Search results for: cosine similarity

Authors: Nassima Noufail, Sara Bouhali

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In this work, we develop a semi-supervised solution for the purpose of action detection in videos and propose an efficient algorithm for video segmentation. The approach is divided into video segmentation, feature extraction, and classification. In the first part, a video is segmented into clips, and we used the K-means algorithm for this segmentation; our goal is to find groups based on similarity in the video. The application of k-means clustering into all the frames is time-consuming; therefore, we started by the identification of transition frames where the scene in the video changes significantly, and then we applied K-means clustering into these transition frames. We used two image filters, the gaussian filter and the Laplacian of Gaussian. Each filter extracts a set of features from the frames. The Gaussian filter blurs the image and omits the higher frequencies, and the Laplacian of gaussian detects regions of rapid intensity changes; we then used this vector of filter responses as an input to our k-means algorithm. The output is a set of cluster centers. Each video frame pixel is then mapped to the nearest cluster center and painted with a corresponding color to form a visual map. The resulting visual map had similar pixels grouped. We then computed a cluster score indicating how clusters are near each other and plotted a signal representing frame number vs. clustering score. Our hypothesis was that the evolution of the signal would not change if semantically related events were happening in the scene. We marked the breakpoints at which the root mean square level of the signal changes significantly, and each breakpoint is an indication of the beginning of a new video segment. In the second part, for each segment from part 1, we randomly selected a 16-frame clip, then we extracted spatiotemporal features using convolutional 3D network C3D for every 16 frames using a pre-trained model. The C3D final output is a 512-feature vector dimension; hence we used principal component analysis (PCA) for dimensionality reduction. The final part is the classification. The C3D feature vectors are used as input to a multi-class linear support vector machine (SVM) for the training model, and we used a multi-classifier to detect the action. We evaluated our experiment on the UCF101 dataset, which consists of 101 human action categories, and we achieved an accuracy that outperforms the state of art by 1.2%.

Keywords: video segmentation, action detection, classification, Kmeans, C3D

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Authors: Pedro Augusto Da Silva E Souza Miranda, Niloofar Jalali, Shweta Mistry

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BACKGROUND: Software developers utilize automated solutions to scrape users’ reviews to extract meaningful knowledge to identify problems (e.g., bugs, compatibility issues) and possible enhancements (e.g., users’ requests) to their solutions. However, most of these solutions do not consider the health risk aspects to users. Recent works have shed light on the importance of including health risk considerations in the development cycle of mHealth apps to prevent harm to its users. PROBLEM: The COVID-19 Pandemic in Canada (and World) is currently forcing physical distancing upon the general population. This new lifestyle made the usage of mHealth applications more essential than ever, with a projected market forecast of 332 billion dollars by 2025. However, this new insurgency in mHealth usage comes with possible risks to users’ health due to mHealth apps problems (e.g., wrong insulin dosage indication due to a UI error). OBJECTIVE: These works aim to raise awareness amongst mHealth developers of the importance of considering risks to users’ health within their development lifecycle. Moreover, this work also aims to help mHealth developers with a Proof-of-Concept (POC) solution to understand, process, and identify possible health risks to users of mHealth apps based on users’ reviews. METHODS: We conducted a mixed-method study design. We developed a crawler to mine the negative reviews from two samples of mHealth apps (my fitness, medisafe) from the Google Play store users. For each mHealth app, we performed the following steps: • The reviews are divided into two groups, before starting the COVID-19 (reviews’ submission date before 15 Feb 2019) and during the COVID-19 (reviews’ submission date starts from 16 Feb 2019 till Dec 2020). For each period, the Latent Dirichlet Allocation (LDA) topic model was used to identify the different clusters of reviews based on similar topics of review The topics before and during COVID-19 are compared, and the significant difference in frequency and severity of similar topics are identified. RESULTS: We successfully scraped, filtered, processed, and identified health-related topics in both qualitative and quantitative approaches. The results demonstrated the similarity between topics before and during the COVID-19.

Keywords: natural language processing (NLP), topic modeling, mHealth, COVID-19, software engineering, telemedicine, health risks

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Authors: Nikolai N. Bogolubov, Andrey V. Soldatov

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Terahertz radiation occupies a range of frequencies somewhere from 100 GHz to approximately 10 THz, just between microwaves and infrared waves. This range of frequencies holds promise for many useful applications in experimental applied physics and technology. At the same time, reliable, simple techniques for generation, amplification, and modulation of electromagnetic radiation in this range are far from been developed enough to meet the requirements of its practical usage, especially in comparison to the level of technological abilities already achieved for other domains of the electromagnetic spectrum. This situation of relative underdevelopment of this potentially very important range of electromagnetic spectrum is known under the name of the 'terahertz gap.' Among other things, technological progress in the terahertz area has been impeded by the lack of compact, low energy consumption, easily controlled and continuously radiating terahertz radiation sources. Therefore, development of new techniques serving this purpose as well as various devices based on them is of obvious necessity. No doubt, it would be highly advantageous to employ the simplest of suitable physical systems as major critical components in these techniques and devices. The purpose of the present research was to show by means of conventional methods of non-equilibrium statistical mechanics and the theory of open quantum systems, that a thoroughly studied two-level quantum system, also known as an one-electron two-level 'atom', being driven by external classical monochromatic high-frequency (e.g. laser) field, can radiate continuously at much lower (e.g. terahertz) frequency in the fluorescent regime if the transition dipole moment operator of this 'atom' possesses permanent non-equal diagonal matrix elements. This assumption contradicts conventional assumption routinely made in quantum optics that only the non-diagonal matrix elements persist. The conventional assumption is pertinent to natural atoms and molecules and stems from the property of spatial inversion symmetry of their eigenstates. At the same time, such an assumption is justified no more in regard to artificially manufactured quantum systems of reduced dimensionality, such as, for example, quantum dots, which are often nicknamed 'artificial atoms' due to striking similarity of their optical properties to those ones of the real atoms. Possible ways to experimental observation and practical implementation of the predicted effect are discussed too.

