Search results for: supply chain delivery models

Authors: Aloke Bapli, Debabrata Seth

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Graphene oxide (GO) is the two-dimensional (2D) nanoscale allotrope of carbon having several physiochemical properties such as high mechanical strength, high surface area, strong thermal and electrical conductivity makes it an important candidate in various modern applications such as drug delivery, supercapacitors, sensors etc. GO has been used in the photothermal treatment of cancers and Alzheimer’s disease etc. The main idea to choose GO in our work is that it is a surface active molecule, it has a large number of hydrophilic functional groups such as carboxylic acid, hydroxyl, epoxide on its surface and in basal plane. So it can easily interact with organic fluorophores through hydrogen bonding or any other kind of interaction and easily modulate the photophysics of the probe molecules. We have used different spectroscopic techniques for our work. The Ground-state absorption spectra and steady-state fluorescence emission spectra were measured by using UV-Vis spectrophotometer from Shimadzu (model-UV-2550) and spectrofluorometer from Horiba Jobin Yvon (model-Fluoromax 4P) respectively. All the fluorescence lifetime and anisotropy decays were collected by using time-correlated single photon counting (TCSPC) setup from Edinburgh instrument (model: LifeSpec-II, U.K.). Herein, we described the photophysics of a hydrophilic molecule 7-(n,n׀-diethylamino) coumarin-3-carboxylic acid (7-DCCA) in the reverse micelles containing GO. It was observed that photophysics of dye is modulated in the presence of GO compared to photophysics of dye in the absence of GO inside the reverse micelles. Here we have reported the solvent relaxation and rotational relaxation time in GO containing reverse micelle and compare our work with normal reverse micelle system by using 7-DCCA molecule. Normal reverse micelle means reverse micelle in the absence of GO. The absorption maxima of 7-DCCA were blue shifted and emission maxima were red shifted in GO containing reverse micelle compared to normal reverse micelle. The rotational relaxation time in GO containing reverse micelle is always faster compare to normal reverse micelle. Solvent relaxation time, at lower w₀ values, is always slower in GO containing reverse micelle compare to normal reverse micelle and at higher w₀ solvent relaxation time of GO containing reverse micelle becomes almost equal to normal reverse micelle. Here emission maximum of 7-DCCA exhibit bathochromic shift in GO containing reverse micelles compared to that in normal reverse micelles because in presence of GO the polarity of the system increases, as polarity increases the emission maxima was red shifted an average decay time of GO containing reverse micelle is less than that of the normal reverse micelle. In GO containing reverse micelle quantum yield, decay time, rotational relaxation time, solvent relaxation time at λₑₓ=375 nm is always higher than λₑₓ=405 nm, shows the excitation wavelength dependent photophysics of 7-DCCA in GO containing reverse micelles.

Keywords: photophysics, reverse micelle, rotational relaxation, solvent relaxation

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Authors: David Pham, Yongfeng Zhang

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Graphs are an important structure for data storage and computation. Recent years have seen the success of deep learning on graphs such as Graph Neural Networks (GNN) on various data mining and machine learning tasks. However, most of the deep learning models on graphs cannot easily explain their predictions and are thus often labelled as “black boxes.” For example, Graph Attention Network (GAT) is a frequently used GNN architecture, which adopts an attention mechanism to carefully select the neighborhood nodes for message passing and aggregation. However, it is difficult to explain why certain neighbors are selected while others are not and how the selected neighbors contribute to the final classification result. In this paper, we present a graph learning model called Explainable Graph Attention Network (XGAT), which integrates graph attention modeling and explainability. We use a single model to target both the accuracy and explainability of problem spaces and show that in the context of graph attention modeling, we can design a unified neighborhood selection strategy that selects appropriate neighbor nodes for both better accuracy and enhanced explainability. To justify this, we conduct extensive experiments to better understand the behavior of our model under different conditions and show an increase in both accuracy and explainability.

Keywords: explainable AI, graph attention network, graph neural network, node classification

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Authors: Sifeddine Abderrahmani, Sonia Bouafia

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The finite element method is the most practical tool for the analysis of structures, whatever the geometrical shape and behavior. It is extensively used in many high-tech industries, such as civil or military engineering, for the modeling of bridges, motor bodies, fuselages, and airplane wings. Additionally, experience demonstrates that engineers like modeling their structures using the most basic finite elements. Numerous models of finite elements may be utilized in the numerical analysis depending on the interpolation field that is selected, and it is generally known that convergence to the proper value will occur considerably more quickly with a good displacement pattern than with a poor pattern, saving computation time. The method for creating finite elements using the strain approach (S.B.A.) is presented in this presentation. When the results are compared with those provided by equivalent displacement-based elements, having the same total number of degrees of freedom, an excellent convergence can be obtained through some application and validation tests using recently developed membrane elements, plate bending elements, and flat shell elements. The effectiveness and performance of the strain-based finite elements in modeling structures are proven by the findings for deflections and stresses.

Keywords: finite elements, plate bending, strain approach, displacement formulation, shell element

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Authors: Michael Scott, Phil Jarrell

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Digitalization seems to be everywhere these days. So if one was to digitalize Functional Safety, what would that require: • Ability to directly use data from intelligent P&IDs / process design in a PHA / LOPA • Ability to directly use data from intelligent P&IDs in the SIS Design to support SIL Verification Calculations, SRS, C&Es, Functional Test Plans • Ability to create Unit Operation / SIF Libraries to radically reduce engineering manhours while ensuring consistency and improving quality of SIS designs • Ability to link data directly from a PHA / LOPA to SIS Designs • Ability to leverage reliability models and SRS details from SIS Designs to automatically program the Safety PLC • Ability to leverage SIS Test Plans to automatically create Safety PLC application logic Test Plans for a virtual FAT • Ability to tie real-time data from Process Historians / CMMS to assumptions in the PHA / LOPA and SIS Designs to generate leading indicators on protection layer health • Ability to flag SIS bad actors for proactive corrective actions prior to a near miss or loss of containment event What if I told you all of this was available today? This paper will highlight how the digital revolution has revolutionized the way Safety Instrumented Systems are designed, configured, operated and maintained.

