Search results for: natural features

Authors: Fatemehsadat Mortazavizadeh, Amin Dehghani, Majid Mirzaei, Nurulhuda Binti Mohammad Ramli, Adnan Dehghani

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Flood is Malaysia's most common and serious natural disaster. Kelantan River Basin is a tropical basin that experiences a rainy season during North-East Monsoon from November to March. It is also one of the hardest hit areas in Peninsular Malaysia during the heavy monsoon rainfall. Considering the consequences of the flood events, it is essential to develop the flood inundation map as part of the mitigation approach. In this study, the delineation of flood inundation zone in the area of Kelantan River basin using a hydrodynamic model is done by HEC-RAS, QGIS and ArcMap. The streamflow data has been generated with the weather generator based on the observation data. Then, the data is statistically analyzed with the Extreme Value (EV1) method for 2-, 5-, 25-, 50- and 100-year return periods. The minimum depth, maximum depth, mean depth, and the standard deviation of all the scenarios, including the OBS, are observed and analyzed. Based on the results, generally, the value of the data increases with the return period for all the scenarios. However, there are certain scenarios that have different results, which not all the data obtained are increasing with the return period. Besides, OBS data resulted in the middle range within Scenario 1 to Scenario 40.

Keywords: flood inundation, kelantan river basin, hydrodynamic model, extreme value analysis

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Authors: Steven D. P Moore

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A novel method referred to asKýklos(Ky) dimensional geometry is proposed as an entity specific core geometric dimensional measurement system. Ky geometric measures can constructscaled multi-dimensionalmodels using regular and irregular sets in IRn. This entity specific-derived geometric measurement system shares similar fractal methods in which a ‘fractal transformation operator’ is applied to a set S to produce a union of N copies. The Kýklos’ inputs use 1D geometry as a core measure. One-dimensional inputs include the radius interval of a circle/sphere or the semiminor/semimajor axes intervals of an ellipse or spheroid. These geometric inputs have finite values that can be measured by SI distance units. The outputs for each interval are divided and subdivided 1D subcomponents with a union equal to the interval geometry/length. Setting a limit of subdivision iterations creates a finite value for each 1Dsubcomponent. The uniqueness of this method is captured by allowing the simplest 1D inputs to define entity specific subclass geometric core measurements that can also be used to derive length measures. Current methodologies for celestial based measurement of time, as defined within SI units, fits within this methodology, thus combining spatial and temporal features into geometric core measures. The novel Ky method discussed here offers geometric measures to construct scaled multi-dimensional structures, even models. Ky classes proposed for consideration include celestial even subatomic. The application of this offers incredible possibilities, for example, geometric architecture that can represent scaled celestial models that incorporates planets (spheroids) and celestial motion (elliptical orbits).

Keywords: Kyklos, geometry, measurement, celestial, dimension

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Authors: Jacob Green, Cecilia Cabrera, Maximilian Jakobs, Andrea Dimitracopoulos, Mark van der Wilk, Ryan Greenhalgh

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Predicting drug properties is key in drug discovery to enable de-risking of assets before expensive clinical trials and to find highly active compounds faster. Interest from the machine learning community has led to the release of a variety of benchmark datasets and proposed methods. However, it remains unclear for practitioners which method or approach is most suitable, as different papers benchmark on different datasets and methods, leading to varying conclusions that are not easily compared. Our large-scale empirical study links together numerous earlier works on different datasets and methods, thus offering a comprehensive overview of the existing property classes, datasets, and their interactions with different methods. We emphasise the importance of uncertainty quantification and the time and, therefore, cost of applying these methods in the drug development decision-making cycle. To the best of the author's knowledge, it has been observed that the optimal approach varies depending on the dataset and that engineered features with classical machine learning methods often outperform deep learning. Specifically, QSAR datasets are typically best analysed with classical methods such as Gaussian Processes, while ADMET datasets are sometimes better described by Trees or deep learning methods such as Graph Neural Networks or language models. Our work highlights that practitioners do not yet have a straightforward, black-box procedure to rely on and sets a precedent for creating practitioner-relevant benchmarks. Deep learning approaches must be proven on these benchmarks to become the practical method of choice in drug property prediction.

Keywords: activity (QSAR), ADMET, classical methods, drug property prediction, empirical study, machine learning

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Authors: Esra Ece Var

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Beekeeping plays essential role both in terms of agricultural yields and agricultural economy; they produce honey, wax, royal jelly, apitoxin, pollen, and propolis. Nowadays, these natural products become more importantly suitable and preferable for nutrition, food supplement, medicine, and industry. However, to produce organic honey, majority of the apiaries are located in remote or distant rural areas where utilities such as electricity and Internet network are not available. Additionally, due to colony failures, world honey production decreases year by year despite the increase in the number of beehives. The objective of this paper is to develop a smart beehive monitoring system for apiaries including those that do not have access to Internet network. In this context, temperature and humidity inside the beehive, and ambient temperature were measured with RFID sensors. Control center, where all sensor data was sent and stored at, has a GSM module used to warn the beekeeper via SMS when an anomaly is detected. Simultaneously, using the collected data, an unsupervised machine learning algorithm is used for detecting anomalies and calibrating the warning system. The results show that the smart beehive monitoring system can detect fatal anomalies up to 4 weeks prior to colony loss.

