Search results for: multiple query optimization

Authors: Gulnara Galeeva, Yulia Kasperskaya

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The study deals with the relevant problem related to the formation of the efficient investment portfolio of an enterprise. The structure of the investment portfolio is connected to the degree of influence of intangible assets on the enterprise’s income. This determines the importance of research on the content of intangible assets. However, intangible assets studies do not take into consideration how the enterprise state can affect the content and the importance of intangible assets for the enterprise`s income. This affects accurateness of the calculations. In order to study this problem, the research was divided into several stages. In the first stage, intangible assets were classified based on their synergies as the underlying intangibles and the additional intangibles. In the second stage, this classification was applied. It showed that the lifecycle model and the theory of abrupt development of the enterprise, that are taken into account while designing investment projects, constitute limit cases of a more general theory of bifurcations. The research identified that the qualitative content of intangible assets significant depends on how close the enterprise is to being in crisis. In the third stage, the author developed and applied the Wide Pairwise Comparison Matrix method. This allowed to establish that using the ratio of the standard deviation to the mean value of the elements of the vector of priority of intangible assets makes it possible to estimate the probability of a full-blown crisis of the enterprise. The author has identified a criterion, which allows making fundamental decisions on investment feasibility. The study also developed an additional rapid method of assessing the enterprise overall status based on using the questionnaire survey with its Director. The questionnaire consists only of two questions. The research specifically focused on the fundamental role of stochastic resonance in the emergence of bifurcation (crisis) in the economic development of the enterprise. The synergetic approach made it possible to describe the mechanism of the crisis start in details and also to identify a range of universal ways of overcoming the crisis. It was outlined that the structure of intangible assets transforms into a more organized state with the strengthened synchronization of all processes as a result of the impact of the sporadic (white) noise. Obtained results offer managers and business owners a simple and an affordable method of investment portfolio optimization, which takes into account how close the enterprise is to a state of a full-blown crisis.

Keywords: analytic hierarchy process, bifurcation, investment portfolio, intangible assets, wide matrix

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Authors: Mohana Basu, Snehamanju Basu

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Urbanization has an immense impact on the holistic development of a region. In that same context, the level of women empowerment plays a significant role in the development of any region, particularly a region belonging to a developing country. The present study investigates the status of women empowerment in the Asansol Durgapur Planning Area of the state of West Bengal, India by investigating the status of women and their access to various facilities and awareness about the various governmental and non-governmental schemes meant for their elevation. Through this study, an attempt has been to made to understand the perception of the respondents on the context of women's empowerment. The study integrates multiple sources of qualitative and quantitative data collected from various reports, field-based measurements, questionnaire survey and community based participatory appraisals. Results reveal that women of the rural parts of the region are relatively disempowered due to the various restrictions imposed on them and enjoy lower socioeconomic clout than their male counterparts in spite of the several remedial efforts taken by the government and NGOs to elevate their position in the society. A considerable gender gap still exists regarding access to education, employment and decision-making power in the family and significant differences in attitude towards women are observable in the rural and urban areas. Freedom of women primarily vary according to their age group, educational level, employment and income status and also on the degree of urbanization. Asansol Durgapur Planning Area is primarily an industrial region where huge employment generation scope exists. But these disparities are quite alarming and indicate that economic development does not always usher in socially justifiable rights and access to resources for both men and women alike in its awake. In this backdrop, this study will attempt to forward relevant suggestions which can be followed for betterment of the status of women.

Keywords: development, disempowered, economic development, urbanization, women empowerment

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Authors: Junie B. Billones, Maria Constancia O. Carrillo, Voltaire G. Organo, Stephani Joy Y. Macalino, Inno A. Emnacen, Jamie Bernadette A. Sy

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The drug discovery and development process is generally known to be a very lengthy and labor-intensive process. Therefore, in order to be able to deliver prompt and effective responses to cure certain diseases, there is an urgent need to reduce the time and resources needed to design, develop, and optimize potential drugs. Computer-aided drug design (CADD) is able to alleviate this issue by applying computational power in order to streamline the whole drug discovery process, starting from target identification to lead optimization. This drug design approach can be predominantly applied to diseases that cause major public health concerns, such as tuberculosis. Hitherto, there has been no concrete cure for this disease, especially with the continuing emergence of drug resistant strains. In this study, CADD is employed for tuberculosis by first identifying a key enzyme in the mycobacterium’s metabolic pathway that would make a good drug target. One such potential target is the lipoate protein ligase B enzyme (LipB), which is a key enzyme in the M. tuberculosis metabolic pathway involved in the biosynthesis of the lipoic acid cofactor. Its expression is considerably up-regulated in patients with multi-drug resistant tuberculosis (MDR-TB) and it has no known back-up mechanism that can take over its function when inhibited, making it an extremely attractive target. Using cutting-edge computational methods, compounds from AnalytiCon Discovery Natural Derivatives database were screened and docked against the LipB enzyme in order to rank them based on their binding affinities. Compounds which have better binding affinities than LipB’s known inhibitor, decanoic acid, were subjected to in silico toxicity evaluation using the ADMET and TOPKAT protocols. Out of the 31,692 compounds in the database, 112 of these showed better binding energies than decanoic acid. Furthermore, 12 out of the 112 compounds showed highly promising ADMET and TOPKAT properties. Future studies involving in vitro or in vivo bioassays may be done to further confirm the therapeutic efficacy of these 12 compounds, which eventually may then lead to a novel class of anti-tuberculosis drugs.