Keywords: IEC 61511, safety instrumented systems, functional safety, digitalization, IIoT

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Authors: M. S. Mahmoud, Samah A. Mohamed, Neama A. Sobhy

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For color removal from wastewater containing organic contaminants, biological treatment systems have been widely used such as physical and chemical methods of flocculation, coagulation. Fungal decolorization of dye containing wastewater is one of important goal in industrial wastewater treatment. This work was aimed to characterize Aspergillus niger strain for dye removal from aqueous solution and from raw textile wastewater. Batch experiments were studied for removal of color using fungal isolate biomass under different conditions. Environmental conditions like pH, contact time, adsorbent dose and initial dye concentration were studied. Influence of the pH on the removal of azo dye by Aspergillus niger was carried out between pH 1.0 and pH 11.0. The optimum pH for red dye decolonization was 9.0. Results showed the decolorization of dye was decreased with the increase of its initial dye concentration. The adsorption data was analyzed based on the models of equilibrium isotherm (Freundlich model and Langmuir model). During the adsorption isotherm studies; dye removal was better fitted to Freundlich model. The isolated fungal biomass was characterized according to its surface area both pre and post the decolorization process by Scanning Electron Microscope (SEM) analysis. Results indicate that the isolated fungal biomass showed higher affinity for dye in decolorization process.

Keywords: biomass, biosorption, dye, isotherms

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Authors: Marzieh Karimihaghighi, Carlos Castillo

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This work studies how Machine Learning (ML) may be used to increase the effectiveness of a criminal recidivism risk assessment tool, RisCanvi. The two key dimensions of this analysis are predictive accuracy and algorithmic fairness. ML-based prediction models obtained in this study are more accurate at predicting criminal recidivism than the manually-created formula used in RisCanvi, achieving an AUC of 0.76 and 0.73 in predicting violent and general recidivism respectively. However, the improvements are small, and it is noticed that algorithmic discrimination can easily be introduced between groups such as national vs foreigner, or young vs old. It is described how effectiveness and algorithmic fairness objectives can be balanced, applying a method in which a single error disparity in terms of generalized false positive rate is minimized, while calibration is maintained across groups. Obtained results show that this bias mitigation procedure can substantially reduce generalized false positive rate disparities across multiple groups. Based on these results, it is proposed that ML-based criminal recidivism risk prediction should not be introduced without applying algorithmic bias mitigation procedures.

Keywords: algorithmic fairness, criminal risk assessment, equalized odds, recidivism

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Authors: Prasanna Ramachandran, Kareem Graham, Helena Kiefel, Sunit Jain, Todd DeSantis

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Microbes that reside inside the mammalian GI tract, commonly referred to as the gut microbiome, have been shown to have therapeutic effects in animal models of disease. We hypothesize that specific proteins produced by these microbes are responsible for this activity and may be used directly as therapeutics. To speed up the discovery of these key proteins from the big-data metagenomics, we have applied machine learning techniques. Using amino acid sequences of known epitopes and their corresponding binding partners, protein interaction descriptors (PID) were calculated, making a positive interaction set. A negative interaction dataset was calculated using sequences of proteins known not to interact with these same binding partners. Using Random Forest and positive and negative PID, a machine learning model was trained and used to predict interacting versus non-interacting proteins. Furthermore, the continuous variable, cosine similarity in the interaction descriptors was used to rank bacterial therapeutic candidates. Laboratory binding assays were conducted to test the candidates for their potential as therapeutics. Results from binding assays reveal the accuracy of the machine learning prediction and are subsequently used to further improve the model.

Keywords: protein-interactions, machine-learning, metagenomics, microbiome

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Authors: Niyati Sharma, Om Anand, Sanjeev Kumar Prasad

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Assuming future sale value for any of the organizations is one of the major essential characteristics of tactical development. Walmart Sales Forecasting is the finest illustration to work with as a beginner; subsequently, it has the major retail data set. Walmart uses this sales estimate problem for hiring purposes also. We would like to analyzing how the internal and external effects of one of the largest companies in the US can walk out their Weekly Sales in the future. Demand forecasting is the planned prerequisite of products or services in the imminent on the basis of present and previous data and different stages of the market. Since all associations is facing the anonymous future and we do not distinguish in the future good demand. Hence, through exploring former statistics and recent market statistics, we envisage the forthcoming claim and building of individual goods, which are extra challenging in the near future. As a result of this, we are producing the required products in pursuance of the petition of the souk in advance. We will be using several machine learning models to test the exactness and then lastly, train the whole data by Using linear regression and fitting the training data into it. Accuracy is 8.88%. The extra trees regression model gives the best accuracy of 97.15%.