Keywords: beekeeping, smart systems, machine learning, anomaly detection, apiculture

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Authors: Denis V. Axenov-Gribanov, Irina V. Voytsekhovskaya, Evgenii S. Protasov, Maxim A. Timofeyev

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Isolated ecosystems existing under specific environmental conditions have been shown to be promising sources of new strains of actinobacteria. The taiga forest of Baikal Siberia has not been well studied, and its actinobacterial population remains uncharacterized. The proximity between the huge water mass of Lake Baikal and high mountain ranges influences the structure and diversity of the plant world in Siberia. Here, we report the isolation of eighteen actinobacterial strains from male cones of Pinus sylvestris trees growing on the shore of the ancient Lake Baikal in Siberia. The actinobacterial strains were isolated on solid nutrient MS media and Czapek agar supplemented with cycloheximide and phosphomycin. Identification of actinobacteria was carried out by 16S rRNA gene sequencing and further analysis of the evolutionary history. Four different liquid and solid media (NL19, DNPM, SG and ISP) were tested for metabolite production. The metabolite extracts produced by the isolated strains were tested for antibacterial and antifungal activities. Also, antiradical activity of crude extracts was carried out. Strain Streptomyces sp. IB 2014 I 74-3 that active against Gram-negative bacteria was selected for dereplication analysis with using the high-yield liquid chromatography with mass-spectrometry. Mass detection was performed in both positive and negative modes, with the detection range set to 160–2500 m/z. Data were collected and analyzed using Bruker Compass Data Analysis software, version 4.1. Dereplication was performed using the Dictionary of Natural Products (DNP) database version 6.1 with the following search parameters: accurate molecular mass, absorption spectra and source of compound isolation. Thus, in addition to more common representative strains of Streptomyces, several species belonging to the genera Rhodococcus, Amycolatopsis, and Micromonospora were isolated. Several of the selected strains were deposited in the Russian Collection of Agricultural Microorganisms (RCAM), St. Petersburg, Russia. All isolated strains exhibited antibacterial and antifungal activities. We identified several strains that inhibited the growth of the pathogen Candida albicans but did not hinder the growth of Saccharomyces cerevisiae. Several isolates were active against Gram-positive and Gram-negative bacteria. Moreover, extracts of several strains demonstrated high antioxidant activity. The high proportion of biologically active strains producing antibacterial and specific antifungal compounds may reflect their role in protecting pollen against phytopathogens. Dereplication of the secondary metabolites of the strain Streptomyces sp. IB 2014 I 74-3 was resulted in the fact that a total of 59 major compounds were detected in the culture liquid extract of strain cultivated in ISP medium. Eight compounds were preliminarily identified based on characteristics described in the Dictionary of Natural Products database, using the search parameters Streptomyces sp. IB 2014 I 74-3 was found to produce saframycin A, Y3 and S; 2-amino-3-oxo-3H-phenoxazine-1,8-dicarboxylic acid; galtamycinone; platencin A4-13R and A4-4S; ganefromycin d1; the antibiotic SS 8201B; and streptothricin D, 40-decarbamoyl, 60-carbamoyl. Moreover, forty-nine of the 59 compounds detected in the extract examined in the present study did not result in any positive hits when searching within the DNP database and could not be identified based on available mass-spec data. Thus, these compounds might represent new findings.

Keywords: actinobacteria, Baikal Lake, biodiversity, male cones, Pinus sylvestris

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Authors: Vaishali D. Khairnar

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The main aim is to provide lower-latency and highly reliable communication facilities for vehicles in the automobile industry; vehicle-to-everything (V2X) communication basically intends to increase expressway road security and its effectiveness. The Ultra-Reliable Low-Latency Communications (URLLC) algorithm and cellular networks are applied in combination with Mobile Broadband (MBB). This is particularly used in express way safety-based driving applications. Expressway vehicle drivers (humans) will communicate in V2X systems using the sixth-generation (6G) communication systems which have very high-speed mobility features. As a result, we need to determine how to ensure reliable and consistent wireless communication links and improve the quality to increase channel gain, which is becoming a challenge that needs to be addressed. To overcome this challenge, we proposed a unique multi-user scheduling algorithm for ultra-massive multiple-input multiple-output (MIMO) systems using 6G. In wideband wireless network access in case of high traffic and also in medium traffic conditions, moreover offering quality-of-service (QoS) to distinct service groups with synchronized contemporaneous traffic on the highway like the Mumbai-Pune expressway becomes a critical problem. Opportunist MAC (OMAC) is a way of proposing communication across a wireless communication link that can change in space and time and might overcome the above-mentioned challenge. Therefore, a multi-user scheduling algorithm is proposed for MIMO systems using a cross-layered MAC protocol to achieve URLLC and high reliability in V2X communication.