Keywords: pharmacophore, molecular docking, lipoate protein ligase B (LipB), ADMET, TOPKAT

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Authors: Sofia Nilsson, Alicia Ohlsson, Linda-Marie Lundqvist, Aida Alvinius, Peder Hyllengren, Gerry Larsson

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In irregular warfare contexts, military personnel are often presented with morally ambiguous situations where they are aware of the morally correct choice but may feel prevented to follow through with it due to organizational demands. Moral stress and/or injury can be the outcome of the individual’s experienced dissonance. These types of challenges put a large demand on the individual to manage their own emotions and the emotions of others, particularly in the case of a leader. Both the ability and inability for emotional regulation can result in different combinations of short and long term reactions after morally stressful events, which can be either positive or negative. Our study analyzed the combination of these reactions based upon the types of morally challenging events that were described by the subjects. 1)What institutionalized norms concerning emotion regulation are favorable in short-and long-term perspectives after a morally stressful event? 2)What individual emotion-focused coping strategies are favorable in short-and long-perspectives after a morally stressful? To address these questions, we conducted a quantitative study in military contexts in Sweden and Norway on upcoming or current military officers (n=331). We tested a theoretical model built upon a recently developed qualitative study. The data was analyzed using factor analysis, multiple regression analysis and subgroup analyses. The results indicated that an individual’s restriction of emotion in order to achieve an organizational goal, which results in emotional dissonance, can be an effective short term strategy for both the individual and the organization; however, it appears to be unfavorable in a long-term perspective which can result in negative reactions. Our results are intriguing because they showed an increased percentage of reported negative long term reactions (13%), which indicated PTSD-related symptoms in comparison to previous Swedish studies which indicated lower PTSD symptomology.

Keywords: emotion culture, emotion coping, emotion management, military

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Authors: S. Albert, R. Cossu, A. Grinham, C. Heatherington, C. Wilson

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Shipping trends suggest increasing vessel size and draught visiting Australian ports highlighting potential challenges to port infrastructure and requiring optimization of shipping channels to ensure safe passage for vessels. The Port of Brisbane in Queensland, Australia has an 80 km long access shipping channel which vessels must transit 15 km of relatively shallow coffee rock (generic class of indurated sands where sand grains are bound within an organic clay matrix) outcrops towards the northern passage in Moreton Bay. This represents a risk to shipping channel deepening and maintenance programs as the dredgeability of this material is more challenging due to its high cohesive strength compared with the surrounding marine sands and potential higher acid sulfate risk. In situ assessment of acid sulfate sediment for dredge spoil control is an important tool in mitigating ecological harm. The coffee rock in an anoxic undisturbed state does not pose any acid sulfate risk, however when disturbed via dredging it’s vital to ensure that any present iron sulfides are either insignificant or neutralized. To better understand the potential risk we examined the reduction potential of coffee rock across the entire dredge cycle in order to accurately portray the true outcome of disturbed acid sulfate sediment in dredging operations in Moreton Bay. In December 2014 a dredge trial was undertaken with a trailing suction hopper dredger. In situ samples were collected prior to dredging revealed acid sulfate potential above threshold guidelines which could lead to expensive dredge spoil management. However, potential acid sulfate risk was then monitored in the hopper and subsequent discharge, both showing a significant reduction in acid sulfate potential had occurred. Additionally, the acid neutralizing capacity significantly increased due to the inclusion of shell fragments (calcium carbonate) from the dredge target areas. This clearly demonstrates the importance of assessing potential acid sulfate risk across the entire dredging cycle and highlights the need to carefully evaluate sources of acidity.

Keywords: acid sulfate, coffee rock, indurated sand, dredging, maintenance dredging

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Authors: Omar Pillaca-Pullo, Arturo Alejandro-Paredes, Carol Flores-Fernandez, Marijuly Sayuri Kina, Amparo Iris Zavaleta

