE) Nb, Zr, Sr, P, and Ti. Geochemical characteristics (major, trace and REE) along with the use of various discrimination schemes revealed their probable correspondence to magma derived from the crustal origin by a different degree of partial melting.

Keywords: A-type granite, neoproterozoic, Malani igneous suite, Khanak, Devsar

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Authors: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

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Authors: Shlomit Paz, Meir Broza

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Cholera is an acute intestinal infection caused by ingestion of food or water contaminated with the bacterium Vibrio cholerae. It has a short incubation period and produces an enterotoxin that causes copious, painless, watery diarrhoea that can quickly lead to severe dehydration and death if treatment is not promptly given. In an epidemic, the source of the contamination is usually the feces of an infected person. The disease can spread rapidly in areas with poor treatment of sewage and drinking water. Cholera remains a global threat and is one of the key indicators of social development. An estimated 3-5 million cases and over 100,000 deaths occur each year around the world. The relevance of climatic events as causative factors for cholera epidemics is well known. However, the examination of the involvement of winds in intra-continental disease distribution is new. The study explore the hypothesis that the spreading of cholera epidemics may be related to the dominant wind direction over land by presenting the influence of the wind direction on windborn dissemination by flying insects, which may serve as vectors. Chironomids ("non-biting midges“) exist in the majority of freshwater aquatic habitats, especially in estuarine and organic-rich water bodies typical to Vibrio cholerae. Chironomid adults emerge into the air for mating and dispersion. They are highly mobile, huge in number and found frequently in the air at various elevations. The huge number of chironomid egg masses attached to hard substrate on the water surface, serve as a reservoir for the free-living Vibrio bacteria. Both male and female, while emerging from the water, may carry the cholera bacteria. In experimental simulation, it was demonstrated that the cholera-bearing adult midges are carried by the wind, and transmit the bacteria from one body of water to another. In our previous study, the geographic diffusions of three cholera outbreaks were examined through their linkage with the wind direction: a) the progress of Vibrio cholerae O1 biotype El Tor in Africa during 1970–1971 and b) again in 2005–2006; and c) the rapid spread of Vibrio cholerae O139 over India during 1992–1993. Using data and map of cholera dissemination (WHO database) and mean monthly SLP and geopotential data (NOAA NCEP-NCAR database), analysis of air pressure data at sea level and at several altitudes over Africa, India and Bangladesh show a correspondence between the dominant wind direction and the intra-continental spread of cholera. The results support the hypothesis that aeroplankton (the tiny life forms that float in the air and that may be caught and carried upward by the wind, landing far from their origin) carry the cholera bacteria from one body of water to an adjacent one. In addition to these findings, the current follow-up study will present new results regarding the possible involvement of winds in the spreading of cholera in recent outbreaks (2010-2013). The findings may improve the understanding of how climatic factors are involved in the rapid distribution of new strains throughout a vast continental area. Awareness of the aerial transfer of Vibrio cholerae may assist health authorities by improving the prediction of the disease’s geographic dissemination.

Keywords: cholera, Vibrio cholerae, wind direction, Vibrio cholerae dissemination

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Authors: Jungyeol Hong, Dongjoo Park

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The primary purpose of this study is to develop a methodological framework to predict daily subway ridership at a station-level and to examine the association between subway ridership and bus demand incorporating commercial business facility in the vicinity of each subway station. The socio-economic characteristics, land-use, and built environment as factors may have an impact on subway ridership. However, it should be considered not only the endogenous relationship between bus and subway demand but also the characteristics of commercial business within a subway station’s sphere of influence, and integrated transit network topology. Regarding a statistical approach to estimate subway ridership at a station level, therefore it should be considered endogeneity and heteroscedastic issues which might have in the subway ridership prediction model. This study focused on both discovering the impacts of bus demand, commercial business characteristics, and network topology on subway ridership and developing more precise subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers entire Seoul city in South Korea and includes 243 stations with the temporal scope set at twenty-four hours with one-hour interval time panels each. The data for subway and bus ridership was collected Seoul Smart Card data from 2015 and 2016. Three-Stage Least Square(3SLS) approach was applied to develop daily subway ridership model as capturing the endogeneity and heteroscedasticity between bus and subway demand. Independent variables incorporating in the modeling process were commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. As a result, it was found that bus ridership and subway ridership were endogenous each other and they had a significantly positive sign of coefficients which means one transit mode could increase another transportation mode’s ridership. In other words, two transit modes of subway and bus have a mutual relationship instead of the competitive relationship. The commercial business characteristics are the most critical dimension among the independent variables. The variables of commercial business facility rate in the paper containing six types; medical, educational, recreational, financial, food service, and shopping. From the model result, a higher rate in medical, financial buildings, shopping, and food service facility lead to increment of subway ridership at a station, while recreational and educational facility shows lower subway ridership. The complex network theory was applied for estimating integrated network topology measures that cover the entire Seoul transit network system, and a framework for seeking an impact on subway ridership. The centrality measures were found to be significant and showed a positive sign indicating higher centrality led to more subway ridership at a station level. The results of model accuracy tests by out of samples provided that 3SLS model has less mean square error rather than OLS and showed the methodological approach for the 3SLS model was plausible to estimate more accurate subway ridership. Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT (2017R1C1B2010175).