Keywords: terahertz gap, two-level atom, resonant fluorescence, quantum dot, resonant fluorescence, two-level atom

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Authors: Nurvadi Albekov

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Communicative situation is a basis, which designates potential models of ‘constructed forms’, a motivated basis of a text, for a text can be assumed as a product of the communicative situation. It is within the field of emergence the models of text, that can be potentially prognosticated in a certain communicative situation, are designated. Every text can be assumed as conceptual system structured on the base of certain communicative situation. However in the process of ‘structuring’ of a certain model of ‘conceptual system’ consciousness of a recipient is able act only within the border of the field of emergence for going out of this border indicates misunderstanding of the communicative situation. On the base of communicative situation we can witness the increment of meaning where the synergizing of the informative model of communication, formed by using of the invariant units of a language system, is a result of verbalization of the communicative situation. The potential of the models of a text, prognosticated within the field of emergence, also depends on the communicative situation. The conception ‘the field of emergence’ is interpreted as a unit of the language system, having poly-directed universal structure, implying the presence of the core, the center and the periphery, including different levels of means of a functioning system of language, both in terms of linguistic resources, and in terms of extra linguistic factors interaction of which results increment of a text. The conception ‘field of emergence’ is considered as the most promising in the analysis of texts: oral, written, printed and electronic. As a unit of the language system field of emergence has several properties that predict its use during the study of a text in different levels. This work is an attempt analysis of entropy in a text in the aspect of lingua-cultural code, prognosticated within the model of the field of emergence. The article describes the problem of entropy in the field of emergence, caused by influence of the extra-linguistic factors. The increasing of entropy is caused not only by the fact of intrusion of the language resources but by influence of the alien culture in a whole, and by appearance of non-typical for this very culture symbols in the field of emergence. The borrowing of alien lingua-cultural symbols into the lingua-culture of the author is a reason of increasing the entropy when constructing a text both in meaning and in structuring level. It is nothing but artificial formatting of lexical units that violate stylistic unity of a phrase. It is marked that one of the important characteristics descending the entropy in the field of emergence is a typical similarity of lexical and semantic resources of the different lingua-cultures in aspects of extra linguistic factors.

Keywords: communicative situation, field of emergence, lingua-culture, entropy

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Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

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It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

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Authors: Morgan Cheng, Wilson Ho, Max Yiu, Dragon Tsui, Wylog Wong, Richard Kwan, K. C. Lam, Hannah Lo, C. L. Wong

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Hong Kong has been known worldwide for its ability to thrive under trying circumstances. The 7.5 million residents of this mature and busy metropolis are living in a primarily high-rise city whereby development and renewal of the cityscape are taking place unceasingly. Hong Kong residents are therefore affected by the virtually continuous and numerous construction activities. In 2020, the Hong Kong environmental protection department (EPD) completed a feasibility study on managing construction noise, including those associated with the renovation of domestic premises. Part of the study was the review of management and control of construction noise in other metropolitan cities globally. As far as the authors are aware of, such worldwide and extensive review of best practices on construction noise control has not been conducted for over 20 years. In order to benefit from international best practices, the extensive review is to identify possible areas for improvement in Hong Kong. The consultant of the study first referred to the United Nations Report ‘The World’s Cities in 2016’ and examined the top 100 cities therein. The 20 most suitable cities were then chosen for further review. Upon screening of each of these 20 cities, 12 cities with the more relevant management practices were selected for further scrutiny. These 12 cities were: Asia – Tokyo, Seoul, Taipei, Guangzhou, Singapore; Europe – City of Westminster (London), Berlin; North America – Toronto, New York City, San Francisco; Oceania – Sydney, Melbourne. Afterwards, three cities, namely Sydney, City of Westminster, and New York City, were selected for in-depth review. These cities were chosen primarily because of the maturity, success, and effectiveness of their construction noise management and control measures, as well as their similarity to Hong Kong in key and selected aspects. One of the more important findings of the review is the usefulness of early focus, with the aim of designing the noise issues away wherever practicable. The consultant examined the similar yet different construction noise early focus mechanisms of the three cities. This paper describes this landmark worldwide and extensive review of international best practices on construction noise management and control. The methodology, approach, and key findings are presented to give readers a succinct yet comprehensive view. The authors shared the findings with the acoustics professionals worldwide with the hope of global advancement of more mature construction noise management while welcoming sustainable development and construction.

Keywords: construction noise, international best practices, noise control, noise management

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Authors: Asif Hasan

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Among the reported suitable mariculture species in Bangladesh, seabass and mullet are the two most popular candidates due to their high market values. Several field studies conducted on the culture of seabass in Bangladesh, it still remains a challenge to commercially grow this species due to its exclusive carnivorous nature. In contrast, the grey mullet (M. cephalus) is a fast-growing, omnivorous euryhaline fish that has shown excellent growth in many areas including South Asia. Choice of a sustainable aquaculture technique must consider the productivity and yield as well as their environmental suitability. This study was designed to elucidate the ecologically suitable culture technique of M. cephalus in brakishwater ponds by comparing the biotic and abiotic components of pond ecosystem. In addition to growth parameters (yield, ADG, SGR, weight gain, FCR), Physicochemical parameters (Temperature, DO, pH, salinity, TDS, transparency, ammonia, and Chlorophyll-a concentration) and biological community composition (phytoplankton, zooplankton and benthic macroinvertebrates) were investigated from ponds under Semi-intensive, Improve extensive and Traditional culture system. While temperature were similar in the three culture types, ponds under improve-extensive showed better environmental conditions with significantly higher mean DO and transparency, and lower TDS and Chlorophyll-a. The abundance of zooplankton, phytoplankton and benthic macroinvertebrates were apparently higher in semi-intensive ponds. The Analysis of Similarity (ANOSIM) suggested moderate difference in the planktonic community composition. While the fish growth parameters of M. cephalus and total yield did not differ significantly between three systems, M. cephalus yield (kg/decimal) was apparently higher in semi-intensive pond due to high stocking density and intensive feeding. The results suggested that the difference between the three systems were due to more efficient utilization of nutrients in improve extensive ponds which affected fish growth through trophic cascades. This study suggested that different culture system of M. cephalus is an alternative and more beneficial method owing to its ecological and economic benefits in brackishwater ponds.

Keywords: Mugil cephalus, pond ecosystem, mariculture, fisheries management

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Authors: Ashish Trivedi, Amol Singh

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In the recent years, the magnitude and frequency of disasters have increased at an alarming rate. Every year, more than 400 natural disasters affect global population. A large-scale disaster leads to destruction or damage to houses, thereby rendering a notable number of residents homeless. Since humanitarian response and recovery process takes considerable time, temporary establishments are arranged in order to provide shelter to affected population. These shelter areas are vital for an effective humanitarian relief; therefore, they must be strategically planned. Choosing the locations of temporary shelter areas for accommodating homeless people is critical to the quality of humanitarian assistance provided after a large-scale emergency. There has been extensive research on the facility location problem both in theory and in application. In order to deliver sufficient relief aid within a relatively short timeframe, humanitarian relief organisations pre-position warehouses at strategic locations. However, such approaches have received limited attention from the perspective of providing shelters to disaster-affected people. In present research work, this aspect of humanitarian logistics is considered. The present work proposes a hybrid decision support model to determine relative preference of potential shelter locations by assessing them based on key subjective criteria. Initially, the factors that are kept in mind while locating potential areas for establishing temporary shelters are identified by reviewing extant literature and through consultation from a panel of disaster management experts. In order to determine relative importance of individual criteria by taking into account subjectivity of judgements, a hybrid approach of fuzzy sets and Analytic Hierarchy Process (AHP) was adopted. Further, Technique for order preference by similarity to ideal solution (TOPSIS) was applied on an illustrative data set to evaluate potential locations for establishing temporary shelter areas for homeless people in a disaster scenario. The contribution of this work is to propose a range of possible shelter locations for a humanitarian relief organization, using a robust multi criteria decision support framework.