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Aqueous two-phase system (ATPS) is an interesting alternative for separating industrial enzymes due to it is easy to scale-up and low cost. Polyethylene glycol (PEG) mixed with potassium phosphate or magnesium sulfate is one of the most frequently polymer/salt ATPS used, but the consequences of its use is a high concentration of phosphates and sulfates in wastewater causing environmental issues. Citrate could replace these inorganic salts due to it is biodegradable and does not produce toxic compounds. On the other hand, statistical design of experiments is widely used for ATPS optimization and it allows to study the effects of the involved variables in the purification, and to estimate their significant effects on selected responses and interactions. The 24 factorial design with four central points (20 experiments) was employed to study the partition and purification of proteases produced by Pseudomonas sp. in PEG/citrate ATPS system. ATPS was prepared with different sodium citrate concentrations [14, 16 and 18% (w/w)], pH values (7, 8 and 9), PEG molecular weight (2,000; 4,000 and 6,000 g/mol) and PEG concentrations [18, 20 and 22 % (w/w)]. All system components were mixed with 15% (w/w) of the fermented broth and deionized water was added to a final weight of 12.5 g. Then, the systems were mixed and kept at room temperature until to reach two-phases separation. Volumes of the top and bottom phases were measured, and aliquots from both phases were collected for subsequent proteolytic activity and total protein determination. Influence of variables such as PEG molar mass (MPEG), PEG concentration (CPEG), citrate concentration (CSal) and pH were evaluated on the following responses: purification factor (PF), activity yield (Y), partition coefficient (K) and selectivity (S). STATISTICA program version 10 was used for the analysis. According to the obtained results, higher levels of CPEG and MPEG had a positive effect on extraction, while pH did not influence on the process. On the other hand, the CSal could be related with low values of Y because of the citrate ions have a negative effect on solubility and enzymatic structure. The optimum values of Y (66.4 %), PF (1.8), K (5.5) and S (4.3) were obtained at CSal (18%), MPEG (6,000 g/mol), CPEG (22%) and pH 9. These results indicated that the PEG/citrate system is accurate to purify these Pseudomonas sp. proteases from fermented broth as a first purification step.

Keywords: citrate, polyethylene glycol, protease, Pseudomonas sp

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Authors: M. Miljkovic, A. Urakpo, M. Simic-Koumoutsaris

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Benefit-risk assessment (BRA) is a valuable tool that takes place in multiple stages during a medicine's lifecycle, and this assessment can be conducted in a variety of ways. The aim was to summarize current BRA methods used during approval decisions and in post-approval settings and to see possible future directions. Relevant reviews, recommendations, and guidelines published in medical literature and through regulatory agencies over the past five years have been examined. BRA implies the review of two dimensions: the dimension of benefits (determined mainly by the therapeutic efficacy) and the dimension of risks (comprises the safety profile of a drug). Regulators, industry, and academia have developed various approaches, ranging from descriptive textual (qualitative) to decision-analytic (quantitative) models, to facilitate the BRA of medicines during the product lifecycle (from Phase I trials, to authorization procedure, post-marketing surveillance and health technology assessment for inclusion in public formularies). These approaches can be classified into the following categories: stepwise structured approaches (frameworks); measures for benefits and risks that are usually endpoint specific (metrics), simulation techniques and meta-analysis (estimation techniques), and utility survey techniques to elicit stakeholders’ preferences (utilities). All these approaches share the following two common goals: to assist this analysis and to improve the communication of decisions, but each is subject to its own specific strengths and limitations. Before using any method, its utility, complexity, the extent to which it is established, and the ease of results interpretation should be considered. Despite widespread and long-time use, BRA is subject to debate, suffers from a number of limitations, and currently is still under development. The use of formal, systematic structured approaches to BRA for regulatory decision-making and quantitative methods to support BRA during the product lifecycle is a standard practice in medicine that is subject to continuous improvement and modernization, not only in methodology but also in cooperation between organizations.

Keywords: benefit-risk assessment, benefit-risk profile, product lifecycle, quantitative methods, structured approaches

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Authors: Rohit Dey, Sailendra Karra

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This paper aims at solving the problem of multi-target searching in a Global Positioning System (GPS) denied environment using swarm robots with limited sensing and communication abilities. Typically, existing swarm-based search algorithms rely on the presence of a global coordinate system (vis-à-vis, GPS) that is shared by the entire swarm which, in turn, limits its application in a real-world scenario. This can be attributed to the fact that robots in a swarm need to share information among themselves regarding their location and signal from targets to decide their future course of action but this information is only meaningful when they all share the same coordinate frame. The paper addresses this very issue by eliminating any dependency of a search algorithm on the need of a predetermined global coordinate frame by the unification of the relative coordinate of individual robots when within the communication range, therefore, making the system more robust in real scenarios. Our algorithm assumes that all the robots in the swarm are equipped with range and bearing sensors and have limited sensing range and communication abilities. Initially, every robot maintains their relative coordinate frame and follow Levy walk random exploration until they come in range with other robots. When two or more robots are within communication range, they share sensor information and their location w.r.t. their coordinate frames based on which we unify their coordinate frames. Now they can share information about the areas that were already explored, information about the surroundings, and target signal from their location to make decisions about their future movement based on the search algorithm. During the process of exploration, there can be several small groups of robots having their own coordinate systems but eventually, it is expected for all the robots to be under one global coordinate frame where they can communicate information on the exploration area following swarm search techniques. Using the proposed method, swarm-based search algorithms can work in a real-world scenario without GPS and any initial information about the size and shape of the environment. Initial simulation results show that running our modified-Particle Swarm Optimization (PSO) without global information we can still achieve the desired results that are comparable to basic PSO working with GPS. In the full paper, we plan on doing the comparison study between different strategies to unify the coordinate system and to implement them on other bio-inspired algorithms, to work in GPS denied environment.