Keywords: subway ridership, bus ridership, commercial business characteristic, endogeneity, network topology

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Authors: M. Beusink, E. W. C. Coenen

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The increased application of novel structural materials, such as high grade asphalt, concrete and laminated composites, has sparked the need for a better understanding of the often complex, non-linear mechanical behavior of such materials. The effective macroscopic mechanical response is generally dependent on the applied load path. Moreover, it is also significantly influenced by the microstructure of the material, e.g. embedded fibers, voids and/or grain morphology. At present, multiscale techniques are widely adopted to assess micro-macro interactions in a numerically efficient way. Computational homogenization techniques have been successfully applied over a wide range of engineering cases, e.g. cases involving first order and second order continua, thin shells and cohesive zone models. Most of these homogenization methods rely on Representative Volume Elements (RVE), which model the relevant microstructural details in a confined volume. Imposed through kinematical constraints or boundary conditions, a RVE can be subjected to a microscopic load sequence. This provides the RVE's effective stress-strain response, which can serve as constitutive input for macroscale analyses. Simultaneously, such a study of a RVE gives insight into fine scale phenomena such as microstructural damage and its evolution. It has been reported by several authors that the type of boundary conditions applied to the RVE affect the resulting homogenized stress-strain response. As a consequence, dedicated boundary conditions have been proposed to appropriately deal with this concern. For the specific case of a planar assumption for the analyzed structure, e.g. plane strain, axisymmetric or plane stress, this assumption needs to be addressed consistently in all considered scales. Although in many multiscale studies a planar condition has been employed, the related impact on the multiscale solution has not been explicitly investigated. This work therefore focuses on the influence of the planar assumption for multiscale modeling. In particular the plane stress case is highlighted, by proposing three different implementation strategies which are compatible with a first-order computational homogenization framework. The first method consists of applying classical plane stress theory at the microscale, whereas with the second method a generalized plane stress condition is assumed at the RVE level. For the third method, the plane stress condition is applied at the macroscale by requiring that the resulting macroscopic out-of-plane forces are equal to zero. These strategies are assessed through a numerical study of a thin walled structure and the resulting effective macroscale stress-strain response is compared. It is shown that there is a clear influence of the length scale at which the planar condition is applied.

Keywords: first-order computational homogenization, planar analysis, multiscale, microstrucutures

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Authors: Mark Darius Juszczak

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While epistemology, as a sub-field of philosophy, is generally concerned with theoretical questions about the nature of knowledge, the explosion in digital media technologies has resulted in an exponential increase in the storage and transmission of human information. That increase has resulted in a particular non-linear dynamic – digital epistemological functions are radically altering how and what we know. Neither the rate of that change nor the consequences of it have been well studied or taken into account in developing state-level strategies for epistemological functions. At the current time, US Federal policy, like that of virtually all other countries, maintains, at the national state level, clearly defined boundaries between various epistemological agencies - agencies that, in one way or another, mediate the functional use of knowledge. These agencies can take the form of patent and trademark offices, national library and archive systems, departments of education, departments such as the FTC, university systems and regulations, military research systems such as DARPA, federal scientific research agencies, medical and pharmaceutical accreditation agencies, federal funding for scientific research and legislative committees and subcommittees that attempt to alter the laws that govern epistemological functions. All of these agencies are in the constant process of creating, analyzing, and regulating knowledge. Those processes are, at the most general level, epistemological functions – they act upon and define what knowledge is. At the same time, however, there are no high-level strategic epistemological directives or frameworks that define those functions. The only time in US history where a proxy state-level epistemological strategy existed was between 1961 and 1969 when the Kennedy Administration committed the United States to the Apollo program. While that program had a singular technical objective as its outcome, that objective was so technologically advanced for its day and so complex so that it required a massive redirection of state-level epistemological functions – in essence, a broad and diverse set of state-level agencies suddenly found themselves working together towards a common epistemological goal. This paper does not call for a repeat of the Apollo program. Rather, its purpose is to investigate the minimum structural requirements for a national state-level epistemological strategy in the United States. In addition, this paper also seeks to analyze how the epistemological work of the multitude of national agencies within the United States would be affected by such a high-level framework. This paper is an exploratory study of this type of framework. The primary hypothesis of the author is that such a function is possible but would require extensive re-framing and reclassification of traditional epistemological functions at the respective agency level. In much the same way that, for example, DHS (Department of Homeland Security) evolved to respond to a new type of security threat in the world for the United States, it is theorized that a lack of coordination and alignment in epistemological functions will equally result in a strategic threat to the United States.