Keywords: AHP, disaster preparedness, fuzzy set theory, humanitarian logistics, TOPSIS, temporary shelters

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Authors: Natalia Rudeli, Elisabeth Viles, Adrian Santilli

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Delays in the construction industry are a global phenomenon. Many construction projects experience extensive delays exceeding the initially estimated completion time. The main purpose of this study is to identify construction projects typical behaviors in order to develop a prognosis and management tool. Being able to know a construction projects schedule tendency will enable evidence-based decision-making to allow resolutions to be made before delays occur. This study presents an innovative approach that uses Cluster Analysis Method to support predictions during Earned Value Analyses. A clustering analysis was used to predict future scheduling, Earned Value Management (EVM), and Earned Schedule (ES) principal Indexes behaviors in construction projects. The analysis was made using a database with 90 different construction projects. It was validated with additional data extracted from literature and with another 15 contrasting projects. For all projects, planned and executed schedules were collected and the EVM and ES principal indexes were calculated. A complete linkage classification method was used. In this way, the cluster analysis made considers that the distance (or similarity) between two clusters must be measured by its most disparate elements, i.e. that the distance is given by the maximum span among its components. Finally, through the use of EVM and ES Indexes and Tukey and Fisher Pairwise Comparisons, the statistical dissimilarity was verified and four clusters were obtained. It can be said that construction projects show an average delay of 35% of its planned completion time. Furthermore, four typical behaviors were found and for each of the obtained clusters, the interim milestones and the necessary rhythms of construction were identified. In general, detected typical behaviors are: (1) Projects that perform a 5% of work advance in the first two tenths and maintain a constant rhythm until completion (greater than 10% for each remaining tenth), being able to finish on the initially estimated time. (2) Projects that start with an adequate construction rate but suffer minor delays culminating with a total delay of almost 27% of the planned time. (3) Projects which start with a performance below the planned rate and end up with an average delay of 64%, and (4) projects that begin with a poor performance, suffer great delays and end up with an average delay of a 120% of the planned completion time. The obtained clusters compose a tool to identify the behavior of new construction projects by comparing their current work performance to the validated database, thus allowing the correction of initial estimations towards more accurate completion schedules.

Keywords: cluster analysis, construction management, earned value, schedule

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Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: Angela Maria Fenu

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The aim of this study was to better characterize the nature of word association responses in people with aphasia. The participants selected for the experimental group were 4 individuals with mild Broca’s aphasia. The control group consisted of 51 cognitively intact age- and gender-matched individuals. The participants were asked to perform a word association task in which they had to say the first word they thought of when hearing each cue. The cue words (n= 16) were the translation in Italian of the set of English cue words of a published study. The participants from the experimental group were administered the word association test every two weeks for a period of two months when they received speech-language therapy A combination of analytical approaches to measure the data was used. To analyse different patterns of word association responses in both groups, the nature of the relationship between the cue and the response was examined: responses were divided into five categories of association. To investigate the similarity between aphasic and non-aphasic subjects, the stereotypy of responses was examined.While certain stimulus words (nouns, adjectives) elicited responses from Broca’s aphasics that tended to resemble those made by non-aphasic subjects; others (adverbs, verbs) showed the tendency to elicit responses different from the ones given by normal subjects. This suggests that some mechanisms underlying certain types of associations are degraded in aphasics individuals, while others display little evidence of disruption. The high number of paradigmatic associations given in response to a noun or an adjective might imply that the mechanisms, largely semantic, underlying paradigmatic associations are relatively preserved in Broca’s aphasia, but it might also mean that some words are more easily processed depending on their grammatical class (nouns, adjectives). The most significant variation was noticed when the grammatical class of the cue word was an adverb. Unlike the normal individuals, the experimental subjects gave the most idiosyncratic associations, which are often produced when the attempt to give a paradigmatic response fails. In turn, the failure to retrieve paradigmatic responses when the cue is an adverb might suggest that Broca’s aphasics are more sensitive to this grammatical class.The findings from this study suggest that, from research on word associations in people with aphasia, important data can arise concerning the specific lexical retrieval impairments that characterize the different types of aphasia and the various treatments that might positively influence the kinds of word association responses affected by language disruption.

Keywords: aphasia therapy, clinical linguistics, word-association behaviour, mental lexicon

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Authors: Mariamawit T. Belete

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Cereal production and marketing are the means of livelihood for millions of households in Ethiopia. However, cereal production is constrained by technical and socio-economic factors. Among the technical factors, cereal crop diseases are the major contributing factors to the low yield. The aim of this research is to develop an integration of data mining and knowledge based system for sorghum anthracnose disease diagnosis that assists agriculture experts and development agents to make timely decisions. Anthracnose diagnosing systems gather information from Melkassa agricultural research center and attempt to score anthracnose severity scale. Empirical research is designed for data exploration, modeling, and confirmatory procedures for testing hypothesis and prediction to draw a sound conclusion. WEKA (Waikato Environment for Knowledge Analysis) was employed for the modeling. Knowledge based system has come across a variety of approaches based on the knowledge representation method; case-based reasoning (CBR) is one of the popular approaches used in knowledge-based system. CBR is a problem solving strategy that uses previous cases to solve new problems. The system utilizes hidden knowledge extracted by employing clustering algorithms, specifically K-means clustering from sampled anthracnose dataset. Clustered cases with centroid value are mapped to jCOLIBRI, and then the integrator application is created using NetBeans with JDK 8.0.2. The important part of a case based reasoning model includes case retrieval; the similarity measuring stage, reuse; which allows domain expert to transfer retrieval case solution to suit for the current case, revise; to test the solution, and retain to store the confirmed solution to the case base for future use. Evaluation of the system was done for both system performance and user acceptance. For testing the prototype, seven test cases were used. Experimental result shows that the system achieves an average precision and recall values of 70% and 83%, respectively. User acceptance testing also performed by involving five domain experts, and an average of 83% acceptance is achieved. Although the result of this study is promising, however, further study should be done an investigation on hybrid approach such as rule based reasoning, and pictorial retrieval process are recommended.