Keywords: bio-inspired search algorithms, decentralized control, GPS denied environment, swarm robotics, target searching, unifying coordinate systems

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Authors: Martin Kittel, Alexander Roth

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The continuous integration of variable renewable energy sources (VRE) in the power sector is required for decarbonizing the European economy. Power sectors become increasingly exposed to weather variability, as the availability of VRE, i.e., mainly wind and solar photovoltaic, is not persistent. Extreme events, e.g., long-lasting periods of scarce VRE availability (‘VRE droughts’), challenge the reliability of supply. Properly accounting for the severity of VRE droughts is crucial for designing a resilient renewable European power sector. Energy system modeling is used to identify such a design. Our analysis reveals the sensitivity of the optimal design of the European power sector towards VRE droughts. We analyze how VRE droughts impact optimal power sector investments, especially in generation and flexibility capacity. We draw upon work that systematically identifies VRE drought patterns in Europe in terms of frequency, duration, and seasonality, as well as the cross-regional and cross-technological correlation of most extreme drought periods. Based on their analysis, the authors provide a selection of relevant historical weather years representing different grades of VRE drought severity. These weather years will serve as input for the capacity expansion model for the European power sector used in this analysis (DIETER). We additionally conduct robustness checks varying policy-relevant assumptions on capacity expansion limits, interconnections, and level of sector coupling. Preliminary results illustrate how an imprudent selection of weather years may cause underestimating the severity of VRE droughts, flawing modeling insights concerning the need for flexibility. Sub-optimal European power sector designs vulnerable to extreme weather can result. Using relevant weather years that appropriately represent extreme weather events, our analysis identifies a resilient design of the European power sector. Although the scope of this work is limited to the European power sector, we are confident that our insights apply to other regions of the world with similar weather patterns. Many energy system studies still rely on one or a limited number of sometimes arbitrarily chosen weather years. We argue that the deliberate selection of relevant weather years is imperative for robust modeling results.

Keywords: energy systems, numerical optimization, variable renewable energy sources, energy drought, flexibility

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Authors: William Kelly, Sorelle Veigne, Xianhua Li, Zuyi Huang, Shyamsundar Subramanian, Eugene Schaefer

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The ambr15™ bioreactor is a single-use microbioreactor for cell line development and process optimization. The ambr system offers fully automatic liquid handling with the possibility of fed-batch operation and automatic control of pH and oxygen delivery. With operating conditions for large scale biopharmaceutical production properly scaled down, micro bioreactors such as the ambr15™ can potentially be used to predict the effect of process changes such as modified media or different cell lines. In this study, gassing rates and dilution rates were varied for a semi-continuous cell culture system in the ambr15™ bioreactor. The corresponding changes to metabolite production and consumption, as well as cell growth rate and therapeutic protein production were measured. Conditions were identified in the ambr15™ bioreactor that produced metabolic shifts and specific metabolic and protein production rates also seen in the corresponding larger (5 liter) scale perfusion process. A Dynamic Flux Balance model was employed to understand and predict the metabolic changes observed. The DFB model-predicted trends observed experimentally, including lower specific glucose consumption when CO₂ was maintained at higher levels (i.e. 100 mm Hg) in the broth. A Computational Fluid Dynamic (CFD) model of the ambr15™ was also developed, to understand transfer of O₂ and CO₂ to the liquid. This CFD model predicted gas-liquid flow in the bioreactor using the ANSYS software. The two-phase flow equations were solved via an Eulerian method, with population balance equations tracking the size of the gas bubbles resulting from breakage and coalescence. Reasonable results were obtained in that the Carbon Dioxide mass transfer coefficient (kLa) and the air hold up increased with higher gas flow rate. Volume-averaged kLa values at 500 RPM increased as the gas flow rate was doubled and matched experimentally determined values. These results form a solid basis for optimizing the ambr15™, using both CFD and FBA modelling approaches together, for use in microscale simulations of larger scale cell culture processes.

Keywords: cell culture, computational fluid dynamics, dynamic flux balance analysis, microbioreactor

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Authors: Massy Guillaume

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Introduction: The implementation of creativity in educational policies or curricula raises several issues, including the evaluation of creativity and the means to do so. This doctoral research focuses on the appropriation and transposition of creativity assessment models by future teachers. Our objective is to identify the elements of the models that are most transferable to practice in order to improve their implementation in the students' curriculum while seeking to create a new model for assessing creativity in the school environment. Methods: In order to meet our objective, this preliminary quantitative exploratory study by questionnaire was conducted at two points in the participants' training: at the beginning of the training module and throughout the practical work. The population is composed of 40 people of diverse origins with an average age of 26 (s:8,623) years. In order to be as close as possible to our research objective and to test our questionnaires, we set up a pre-test phase during the spring semester of 2022. Results: The results presented focus on aspects of the OECD Creative Competencies Assessment Model. Overall, 72% of participants support the model's focus on skill levels as appropriate for the school context. More specifically, the data indicate that the separation of production and process in the rubric facilitates observation by the assessor. From the point of view of transposing the grid into teaching practice, the participants emphasised that production is easier to plan and observe in students than in the process. This difference is reinforced by a lack of knowledge about certain concepts such as innovation or risktaking in schools. Finally, the qualitative results indicate that the addition of multiple levels of competencies to the OECD rubric would allow for better implementation in the classroom. Conclusion: The identification by the students of the elements allowing the evaluation of creativity in the school environment generates an innovative approach to the training contents. These first data, from the test phase of our research, demonstrate the difficulty that exists between the implementation of an evaluation model in a training program and its potential transposition by future teachers.