Keywords: strategic security, epistemological functions, epistemological agencies, Apollo program

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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Authors: Shinji Ukita, Naohiro Nakamura, Yuji Miyazu

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In considering the dynamic characteristics of structure, natural frequency and damping ratio are useful indicator. When performing dynamic design, it's necessary to select an appropriate initial damping model and hysteretic model. In the linear region, the setting of initial damping model influences the response, and in the nonlinear region, the combination of initial damping model and hysteretic model influences the response. However, the dynamic characteristics of structure in the nonlinear region remain unclear. In this paper, we studied the effect of setting of initial damping model and hysteretic model on the dynamic characteristics of structure. On initial damping model setting, Initial stiffness proportional, Tangent stiffness proportional, and Rayleigh-type were used. On hysteretic model setting, TAKEDA model and Normal-trilinear model were used. As a study method, dynamic analysis was performed using a lumped mass model of base-fixed. During analysis, the maximum acceleration of input earthquake motion was gradually increased from 1 to 600 gal. The dynamic characteristics were calculated using the ARX model. Then, the characteristics of 1st and 2nd natural frequency and 1st damping ratio were evaluated. Input earthquake motion was simulated wave that the Building Center of Japan has published. On the building model, an RC building with 30×30m planes on each floor was assumed. The story height was 3m and the maximum height was 18m. Unit weight for each floor was 1.0t/m2. The building natural period was set to 0.36sec, and the initial stiffness of each floor was calculated by assuming the 1st mode to be an inverted triangle. First, we investigated the difference of the dynamic characteristics depending on the difference of initial damping model setting. With the increase in the maximum acceleration of the input earthquake motions, the 1st and 2nd natural frequency decreased, and the 1st damping ratio increased. Then, in the natural frequency, the difference due to initial damping model setting was small, but in the damping ratio, a significant difference was observed (Initial stiffness proportional≒Rayleigh type>Tangent stiffness proportional). The acceleration and the displacement of the earthquake response were largest in the tangent stiffness proportional. In the range where the acceleration response increased, the damping ratio was constant. In the range where the acceleration response was constant, the damping ratio increased. Next, we investigated the difference of the dynamic characteristics depending on the difference of hysteretic model setting. With the increase in the maximum acceleration of the input earthquake motions, the natural frequency decreased in TAKEDA model, but in Normal-trilinear model, the natural frequency didn’t change. The damping ratio in TAKEDA model was higher than that in Normal-trilinear model, although, both in TAKEDA model and Normal-trilinear model, the damping ratio increased. In conclusion, in initial damping model setting, the tangent stiffness proportional was evaluated the most. In the hysteretic model setting, TAKEDA model was more appreciated than the Normal-trilinear model in the nonlinear region. Our results would provide useful indicator on dynamic design.

Keywords: initial damping model, damping ratio, dynamic analysis, hysteretic model, natural frequency

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Authors: Ali H. Daraji, Jack M. Hale, Ye Jianqiao

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With the extensive use of high specific strength structures to optimise the loading capacity and material cost in aerospace and most engineering applications, much effort has been expended to develop intelligent structures for active vibration reduction and structural health monitoring. These structures are highly flexible, inherently low internal damping and associated with large vibration and long decay time. The modification of such structures by adding lightweight piezoelectric sensors and actuators at efficient locations integrated with an optimal control scheme is considered an effective solution for structural vibration monitoring and controlling. The size and location of sensor and actuator are important research topics to investigate their effects on the level of vibration detection and reduction and the amount of energy provided by a controller. Several methodologies have been presented to determine the optimal location of a limited number of sensors and actuators for small-scale structures. However, these studies have tackled this problem directly, measuring the fitness function based on eigenvalues and eigenvectors achieved with numerous combinations of sensor/actuator pair locations and converging on an optimal set using heuristic optimisation techniques such as the genetic algorithms. This is computationally expensive for small- and large-scale structures subject to optimise a number of s/a pairs to suppress multiple vibration modes. This paper proposes an efficient method to determine optimal locations for a limited number of sensor/actuator pairs for active vibration reduction of a flexible structure based on finite element method and Hamilton’s principle. The current work takes the simplified approach of modelling a structure with sensors at all locations, subjecting it to an external force to excite the various modes of interest and noting the locations of sensors giving the largest average percentage sensors effectiveness measured by dividing all sensor output voltage over the maximum for each mode. The methodology was implemented for a cantilever plate under external force excitation to find the optimal distribution of six sensor/actuator pairs to suppress the first six modes of vibration. It is shown that the results of the optimal sensor locations give good agreement with published optimal locations, but with very much reduced computational effort and higher effectiveness. Furthermore, it is shown that collocated sensor/actuator pairs placed in these locations give very effective active vibration reduction using optimal linear quadratic control scheme.