Keywords: ultra-reliable low latency communications, vehicle-to-everything communication, multiple-input multiple-output systems, multi-user scheduling algorithm

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Authors: Khin Thanda Win, Chunying Zhang, Sanghyeob Lee

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Mildew resistance locus o (Mlo), a plant-specific gene family with seven-transmembrane (TM), plays an important role in plant resistance to powdery mildew (PM). PM caused by Podosphaera xanthii is a widespread plant disease and probably represents the major fungal threat for many Cucurbits. The recent Cucurbita maxima genome sequence data provides an opportunity to identify and characterize the MLO gene family in this species. Total twenty genes (designated CmaMLO1 through CmaMLO20) have been identified by using an in silico cloning method with the MLO gene sequences of Cucumis sativus, Cucumis melo, Citrullus lanatus and Cucurbita pepo as probes. These CmaMLOs were evenly distributed on 15 chromosomes of 20 C. maxima chromosomes without any obvious clustering. Multiple sequence alignment showed that the common structural features of MLO gene family, such as TM domains, a calmodulin-binding domain and 30 important amino acid residues for MLO function, were well conserved. Phylogenetic analysis of the CmaMLO genes and other plant species reveals seven different clades (I through VII) and only clade IV is specific to monocots (rice, barley, and wheat). Phylogenetic and structural analyses provided preliminary evidence that five genes belonged to clade V could be the susceptibility genes which may play the importance role in PM resistance. This study is the first comprehensive report on MLO genes in C. maxima to our knowledge. These findings will facilitate the functional analysis of the MLOs related to PM susceptibility and are valuable resources for the development of disease resistance in pumpkin.

Keywords: Mildew resistance locus o (Mlo), powdery mildew, phylogenetic relationship, susceptibility genes

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Authors: H. D. Arora, Anjali Dhiman

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Uncertainty is found everywhere and its understanding is central to decision making. Uncertainty emerges as one has less information than the total information required describing a system and its environment. Uncertainty and information are so closely associated that the information provided by an experiment for example, is equal to the amount of uncertainty removed. It may be pertinent to point out that uncertainty manifests itself in several forms and various kinds of uncertainties may arise from random fluctuations, incomplete information, imprecise perception, vagueness etc. For instance, one encounters uncertainty due to vagueness in communication through natural language. Uncertainty in this sense is represented by fuzziness resulting from imprecision of meaning of a concept expressed by linguistic terms. Fuzzy set concept provides an appropriate mathematical framework for dealing with the vagueness. Both information theory, proposed by Shannon (1948) and fuzzy set theory given by Zadeh (1965) plays an important role in human intelligence and various practical problems such as image segmentation, medical diagnosis etc. Numerous approaches and theories dealing with inaccuracy and uncertainty have been proposed by different researcher. In the present communication, we generalize fuzzy entropy proposed by De Luca and Termini (1972) corresponding to Shannon entropy(1948). Further, some of the basic properties of the proposed measure were examined. We also applied the proposed measure to the real life decision making problem.

Keywords: entropy, fuzzy sets, fuzzy entropy, generalized fuzzy entropy, decision making

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Authors: Minho Kwon, Jeonghee Lim, Yeongseok Jeong, Donghoon Shin, Kiyoung Kim

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Recently, global warming phenomenon has led to natural disasters caused by global environmental changes, and due to abnormal weather events, the frequency and intensity of heavy rain storm typhoons are increasing. Therefore, it is imperative to prepare for future heavy rain storms and typhoons. This study selects arbitrary target bridges and performs numerical analysis to evaluate the safety of bridge piers in the event that the water level changes. The numerical model is based on two-dimensional surface elements. Actual reinforced concrete was simulated by modeling concrete to include reinforcements, and a contact boundary model was applied between the ground and the concrete. The water level applied to the piers was considered at 18 levels between 7.5 m and 16.1 m. The elastic modulus, compressive strength, tensile strength, and yield strength of the reinforced concrete were calculated using 250 random combinations and numerical analysis was carried out for each water level. In the results of analysis, the bridge exceeded the stated limit at 15.0 m. At the maximum water level of 16.1m, the concrete’s failure rate was 35.2%, but the probability that the reinforcement would fail was 61.2%.

Keywords: Monte-Carlo method, pier, water level change, limit state

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Authors: Muhammad Umar

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Safety and Assets management is considering a backbone of every department. GIS in the Railway become very important to Manage Assets and Security through Digital Maps and Web based GIS Maps. It provides a complete frame of work to the organization for the management of assets. Pakistan Railway is the most common and safest mode of traveling in Pakistan. Due to ever-increasing demand of transporting huge amount of information generated from various sources and this information must be accurate. This creates problems for Passengers and Administration that causes finical and time loss. GIS Solve this problem by Digital Maps & Database. It provides you a real time Spatial and Statistical analysis that helps you to communicate and exchange the information in a sophisticated way to the users. GIS Based Web system provides a facility to different end user to make query at a time as per requirements. This GIS System provides an advancement in an organization for a complete Monitoring, Safety and Decision System for tracks, Stations and Junctions that further use for the Analysis of different areas i.e. analysis of tracks, junctions and Stations in case of reconstruction, Rescue for rail accidents and Natural disasters .This Research work helps to reduce the financial loss and reduce human mistakes helps you provide a complete security and Management system of assets.