Keywords: creativity, evaluation, schooling, training

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Authors: Yasmin Begum Mohammed

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Ketorolac tromethamine (KTM) is a non-steroidal anti-inflammatory drug with a potent analgesic and anti-inflammatory activity due to prostaglandin related inhibitory effect of drug. It is a non-selective cyclo-oxygenase inhibitor. The drug is currently used orally and intramuscularly in multiple divided doses, clinically for the management arthritis, cancer pain, post-surgical pain, and in the treatment of migraine pain. KTM has short biological half-life of 4 to 6 hours, which necessitates frequent dosing to retain the action. The frequent occurrence of gastrointestinal bleeding, perforation, peptic ulceration, and renal failure lead to the development of other drug delivery strategies for the appropriate delivery of KTM. The ideal solution would be to target the drug only to the cells or tissues affected by the disease. Drug targeting could be achieved effectively by liposomes that are biocompatible and biodegradable. The aim of the study was to develop a parenteral liposome formulation of KTM with improved efficacy while reducing side effects by targeting the inflammation due to arthritis. PEG-anchored (stealth) and non-PEG-anchored liposomes were prepared by thin film hydration technique followed by extrusion cycle and characterized for in vitro and in vivo. Stealth liposomes (SLs) exhibited increase in percent encapsulation efficiency (94%) and 52% percent of drug retention during release studies in 24 h with good stability for a period of 1 month at -20°C and 4°C. SLs showed about maximum 55% of edema inhibition with significant analgesic effect. SLs produced marked differences over those of non-SL formulations with an increase in area under plasma concentration time curve, t₁/₂, mean residence time, and reduced clearance. 0.3% of the drug was detected in arthritic induced paw with significantly reduced drug localization in liver, spleen, and kidney for SLs when compared to other conventional liposomes. Thus SLs help to increase the therapeutic efficacy of KTM by increasing the targeting potential at the inflammatory region.

Keywords: biodistribution, ketorolac tromethamine, stealth liposomes, thin film hydration technique

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Authors: Dharminder Singh, Sanjeev Yadav, Pravakar Mohanty

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In this work, study of temperature profile in a pilot scale air bubbling fluidized bed (ABFB) gasifier for rice husk gasification was carried out. Effects of different factors such as multiple cyclones, gas cooling system, ventilate gas pipe length, and catalyst on temperature profile was examined. ABFB gasifier used in this study had two sections, one is bed section and the other is freeboard section. River sand was used as bed material with air as gasification agent, and conventional charcoal as start-up heating medium in this gasifier. Temperature of different point in both sections of ABFB gasifier was recorded at different ER value and ER value was changed by changing the feed rate of biomass (rice husk) and by keeping the air flow rate constant for long durational of gasifier operation. ABFB with double cyclone with gas coolant system and with short length ventilate gas pipe was found out to be optimal gasifier design to give temperature profile required for high gasification performance in long duration operation. This optimal design was tested with different ER values and it was found that ER of 0.33 was most favourable for long duration operation (8 hr continuous operation), giving highest carbon conversion efficiency. At optimal ER of 0.33, bed temperature was found to be stable at 700 °C, above bed temperature was found to be at 628.63 °C, bottom of freeboard temperature was found to be at 600 °C, top of freeboard temperature was found to be at 517.5 °C, gas temperature was found to be at 195 °C, and flame temperature was found to be 676 °C. Temperature at all the points showed fluctuations of 10 – 20 °C. Effect of catalyst i.e. dolomite (20% with sand bed) was also examined on temperature profile, and it was found that at optimal ER of 0.33, the bed temperature got increased to 795 °C, above bed temperature got decreased to 523 °C, bottom of freeboard temperature got decreased to 548 °C, top of freeboard got decreased to 475 °C, gas temperature got decreased to 220 °C, and flame temperature got increased to 703 °C. Increase in bed temperature leads to higher flame temperature due to presence of more hydrocarbons generated from more tar cracking at higher temperature. It was also found that the use of dolomite with sand bed eliminated the agglomeration in the reactor at such high bed temperature (795 °C).