Keywords: sorghum anthracnose, data mining, case based reasoning, integration

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Authors: Mona G. Alharbi

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A new family of methionine-sulfoxide reductase (Msr) was recently discovered and was named free methionine sulfoxide reductase (fRMsr). This family includes enzymes with a reductase activity toward the free R isomer of a methionine sulfoxide substrate. The fRMsrs have a GAF domain topology, a domain, which was previously identified as having in some cases a cyclic nucleotide phosphodiesterase activity. The classification of fRMsrs as GAF domains revealed a new function can be added to the GAF domain family. Interestingly the four members identified in the fRMsr family share the GAF domain structure and the presence of three conserved cysteines in the active site with free R methionine sulfoxide substrate specificity. This thesis presents the crystal structures of reduced, free Met-SO substrate-bound and MES-bound forms of a new fRMsr from Burkholderia pseudomallei (BPSL2418). BPSL2418 was cloned, overexpressed and purified to enable protein crystallization. The crystallization trials for reduced, Met-SO-bound and MES-bound forms of BPSL2418 were prepared and reasonable crystals of each form were produced. The crystal structures of BPSL2418MES, BPSL2418Met-SO and BPSL2418Reduced were solved at 1.18, 1.4 and 2.0Å, respectively by molecular replacement. The BPSL2418MES crystal belongs to space group P 21 21 21 while BPSL2418Met-SO and BPSL2418Reduced crystals belong to space group P 1 21 1. All three forms share the GAF domain structure of six antiparallel β-strands and four α-helices with connecting loops. The antiparallel β-strands (β1, β2, β5 and β6) are located in the center of the BPSL2418 structure flanked on one side by a three α-helices (α1, α2 and α4) and on the other side by a (loop1, β3, loop2, α3, β4 loop4) unit where loop4 forms a capping flap and covers the active site. The structural comparison of the three forms of BPSL2418 indicates that the catalytically important cysteine is CYS109, where the resolving cysteine is CYS75, which forms a disulfide bond with CYS109. They also suggest that the third conserved cysteine in the active site, CYS85, which is located in α3, is a non-essential cysteine for the catalytic function but it may play a role in the binding of the substrate. The structural comparison of the three forms reveals that conformational changes appear in the active site particularly involving loop4 and CYS109 during catalysis. The 3D structure of BPSL2418 shows strong structure similarity to fRMsrs enzymes, which further suggests that BPSL2418 acts as a free Met-R-SO reductase and shares the catalytic mechanism of fRMsr family.

Keywords: Burkholderia pseudomallei, GAF domain protein, methionine sulfoxide reductase, protein crystallization

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Authors: Mohammad Khoshini, Arman Khoshghalb, Meghdad Payan, Nasser Khalili

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Most of the Earth’s crust surface rocks are technically categorized as weak rocks or weakly bonded geomaterials. Deeply weathered, weakly cemented, friable and easily erodible, they demonstrate complex material behaviour and understanding the overlooked mechanical behaviour of such materials is of particular importance in geotechnical engineering practice. Weakly bonded geomaterials are so susceptible to surface shear and moisture that conventional methods of core drilling fail to extract high-quality undisturbed samples out of them. Moreover, most of these geomaterials are of high heterogeneity rendering less reliable and feasible material characterization. In order to compensate for the unpredictability of the material response, either numerous experiments are needed to be conducted or large factors of safety must be implemented in the design process. However, none of these approaches is sustainable. In this study, a method for dry core drilling of such materials is introduced to take high-quality undisturbed core samples. By freezing the material at certain moisture content, a secondary structure is developed throughout the material which helps the whole structure to remain intact during the core drilling process. Moreover, to address the heterogeneity issue, the natural material was reconstructed artificially to obtain a homogeneous material with very high similarity to the natural one in both micro and macro-mechanical perspectives. The method is verified for both micro and macro scale. In terms of micro-scale analysis, using Scanning Electron Microscopy (SEM), pore spaces and inter-particle bonds were investigated and compared between natural and artificial materials. X-Ray Diffraction, XRD, analyses are also performed to control the chemical composition. At the macro scale, several uniaxial compressive strength tests, as well as triaxial tests, were performed to verify the similar mechanical response of the materials. A high level of agreement is observed between micro and macro results of natural and artificially bonded geomaterials. The proposed methods can play an important role to cut down the costs of experimental programs for material characterization and also to promote the accuracy of the numerical modellings based on the experimental results.

Keywords: Artificial geomaterial, core drilling, macro-mechanical behavior, micro-scale, sample preparation, SEM photography, weakly bonded geomaterials

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Authors: Xiujing Chen, Thammananya Sakcharoen, Wilailuk Niyommaneerat

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China's tourism industry is in a state of shock and recovery, although COVID-19 has brought great impact and challenges to the tourism industry. The theory of sustainable development originates from the contradiction of increasing awareness of environmental protection and the pursuit of economic interests. The sustainable development of tourism should consider social, economic, and environmental factors and develop tourism in a planned and targeted way from the overall situation. Guilin is one of the popular tourist cities in China. However, there exist several problems in Guilin tourism, such as low quality of scenic spot construction and low efficiency of tourism resource development. Due to its unwell-managed, Guilin's tourism industry is facing problems such as supply and demand crowding pressure for tourists. According to the data from 2009 to 2019, there is a change in the degree of sustainable development of Guilin tourism. This research aimed to evaluate the sustainable development state of Guilin tourism using the DPSIR (driving force/pressure/state/impact/response) framework and to provide suggestions and recommendations for sustainable development in Guilin. An improved TOPSIS (technology for order preference by similarity to an ideal solution) model based on the entropy weights relationship is applied to the quantitative analysis and to analyze the mechanisms of sustainable development of tourism in Guilin. The DPSIR framework organizes indicators into sub-five categories: of which twenty-eight indicators related to sustainable aspects of Guilin tourism are classified. The study analyzed and summarized the economic, social, and ecological effects generated by tourism development in Guilin from 2009-2019. The results show that the conversion rate of tourism development in Guilin into regional economic benefits is more efficient than that into social benefits. Thus, tourism development is an important driving force of Guilin's economic growth. In addition, the study also analyzed the static weights of 28 relevant indicators of sustainable development of tourism in Guilin and ranked them from largest to smallest. Then it was found that the economic and social factors related to tourism revenue occupy the highest weight, which means that the economic and social development of Guilin can influence the sustainable development of Guilin tourism to a greater extent. Therefore, there is a two-way causal relationship between tourism development and economic growth in Guilin. At the same time, ecological development-related indicators also have relatively large weights, so ecological and environmental resources also have a great influence on the sustainable development of Guilin tourism.

Keywords: DPSIR framework, entropy weights analysis, sustainable development of tourism, TOPSIS analysis

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Authors: Konstantin S. Vainutis, Mark E. Andreev, Anastasia N. Voronova, Mikhail Yu. Shchelkanov