Keywords: random forest algorithm, linear regression algorithm, extra trees classifier, mean absolute error

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Authors: Gabriela Kalcikova, Igor Bosevski, Ula Rozman, Andreja Zgajnar Gotvajn

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Antibiotics are extensively used in human medicine and also in animal husbandry to prevent or control infections. Recently, a lot of attention has been put on veterinary antibiotics, because their global consumption is increasing and it is expected to be 106.600 tons in 2030. Most of veterinary antibiotics are introduced into the environment via animal manure, which is used as fertilizer. One of such veterinary antibiotics is tiamulin. It is used the form of fumarate for treatment of pig and poultry. It is used against prophylaxis of dysentery, pneumonia and mycroplasmal infections, but its environmental impact is practically unknown. Tiamulin has been found very persistent in animal manure and thus it is expected that can be, during rainfalls, transported into the aquatic environment and affect various organisms. For assessment of its environmental impact, it is necessary to evaluate its biodegradability and toxicity to various organisms from different levels of a food chain. Therefore, the aim of our study was to evaluate ready biodegradability and toxicity of tiamulin fumarate to various organisms. Bioassay used included luminescent bacterium Vibrio fischeri heterotrophic and nitrifying microorganisms of activated sludge, water flea Daphnia magna and duckweed Lemna minor. For each species, EC₅₀ values were calculated. Biodegradability test was used for determination of ready biodegradability and it provides information about biodegradability of tiamulin under the most common environmental conditions. Results of our study showed that tiamulin differently affects selected organisms. The most sensitive organisms were water fleas with 48hEC₅₀ = 14.2 ± 4.8 mg/L and duckweed with 168hEC₅₀ = 22.6 ± 0.8 mg/L. Higher concentrations of tiamulin (from 10 mg/L) significantly affected photosynthetic pigments content in duckweed and concentrations above 80 mg/L cause visible chlorosis. It is in agreement with previous studies showing significant effect of tiamulin on green algae and cyanobacteria. Tiamuline has a low effect on microorganisms. The lower toxicity was observed for heterotrophic microorganisms (30minEC₅₀ = 1656 ± 296 mg/L), than Vibrio fisheri (30minEC₅₀ = 492 ± 21) and the most sensitive organisms were nitrifying microorganisms (30minEC₅₀ = 183 ± 127 mg/L). The reason is most probably the mode of action of tiamulin being effective to gram-positive bacteria while gram-negative (e.g., Vibrio fisheri) are more tolerant to tiamulin. Biodegradation of tiamulin was very slow with a long lag-phase being 20 days. The maximal degradation reached 40 ± 2 % in 43 days of the test and tiamulin as other antibiotics (e.g. ciprofloxacin) are not easily biodegradable. Tiamulin is widely used antibiotic in veterinary medicine and thus present in the environment. According to our results, tiamulin can have negative effect on water fleas and duckweeds, but the concentrations are several magnitudes higher than that found in any environmental compartment. Tiamulin is low toxic to tested microorganisms, but it is very low biodegradable and thus possibly persistent in the environment.

Keywords: antibiotics, biodegradability, tiamulin, toxicity

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Authors: Andrzej Kesiak

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Contemporary theology is often accused of answering questions that nobody is asking, and of employing hermetic language that has lost its communication capacity. There is also a question that theology is asking itself: how theological discourse can still be influential on other disciplines and, how to overcome the separation of theology and belief. Undoubtedly, in the wider spectrum, the theological discourse has been and will be needed. The difficulty is how to find the right model of it, the model that would help theology to enter in dialogue with culture, art, science, and politics. Presumably, there is no only one such model, theology constantly needs to seek such models, and this is probably a never-ending journey; in other words, theology should adopt a profile of ‘a restless being’ if it wants to remain influential. Music, on the other hand, has always been very close to theology; in fact, a huge part of classical music is either sacred or religious. Many composers sought inspiration in religion, liturgy, religious painting and sacred texts. This paper will argue that despite all that it seems that a proper and factual dialogue is still in a starting phase. Such a thing as a reciprocal relationship between theology and music definitely exists, but it has not yet been theoretically developed enough. Correlation between musical and theological disciplines constitutes a very broad and complex discourse. Therefore this study would rather narrow the subject and put it in a specific context: Theology and Music in the XXI. Century. This paper is a text-based study; therefore it will be based on textual-analysis with elements of the text hermeneutics.

Keywords: music, theology, reciprocal relationship between theology and music, XXI Century

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Authors: Liang Wang, Beste F. Yuksel, David Guy Brizan

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A computational model of affect that can distinguish between spontaneous and posed smiles with no errors on a large, popular data set using deep learning techniques is presented in this paper. A Long Short-Term Memory (LSTM) classifier, a type of Recurrent Neural Network, is utilized and compared to human classification. Results showed that while human classification (mean of 0.7133) was above chance, the LSTM model was more accurate than human classification and other comparable state-of-the-art systems. Additionally, a high accuracy rate was maintained with small amounts of training videos (70 instances). The derivation of important features to further understand the success of our computational model were analyzed, and it was inferred that thousands of pairs of points within the eyes and mouth are important throughout all time segments in a smile. This suggests that distinguishing between a posed and spontaneous smile is a complex task, one which may account for the difficulty and lower accuracy of human classification compared to machine learning models.

Keywords: affective computing, affect detection, computer vision, deep learning, human-computer interaction, machine learning, posed smile detection, spontaneous smile detection

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Authors: Mehvish Bilal, Navneet Singh, Jasir Mushtaq

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Water pollution puts people's health at risk, and it can also impact the ecology. For practitioners of integrated water resources management (IWRM), water quality modelling may be useful for informing decisions about pollution control (such as discharge permitting) or demand management (such as abstraction permitting). To comprehend the current pollutant load, movement of effective load movement of contaminants generates effective relation between pollutants, mathematical simulation, source, and water quality is regarded as one of the best estimating tools. The current study involves the Qual2k model, which includes manual simulation of the various physiochemical characteristics of water. To this end, various sensors could be installed for the automatic simulation of various physiochemical characteristics of water. An artificial intelligence model has been proposed for the automatic simulation of water quality parameters. Models of water quality have become an effective tool for identifying worldwide water contamination, as well as the ultimate fate and behavior of contaminants in the water environment. Water quality model research is primarily conducted in Europe and other industrialized countries in the first world, where theoretical underpinnings and practical research are prioritized.