Keywords: air bubbling fluidized bed gasifier, bed temperature, charcoal heating, dolomite, flame temperature, rice husk

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Authors: Y. A. Prada, Fanny Guzman, Rafael Cabanzo, John J. Castillo, Enrique Mejia-Ospino

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In this work, we show the important results about of synthesis of photoluminiscents gold nanoclusters using a small peptide as template for biosensing applications. Interestingly, we design one peptide (NBC2854) homologue to conservative domain from 215 250 residue of a galactolectin protein which can recognize the proteophosphoglycans (PPG) from Leishmania. Peptide was synthetized by multiple solid phase synthesis using FMoc group methodology in acid medium. Finally, the peptide was purified by High-Performance Liquid Chromatography using a Vydac C-18 preparative column and the detection was at 215 nm using a Photo Diode Array detector. Molecular mass of this peptide was confirmed by MALDI-TOF and to verify the α-helix structure we use Circular Dichroism. By means of the methodology used we obtained a novel fluorescents gold nanoclusters (AuNC) using NBC2854 as a template. In this work, we described an easy and fast microsonic method for the synthesis of AuNC with ≈ 3.0 nm of hydrodynamic size and photoemission at 630 nm. The presence of cysteine residue in the C-terminal of the peptide allows the formation of Au-S bond which confers stability to Peptide-based gold nanoclusters. Interactions between the peptide and gold nanoclusters were confirmed by X-ray Photoemission and Raman Spectroscopy. Notably, from the ultrafine spectra shown in the MALDI-TOF analysis which containing only 3-7 KDa species was assigned to Au₈-₁₈[NBC2854]₂ clusters. Finally, we evaluated the Peptide-gold nanocluster as an optical biosensor based on fluorescence spectroscopy and the fluorescence signal of PPG (0.1 µg-mL⁻¹ to 1000 µg-mL⁻¹) was amplified at the same wavelength emission (≈ 630 nm). This can suggest that there is a strong interaction between PPG and Pep@AuNC, therefore, the increase of the fluorescence intensity can be related to the association mechanism that take place when the target molecule is sensing by the Pep@AuNC conjugate. Further spectroscopic studies are necessary to evaluate the fluorescence mechanism involve in the sensing of the PPG by the Pep@AuNC. To our best knowledge the fabrication of an optical biosensor based on Pep@AuNC for sensing biomolecules such as Proteophosphoglycans which are secreted in abundance by parasites Leishmania.

Keywords: biosensing, fluorescence, Leishmania, peptide-gold nanoclusters, proteophosphoglycans

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Authors: Daeung Jung

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Background: In case of patients with missing teeth, multiple implant restoration has been widely used and is inevitable. To increase its survival rate, it is important to understand the influence of different implant designs on inter-implant crestal bone resorption. There are several implant systems designed to minimize loss of crestal bone, and the Astra Tech and Brånemark Implant are two of them. Aim/Hypothesis: The aim of this 10-year study was to compare the height of inter-implant bone crest in two implant systems; the Astra Tech and the Brånemark implant system. Material and Methods: In this retrospective study, 40 consecutively treated patients were utilized; 23 patients with 30 sites for Astra Tech system and 17 patients with 20 sites for Brånemark system. The implant restoration was comprised of splinted crown in partially edentulous patients. Radiographs were taken immediately after 1st surgery, at impression making, at prosthetics setting, and annually after loading. Lateral distance from implant to bone crest, inter-implant distance was gauged, and crestal bone height was measured from the implant shoulder to the first bone contact. Calibrations were performed with known length of thread pitch distance for vertical measurement, and known diameter of abutment or fixture for horizontal measurement using ImageJ. Results: After 10 years, patients treated with Astra Tech implant system demonstrated less inter-implant crestal bone resorption when implants had a distance of 3mm or less between them. In cases of implants that had a greater than 3 mm distance between them, however, there appeared to be no statistically significant difference in crestal bone loss between two systems. Conclusion and clinical implications: In the situation of partially edentulous patients planning to have more than two implants, the inter-implant distance is one of the most important factors to be considered. If it is impossible to make sure of having sufficient inter-implant distance, the implants with less micro gap in the fixture-abutment junction, less traumatic 2nd surgery approach, and the adequate surface topography would be choice of appropriate options to minimize inter-implant crestal bone resorption.

Keywords: implant design, crestal bone loss, inter-implant distance, 10-year retrospective study

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Authors: Xinchao Liu

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Regulating environmental and human rights damages caused by transnational corporations in host States is a core issue in the business and human rights discourse. In current regulatory practices, host States, which are territorially based and should bear primary regulation responsibility, face dual challenges at both domestic and international levels, leading to their continued marginalization. Specifically, host States as TNC damage regulators are constrained domestically by territorial jurisdiction limitations and internationally by the neoliberal international economic order exemplified by investment protection mechanisms. Taking China as a sample, it currently lacks a comprehensive regulation system to address TNC damages; while domestic constraints manifest as the marginalization of judicial regulation, the absence of corporate duty of care, and inadequate extraterritorial regulation effectiveness, international constraints are reflected in the absence of foreign investor obligations in investment agreements and the asymmetry of dispute resolution clauses, challenging regulatory sovereignty. As China continues to advance its policy of high-quality opening up, the risks of negative externalities from transnational capital will continue to increase, necessitating a focus on building and perfecting a regulation mechanism for TNC damages within the framework of international law. To address domestic constraints, it is essential to clarify the division of regulation responsibilities between judicial and administrative bodies, promote the normalization of judicial regulation, and enhance judicial oversight of governmental settlements. Improving the choice of law rules for cross-border torts and the standards for parent company liability for omissions, and enhancing extraterritorial judicial effectiveness through transnational judicial dialogue and cooperation mechanisms are also crucial. To counteract international constraints, specifying investor obligations in investment treaties and designing symmetrical dispute resolution clauses are indispensable to eliminate regulatory chill. Additionally, actively advancing the implementation of TNC obligations in business and human rights treaty negotiations will lay an international legal foundation for the regulation sovereignty of host States.