Keywords: optimisation, plate, sensor effectiveness, vibration control

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Authors: William Creighton, Jan Smitheram

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Queer discourse has been tied to a middle-class, urban-centric, white approach to the discussion of queerness. In doing so, the multilayeredness of queer existence has been washed away in favour of palatable queer occupation. This paper uses design to explore a queer anti-urbanist approach to facilitate a more egalitarian architectural occupancy. Scott Herring’s work on queer anti-urbanism is key to this approach. Herring redeploys anti-urbanism from its historical understanding of open hostility, rejection and desire to destroy the city towards a mode of queer critique that counters normative ideals of homonormative metronormative gay lifestyles. He questions how queer identity has been closed down into a more diminutive frame where those who do not fit within this frame are subjected to persecution or silenced through their absence. We extend these ideas through design to ask how a queer anti-urbanist approach facilitates a more egalitarian architectural occupancy. Following a “design as research” methodology, the design outputs allow a vehicle to ask how we might live, otherwise, in architectural space. A design as research methodologically is a process of questioning, designing and reflecting – in a non-linear, iterative approach – establishes itself through three projects, each increasing in scale and complexity. Each of the three scales tackled a different body relationship. The project began exploring the relations between body to body, body to known others, and body to unknown others. Moving through increasing scales was not to privilege the objective, the public and the large scale; instead, ‘intra-scaling’ acts as a tool to re-think how scale reproduces normative ideas of the identity of space. There was a queering of scale. Through this approach, the results were an installation that brings two people together to co-author space where the installation distorts the sensory experience and forces a more intimate and interconnected experience challenging our socialized proxemics: knees might touch. To queer the home, the installation was used as a drawing device, a tool to study and challenge spatial perception, drawing convention, and as a way to process practical information about the site and existing house – the device became a tool to embrace the spontaneous. The final design proposal operates as a multi-scalar boundary-crossing through “private” and “public” to support kinship through communal labour, queer relationality and mooring. The resulting design works to set adrift bodies in a sea of sensations through a mix of pleasure programmes. To conclude, through three design proposals, this design research creates a relationship between queer anti-urbanism and design. It asserts that queering the design process and outcome allows a more inclusive way to consider place, space and belonging. The projects lend to a queer relationality and interdependence by making spaces that support the unsettled, out-of-place, but is it queer enough?

Keywords: queer, queer anti-urbanism, design as research, design

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Authors: Celeste E. van Rinsum, Sanne M. P. L. Gerards, Geert M. Rutten, Ien A. M. van de Goor, Stef P. J. Kremers

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Combined lifestyle interventions have shown to be effective in changing and maintaining behavioral lifestyle changes and reducing overweight and obesity. A lifestyle coach is expected to promote lifestyle changes in adults related to physical activity and diet. The present Coaching on Lifestyle (CooL) study examined participants’ physical activity level, dietary behavioral, and motivational changes immediately after the intervention and at 1.5 years after baseline. In CooL intervention a lifestyle coach coaches individuals from eighteen years and older with (a high risk of) obesity in group and individual sessions. In addition a process evaluation was conducted in order to examine the implementation process and to be able to interpret the changes within the participants. This action-oriented research has a pre-post design. Participants of the CooL intervention (N = 200) completed three questionnaires: at baseline, immediately after the intervention (on average after 44 weeks), and at 1.5 years after baseline. T-tests and linear regressions were conducted to test self-reported changes in physical activity (IPAQ), dietary behaviors, their quality of motivation for physical activity (BREQ-3) and for diet (REBS), body mass index (BMI), and quality of life (EQ-5D-3L). For the process evaluation, we used individual and group interviews, observations and document analyses to gain insight in the implementation process (e.g. the recruitment) and how the intervention was valued by the participants, lifestyle coaches, and referrers. The study is currently ongoing and therefore the results presented here are preliminary. On average, the participants that finished the intervention and those that have completed the long-term measurement improved their level of vigorous-intense physical activity, sedentary behavior, sugar-sweetened beverage consumption and BMI. Mixed results were observed in motivational regulation for physical activity and nutrition. Moreover, an improvement on the quality of life dimension anxiety/depression was found, also in the long-term. All the other constructs did not show significant change over time. The results of the process evaluation have shown that recruitment of clients was difficult. Participants evaluated the intervention positively and the lifestyle coaches have continuously adapted the structure and contents of the intervention throughout the study period, based on their experiences and feedback from research. Preliminary results indicate that the CooL-intervention may have beneficial effects on overweight and obese participants in terms of energy balance-related behaviors, weight reduction, and quality of life. Recruitment of participants and embedding the position of the lifestyle coach in traditional care structures is challenging.