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Introduction: The trematodes from the family Cyclocoelidae (cyclocoelids) belong to the superfamily Echinostomatoidea infecting air sacs and trachea of wild birds. At present, the family Cyclocoelidae comprises nine valid genera in three subfamilies: Cyclocoelinae (type taxon), Haematotrephinae, and Typhlocoelinae. To our best knowledge, in this study, molecular genetic methods were used for the first time for studying cyclocoelids from the Russian Far East. Here we provide the data on the morphology and phylogeny of cyclocoelids from gadwall from the Russian Far East. The morphological and genetic data obtained for cyclocoelids indicated the necessity to revise the previously proposed classification within the family Cyclocoelidae. Objectives: The first objective was performing the morphological study of cyclocoelids found in M. strepera from the Russian Far East. The second objective is to reconstruct the phylogenetic relationships of the studied trematodes with other cyclocoelids using the 28S gene. Material and methods: During the field studies in the Khasansky district of the Primorsky region, 21 cyclocoelids were recovered from the air sacs of a single gadwall Mareca strepera. Seven samples of cyclocoelids were overstained in alum carmine, dehydrated in a graded ethanol series, cleared in clove oil, and mounted in Canada balsam. Genomic DNA was extracted from four cyclocoelids using the alkaline lysis method HotShot. The 28S rDNA fragment was amplified using the forward primer Digl2 and the reverse primer 1500R. Results: According to morphological features (ovary intratesticular, forming a triangle with the testes), the studied worms belong to the subfamily Cyclocoelinae Stossich, 1902. In particular, the highest morphological similarity was observed in relation to the trematodes of the genus Cyclocoelum Brandes, 1892 – genital pores are pharyngeal. However, the genetic analysis has shown significant discrepancies between the trematodes studied regarding the genus Cyclocoelum. On the phylogenetic tree, these trematodes took the sister position in relation to the genus Morishitium (previously considered in the subfamily Szidatitrematinae). Conclusion: Based on the results of the morphological and genetic studies, cyclocoelids isolated from Mareca strepera are suggested to be described in the previously unknown genus and differentiated from the type genus Cyclocoelum of the type subfamily Cyclocoelinae. Considering the available molecular data, including described cyclocoelids, the family Cyclocoelidae comprises ten valid genera in the three subfamilies mentioned above.

Keywords: new species, trematoda, phylogeny, cyclocoelidae

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Authors: Ibrahim Burki

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Unfortunately, all organizations (Industrial and Humanitarian/ Non-governmental organizations) are prone to fraud and corruption in their supply chain management routines. The reputational and financial fallout can be disastrous. With the growing number of companies using suppliers based in the local market has certainly increased the threat of fraud as well as corruption. There are various potential threats like, poor or non-existent record keeping, purchasing of lower quality goods at higher price, excessive entertainment of staff by suppliers, deviations in communications between procurement staff and suppliers, such as calls or text messaging to mobile phones, staff demanding extended periods of notice before they allow an audit to take place, inexperienced buyers and more. But despite all the above-mentioned threats, this research paper emphasize upon the effectiveness of well-maintained vendor/s records and sorting/filtration of vendor/s to cut down the possible threats of corruption and fraud. This exercise is applied in a humanitarian organization of Pakistan but it is applicable to whole South Asia region due to the similarity of culture and contexts. In that firm, there were more than 550 (five hundred and fifty) registered vendors. As during the disasters or emergency phases requirements are met on urgent basis thus, providing golden opportunities for the fake companies or for the brother/sister companies of the already registered companies to be involved in the tendering process without declaration or even under some different (new) company’s name. Therefore, a list of required documents (along with checklist) was developed and sent to all of the vendor(s) in the current database and based upon the receipt of the requested documents vendors were sorted out. Furthermore, these vendors were divided into active (meeting the entire set criterion) and non-active groups. This initial filtration stage allowed the firm to continue its work without a complete shutdown that is only vendors falling in the active group shall be allowed to participate in the tenders by the time whole process is completed. Likewise only those companies or firms meeting the set criterion (active category) shall be allowed to get registered in the future along with a dedicated filing system (soft and hard shall be maintained), and all of the companies/firms in the active group shall be physically verified (visited) by the Committee comprising of senior members of at least Finance department, Supply Chain (other than procurement) and Security department.

Keywords: corruption reduction, fraud prevention, supplier management, industrial/humanitarian organizations

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Authors: Renata Hrecska

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This research seeks to fully examine the internal employment law of international organizations by comparing it with the characteristics of the national civil service. The aim of the research is to compare the legal system that has developed over many centuries and the relatively new internal staffing regulations to find out what solution schemes can help each other through mutual legal development in order to respond effectively to the social challenges of everyday life. Generally, the rules of civil service of any country or international entity have in common that they have, in their pragmatics inherently, the characteristic that makes them serving public interests. Though behind the common base there are many differences: there is the clear fragmentation of state regulation and the unity of organizational regulation. On the other hand, however, this difference disappears to some extent: the public service regulation of international organizations can be considered uniform until we examine it within, but not outside an organization. As soon as we compare the different organizations we may find many different solutions for staffing regulations. It is clear that the national civil service is a strong model for international organizations, but the question may be whether the staffing policy of international organizations can serve the national civil service as an example, too. In this respect, the easiest way to imagine a legislative environment would be to have a single comprehensive code, the general part of which is the Civil Service Act itself, and the specific part containing specific, necessarily differentiating rules for each layer of the civil service. Would it be advantageous to follow the footsteps of the leading international organizations, or is there any speciality in national level civil service that we cannot avoid during regulating processes? In addition to the above, the personal competencies of officials working in international organizations and public administrations also show a high degree of similarity, regardless of the type of employment. Thus, the whole public service system is characterized by the fundamental and special values that a person capable of holding a public office must be able to demonstrate, in some cases, even without special qualifications. It is also interesting how we can compare the two spheres of employment in light of the theory of Lawyer Louis Brandeis, a judge at the US Supreme Court, who formulated a complex theory of profession as distinguished from other occupations. From this point of view we can examine the continuous development of research and specialized knowledge at work; the community recognition and social status; that to what extent we can see a close-knit professional organization of altruistic philosophy; that how stability grows in the working conditions due to the stability of the profession; and that how the autonomy of the profession can prevail.

Keywords: civil service, comparative law, international organizations, regulatory systems

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Authors: Sridhar A. Malkaram, Tamer E. Fandy

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Purpose: 5-Azacytidine (5AC) and decitabine (DC) are DNA hypomethylating agents. We recently demonstrated that both drugs increase the enzymatic activity of the histone deacetylase enzyme SIRT6. Accordingly, we are comparing the changes H3K9 acetylation changes in the whole genome induced by both drugs using leukemia cells. Description of Methods & Materials: Mononuclear cells from the bone marrow of six de-identified naive acute myeloid leukemia (AML) patients were cultured with either 500 nM of DC or 5AC for 72 h followed by ChIP-Seq analysis using a ChIP-validated acetylated-H3K9 (H3K9ac) antibody. Chip-Seq libraries were prepared from treated and untreated cells using SMARTer ThruPLEX DNA- seq kit (Takara Bio, USA) according to the manufacturer’s instructions. Libraries were purified and size-selected with AMPure XP beads at 1:1 (v/v) ratio. All libraries were pooled prior to sequencing on an Illumina HiSeq 1500. The dual-indexed single-read Rapid Run was performed with 1x120 cycles at 5 pM final concentration of the library pool. Sequence reads with average Phred quality < 20, with length < 35bp, PCR duplicates, and those aligning to blacklisted regions of the genome were filtered out using Trim Galore v0.4.4 and cutadapt v1.18. Reads were aligned to the reference human genome (hg38) using Bowtie v2.3.4.1 in end-to-end alignment mode. H3K9ac enriched (peak) regions were identified using diffReps v1.55.4 software using input samples for background correction. The statistical significance of differential peak counts was assessed using a negative binomial test using all individuals as replicates. Data & Results: The data from the six patients showed significant (Padj<0.05) acetylation changes at 925 loci after 5AC treatment versus 182 loci after DC treatment. Both drugs induced H3K9 acetylation changes at different chromosomal regions, including promoters, coding exons, introns, and distal intergenic regions. Ten common genes showed H3K9 acetylation changes by both drugs. Approximately 84% of the genes showed an H3K9 acetylation decrease by 5AC versus 54% only by DC. Figures 1 and 2 show the heatmaps for the top 100 genes and the 99 genes showing H3K9 acetylation decrease after 5AC treatment and DC treatment, respectively. Conclusion: Despite the similarity in hypomethylating activity and chemical structure, the effect of both drugs on H3K9 acetylation change was significantly different. More changes in H3K9 acetylation were observed after 5 AC treatments compared to DC. The impact of these changes on gene expression and the clinical efficacy of these drugs requires further investigation.