Keywords: artificial intelligence, QUAL2K, simulation, physiochemical parameters

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Authors: Hiba Hamdi, Thomas Corpetti, Laure Roupioz, Xavier Briottet

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Air temperatures are generally higher in cities than in their rural surroundings. The overheating of cities is a direct consequence of increasing urbanization, characterized by the artificial filling of soils, the release of anthropogenic heat, and the complexity of urban geometry. This phenomenon, referred to as urban heat island (UHI), is more prevalent during heat waves, which have increased in frequency and intensity in recent years. In the context of global warming and urban population growth, helping urban planners implement UHI mitigation and adaptation strategies is critical. In practice, the study of UHI requires air temperature information at the street canyon level, which is difficult to obtain. Many urban air temperature simulation models have been proposed (mostly based on physics or statistics), all of which require a variety of input parameters related to urban morphology, land use, material properties, or meteorological conditions. In this paper, we build and evaluate a neural network model based on Urban Weather Generator (UWG) model simulations and data from meteorological stations that simulate air temperature over Toulouse, France, on days favourable to UHI.

Keywords: air temperature, neural network model, urban heat island, urban weather generator

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Authors: Layla Mujahed

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COVID-19 is an exam for all the city’s systems. It shows many gaps in the systems such as healthcare, economic, social, and environment. This pandemic is paving for a new era, an era of technology and it has changed people’s lives, such as physical, and emotional changes, and converting communication into digitalized. The effect of COVID-19 has covered all urban city parts. COVID-19 will not be the last pandemic our cities will face. For that, more researches focus on enhancing the quality of the urban environment. This pandemic encourages a rethinking of the environment’s role, especially in cities. Cities are trying to provide the best suitable strategies and regulations to prevent the spread of COVID-19, and an example of that is Amman city. Amman has a high increment in the number of COVID-19 infected people, while it has controlled the situation for months. For that, this paper studies the relation between COVID-19 and urban environmental studies cases about cities around the world, and learns from their models to face COVID-19. In Amman, people’s behavior has changed towards public transportation and public green spaces. N­ew governmental regulations focus on increasing people’s mental awareness, supporting local businesses, and enhancing neighborhood planning that can help Amman to face any future pandemics.

Keywords: COVID-19, urban environment, urban planning, urban resilience

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Authors: Vanessa Cho, Janet Hsiao, Nigel King, Robert Anthonappa

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Background: The personal protective equipment (PPE) requirements for health care workers (HCWs) have changed significantly during the COVID-19 pandemic. Aim: To ascertain, using eye-tracking technology, what children notice the most when seeing HCWs in various PPE. Design: A Tobii nano pro-eye-tracking camera tracked 156 children's visual attention while they viewed photographs of HCWs in various PPEs. Eye Movement analysis with Hidden Markov Models (EMHMM) was employed to analyse 624 recordings using two approaches, namely (i) data-driven where children's fixation determined the regions of interest (ROIs), and (ii) fixed ROIs where the investigators predefined the ROIs. Results: Two significant eye movement patterns, namely distributed(85.2%) and selective(14.7%), were identified(P<0.05). Most children fixated primarily on the face regardless of the different PPEs. Children fixated equally on all PPE images in the distributed pattern, while a strong preference for unmasked faces was evident in the selective pattern (P<0.01). Conclusion: Children as young as 2.5 years used a top-down visual search behaviour and demonstrated their face processing ability. Most children did not show a strong visual preference for a specific PPE, while a minority preferred PPE with distinct facial features, namely without masks and loupes.

Keywords: COVID-19, PPE, dentistry, pediatric

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Authors: William Michael Short

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Semantic Web’ technologies such as the Unified Medical Language System Metathesaurus, SNOMED-CT, and MeSH have been touted as transformational for the way users access online medical and health information, enabling both the automated analysis of natural-language data and the integration of heterogeneous healthrelated resources distributed across the Internet through the use of standardized terminologies that capture concepts and relationships between concepts that are expressed differently across datasets. However, the approaches that have so far characterized ‘semantic bioinformatics’ have not yet fulfilled the promise of the Semantic Web for medical and health information retrieval applications. This paper argues within the perspective of cognitive linguistics and cognitive anthropology that four features of human meaning-making must be taken into account before the potential of semantic technologies can be realized for this domain. First, many semantic technologies operate exclusively at the level of the word. However, texts convey meanings in ways beyond lexical semantics. For example, transitivity patterns (distributions of active or passive voice) and modality patterns (configurations of modal constituents like may, might, could, would, should) convey experiential and epistemic meanings that are not captured by single words. Language users also naturally associate stretches of text with discrete meanings, so that whole sentences can be ascribed senses similar to the senses of words (so-called ‘discourse topics’). Second, natural language processing systems tend to operate according to the principle of ‘one token, one tag’. For instance, occurrences of the word sound must be disambiguated for part of speech: in context, is sound a noun or a verb or an adjective? In syntactic analysis, deterministic annotation methods may be acceptable. But because natural language utterances are typically characterized by polyvalency and ambiguities of all kinds (including intentional ambiguities), such methods leave the meanings of texts highly impoverished. Third, ontologies tend to be disconnected from everyday language use and so struggle in cases where single concepts are captured through complex lexicalizations that involve profile shifts or other embodied representations. More problematically, concept graphs tend to capture ‘expert’ technical models rather than ‘folk’ models of knowledge and so may not match users’ common-sense intuitions about the organization of concepts in prototypical structures rather than Aristotelian categories. Fourth, and finally, most ontologies do not recognize the pervasively figurative character of human language. However, since the time of Galen the widespread use of metaphor in the linguistic usage of both medical professionals and lay persons has been recognized. In particular, metaphor is a well-documented linguistic tool for communicating experiences of pain. Because semantic medical knowledge-bases are designed to help capture variations within technical vocabularies – rather than the kinds of conventionalized figurative semantics that practitioners as well as patients actually utilize in clinical description and diagnosis – they fail to capture this dimension of linguistic usage. The failure of semantic technologies in these respects degrades the efficiency and efficacy not only of medical research, where information retrieval inefficiencies can lead to direct financial costs to organizations, but also of care provision, especially in contexts of patients’ self-management of complex medical conditions.