Keywords: combined lifestyle intervention, effect evaluation, lifestyle coaching, process evaluation, overweight, the Netherlands

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Authors: Juan A. Arzate, Funda C. Ertem, M. Nicolas Cruz-Bournazou, Peter Neubauer, Stefan Junne

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— One of the biggest challenges the world faces today is global warming that is caused by greenhouse gases (GHGs) coming from the combustion of fossil fuels for energy generation. In order to mitigate climate change, the European Union has committed to reducing GHG emissions to 80–95% below the level of the 1990s by the year 2050. Renewable technologies are vital to diminish energy-related GHG emissions. Since water and biomass are limited resources, the largest contributions to renewable energy (RE) systems will have to come from wind and solar power. Nevertheless, high proportions of fluctuating RE will present a number of challenges, especially regarding the need to balance the variable energy demand with the weather dependent fluctuation of energy supply. Therefore, biogas plants in this content would play an important role, since they are easily adaptable. Feedstock availability varies locally or seasonally; however there is a lack of knowledge in how biogas plants should be operated in a stable manner by local feedstock. This problem may be prevented through suitable control strategies. Such strategies require the development of convenient mathematical models, which fairly describe the main processes. Modelling allows us to predict the system behavior of biogas plants when different feedstocks are used with different loading rates. Life cycle assessment (LCA) is a technique for analyzing several sides from evolution of a product till its disposal in an environmental point of view. It is highly recommend to use as a decision making tool. In order to achieve suitable strategies, the combination of a flexible energy generation provided by biogas plants, a secure production process and the maximization of the environmental benefits can be obtained by the combination of process modelling and LCA approaches. For this reason, this study focuses on the biogas plant which flexibly generates required energy from the co-digestion of maize, grass and cattle manure, while emitting the lowest amount of GHG´s. To achieve this goal AMOCO model was combined with LCA. The program was structured in Matlab to simulate any biogas process based on the AMOCO model and combined with the equations necessary to obtain climate change, acidification and eutrophication potentials of the whole production system based on ReCiPe midpoint v.1.06 methodology. Developed simulation was optimized based on real data from operating biogas plants and existing literature research. The results prove that AMOCO model can successfully imitate the system behavior of biogas plants and the necessary time required for the process to adapt in order to generate demanded energy from available feedstock. Combination with LCA approach provided opportunity to keep the resulting emissions from operation at the lowest possible level. This would allow for a prediction of the process, when the feedstock utilization supports the establishment of closed material circles within a smart bio-production grid – under the constraint of minimal drawbacks for the environment and maximal sustainability.

Keywords: AMOCO model, GHG emissions, life cycle assessment, modelling

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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: Ioanna Taouki, Marie Lallier, David Soto

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Metacognition refers to the capacity to reflect upon our own cognitive processes. Although there is an ongoing discussion in the literature on the role of metacognition in learning and academic achievement, little is known about its neurodevelopmental trajectories in early childhood, when children begin to receive formal education in reading. Here, we evaluate the metacognitive ability, estimated under a recently developed Signal Detection Theory model, of a cohort of children aged between 6 and 7 (N=60), who performed three two-alternative-forced-choice tasks (two linguistic: lexical decision task, visual attention span task, and one non-linguistic: emotion recognition task) including trial-by-trial confidence judgements. Our study has three aims. First, we investigated how metacognitive ability (i.e., how confidence ratings track accuracy in the task) relates to performance in general standardized tasks related to students' reading and general cognitive abilities using Spearman's and Bayesian correlation analysis. Second, we assessed whether or not young children recruit common mechanisms supporting metacognition across the different task domains or whether there is evidence for domain-specific metacognition at this early stage of development. This was done by examining correlations in metacognitive measures across different task domains and evaluating cross-task covariance by applying a hierarchical Bayesian model. Third, using robust linear regression and Bayesian regression models, we assessed whether metacognitive ability in this early stage is related to the longitudinal learning of children in a linguistic and a non-linguistic task. Notably, we did not observe any association between students’ reading skills and metacognitive processing in this early stage of reading acquisition. Some evidence consistent with domain-general metacognition was found, with significant positive correlations between metacognitive efficiency between lexical and emotion recognition tasks and substantial covariance indicated by the Bayesian model. However, no reliable correlations were found between metacognitive performance in the visual attention span and the remaining tasks. Remarkably, metacognitive ability significantly predicted children's learning in linguistic and non-linguistic domains a year later. These results suggest that metacognitive skill may be dissociated to some extent from general (i.e., language and attention) abilities and further stress the importance of creating educational programs that foster students’ metacognitive ability as a tool for long term learning. More research is crucial to understand whether these programs can enhance metacognitive ability as a transferable skill across distinct domains or whether unique domains should be targeted separately.