Keywords: Geographical Information System (GIS) for assets management, geo spatial database, railway assets management, Pakistan

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Authors: Zeynep Tanrıverdi

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The Bosphorus is an international waterway in Istanbul city of Turkey connecting the Sea of Marmara and the Black Sea. The Bosphorus, which has formed an important part of the silhouette of Istanbul throughout history, has also influenced the design of the coastal structures built around it. The waterfront mansions, which are located on both sides of the Bosphorus by the sea, and can be generally of two or three storeys, are called “yalı”. The yalı buildings with their architectural characteristics of the traditional Turkish House are the most grandiose examples of Ottoman residential architecture. However, the classical Ottoman yalı architecture of the 18th century can only be seen in engravings, and today only the modest and smaller yalı examples from the 19th century can be seen because of their disappearance over time. The study aims to reveal the architectural conservation and restoration problems of waterfront mansions and propose solutions for them. Firstly, the development of the waterfront mansion architecture in Bosphorus was evaluated in its historical process. Secondly, the waterfront mansions and their architectural features were explained. Thirdly, the architectural conservation and restoration problems that caused the disappearance of waterfront mansions were discussed. These problems include disruptions in legal regulations and practices about the Bosphorus, dramatic changes in Turkey’s socio-cultural life from the Ottoman Empire to the present, inadequacies in economic resources, negative environmental effects, and errors in restoration works. Finally, solution suggestions were proposed for the problems that threaten the protection of waterfront mansions. In the study, literature on waterfront mansions was reviewed using historical reports, photographs, maps, and drawings in archival documents. It is hoped that this study will contribute the conservation of the “Yalı” waterfront mansions, which occupy a particular role in the cultural heritage of Turkey, and to their transmission with their authentic values to the next generation.

Keywords: bosphorus architecture, conservation, heritage, Istanbul, waterfront mansions (yalı)

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Authors: R. Tlili Yaakoubi, H.Nakouri, O. Blanpain, S. Lallahem

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The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 19 to 100 %. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 40 % of total volume rejected to the natural environment and of 65 % in the number of discharges.

Keywords: automation, optimization, paradigm, RTC

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Authors: Sreeja Shaw, Prosenjit Samanta, Asish Kumar Mukhopadhyay

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Cholera is still a global public health burden and is caused by Vibrio cholerae O1 and O139 serogroups. Evidence from recent outbreaks in Haiti and Yemen suggested that circulating V. cholerae O1 El Tor variant strains are continuously changing to cause more ruinous outbreaks worldwide, and most of them have emerged from the Indian subcontinents. Therefore, we studied the changing virulence characteristics along with the antibiotic resistance profile of V. cholerae O1strains isolated from seasonal outbreaks in three cholera endemic regions during 2018, Gujarat and Maharashtra in Western India (87 strains), and to compare those features with the isolates of West Bengal in Eastern India (48 strains) collected during the same period. All the strains from Western India were of Ogawa serotype, polymyxin B-sensitive, hemolytic, and contained a large fragment deletion in VSP-II genomic region similar with Yemen outbreak strains and carried more virulent Haitian genetic alleles of major virulence associated genes ctxB, tcpA, and rtxA. Conversely, 14.6% (7/48) of the strains from Eastern India were belong to the Inaba serotype, polymyxin B-resistant, non-hemolytic, harbored intact VSP-II region, classical ctxB, Haitian tcpA, and El Tor rtxA alleles. Interestingly, resistance to tetracycline and chloramphenicol was seen in isolates from both regions, which are not very common among V. cholerae O1 isolates in India. Therefore, this study indicated West Bengal as a diverse region where two different types of El Tor variant hypervirulent strains are co-existed, probably competing for their better environmental survival, which may result in severe irrepressible disease outcome in the future.

Keywords: cholera, vibrio cholerae, polymyxin B, Non-hemolytic, ctxB, tcpA, rtxA, VSP-II

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Authors: Shreya Ghosh, Akansha Garg, Chayanika Kala, Ashwani Kumar Thakur

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Background: Granuloma formation is one of the characteristic features of tuberculosis. Besides, chronic inflammation underlying tuberculosis is often indicated by an increase in the concentration of serum amyloid A (SAA) protein. The connection between tuberculosis and SAA-driven secondary amyloidosis is well documented. However, SAA-derived amyloid deposition start sites are not well understood in tuberculosis and other chronic inflammatory conditions. It was hypothesized that granuloma could be a potential site for an amyloid deposition because both SAA protein and proteases that cleave SAA into aggregation-prone fragments are reported to be present in the granuloma. Here the authors have shown the presence of SAA-derived amyloid deposits in the granuloma of tuberculosis patients. Methodology: Over a period of two years, tuberculosis patients were screened, and biopsies were collected from the affected organs of the patients. The gold standard, Congo red dye staining, was used to identify amyloid deposits in the tissue sections of tuberculosis patients containing granulomatous structure. Results: 11 out of 150 FFPE biopsy specimens of tuberculosis patients showed eosinophilic hyaline-rich deposits surrounding granuloma. Upon Congo red staining, these deposits exhibited characteristic apple-green birefringence under polarized light, confirming amyloid deposits. Further, upon immunohistochemical staining with anti-SAA, the amyloid enriched areas showed positive immunoreactivity. Conclusion: In this pilot study, we have shown that granuloma can be a potential site for serum amyloid A-derived amyloid formation in tuberculosis patients. Moreover, the presence of amyloid gave significant cues that granuloma might be a probable amyloid deposition start in tuberculosis patients. This study will set a stage to expand the clinical and fundamental research in the understanding of amyloid formation in granuloma underlying tuberculosis and chronic inflammatory conditions.