Keywords: DNA methylation, leukemia, decitabine, 5-Azacytidine, epigenetics

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Authors: X. Wang

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Timely and accurate information on urban building damage caused by earthquake is important basis for disaster assessment and emergency relief. Very high resolution (VHR) remotely sensed imagery containing abundant fine-scale information offers a large quantity of data for detecting and assessing urban building damage in the aftermath of earthquake disasters. However, the accuracy obtained using spectral features alone is comparatively low, since building damage, intact buildings and pavements are spectrally similar. Therefore, it is of great significance to detect urban building damage effectively using multi-source data. Considering that in general height or geometric structure of buildings change dramatically in the devastated areas, a novel multi-stage urban building damage detection method, using bi-temporal spectral, height and corner information, was proposed in this study. The pre-event height information was generated using stereo VHR images acquired from two different satellites, while the post-event height information was produced from airborne LiDAR data. The corner information was extracted from pre- and post-event panchromatic images. The proposed method can be summarized as follows. To reduce the classification errors caused by spectral similarity and errors in extracting height information, ground surface, shadows, and vegetation were first extracted using the post-event VHR image and height data and were masked out. Two different types of building damage were then extracted from the remaining areas: the height difference between pre- and post-event was used for detecting building damage showing significant height change; the difference in the density of corners between pre- and post-event was used for extracting building damage showing drastic change in geometric structure. The initial building damage result was generated by combining above two building damage results. Finally, a post-processing procedure was adopted to refine the obtained initial result. The proposed method was quantitatively evaluated and compared to two existing methods in Port au Prince, Haiti, which was heavily hit by an earthquake in January 2010, using pre-event GeoEye-1 image, pre-event WorldView-2 image, post-event QuickBird image and post-event LiDAR data. The results showed that the method proposed in this study significantly outperformed the two comparative methods in terms of urban building damage extraction accuracy. The proposed method provides a fast and reliable method to detect urban building collapse, which is also applicable to relevant applications.

Keywords: building damage, corner, earthquake, height, very high resolution (VHR)

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Authors: Barbara Peric

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The study of acquiring a third and additional language has garnered significant focus within second language acquisition (SLA) research. Initially, it was commonly viewed as merely an extension of second language acquisition (SLA). However, in the last two decades, numerous researchers have emphasized the need to recognize the unique characteristics of third language acquisition (TLA). This recognition is crucial for understanding the intricate cognitive processes that arise from the interaction of more than two linguistic systems in the learner's mind. This study investigates cross-linguistic influences in the acquisition of Spanish as a fourth language by students who have Croatian as a first language (L1). English as a second language (L2), and Italian as a third language (L3). Observational data suggests that influence or transfer of linguistic elements can arise not only from one's native language (L1) but also from non-native languages. This implies that, for individuals proficient in multiple languages, the native language doesn't consistently hold a superior position. Instead, it should be examined alongside other potential sources of linguistic transfer. Earlier studies have demonstrated that high proficiency in a second language can significantly impact cross-linguistic influences when acquiring a third and additional language. Among the extensively examined factors, the typological relationship stands out as one of the most scrutinized variables. The goal of the present study was to explore whether language typology and formal similarity or proficiency in the second language had a more significant impact on L4 acquisition. Participants in this study were third-year undergraduate students at Rochester Institute of Technology’s subsidiary in Croatia (RIT Croatia). All the participants had exclusively Croatian as L1, English as L2, Italian as L3 and were learning Spanish as L4 at the time of the study. All the participants had a high level of proficiency in English and low level of proficiency in Italian. Based on the error analysis the findings indicate that for some types of lexical errors such as coinage, language typology had a more significant impact and Italian language was the preferred source of transfer despite the law proficiency in that language. For some other types of lexical errors, such as calques, second language proficiency had a more significant impact, and English language was the preferred source of transfer. On the other hand, Croatian, Italian, and Spanish are more similar in the area of morphology due to higher degree of inflection compared to English and the strongest influence of the Croatian language was precisely in the area of morphology. The results emphasize the need to consider linguistic resemblances between the native language (L1) and the third and additional language as well as the learners' proficiency in the second language when developing successful teaching strategies for acquiring the third and additional language. These conclusions add to the expanding knowledge in the realm of Second Language Acquisition (SLA) and offer practical insights for language educators aiming to enhance the effectiveness of learning experiences in acquiring a third and additional language.

Keywords: third and additional language acquisition, cross-linguistic influences, language proficiency, language typology

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Authors: Hyuk Sung Yoon, In-Lee Choi, Mohammad Zahirul Islam, Jun Pill Baek, Ho-Min Kang

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The strawberry ‘Maehyang’ cultivated in South Korea has been increased to export to Southeast Asia. The degradation of quality often occurs in strawberries during short export period. Botrytis cinerea has been known to cause major damage to the export strawberries and the disease was caused during shipping and distribution. This study was conducted to find out the sterilized effect of chlorine dioxide(ClO2) gas and high concentration of CO2 gas injection for ‘Maehyang’ strawberry and it was packaged with oxygen transmission rate (OTR) films. The strawberry was harvested at 80% color changed stage and packaged with OTR film and perforated film (control). The treatments were a MAP used by with 20,000 cc·m-2·day·atm OTR film and gas injection in packages. The gas type of ClO2 and CO2 were injected into OTR film packages, and treatments were 6 mg/L ClO2, 15% CO2, and they were combined. The treated strawberries were stored at 3℃ for 30 days. Fresh weight loss rate was less than 1% in all OTR film packages but it was more than 15% in a perforated film treatment that showed severe deterioration of visual quality during storage. Carbon dioxide concentration within a package showed approximately 15% of the maximum CO2 concentration in all treatments except control until the 21st day, it was the tolerated range of maximum CO2 concentration of strawberry in recommended CA or MA conditions. But, it increased to almost 50% on the 30th day. Oxygen concentration showed a decrease down to approximately 0% in all treatments except control for 25 days. Ethylene concentration was shown to be steady until the 17th day, but it quickly increased on the 17th day and dropped down on the final storage day (30th day). All treatments did not show any significant differences in gas treatments. Firmness increased in CO2 (15%) and ClO2 (6mg/L) + CO2 (15%) treatments during storage. It might be the effect of high concentration CO2 known by reducing decay and cell wall degradation. The soluble solid decreased in all treatments during storage. These results were caused to use up the sugar by the increase of respiration during storage. The titratable acidity showed a similarity in all treatments. Incidence of fungi was 0% in CO2 (15%) and ClO2 (6mg/L)+ CO2 (15%), but was more than 20% in a perforated film treatment. Consequently, The result indicates that Chloride Dioxide(ClO2) and high concentration of CO2 inhibited fungi growth. Due to the fact that fresh weight loss rate and incidence of fungi were lower, the ClO2(6mg/L)+ CO2(15%) prove to be most efficient in sterilization. These results suggest that Chloride Dioxide (ClO2) and high concentration of CO2 gas injection treatments were an effective decontamination technique for improving the safety of strawberries.