Keywords: confidence ratings, development, metacognitive efficiency, reading acquisition

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Authors: Maria Ledinskaya

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This paper examines the Morris Collection Conservation Project at the Sainsbury Centre for Visual Arts in the context of Agile, Lean, and Hybrid project management. It is part case study and part literature review. To date, relatively little has been written about non-traditional project management approaches in heritage conservation. This paper seeks to introduce Agile, Lean, and Hybrid project management concepts from business, software development, and manufacturing fields to museum conservation, by referencing their practical application on a recent museum-based conservation project. The Morris Collection Conservation Project was carried out in 2019-2021 in Norwich, UK, and concerned the remedial conservation of around 150 Abstract Constructivist artworks bequeathed to the Sainsbury Centre for Visual Arts by private collectors Michael and Joyce Morris. The first part introduces the chronological timeline and key elements of the project. It describes a medium-size conservation project of moderate complexity, which was planned and delivered in an environment with multiple known unknowns – unresearched collection, unknown condition and materials, unconfirmed budget. The project was also impacted by the unknown unknowns of the COVID-19 pandemic, such as indeterminate lockdowns, and the need to accommodate social distancing and remote communications. The author, a staff conservator at the Sainsbury Centre who acted as project manager on the Morris Collection Conservation Project, presents an incremental, iterative, and value-based approach to managing a conservation project in an uncertain environment. Subsequent sections examine the project from the point of view of Traditional, Agile, Lean, and Hybrid project management. The author argues that most academic writing on project management in conservation has focussed on a Traditional plan-driven approach – also known as Waterfall project management – which has significant drawbacks in today’s museum environment, due to its over-reliance on prediction-based planning and its low tolerance to change. In the last 20 years, alternative Agile, Lean and Hybrid approaches to project management have been widely adopted in software development, manufacturing, and other industries, although their recognition in the museum sector has been slow. Using examples from the Morris Collection Conservation Project, the author introduces key principles and tools of Agile, Lean, and Hybrid project management and presents a series of arguments on the effectiveness of these alternative methodologies in museum conservation, as well as the ethical and practical challenges to their implementation. These project management approaches are discussed in the context of consequentialist, relativist, and utilitarian developments in contemporary conservation ethics, particularly with respect to change management, bespoke ethics, shared decision-making, and value-based cost-benefit conservation strategy. The author concludes that the Morris Collection Conservation Project had multiple Agile and Lean features which were instrumental to the successful delivery of the project. These key features are identified as distributed decision making, a co-located cross-disciplinary team, servant leadership, focus on value-added work, flexible planning done in shorter sprint cycles, light documentation, and emphasis on reducing procedural, financial, and logistical waste. Overall, the author’s findings point largely in favour of a Hybrid model which combines traditional and alternative project processes and tools to suit the specific needs of the project.

Keywords: project management, conservation, waterfall, agile, lean, hybrid

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Authors: Vinay A. Sharma, Shiva Prasad H. C.

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The initial stages of any project are often observed to be in a mixed set of conditions. Setting up the project is a tough task, but taking the initial decisions is rather not complex, as some of the critical factors are yet to be introduced into the scenario. These simple initial decisions potentially shape the timeline and subsequent events that might later be plotted on it. Proceeding towards the solution for a problem is the primary objective in the initial stages. The optimization in the solutions can come later, and hence, the resources deployed towards attaining the solution are higher than what they would have been in the optimized versions. A ‘logic’ that counters the problem is essentially the core of the desired solution. Thus, if the problem is solved, the deployment of resources has led to the required logic being attained. As the project proceeds along, the individuals working on the project face fresh challenges as a team and are better accustomed to their surroundings. The developed, optimized solutions are then considered for implementation, as the individuals are now experienced, and know better of the consequences and causes of possible failure, and thus integrate the adequate tolerances wherever required. Furthermore, as the team graduates in terms of strength, acquires prodigious knowledge, and begins its efficient transfer, the individuals in charge of the project along with the managers focus more on the optimized solutions rather than the traditional ones to minimize the required resources. Hence, as time progresses, the authorities prioritize attainment of the required logic, at a lower amount of dedicated resources. For empirical analysis of the stated theory, leaders and key figures in organizations are surveyed for their ideas on appropriate logic required for tackling a problem. Key-pointers spotted in successfully implemented solutions are noted from the analysis of the responses and a metric for measuring logic is developed. A graph is plotted with the quantifiable logic on the Y-axis, and the dedicated resources for the solutions to various problems on the X-axis. The dedicated resources are plotted over time, and hence the X-axis is also a measure of time. In the initial stages of the project, the graph is rather linear, as the required logic will be attained, but the consumed resources are also high. With time, the authorities begin focusing on optimized solutions, since the logic attained through them is higher, but the resources deployed are comparatively lower. Hence, the difference between consecutive plotted ‘resources’ reduces and as a result, the slope of the graph gradually increases. On an overview, the graph takes a parabolic shape (beginning on the origin), as with each resource investment, ideally, the difference keeps on decreasing, and the logic attained through the solution keeps increasing. Even if the resource investment is higher, the managers and authorities, ideally make sure that the investment is being made on a proportionally high logic for a larger problem, that is, ideally the slope of the graph increases with the plotting of each point.