Keywords: amyloid, granuloma, periphery, serum amyloid A, tuberculosis

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Authors: Agada N. Ihuoma, Nagata Yasunori

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Artificial intelligence (AI) techniques play a crucial role in predicting the expected energy outcome and its performance, analysis, modeling, and control of renewable energy. Renewable energy is becoming more popular for economic and environmental reasons. In the face of global energy consumption and increased depletion of most fossil fuels, the world is faced with the challenges of meeting the ever-increasing energy demands. Therefore, incorporating artificial intelligence to predict solar radiation outcomes from the intermittent sunlight is crucial to enable a balance between supply and demand of energy on loads, predict the performance and outcome of solar energy, enhance production planning and energy management, and ensure proper sizing of parameters when generating clean energy. However, one of the major problems of forecasting is the algorithms used to control, model, and predict performances of the energy systems, which are complicated and involves large computer power, differential equations, and time series. Also, having unreliable data (poor quality) for solar radiation over a geographical location as well as insufficient long series can be a bottleneck to actualization. To overcome these problems, this study employs the anaconda Navigator (Jupyter Notebook) for machine learning which can combine larger amounts of data with fast, iterative processing and intelligent algorithms allowing the software to learn automatically from patterns or features to predict the performance and outcome of Solar Energy which in turns enables the balance of supply and demand on loads as well as enhance production planning and energy management.

Keywords: artificial Intelligence, backward elimination, linear regression, solar energy

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Authors: Andrew Sutherland

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In many ways, opera is not a natural domain for children. It is hardly surprising that from the thousands of works, comparatively few include roles for children. There are several possibilities for this, the dramatic themes in opera are often about the human condition from the adult perspective; the need for developed voices to project in large, theatrical spaces underpinned by orchestral accompaniment does not naturally suit the child’s voice, and enabling children to cope with long runs of performances on top of their education requires vocal and physical stamina. In more recent times, the involvement of children contributes another layer of difficulty in terms of having access to young singers while adhering to laws that protect their working rights. Despite these points, children have been in opera since its inception in a variety of ways, but their contribution is often undervalued or ignored by musicologists and even the industry itself. In this paper, the phenomenon of children in opera from the late 16th century to the present day is explored through empirical, socio-musicological observations with reference to score analysis. Conclusions are drawn regarding the changing attitudes of composers when scoring for children’s voices in relation to societal developments. From the use of ‘kindertruppen’ in the pre-enlightenment period to Handel’s virtuosic writing for William Savage, to the darkness of the inter-war eras which saw a proliferation of operatic characters for children and the post-war era which saw children as the new frontier of building audiences for opera, the links between changes in society and the inclusion, portrayal and scoring for children in opera are largely congruent.

Keywords: children, musical analysis, opera, sociology

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Authors: Hamid Yazdani, Fatemeh Abbasi

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Biomimicry, where flora, fauna or entire ecosystems are emulated as a basis for design, is a growing area of research in the fields of architecture and engineering. This is due to both the fact that it is an inspirational source of possible new innovation and because of the potential it offers as a way to create a more sustainable and even regenerative built environment. The widespread and practical application of biomimicry as a design method remains however largely unrealised. A growing body of international research identifies various obstacles to the employment of biomimicry as an architectural design method. One barrier of particular note is the lack of a clear definition of the various approaches to biomimicry that designers can initially employ. Through a comparative literature review, and an examination of existing biomimetic technologies, this paper elaborates on distinct approaches to biomimetic design that have evolved. A framework for understanding the various forms of biomimicry has been developed, and is used to discuss the distinct advantages and disadvantages inherent in each as a design methodology. It is shown that these varied approaches may lead to different outcomes in terms of overall sustainability or regenerative potential. It is posited that a biomimetic approach to architectural design that incorporates an understanding of ecosystems could become a vehicle for creating a built environment that goes beyond simply sustaining current conditions to a restorative practice where the built environment becomes a vital component in the integration with and regeneration of natural ecosystems.

Keywords: biomimicry, bio-inspired design, ecology, ecomimicry, industrial ecology

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Authors: Alev Atak

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In this paper, we aim to create a financial sentiment index by investigating the company’s voluntary information disclosures. We retrieve structured content from BIST 100 companies’ financial reports for the period 1998-2018 and extract relevant financial information for sentiment analysis through Natural Language Processing. We measure strategy-related disclosures and their cross-sectional variation and classify report content into generic sections using synonym lists divided into four main categories according to their liquidity risk profile, risk positions, intra-annual information, and exposure to risk. We use Word Error Rate and Cosin Similarity for comparing and measuring text similarity and derivation in sets of texts. In addition to performing text extraction, we will provide a range of text analysis options, such as the readability metrics, word counts using pre-determined lists (e.g., forward-looking, uncertainty, tone, etc.), and comparison with reference corpus (word, parts of speech and semantic level). Therefore, we create an adequate analytical tool and a financial dictionary to depict the importance of granular financial disclosure for investors to identify correctly the risk-taking behavior and hence make the aggregated effects traceable.