Keywords: ambiguity, bioinformatics, language, meaning, metaphor, ontology, semantic web, semantics

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Authors: M. Mutoti, J. Gumbo, A. Jideani

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Cyanobacteria or blue green algae have been part of the human diet for thousands of years. Cyanobacteria can multiply quickly in surface waters and form blooms when favorable conditions prevail, such as high temperature, intense light, high pH, and increased availability of nutrients, especially phosphorous and nitrogen, artificially released by anthropogenic activities. Consumption of edible cyanotoxins such as Spirulina may reduce risks of cataracts and age related macular degeneration. Sulfate polysaccharides exhibit antitumor, anticoagulant, anti-mutagenic, anti-inflammatory, antimicrobial, and even antiviral activity against HIV, herpes, and hepatitis. In humans, exposure to cyanotoxins can occur in various ways; however, the oral route is the most important. This is mainly through drinking water, or by eating contaminated foods; it may even involve ingesting water during recreational activities. This paper seeks to present a review on cyanobacteria/cyanotoxin contamination of water and food and implications for human health. In particular, examining the water quality used during maize seed that passes through mill grinding processes. In order to fulfil the objective, this paper starts with the theoretical framework on cyanobacteria contamination of food that will guide review of the present paper. A number of methods for decontaminating cyanotoxins in food is currently available. Therefore, physical, chemical, and biological methods for treating cyanotoxins are reviewed and compared. Furthermore, methods that are utilized for detecting and identifying cyanobacteria present in water and food were also informed in this review. This review has indicated various routes through which humans can be exposed to cyanotoxins. Accumulation of cyanotoxins, mainly microcystins, in food has raised an awareness of the importance of food as microcystins exposure route to human body. Therefore, this review demonstrates the importance of expanding research on cyanobacteria/cyanotoxin contamination of water and food for water treatment and water supply management, with focus on examining water for domestic use. This will help providing information regarding the prevention or minimization of contamination of water and food, and also reduction or removal of contamination through treatment processes and prevention of recontamination in the distribution system.

Keywords: biofilm, cyanobacteria, cyanotoxin, food contamination

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Authors: Amir Hossein Ghaffari Nejad, Forouhar Ferdowsi, Reza Mashhadi

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In the interest-free banking system of Iran, the savings of society are in the form of bank deposits, and banks using the Islamic contracts, allocate the resources to applicants for obtaining facilities and credit. In the meantime, the central bank, with the aim of introducing monetary policy, determines the maximum interest rate on bank deposits in terms of macroeconomic requirements. But in recent years, the country's economic constraints with the stagflation and the consequence of the institutional weaknesses of the financial market of Iran have resulted in massive disturbances in the balance sheet of the banking system, resulting in a period of mismatch maturity in the banks' assets and liabilities and the implementation of a Ponzi game. This issue caused determination of the interest rate in long-term bank deposit contracts to be associated with non-observance of the maximum rate set by the central bank. The result of this condition was in the allocation of new sources of equipment to meet past commitments towards the old depositors and, as a result, a significant part of the supply of equipment was leaked out of the facilitating cycle and credit crunch emerged. The purpose of this study is to identify the most important factors affecting the occurrence of non-confirmatory financial banking behavior using data from 19 public and private banks of Iran. For this purpose, the causes of this non-confirmatory behavior of banks have been investigated using the panel vector autoregression method (PVAR) for the period of 2007-2015. Granger's causality test results suggest that the return of parallel markets for bank deposits, non-performing loans and the high share of the ratio of facilities to banks' deposits are all a cause of the formation of non-confirmatory behavior. Also, according to the results of impulse response functions and variance decomposition, NPL and the ratio of facilities to deposits have the highest long-term effect and also have a high contribution to explaining the changes in banks' non-confirmatory behavior in determining the interest rate on deposits.

Keywords: non-conformity behavior, Ponzi Game, panel vector autoregression, nonperforming loans

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Authors: Tomokazu Nagata, Jawid Ahmad Baktash

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The goal of this paper is to explore the use of formal methods for Electronic Identity Card System. Nowadays, one of the core research directions in a constantly growing distributed environment is the improvement of the communication process. The responsibility for proper verification becomes crucial. Formal methods can play an essential role in the development and testing of systems. The thesis presents two different methodologies for assessing correctness. Our first approach employs abstract interpretation techniques for creating a trace based model for Electronic Identity Card System. The model was used for building a semi decidable procedure for verifying the system model. We also developed the code for the eID System and can cover three parts login to system sending of Acknowledgment from user side, receiving of all information from server side and log out from system. The new concepts of impasse and spawned sessions that we introduced led our research to original statements about the intruder’s knowledge and eID system coding with respect to secrecy. Furthermore, we demonstrated that there is a bound on the number of sessions needed for the analysis of System.Electronic identity (eID) cards promise to supply a universal, nation-wide mechanism for user authentication. Most European countries have started to deploy eID for government and private sector applications. Are government-issued electronic ID cards the proper way to authenticate users of online services? We use the eID project as a showcase to discuss eID from an application perspective. The new eID card has interesting design features, it is contact-less, it aims to protect people’s privacy to the extent possible, and it supports cryptographically strong mutual authentication between users and services. Privacy features include support for pseudonymous authentication and per service controlled access to individual data items. The article discusses key concepts, the eID infrastructure, observed and expected problems, and open questions. The core technology seems ready for prime time and government projects deploy it to the masses. But application issues may hamper eID adoption for online applications.