Keywords: transnational corporate damages, home state litigation, optimization limit, investor-state dispute settlement

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Authors: Mehena Fedoul

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This paper examines the intersection of race, gender, and disability through a Critical disability race theory and black feminist disability perspective in Keah Brown's memoir, "The Pretty One." The background of the study highlights the significance of intersectionality in understanding the multifaceted experiences of individuals who navigate multiple marginalized identities. The study contributes to the underrepresented field of disability studies from Critical race and black feminist perspectives, shedding light on the unique challenges and resilience of black disabled women. The study employs a qualitative analysis of Keah Brown's memoir as a primary text. Drawing on intersectionality theory and black feminist disability scholarship, the analysis focuses on how Brown's memoir illuminates the ways in which her race, gender, and disability intersect and shape her lived experiences. The analysis reveals how Brown's memoir challenges traditional notions of disability, beauty, and empowerment through the unapologetic celebration of her blackness, femaleness, and disability. The major findings of the study indicate that Brown's memoir provides a powerful narrative of the complexity, uniqueness and richness of the lived experiences of black disabled women. It demonstrates how the intersectionality of race, gender, and disability shapes Brown's identity, body image, relationships, and societal interactions. The paper also highlights how Brown's memoir emphasizes the importance of inclusivity and intersectionality in understanding and addressing the challenges faced by black disabled women. In conclusion, this study offers a critical analysis of the intersection of race, gender, and disability in Keah Brown's memoir, "The Pretty One," from a black feminist disability perspective. It contributes to the growing body of literature that recognizes the significance of intersectionality in understanding the experiences of marginalized individuals in the disability community. The study underscores the need for more inclusive and intersectional perspectives in disability studies and advocates for greater recognition of the voices and experiences of black disabled women in academic and societal discourse.

Keywords: disability studies, intersectionality, black feminism, Keah Brown

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Authors: Moustafa Osman Mohammed

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Construction industry, as one of the main contributor in depletion of natural resources, influences climate change. This paper discusses incremental and evolutionary development of the proposed models for optimization of a life-cycle analysis to explicit strategy for evaluation systems. The main categories are virtually irresistible for introducing uncertainties, uptake composite structure model (CSM) as environmental management systems (EMSs) in a practice science of evaluation small and medium-sized enterprises (SMEs). The model simplified complex systems to reflect nature systems’ input, output and outcomes mode influence “framework measures” and give a maximum likelihood estimation of how elements are simulated over the composite structure. The traditional knowledge of modeling is based on physical dynamic and static patterns regarding parameters influence environment. It unified methods to demonstrate how construction systems ecology interrelated from management prospective in procedure reflects the effect of the effects of engineering systems to ecology as ultimately unified technologies in extensive range beyond constructions impact so as, - energy systems. Sustainability broadens socioeconomic parameters to practice science that meets recovery performance, engineering reflects the generic control of protective systems. When the environmental model employed properly, management decision process in governments or corporations could address policy for accomplishment strategic plans precisely. The management and engineering limitation focuses on autocatalytic control as a close cellular system to naturally balance anthropogenic insertions or aggregation structure systems to pound equilibrium as steady stable conditions. Thereby, construction systems ecology incorporates engineering and management scheme, as a midpoint stage between biotic and abiotic components to predict constructions impact. The later outcomes’ theory of environmental obligation suggests either a procedures of method or technique that is achieved in sustainability impact of construction system ecology (SICSE), as a relative mitigation measure of deviation control, ultimately.

Keywords: sustainability, environmental impact assessment, environemtal management, construction ecology

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Authors: Vishal Raj, Noorhan Abbas

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Ambiguity in NLP (Natural language processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential am-biguities. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a novel method to create an affinity matrix to calculate the affinity be-tween any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an al-gorithm to create the sense clusters of tokens using affinity matrix under hierar-chy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contex-tual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and chal-lenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

Keywords: word sense disambiguation (wsd), contextual sense model (csm), most frequent sense (mfs), part of speech (pos), natural language processing (nlp), oov (out of vocabulary), lemma_pos (a token where lemma and pos of word are joined by underscore), information retrieval (ir), machine translation (mt)