Keywords: financial sentiment, machine learning, information disclosure, risk

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Authors: Umedov Mekhroz, Griaznova Svetlana

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The quality of life and well-being of patients, staff and visitors are central to the delivery of health care. Architecture and design are becoming an integral part of the healing and recovery approach. The most significant point that can be implemented in hospital buildings is the therapeutic value of the artificial environment, the design and integration of plants to bring the natural world into the healthcare environment. The hospital environment should feel like home comfort. The techniques that therapeutic architecture uses are very cheap, but provide real benefit to patients, staff and visitors, demonstrating that the difference is not in cost but in design quality. The best environment is not necessarily more expensive - it is about special use of light and color, rational use of materials and flexibility of premises. All this forms innovative concepts in modern hospital architecture, in new construction, renovation or expansion projects. The aim of the study is to identify the methods and principles of therapeutic architecture. The research methodology consists in studying and summarizing international experience in scientific research, literature, standards, methodological manuals and project materials on the research topic. The result of the research is the development of graphic-analytical tables based on the system analysis of the processed information; 3d visualization of hospital interiors based on processed information.

Keywords: therapeutic architecture, healthcare interiors, sustainable design, materials, color scheme, lighting, environment.

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Authors: Muhammad Farooq, Muhammad R. Shahid, M. Shakeel, A. Iftikhar, M. Sagheer, Riaz A. Kainth

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Comparative demography of Coccinella septempunctata Linnaeus (Coleoptera: Coccinellidae) was studied with respect to four host aphid species viz; Rhopalosiphum padi, Rhopalosiphum maidis, Sitobion avenae, and Shizaphis graminum under laboratory conditions using Two-sex Age-stage life table instead of traditional age specific life table which considers only female. Results revealed that developmental period from egg to adult of C. septempunctata were shorter on R. padi (16.49 days) whereas longer on R. maidis (22.83 days). Net reproductive rate varied from 110.01 offspring on R. maidis to 288.78 offspring on R. padi. Mean generation time (T) ranged from 29.02 d on R. padi to 39.788 d on R. maidis. Highest to lowest values of intrinsic rate of increase (rm) were recorded on R. padi, S. graminum, S. avenae, and R. maidis (0.194, 0.143, 0.140 and 0.117 d⁻¹, respectively). Highest finite rate of increase was observed on R. padi (1.214 d⁻¹) followed by S. graminum (1.154 d⁻¹) whereas lowest values were obtained on R. maidis and S. avenae (1.124 and 1.150 d⁻¹, respectively). In this study, the data on the life table of both predator and prey provide useful information in the mass rearing and practical application of a natural agent to biological control systems.

Keywords: C. septempunctata, two-sex age-stage life table, population parameters, aphid species

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Authors: Laref Nora, Guessas Bettache

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Lactic acid bacteria (LAB) have a major potential to be used in biopreservation methods because they are safe to consume (GRAS: generally regarded as safe) and they naturally occurring microflora of many foods. The preservative action of LAB is due to several antimicrobial metabolites, including lactic acid, acetic acid, hydrogen peroxide, bacteriocins, carbon dioxide, diacetyl, and reuterin. Several studies have focused on the antifungal activity compounds from natural sources for biopreservation in alternatives to chemical use. LAB has an antifungal activity which may inhibit food spoilage fungi. Lactobacillus strains isolated from silage prepared in our laboratory by fermentation of grass in anaerobic condition were screened for antifungal activity with overlay assay against Aspergillus spp. The antifungal compounds were originated from organic acids; inhibitory activity did not change after treatment with proteolytic enzymes. Lactobacillus strains were able also to inhibit Trichoderma spp, Penicillium spp, Fusarium roseum, and Stemphylim spp by confrontation assay. The inhibitory activity could be detected against the mould Aspergillus spp in the apricot juice but not in a bakery product. These antifungal compounds have the potential to be used as food biopreservation to inhibit conidia germination, and mycelia growth of spoilage fungi depending on food type, pH of food especially in heat, and cold processed foods.

Keywords: lactic acid bacteria, Lactobacillus, Aspergillus, antifungal activity

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Authors: Iyasu Eibedingil

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The construction industry is one of the major factors responsible for causing a negative impact on the environment. It has the largest share in the use of natural resources including land use, material extraction, and greenhouse gases emissions. For this reason, it is imperative to reduce its environmental impact through the construction of sustainable buildings with less impact. These days, it is possible to measure the environmental impact by using different tools such as the life cycle assessment (LCA) approach. Given this premise, this study explored the environmental impact of two types of roofing systems through comparative life cycle assessment approach. The tiles were analyzed to select the most environmentally friendly roofing system for the villa at Khalifa City A, Abu Dhabi, United Arab Emirates. These products are available in various forms; however, in this study concrete roof tiles and clay roof tiles were considered. The results showed that concrete roof tiles have lower environmental impact. In all scenarios considered, manufacturing the roof tiles locally, using recovered fuels for firing clay tiles, and using renewable energy (electricity from PV plant) showed that the concrete roof tiles were found to be excellent in terms of its embodied carbon, embodied the energy and various other environmental performance indicators.