Keywords: eID, event-B, Pro-B, formal method, message passing

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Authors: Yasin Kutuk, Bengi Yanik Ilhan

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Previous studies investigate the wage differentiations among regions in Turkey between couples who work in the same industry and those who work in different industries by using the models that is appropriate for cross sectional data. However, since there is no available panel data for this investigation in Turkey, pseudo panels using repeated cross-section data sets of the Household Labor Force Surveys 2004-2014 are employed in order to open a new way to examine wage differentiation patterns. For this purpose, household heads are separated into groups with respect to their household composition. These groups’ membership is assumed to be fixed over time such as age groups, education, gender, and NUTS1 (12 regions) Level. The average behavior of them can be tracked overtime same as in the panel data. Estimates using the pseudo panel data would be consistent with the estimates using genuine panel data on individuals if samples are representative of the population which has fixed composition, characteristics. With controlling the socioeconomic factors, wage differentiation of household income is affected by social, cultural and economic changes after global economic crisis emerged in US. It is also revealed whether wage differentiation is changing among the birth cohorts.

Keywords: wage income, same industry, pseudo panel, panel data econometrics

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Authors: Cristiane C. B. Alves, Livia Eisler, Gustavo Mota, Kurt Faltin Jr., Cristina L. F. Ortolani

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The correct positioning of the brackets is essential for the success of orthodontic treatment. Indirect bracket placing technique has the main objective of eliminating the positioning errors, which commonly occur in the technique of direct system of brackets. The objective of this study is to demonstrate that the exact positioning of the brackets is of extreme relevance for the success of the treatment. The present work shows a case report of an adult female patient who attended the clinic with the complaint of being in orthodontic treatment for more than 5 years without noticing any progress. As a result of the intra-oral clinical examination and documentation analysis, a class III malocclusion, an anterior open bite, and absence of all third molars and first upper and lower bilateral premolars were observed. For the treatment, the indirect bonding technique with self-ligating ceramic braces was applied. The preparation of the trays was done after the intraoral digital scanning and printing of models with a 3D printer. Brackets were positioned virtually, using a specialized software. After twelve months of treatment, correction of the malocclusion was observed, as well as the closing of the anterior open bite. It is concluded that the adequate and precise positioning of brackets is necessary for a successful treatment.

Keywords: anterior open-bite, CAD/CAM, orthodontics, malocclusion, angle class III

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Authors: Wajahat Ali, Shakeel Javaid

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In this study, we have developed a mathematical programming model for a solid transportation problem with three objective functions arranged in hierarchical order. The mathematical programming models with more than one objective function to be solved in hierarchical order is termed as a multi-level programming model. Our study explores a Multi-Level Solid Transportation Problem with Uncertain Parameters (MLSTPWU). The proposed MLSTPWU model consists of three objective functions, viz. minimization of transportation cost, minimization of total transportation time, and minimization of deterioration during transportation. These three objective functions are supposed to be solved by decision-makers at three consecutive levels. Three constraint functions are added to the model, restricting the total availability, total demand, and capacity of modes of transportation. All the parameters involved in the model are assumed to be uncertain in nature. A solution method based on fuzzy logic is also discussed to obtain the compromise solution for the proposed model. Further, a simulated numerical example is discussed to establish the efficiency and applicability of the proposed model.

Keywords: solid transportation problem, multi-level programming, uncertain variable, uncertain environment

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Authors: Agumah N. B. Orji, M. U., Oru C. M., Ugbo, E. N., Onwuliri E. A Nwakaeze, E. A.,

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ERG11 gene has been reported to be one of the genes whose expression is responsible for resistance of Candida to various triazole drugs, which are first line treatment for candidiasis. This study was carried out to determine the prevalence of Triazole (Fluconazole and voriconazole) resistant Candida albicans expressing ERG11 gene from adult females in Abakaliki. Urine and vaginal swab samples were randomly collected from volunteers after obtaining their consent to participate in the study. A total of 565 adult females participated in the study. A total of 340 urine specimens and 288 vaginal swab specimens were collected. Direct wet mount technique, as well as culture in Trichomonas broth, were used to examine the urine and vaginal swab specimens for the presence of motile Trichomonads. The Trichomonas broth used was selective for both T. vaginalis and C. albicans. Broths that yielded budding yeast cells after microscopy were subcultured on to Sabouraud dextrose agar, after which Germ tube test was carried out to confirm the presence of C. albicans. Biochemical tests, including carbohydrate fermentation and urease utilization, were also performed. Antibiogram of C. albicans isolates obtained from this study was carried out using commercially available azole drugs. Fluconazole and voriconazole were selected as Triazole drugs used for this study. Nystatin was used as a tangential control. An MIC test was carried out with E-strips on some of the resistant C. albicans isolates A total of 6 isolates that resisted all the azole drugs were selected and screened for the presence of ERG11 gene using Reverse transcriptase polymerase chain reaction technique. The total prevalence recorded for C. albicans was 13.0%. Frequency was statistically higher in Pregnant (7.96%) than non pregnant (5.09%) volunteers (X2=0.94 at P=0.05). With respect to clinical samples, frequency was higher in vaginal swabs samples (7.96%) than Urine samples (5.09%) (X2=9.05 at P=0.05). Volunteers within the age group 26-30 years recorded the highest prevalence (4.46%), while those within the age group 36-40 years recorded the lowest at 1.27%(X2=4.34 at P=0.05). In pregnant female participants, the highest frequency was recorded with those in their 3rd trimester (4.14%), while lowest incidence was recorded for those in their first trimester (0.80%). Antibiogram results from this study showed that C. albicans isolates obtained from this study resisted Fluconazole (72%) more than Voriconazole (57%). Only one out of the six selected isolates yielded resistance in the MIC test. Results obtained from the RT-PCR showed that there was no expression of ERG11 gene among the fluconazole resistant isolates of C. albicans. Observed resistance may be due to other factors other than expression of ERG11 gene.