Keywords: decision-making, leadership, logic, strategic management

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Authors: Soumya Dutta

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This research paper aims at investigating the impact of emotional intelligence and cognitive intelligence on radio presenter’s performance in the All India Radio, Kolkata (India’s public service broadcaster). The ancient concept of productivity is the ratio of what is produced to what is required to produce it. But, father of modern management Peter F. Drucker (1909-2005) defined productivity of knowledge work and knowledge workers in a new form. In the other hand, the concept of Emotional Intelligence (EI) originated back in 1920’s when Thorndike (1920) for the first time proposed the emotional intelligence into three dimensions, i.e., abstract intelligence, mechanical intelligence, and social intelligence. The contribution of Salovey and Mayer (1990) is substantive, as they proposed a model for emotional intelligence by defining EI as part of the social intelligence, which takes measures the ability of an individual to regulate his/her personal and other’s emotions and feeling. Cognitive intelligence illustrates the specialization of general intelligence in the domain of cognition in ways that possess experience and learning about cognitive processes such as memory. The outcomes of past research on emotional intelligence show that emotional intelligence has a positive effect on social- mental factors of human resource; positive effects of emotional intelligence on leaders and followers in terms of performance, results, work, satisfaction; emotional intelligence has a positive and significant relationship with the teachers' job performance. In this paper, we made a conceptual framework based on theories of emotional intelligence proposed by Salovey and Mayer (1989-1990) and a compensatory model of emotional intelligence, cognitive intelligence, and job performance proposed by Stephen Cote and Christopher T. H. Miners (2006). For investigating the impact of emotional intelligence and cognitive intelligence on radio presenter’s performance, sample size consists 59 radio presenters (considering gender, academic qualification, instructional mood, age group, etc.) from All India Radio, Kolkata station. Questionnaires prepared based on cognitive (henceforth called C based and represented by C1, C2,.., C5) as well as emotional intelligence (henceforth called E based and represented by E1, E2,., E20). These were sent to around 59 respondents (Presenters) for getting their responses. Performance score was collected from the report of program executive of All India Radio, Kolkata. The linear regression has been carried out using all the E-based and C-based variables as the predictor variables. The possible problem of autocorrelation has been tested by having the Durbinson-Watson (DW) Statistic. Values of this statistic, almost within the range of 1.80-2.20, indicate the absence of any significant problem of autocorrelation. The possible problem of multicollinearity has been tested by having the Variable Inflation Factor (VIF) value. Values of this statistic, around within 2, indicates the absence of any significant problem of multicollinearity. It is inferred that the performance scores can be statistically regressed linearly on the E-based and C-based scores, which can explain 74.50% of the variations in the performance.

Keywords: cognitive intelligence, emotional intelligence, performance, productivity

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Authors: Abderrazak Bannari, Ghadeer Kadhem

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The objectives of this paper are the validation and the evaluation of MBES-CARIS BASE surface data performance for bathymetric mapping of shallow water in the Kingdom of Bahrain. The latter is an archipelago with a total land area of about 765.30 km², approximately 126 km of coastline and 8,000 km² of marine area, located in the Arabian Gulf, east of Saudi Arabia and west of Qatar (26° 00’ N, 50° 33’ E). To achieve our objectives, bathymetric attributed grid files (X, Y, and depth) generated from the coverage of ship-track MBSE data with 300 x 300 m cells, processed with CARIS-HIPS, were downloaded from the General Bathymetric Chart of the Oceans (GEBCO). Then, brought into ArcGIS and converted into a raster format following five steps: Exportation of GEBCO BASE surface data to the ASCII file; conversion of ASCII file to a points shape file; extraction of the area points covering the water boundary of the Kingdom of Bahrain and multiplying the depth values by -1 to get the negative values. Then, the simple Kriging method was used in ArcMap environment to generate a new raster bathymetric grid surface of 30×30 m cells, which was the basis of the subsequent analysis. Finally, for validation purposes, 2200 bathymetric points were extracted from a medium scale nautical map (1:100 000) considering different depths over the Bahrain national water boundary. The nautical map was scanned, georeferenced and overlaid on the MBES-CARIS generated raster bathymetric grid surface (step 5 above), and then homologous depth points were selected. Statistical analysis, expressed as a linear error at the 95% confidence level, showed a strong correlation coefficient (R² = 0.96) and a low RMSE (± 0.57 m) between the nautical map and derived MBSE-CARIS depths if we consider only the shallow areas with depths of less than 10 m (about 800 validation points). When we consider only deeper areas (> 10 m) the correlation coefficient is equal to 0.73 and the RMSE is equal to ± 2.43 m while if we consider the totality of 2200 validation points including all depths, the correlation coefficient is still significant (R² = 0.81) with satisfactory RMSE (± 1.57 m). Certainly, this significant variation can be caused by the MBSE that did not completely cover the bottom in several of the deeper pockmarks because of the rapid change in depth. In addition, steep slopes and the rough seafloor probably affect the acquired MBSE raw data. In addition, the interpolation of missed area values between MBSE acquisition swaths-lines (ship-tracked sounding data) may not reflect the true depths of these missed areas. However, globally the results of the MBES-CARIS data are very appropriate for bathymetric mapping of shallow water areas.