Keywords: clay roof tile, concrete roof tile, life cycle assessment, sensitivity analysis

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Authors: C. Salis, D. Zedda, M. F. Wilson

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The IDEA project was conceived for teachers who are interested in enhancing their capacity to effectively implement the use of specific technologies in their teaching practice. Participating teachers are coached and supported as they explore technologies applied to the educational context. They access tools such as the technological platform developed by our team. Among the platform functionalities, teachers access an instructional systems design (ISD) tool (learning designer) that was adapted to the needs of our project. The tool is accessible from computers or mobile devices and used in association with other technologies to create new, meaningful learning environments. The objective of an instructional systems design is to guarantee the quality and effectiveness of education and to enhance learning. This goal involves both teachers who want to become more efficient in transferring knowledge or skills and students as the final recipient of their teaching. The use of Blooms’s taxonomy enables teachers to classify the learning objectives into levels of complexity and specificity, thus making it possible to highlight the kind of knowledge teachers would like their students to reach. The fact that the instructional design features can be visualized through the IDEA platform is a guarantee for those who are looking for specific educational materials to be used in their lessons. Despite the benefits offered, a number of teachers are reluctant to use ISD because the preparatory work of having to thoroughly analyze the teaching/learning objectives, the planning of learning material, assessment activities, etc., is long and felt to be time-consuming. This drawback is minimized using a learning designer, as the tool facilitates to reuse of the didactic contents having a clear view of the processes of analysis, planning, and production of educational or testing materials uploaded on our platform. In this paper, we shall present the feedback of the teachers who used our tool in their didactic.

Keywords: educational benefits, educational quality, educational technology, ISD tool

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Authors: Jingjue Bao, Ye Li, Yujie Qi

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The explosive growth of ride-hailing has reshaped residents' travel behavior and plays a crucial role in urban mobility within the built environment. Contributing to the research of the spatial variation of ride-hailing demand and its relationship to the built environment and socioeconomic factors, this study utilizes multi-source data from Haikou, China, to construct a Multi-scale Geographically Weighted Regression model (MGWR), considering spatial scale heterogeneity. The regression results showed that MGWR model was demonstrated superior interpretability and reliability with an improvement of 3.4% on R2 and from 4853 to 4787 on AIC, compared with Geographically Weighted Regression model (GWR). Furthermore, to precisely identify the surrounding environment of sampling point, DeepLabv3+ model is employed to segment street-level images. Features extracted from these images are incorporated as variables in the regression model, further enhancing its rationality and accuracy by 7.78% improvement on R2 compared with the MGWR model only considered region-level variables. By integrating multi-scale geospatial data and utilizing advanced computer vision techniques, this study provides a comprehensive understanding of the spatial dynamics between ride-hailing demand and the urban built environment. The insights gained from this research are expected to contribute significantly to urban transportation planning and policy making, as well as ride-hailing platforms, facilitating the development of more efficient and effective mobility solutions in modern cities.

Keywords: travel behavior, ride-hailing, spatial relationship, built environment, street-level image

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Authors: Sihem Benmimoune, Abdelbaki Lemgharbi, Ahmed Ait Yahia, Abdelkrim Kameli

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Our study is based on chemical and phytochemical characterization of Artemisia absinthium L and in vitro tests to demonstrate the biological activities of essential oil and natural extract. A qualitative and quantitative comparison of the essential oil extracted by two extraction procedures was performed by analysis of CG/SM and the yield calculation. The method of hydrodistillation has a chemical composition and provides oil content than the best training water vapor. These oils are composed mainly of thujone followed chamazulene and ρ-cymene. The antimicrobial activity of wormwood oil was tested in vitro by two methods (agar diffusion and microdilution) on four plant pathogenic fungi (Aspergillus sp, Botrytis cinerea, Fusarium culmorum and Helminthosporium sp). The study of the antifungal effect showed that this oil has an inhibitory effect counterpart the microorganisms tested in particular the strain Botrytis cinerea. Otherwise, this activity depends on the nature of the oil and the germ itself. The antioxidant activity in vitro was studied with the DPPH method. The activity test shows that the oil and extract of Artemisia absinthium have a very low antioxidant capacity compared to the antioxidants used as a reference. The extract has a potentially high antiradical power not from its oil. The quantitative determinations of phenolic compounds by the Folin-Ciocalteu revealed that absinthe is low in total polyphenols and tannins.