Keywords: candida, ERG11, triazole, nigeria

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Authors: Samson Obiene, Khamati Shilabukha, Geoffrey Muga, James Kairo

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Mangroves play a vital role in the achievement of multiple goals of global sustainable development (SDG’s), particularly SDG SDG 14 (life under water). Their management, however, is faced with several shortcomings arising from inadequate knowledge on the perceptions of their ecosystem services, hence a need to map mangrove goods and services within SDGs while interrogating the disaggregated perceptions. This study therefore aimed at exploring the parities and disparities in attitudes and perceptions of mangrove ecosystem services among community members of Vanga and the link of the ecosystem services (ESs) to specific SDG targets. The study was based at the Kenya-Tanzania transboundary area in Vanga; where a carbon-offset project on mangroves is being up scaled. Mixed methods approach employing surveys, focus group discussions (FGDs) and reviews of secondary data were used in the study. A two stage cluster samplings was used to select the study population and the sample size. FGDs were conducted purposively selecting active participants in mangrove related activities with distinct socio-demographic characteristics. Sampled respondents comprised of males and females of different occupations and age groups. Secondary data review was used to select specific SDG targets against which mangrove ecosystem services identified through a value chain analysis were mapped. In Vanga, 20 ecosystem services were identified and categorized under supporting, cultural and aesthetic, provisioning and regulating services. According to the findings of this study, 63.9% (95% ci 56.6-69.3) perceived of the ESs as very important for economic development, 10.3% (95% ci 0-21.3) viewed them as important for environmental and ecological development while 25.8% (95% ci 2.2-32.8) were not sure of any role they play in development. In the social-economic disaggregation, ecosystem service values were found to vary with the level of interaction with the ecosystem which depended on gender and other social-economic classes within the study area. The youths, low income earners, women and those with low education levels were also identified as the primary beneficiaries of mangrove ecosystem services. The study also found that of the 17 SDGs, mangroves have a potential of influencing the achievement 12, including, SDGs 1, 2, 3, 4, 6, 8 10, 12, 13, 14, 15 and 17 either directly or indirectly. Generally therefore, the local community is aware of the critical importance mangroves for enhanced livelihood and ecological services but challenges in sustainability still occur as a result the diverse values and of the services and the contradicting interests of the different actors around the ecosystem. It is therefore important to consider parities in values and perception to avoid a ‘tragedy of the commons’ while striving to enhance sustainability of the Mangrove ecosystem.

Keywords: sustainable development, community values, socio-demographics, Vanga, mangrove ecosystem services

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Authors: A. Shebani, C. Pislaru

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Wear of materials is an everyday experience and has been observed and studied for long time. The prediction of wear is a fundamental problem in the industrial field, mainly correlated to the planning of maintenance interventions and economy. Pin-on-disc test is the most common test which is used to study the wear behaviour. In this paper, the pin-on-disc (AEROTECH UNIDEX 11) is used for the investigation of the effects of normal load and hardness of material on the wear under dry and sliding conditions. In the pin-on-disc rig, two specimens were used; one, a pin which is made of steel with a tip, is positioned perpendicular to the disc, where the disc is made of aluminium. The pin wear and disc wear were measured by using the following instruments: The Talysurf instrument, a digital microscope, and the alicona instrument; where the Talysurf profilometer was used to measure the pin/disc wear scar depth, and the alicona was used to measure the volume loss for pin and disc. After that, the Archard model, American Society for Testing and Materials model (ASTM), and neural network model were used for pin/disc wear modelling and the simulation results are implemented by using the Matlab program. This paper focuses on how the alicona can be considered as a powerful tool for wear measurements and how the neural network is an effective algorithm for wear estimation.

Keywords: wear modelling, Archard Model, ASTM Model, Neural Networks Model, Pin-on-disc Test, Talysurf, digital microscope, Alicona

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Authors: Humayun Murshed, Shibly Abdullah

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The research conducted in early seventies apparently assumed the existence of a universal decision model for union negotiators and furthermore tended to regard financial information as a ‘neutral’ input into a rational decision-making process. However, research in the eighties began to question the neutrality of financial information as an input in collective bargaining rather viewing it as a potentially effective means for controlling the labour force. Furthermore, this later research also started challenging the simplistic assumptions relating particularly to union objectives which have underpinned the earlier search for universal union decision models. Despite the above developments there seems to be a dearth of studies in developing countries concerning the use of financial information in collective bargaining. This paper seeks to begin to remedy this deficiency. Utilising a case study approach based on two enterprises, one in the public sector and the other a multinational, the universal decision model is rejected and it is argued that the decision whether or not to use financial information is a contingent one and such a contingency is largely defined by the context and environment in which both union and management negotiators work. An attempt is also made to identify the factors constraining as well as promoting the use of financial information in collective bargaining, these being regarded as unique to the organizations within which the case studies are conducted.