Keywords: chloride dioxide, high concentration of CO2, modified atmosphere condition, oxygen transmission rate films

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Authors: Wael M. Rabeh, Cesar Carrasco-Lopez, Juliana C. Ferreira, Pance Naumov

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Bioluminescence, the emission of light from a biological process, is found in various living organisms including bacteria, fireflies, beetles, fungus and different marine organisms. Luciferase is an enzyme that catalyzes a two steps oxidation of luciferin in the presence of Mg2+ and ATP to produce oxyluciferin and releases energy in the form of light. The luciferase assay is used in biological research and clinical applications for in vivo imaging, cell proliferation, and protein folding and secretion analysis. The luciferase enzyme consists of two domains, a large N-terminal domain (1-436 residues) that is connected to a small C-terminal domain (440-544) by a flexible loop that functions as a hinge for opening and closing the active site. The two domains are separated by a large cleft housing the active site that closes after binding the substrates, luciferin and ATP. Even though all insect luciferases catalyze the same chemical reaction and share 50% to 90% sequence homology and high structural similarity, they emit light of different colors from green at 560nm to red at 640 nm. Currently, the majority of the structural and biochemical studies have been conducted on green-emitting firefly luciferases. To address the color emission mechanism, we expressed and purified two luciferase enzymes with blue-shifted green and red emission from indigenous Brazilian species Amydetes fanestratus and Phrixothrix, respectively. The two enzymes naturally emit light of different colors and they are an excellent system to study the color-emission mechanism of luciferases, as the current proposed mechanisms are based on mutagenesis studies. Using a vapor-diffusion method and a high-throughput approach, we crystallized and solved the crystal structure of both enzymes, at 1.7 Å and 3.1 Å resolution respectively, using X-ray crystallography. The free enzyme adopted two open conformations in the crystallographic unit cell that are different from the previously characterized firefly luciferase. The blue-shifted green luciferase crystalized as a monomer similar to other luciferases reported in literature, while the red luciferases crystalized as an octamer and was also purified as an octomer in solution. The octomer conformation is the first of its kind for any insect’s luciferase, which might be relate to the red color emission. Structurally designed mutations confirmed the importance of the transition between the open and close conformations in the fine-tuning of the color and the characterization of other interesting mutants is underway.

Keywords: bioluminescence, enzymology, structural biology, x-ray crystallography

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Authors: W. Meron Mebrahtu, R. Absi

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Velocity distribution in turbulent open-channel flows is organized in a complex manner. This is due to the large spatial and temporal variability of fluid motion resulting from the free-surface turbulent flow condition. This phenomenon is complicated further due to the complex geometry of channels and the presence of solids transported. Thus, several efforts were made to understand the phenomenon and obtain accurate mathematical models that are suitable for engineering applications. However, predictions are inaccurate because oversimplified assumptions are involved in modeling this complex phenomenon. Therefore, the aim of this work is to study velocity distribution profiles and obtain simple, more accurate, and predictive mathematical models. Particular focus will be made on the acceptable simplification of the general transport equations and an accurate representation of eddy viscosity. Wide rectangular open-channel seems suitable to begin the study; other assumptions are smooth-wall, and sediment-free flow under steady and uniform flow conditions. These assumptions will allow examining the effect of the bottom wall and the free surface only, which is a necessary step before dealing with more complex flow scenarios. For this flow condition, two ordinary differential equations are obtained for velocity profiles; from the Reynolds-averaged Navier-Stokes (RANS) equation and equilibrium consideration between turbulent kinetic energy (TKE) production and dissipation. Then different analytic models for eddy viscosity, TKE, and mixing length were assessed. Computation results for velocity profiles were compared to experimental data for different flow conditions and the well-known linear, log, and log-wake laws. Results show that the model based on the RANS equation provides more accurate velocity profiles. In the viscous sublayer and buffer layer, the method based on Prandtl’s eddy viscosity model and Van Driest mixing length give a more precise result. For the log layer and outer region, a mixing length equation derived from Von Karman’s similarity hypothesis provides the best agreement with measured data except near the free surface where an additional correction based on a damping function for eddy viscosity is used. This method allows more accurate velocity profiles with the same value of the damping coefficient that is valid under different flow conditions. This work continues with investigating narrow channels, complex geometries, and the effect of solids transported in sewers.

Keywords: accuracy, eddy viscosity, sewers, velocity profile

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Authors: Shubham Gogri, Lucia Florescu

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Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

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Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

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Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

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Authors: Shilpa Sahoo, Michel Louge, Anthony Reeves, Olivier Desjardins, Susan Daniel, Sadik Omowunmi

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The microgravity on the International Space Station (ISS) was exploited to study the imbibition of water into a network of hydrophilic cylindrical capillaries on time and length scales long enough to observe details hitherto inaccessible under Earth gravity. When a drop touches a porous medium, it spreads as if laid on a composite surface. The surface first behaves as a hydrophobic material, as liquid must penetrate pores filled with air. When contact is established, some of the liquid is drawn into pores by a capillarity that is resisted by viscous forces growing with length of the imbibed region. This process always begins with an inertial regime that is complicated by possible contact pinning. To study imbibition on Earth, time and distance must be shrunk to mitigate gravity-induced distortion. These small scales make it impossible to observe the inertial and pinning processes in detail. Instead, in the International Space Station (ISS), astronaut Luca Parmitano slowly extruded water spheres until they touched any of nine capillary plates. The 12mm diameter droplets were large enough for high-speed GX1050C video cameras on top and side to visualize details near individual capillaries, and long enough to observe dynamics of the entire imbibition process. To investigate the role of contact pinning, a text matrix was produced which consisted nine kinds of porous capillary plates made of gold-coated brass treated with Self-Assembled Monolayers (SAM) that fixed advancing and receding contact angles to known values. In the ISS, long-term microgravity allowed unambiguous observations of the role of contact line pinning during the inertial phase of imbibition. The high-speed videos of spreading and imbibition on the porous plates were analyzed using computer vision software to calculate the radius of the droplet contact patch with the plate and height of the droplet vs time. These observations are compared with numerical simulations and with data that we obtained at the ESA ZARM free-fall tower in Bremen with a unique mechanism producing relatively large water spheres and similarity in the results were observed. The data obtained from the ISS can be used as a benchmark for further numerical simulations in the field.