Keywords: artemisia absinthium, biological activities, essential oil, extraction processes

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Authors: M. Eskandarighadi, C. R. McGann

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It is observed from past experiences of earthquakes that local site conditions can significantly affect the strong ground motion characteristics experience at the site. One-dimensional seismic site response analysis is the most common approach for investigating site response. This approach assumes that soil is homogeneous and infinitely extended in the horizontal direction. Therefore, tying side boundaries together is one way to model this behavior, as the wave passage is assumed to be only vertical. However, 1D analysis cannot capture the 2D nature of wave propagation, soil heterogeneity, and 2D soil profile with features such as inclined layer boundaries. In contrast, 2D seismic site response modeling can consider all of the mentioned factors to better understand local site effects on strong ground motions. 2D wave propagation and considering that the soil profile on the two sides of the model may not be identical clarifies the importance of a boundary condition on each side that can minimize the unwanted reflections from the edges of the model and input appropriate loading conditions. Ideally, the model size should be sufficiently large to minimize the wave reflection, however, due to computational limitations, increasing the model size is impractical in some cases. Another approach is to employ free-field boundary conditions that take into account the free-field motion that would exist far from the model domain and apply this to the sides of the model. This research focuses on implementing free-field boundary conditions in OpenSees for 2D site response analysisComparisons are made between 1D models and 2D models with various boundary conditions, and details and limitations of the developed free-field boundary modeling approach are discussed.

Keywords: boundary condition, free-field, opensees, site response analysis, wave propagation

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Authors: Soheila Sadeghi

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Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast project performance metrics, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category in an urban road reconstruction project. The proposed model utilizes time series forecasting techniques, including Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance based on historical data and project progress. The model also incorporates external factors, such as weather patterns and resource availability, as features to enhance the accuracy of forecasts. By applying the predictive power of machine learning, the performance forecasting model enables proactive identification of potential deviations from the baseline plan, which allows project managers to take timely corrective actions. The research aims to validate the effectiveness of the proposed approach using a case study of an urban road reconstruction project, comparing the model's forecasts with actual project performance data. The findings of this research contribute to the advancement of project management practices in the construction industry, offering a data-driven solution for improving project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, earned value management

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Authors: Ali Ait Si Mhamed, Rita Kasa, Hans Vossensteyn

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Kazakhstan is the eight largest country on the globe, in terms of the territory, it is rich in natural resources and is developing dynamically. Kazakhstan strives to become one of the top 30 global economies by 2050. This goal preconditions intensive reforms in all sectors of economy, including higher education. This paper focuses on the higher education funding reforms that take place in Kazakhstan and their alignment with the strategic goals of national development. Currently, the government funds higher education costs for only a limited number of students while the majority of students pay full cost covering tuition fees. Only students with high examination scores at the end of the secondary education are eligible to be admitted to publically funded study places in higher education. While this merit-based higher education funding model is overall well-received in the country, there is also a discourse calling to change the existing approach of higher education funding. This paper draws on interviews with national policy makers and leadership at institutions of higher education in Kazakhstan collected during 2016. It seeks to answer a question about how well the current higher education funding mechanism is aligned with the strategic development goals in higher education. The paper discusses how stakeholders see the fit between the current higher education funding mechanism and the ability of higher education institutions to achieve the aims of national strategic development.

Keywords: higher education reform, higher education funding, higher education policy, Kazakhstan

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Authors: Sharareh Sharifi, Pargol Ghavam Mostafavi, Ali Mashinchian Moradi, Mohammad Hadi Givianrad, Hassan Niknejad

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Marine organisms such as soft coral, sponge, ascidians, and tunicate containing rich source of natural compound have been studied in last decades because of their special chemical compounds with anticancer properties. The aim of this study was to investigate anti-cancer property of ethyl acetate extracted from marine sea pen Virgularia gustaviana found from Persian Gulf coastal (Bandar Abbas). The extraction processes were carried out with ethyl acetate for five days. Thin layer chromatography (TLC) and high-performance liquid chromatography (HPLC) were used for qualitative identification of crude extract. The viability of HeLa and MDA-Mb-231 cancer cells was investigated using MTT assay at the concentration of 25, 50, and a 100 µl/ml of ethyl acetate is extracted. The crude extract of Virgularia gustaviana demonstrated ten fractions with different Retention factor (Rf) by TLC and Retention time (Rt) evaluated by HPLC. The crude extract dose-dependently decreased cancer cell viability compared to control group. According to the results, the ethyl acetate extracted from Virgularia gustaviana inhibits the growth of cancer cells, an effect which needs to be further investigated in the future studies.

Keywords: anti-cancer, Hela cancer cell, MDA-Md-231 cancer cell, Virgularia gustavina

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Authors: Vishal Kumar Singh

Abstract:

Bioprocess development is a time-constrained activity aimed at harnessing the full potential of culture performance in an ambience that is not natural to cells. Even with the use of chemically defined media and feeds, a significant amount of time is devoted in identifying the apt operating parameters. In addition, the scale-up of these processes is often accompanied by loss of antibody titer and product quality, which further delays the commercialization of the drug product. In such a scenario, the investigation of this disparity of culture performance is done by further experimentation at a smaller scale that is representative of at-scale production bioreactors. These scale-down model developments are also time-intensive. In this study, a computation fluid dynamics-based multi-objective scaling approach has been illustrated to speed up the process transfer. For the implementation of this approach, a transient multiphase water-air system has been studied in Ansys CFX to visualize the air bubble distribution and volumetric mass transfer coefficient (kLa) profiles, followed by the design of experiment based parametric optimization approach to define the operational space. The proposed approach is completely in silico and requires minimum experimentation, thereby rendering a high throughput to the overall process development.

Keywords: bioprocess development, scale up, scale down, computation fluid dynamics, multi-objective, Ansys CFX, design of experiment

Procedia PDF Downloads 82