Keywords: collective bargaining, developing countries, disclosures, financial information

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Authors: Dharni Vasudhevan Venkatesan, K. E. Shanjay, H. Sujith Kumar, N. A. Abhilash, D. Aswin Ram, V. R. Sanal Kumar

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Numerical studies on race car aerodynamics at wing in ground effect have been carried out using a steady 3d, double precision, pressure-based, and standard k-epsilon turbulence model. Through various parametric analytical studies we have observed that at a particular speed and ground clearance of the wings a favorable negative lift was found high at a particular angle of attack for all the physical models considered in this paper. The fact is that if the ground clearance height to chord length (h/c) is too small, the developing boundary layers from either side (the ground and the lower surface of the wing) can interact, leading to an altered variation of the aerodynamic characteristics at wing in ground effect. Therefore a suitable ground clearance must be predicted throughout the racing for a better performance of the race car, which obviously depends upon the coupled effects of the topography, wing orientation with respect to the ground, the incoming flow features and/or the race car speed. We have concluded that for the design of high performance and high speed race cars the adjustable wings capable to alter the ground clearance and the angles of attack is the best design option for any race car for racing safely with variable speeds.

Keywords: external aerodynamics, external flow choking, race car aerodynamics, wing in ground effect

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Authors: Yannis Stavrakakis, Damian Gordon

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Critical Thinking and Reflective Practice are two vital skills that students undertaking postgraduate studies should ideally possess. To help students develop and enhance these skills, this research developed several authentic activities to be undertaken as part of a module that is delivered early in a taught MSc to enhance these skills. One of the challenges of these topics is that they are somewhat ill-defined in terms of precisely what they mean, and also, there is no clear route to operationalizing the teaching of these skills. This research focuses on identifying suitable models of these skills and delivering them in a manner that is both clear and highly motivating. To achieve this, a class of 22 Master's students was divided into two groups, one was provided with a presentation and checklist about critical thinking skills, and the other group was given the same materials on the reflective practice process. The groups were given two scenarios each to analyze using their respective checklists and were asked to present their outcomes to each other and give peer review. The results were coded and compared, and key differences were noted, including the fact that the Critical Thinking outcomes were more future-focused, and the Reflective Practice outcomes were more past-focused and present-focused, as well as the fact that the Reflective Practice process generated a significantly wider range of perspectives on the scenarios.

Keywords: critical thinking, ethical scenarios, formative assessment, reflective practice

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Authors: Cristina Lavilla, Andreas Heise

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The synthesis of sequence-controlled polymers has received increasing attention in the last years. Well-defined polyacrylates, polyacrylamides and styrene-maleimide copolymers have been synthesized by sequential or kinetic addition of comonomers. However this approach has not yet been introduced to the synthesis of polypeptides, which are in fact polymers developed by nature in a sequence-controlled way. Polypeptides are natural materials that possess the ability to self-assemble into complex and highly ordered structures. Their folding and properties arise from precisely controlled sequences and compositions in their constituent amino acid monomers. So far, solid-phase peptide synthesis is the only technique that allows preparing short peptide sequences with excellent sequence control, but also requires extensive protection/deprotection steps and it is a difficult technique to scale-up. A new strategy towards sequence control in the synthesis of polypeptides is introduced, based on the sequential addition of α-amino acid-N-carboxyanhydrides (NCAs). The living ring-opening process is conducted to full conversion and no purification or deprotection is needed before addition of a new amino acid. The length of every block is predefined by the NCA:initiator ratio in every step. This method yields polypeptides with a specific sequence and controlled molecular weights. A series of polypeptides with varying block sequences have been synthesized with the aim to identify structure-property relationships. All of them are able to adopt secondary structures similar to natural polypeptides, and display properties in the solid state and in solution that are characteristic of the primary structure. By design the prepared polypeptides allow selective modification of individual block sequences, which has been exploited to introduce functionalities in defined positions along the polypeptide chain. Poly(ethylene glycol)(PEG) was the functionality chosen, as it is known to favor hydrophilicity and also yield thermoresponsive materials. After PEGylation, hydrophilicity of the polypeptides is enhanced, and their thermal response in H2O has been studied. Noteworthy differences in the behavior of the polypeptides having different sequences have been found. Circular dichroism measurements confirmed that the α-helical conformation is stable over the examined temperature range (5-90 °C). It is concluded that PEG units are the main responsible of the changes in H-bonding interactions with H2O upon variation of temperature, and the position of these functional units along the backbone is a factor of utmost importance in the resulting properties of the α-helical polypeptides.

Keywords: α-amino acid N-carboxyanhydrides, multiblock copolymers, poly(ethylene glycol), polypeptides, ring-opening polymerization, sequence control

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Authors: Mouli Banga, Chaya Ravindra

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Wound classification is a crucial step in wound diagnosis. An effective classifier can aid wound specialists in identifying wound types with reduced financial and time investments, facilitating the determination of optimal treatment procedures. This study presents a deep neural network-based classifier that leverages wound images and their corresponding locations to categorize wounds into various classes, such as diabetic, pressure, surgical, and venous ulcers. By incorporating a developed body map, the process of tagging wound locations is significantly enhanced, providing healthcare specialists with a more efficient tool for wound analysis. We conducted a comparative analysis between two prominent convolutional neural network models, ResNet50 and MobileNetV2, utilizing a dataset of 730 images. Our findings reveal that the RestNet50 outperforms MovileNetV2, achieving an accuracy of approximately 90%, compared to MobileNetV2’s 83%. This disparity highlights the superior capability of ResNet50 in the context of this dataset. The results underscore the potential of integrating deep learning with spatial data to improve the precision and efficiency of wound diagnosis, ultimately contributing to better patient outcomes and reducing healthcare costs.

Keywords: wound classification, MobileNetV2, ResNet50, multimodel

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