Keywords: bathymetry mapping, multibeam echosounder systems, CARIS-HIPS, shallow water

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Authors: Anchal Rana

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Indian Himalayas with their diverse climatic conditions are home to many rare and endangered medicinal flora. One such species is Polygonatum verticillatum Linn., popularly known as King Solomon’s Seal or Solomon’s Seal. Its mention as an incredible medicinal herb comes from 5000 years ago in Indian Materia Medica as a component of Ashtavarga, a poly-herbal formulation comprising of eight herbs illustrated as world’s first ever revitalizing and rejuvenating nutraceutical food, which is now commercialised in the name ‘Chaywanprash’. It is an erect tall (60 to 120 cm) perennial herb with sessile, linear leaves and white pendulous flowers. The species grows well in an altitude range of 1600 to 3600 m amsl, and propagates mostly through rhizomes. The rhizomes are potential source for significant phytochemicals like flavonoids, phenolics, lectins, terpenoids, allantoin, diosgenin, β-Sitosterol and quinine. The presence of such phytochemicals makes the species an asset for antioxidant, cardiotonic, demulcent, diuretic, energizer, emollient, aphrodisiac, appetizer, glactagogue, etc. properties. Having profound concentrations of macro and micronutrients, species has fine prospects of being used as a diet supplement. However, due to unscientific and gregarious uprooting, it has been assigned a status of ‘vulnerable’ and ‘endangered’ in the Conservation Assessment and Management Plan (CAMP) process conducted by Foundation for Revitalisation of Local Health Traditions (FRLHT) during 2010, according to IUCN Red-List Criteria. Further, destructive harvesting, land use disturbances, heavy livestock grazing, climatic changes and habitat fragmentation have substantially contributed towards anomaly of the species. It, therefore, became imperative to conserve the diversity of the species and make judicious use in future research and commercial programme and schemes. A Gene Bank was therefore established at High Altitude Herbal Garden of the Forest Research Institute, Dehradun, India situated at Chakarata (30042’52.99’’N, 77051’36.77’’E, 2205 m amsl) consisting 149 accessions collected from thirty-one geographical locations spread over three Himalayan States of Jammu and Kashmir, Himachal Pradesh, and Uttarakhand. The present investigations purport towards sampling and collection of divergent germplasm followed by planting and cultivation techniques. The ultimate aim is thereby focussed on analysing genetic diversity of the species and capturing promising genotypes for carrying out further genetic improvement programme so to contribute towards sustainable development and healthcare.

Keywords: Polygonatum verticillatum Linn., phytochemicals, genetic diversity, conservation, gene bank

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Authors: Bishnupriya Sahoo, Prasad K. Bhaskaran

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Tropical cyclone is one among the worst natural hazards that results in a trail of destruction causing enormous damage to life, property, and coastal infrastructures. In a global perspective, the Indian Ocean is considered as one of the cyclone prone basins in the world. Specifically, the frequency of cyclogenesis in the Bay of Bengal is higher compared to the Arabian Sea. Out of the four maritime states in the East coast of India, Odisha is highly susceptible to tropical cyclone landfall. Historical records clearly decipher the fact that the frequency of cyclones have reduced in this basin. However, in the recent decades, the intensity and size of tropical cyclones have increased. This is a matter of concern as the risk and vulnerability level of Odisha coast exposed to high wind speed and gusts during cyclone landfall have increased. In this context, there is a need to assess and evaluate the severity of coastal risk, area of exposure under risk, and associated vulnerability with a higher dimension in a multi-risk perspective. Changing climate can result in the emergence of a new hazard and vulnerability over a region with differential spatial and socio-economic impact. Hence there is a need to have coastal vulnerability projections in a changing climate scenario. With this motivation, the present study attempts to estimate the destructiveness of tropical cyclones based on Power Dissipation Index (PDI) for those cyclones that made landfall along Odisha coast that exhibits an increasing trend based on historical data. The study also covers the futuristic scenarios of integral coastal vulnerability based on the trends in PDI for the Odisha coast. This study considers 11 essential and important parameters; the cyclone intensity, storm surge, onshore inundation, mean tidal range, continental shelf slope, topo-graphic elevation onshore, rate of shoreline change, maximum wave height, relative sea level rise, rainfall distribution, and coastal geomorphology. The study signifies that over a decadal scale, the coastal vulnerability index (CVI) depends largely on the incremental change in variables such as cyclone intensity, storm surge, and associated inundation. In addition, the study also performs a critical analysis on the modulation of PDI on storm surge and inundation characteristics for the entire coastal belt of Odisha State. Interestingly, the study brings to light that a linear correlation exists between the storm-tide with PDI. The trend analysis of PDI and its projection for coastal Odisha have direct practical applications in effective coastal zone management and vulnerability assessment.

Keywords: Bay of Bengal, coastal vulnerability index, power dissipation index, tropical cyclone

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