Keywords: droplet imbibition, hydrophilic surface, inertial phase, porous medium

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Authors: Amani Tahat, Serdal Kirmizialtin

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Trajectory fragment methods such as Markov State Models (MSM), Milestoning (MS) and Transition Path sampling are the prime choice of extending the timescale of all atom Molecular Dynamics simulations. In these approaches, a set of structures that covers the accessible phase space has to be chosen a priori using cluster analysis. Structural clustering serves to partition the conformational state into natural subgroups based on their similarity, an essential statistical methodology that is used for analyzing numerous sets of empirical data produced by Molecular Dynamics (MD) simulations. Local transition kernel among these clusters later used to connect the metastable states using a Markovian kinetic model in MSM and a non-Markovian model in MS. The choice of clustering approach in constructing such kernel is crucial since the high dimensionality of the biomolecular structures might easily confuse the identification of clusters when using the traditional hierarchical clustering methodology. Of particular interest, in the case of MS where the milestones are very close to each other, accurate determination of the milestone identity of the trajectory becomes a challenging issue. Throughout this work we present two cluster analysis methods applied to the cis–trans isomerism of dinucleotide AA. The choice of nucleic acids to commonly used proteins to study the cluster analysis is two fold: i) the energy landscape is rugged; hence transitions are more complex, enabling a more realistic model to study conformational transitions, ii) Nucleic acids conformational space is high dimensional. A diverse set of internal coordinates is necessary to describe the metastable states in nucleic acids, posing a challenge in studying the conformational transitions. Herein, we need improved clustering methods that accurately identify the AA structure in its metastable states in a robust way for a wide range of confused data conditions. The single linkage approach of the hierarchical clustering available in GROMACS MD-package is the first clustering methodology applied to our data. Self Organizing Map (SOM) neural network, that also known as a Kohonen network, is the second data clustering methodology. The performance comparison of the neural network as well as hierarchical clustering method is studied by means of computing the mean first passage times for the cis-trans conformational rates. Our hope is that this study provides insight into the complexities and need in determining the appropriate clustering algorithm for kinetic analysis. Our results can improve the effectiveness of decisions based on clustering confused empirical data in studying conformational transitions in biomolecules.

Keywords: milestoning, self organizing map, single linkage, structure clustering

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Authors: Josiah Damisa, Michelle Louise Richardson, Morenike Adewuyi

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Lower back pain is a significant cause of disability worldwide and associated with great implications in terms of the well-being of affected individuals and society as a whole due to its undeniable socio-economic impact. With its prevalence on the increase as a result of an aging global population, the need for novel forms of pain management is ever paramount. This review aims to provide further insight into current research regarding a role for the endocannabinoid signaling pathway as a target in the treatment of chronic pain, with particular emphasis on its potential use as part of the treatment of lower back pain. Potential advantages and limitations of cannabis-based medicines over other forms of analgesia currently licensed for medical use are discussed in addition to areas that require ongoing consideration and research. To evaluate the efficacy of cannabis-based medicines in chronic pain, studies pertaining to the role of medical cannabis in chronic disease were reviewed. Standard searches of PubMed, Google Scholar and Web of Science databases were undertaken with peer-reviewed journal articles reviewed based on the indication for pain management, cannabis treatment modality used and study outcomes. Multiple studies suggest an emerging role for cannabis-based medicines as therapeutic agents in the treatment of chronic back pain. A potential synergistic effect has also been purported if these medicines are co-administered with opiate analgesia due to the similarity of the opiate and endocannabinoid signaling pathways. However, whilst recent changes to legislation in the United Kingdom mean that cannabis is now licensed for medicinal use on NHS prescription for a number of chronic health conditions, concerns remain as to the efficacy and safety of cannabis-based medicines. Research is lacking into both their side effect profiles and the long-term effects of cannabis use. Legal and ethical considerations to the use of these products in standardized medical practice also persist due to the notoriety of cannabis as a drug of abuse. Despite this, cannabis is beginning to gain traction as an alternative or even complementary drug to opiates, with some preclinical studies showing opiate-sparing effects. Whilst there is a paucity of clinical trials in this field, there is scope for cannabinoids to be successful anti-nociceptive agents in managing chronic back pain. The ultimate aim would be to utilize cannabis-based medicines as alternative or complementary therapies, thereby reducing opiate over-reliance and providing hope to individuals who have exhausted all other forms of standard treatment.

Keywords: endocannabinoids, cannabis-based medicines, chronic pain, lower back pain

Procedia PDF Downloads 175

Authors: Chantal Maille

Abstract:

This paper is about gender-based analysis plus (GBA+), an intersectional gender policy used in Canada to assess the impact of policies and programs for men and women from different origins. It looks at Canada’s political culture to explain the nature of its gender policies. GBA+ is defined as an analysis method that makes it possible to assess the eventual effects of policies, programs, services, and other initiatives on women and men of different backgrounds because it takes account of gender and other identity factors. The ‘plus’ in the name serves to emphasize that GBA+ goes beyond gender to include an examination of a wide range of other related identity factors, such as age, education, language, geography, culture, and income. The point of departure for GBA+ is that women and men are not homogeneous populations and gender is never the only factor in defining a person’s identity; rather, it interacts with factors such as ethnic origin, age, disabilities, where the person lives, and other aspects of individual and social identity. GBA+ takes account of these factors and thus challenges notions of similarity or homogeneity within populations of women and men. Comparative analysis based on sex and gender may serve as a gateway to studying a given question, but women, men, girls, and boys do not form homogeneous populations. In the 1990s, intersectionality emerged as a new feminist framework. The popularity of the notion of intersectionality corresponds to a time when, in hindsight, the damage done to minoritized groups by state disengagement policies in concert with global intensification of neoliberalism, and vice versa, can be measured. Although GBA+ constitutes a form of intersectionalization of GBA, it must be understood that the two frameworks do not spring from a similar logic. Intersectionality first emerged as a dynamic analysis of differences between women that was oriented toward change and social justice, whereas GBA is a technique developed by state feminists in a context of analyzing governmental policies and aiming to promote equality between men and women. It can nevertheless be assumed that there might be interest in such a policy and program analysis grid that is decentred from gender and offers enough flexibility to take account of a group of inequalities. In terms of methodology, the research is supported by a qualitative analysis of governmental documents about GBA+ in Canada. Research findings identify links between Canadian gender policies and its political culture. In Canada, diversity has been taken into account as an element at the basis of gendered analysis of public policies since 1995. The GBA+ adopted by the government of Canada conveys an opening to intersectionality and a sensitivity to multiculturalism. The Canadian Multiculturalism Act, adopted 1988, proposes to recognize the fact that multiculturalism is a fundamental characteristic of the Canadian identity and heritage and constitutes an invaluable resource for the future of the country. In conclusion, Canada’s distinct political culture can be associated with the specific nature of its gender policies.

Keywords: Canada, gender-based analysis, gender policies, political culture

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