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Authors: Kafeero Frank

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This study aimed at developing a frame work for open source software adoption in an institution of higher learning in Uganda, with the case of KIU as a study area. There were mainly four research questions based on; individual staff interaction with open source software forum, perceived FOSS characteristics, organizational characteristics and external characteristics as factors that affect open source software adoption. The researcher used causal-correlation research design to study effects of these variables on open source software adoption. A quantitative approach was used in this study with self-administered questionnaire on a purposively and randomly sampled sample of university ICT staff. Resultant data was analyzed using means, correlation coefficients and multivariate multiple regression analysis as statistical tools. The study reveals that individual staff interaction with open source software forum and perceived FOSS characteristics were the primary factors that significantly affect FOSS adoption while organizational and external factors were secondary with no significant effect but significant correlation to open source software adoption. It was concluded that for effective open source software adoption to occur there must be more effort on primary factors with subsequent reinforcement of secondary factors to fulfill the primary factors and adoption of open source software. Lastly recommendations were made in line with conclusions for coming up with Kyambogo University frame work for open source software adoption in institutions of higher learning. Areas of further research recommended include; Stakeholders’ analysis of open source software adoption in Uganda; Challenges and way forward. Evaluation of Kyambogo University frame work for open source software adoption in institutions of higher learning. Framework development for cloud computing adoption in Ugandan universities. Framework for FOSS development in Uganda IT industry

Keywords: open source software., organisational characteristics, external characteristics, cloud computing adoption

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Authors: Xiao Yang, Ji Zhang, Yingli Song, Hui Huang, Jing Zhang, Yan Wang, Rongrong Han, Zhixuan Xiang, Lu Chen, Lingling Gao

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Aim and Objectives: To examine physical activity self-efficacy, identify its predictors, and further explore the mechanism of action among the predictors in mainland Chinese pregnant women with high risk for gestational diabetes mellitus (GDM). Background: Physical activity could protect pregnant women from developing GDM. Physical activity self-efficacy was the key predictor of physical activity. Design: A cross-sectional study was conducted from October 2021 to May 2022 in Zhengzhou, China. Methods: 252 eligible pregnant women completed the Pregnancy Physical Activity Self-efficacy Scale, the Social Support for Physical Activity Scale, the Knowledge on Physical Activity Questionnaire, the 7-item Generalized Anxiety Disorder scale, the Edinburgh Postnatal Depression Scale, and a socio-demographic data sheet. Multiple linear regression was applied to explore the predictors of physical activity self-efficacy. Structural equation modeling was used to explore the mechanism of action among the predictors. Results: Chinese pregnant women with a high risk for GDM reported a moderate level of physical activity self-efficacy. The best-fit regression analysis revealed four variables explained 17.5% of the variance in physical activity self-efficacy. Social support for physical activity was the strongest predictor, followed by knowledge of the physical activity, intention to do physical activity, and anxiety symptoms. The model analysis indicated that knowledge of physical activity could release anxiety and depressive symptoms and then increase physical activity self-efficacy. Conclusion: The present study revealed a moderate level of physical activity self-efficacy. Interventions targeting pregnant women with high risk for GDM need to include the predictors of physical activity self-efficacy. Relevance to clinical practice: To facilitate pregnant women with high risk for GDM to engage in physical activity, healthcare professionals may find assess physical activity self-efficacy and intervene as soon as possible on their first antenatal visit. Physical activity intervention programs focused on self-efficacy may be conducted in further research.

Keywords: physical activity, gestational diabetes, self-efficacy, predictors

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Authors: Rebecca S. Hock, Cyralene P. Bryce, Kevin Williams, Arielle G. Rabinowitz, Janina R. Galler

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Background: Findings have been mixed regarding whether offspring of parents who were abused or neglected as children have a greater risk of experiencing abuse or neglect themselves. In addition, many studies on this topic are restricted to physical abuse and take place in a limited number of countries, representing a small segment of the world's population. Methods: We examined relationships between childhood maltreatment history assessed in a subset (N=68) of the original longitudinal birth cohort (G1) of the Barbados Nutrition Study and their now-adult offspring (G2) (N=111) using the Childhood Trauma Questionnaire-Short Form (CTQ-SF). We used Pearson correlations to assess relationships between parent and offspring CTQ-SF total and subscale scores (physical, emotional, and sexual abuse; physical and emotional neglect). Next, we ran multiple regression analyses, using the parental CTQ-SF total score and the parental Sexual Abuse score as primary predictors separately in our models of G2 CTQ-SF (total and subscale scores). Results: G1 total CTQ-SF scores were correlated with G2 offspring Emotional Neglect and total scores. G1 Sexual Abuse history was significantly correlated with G2 Emotional Abuse, Sexual Abuse, Emotional Neglect, and Total Score. In fully-adjusted regression models, parental (G1) total CTQ-SF scores remained significantly associated with G2 offspring reports of Emotional Neglect, and parental (G1) Sexual Abuse was associated with offspring (G2) reports of Emotional Abuse, Physical Abuse, Emotional Neglect, and overall CTQ-SF scores. Conclusions: Our findings support a link between parental exposure to childhood maltreatment and their offspring's self-reported exposure to childhood maltreatment. Of note, there was not an exact correspondence between the subcategory of maltreatment experienced from one generation to the next. Compared with other subcategories, G1 Sexual Abuse history was the most likely to predict G2 offspring maltreatment. Further studies are needed to delineate underlying mechanisms and to develop intervention strategies aimed at preventing intergenerational transmission.

Keywords: trauma, family, adolescents, intergenerational trauma, child abuse, child neglect, global mental health, North America

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Authors: Yuwaratu Syafira, Wahyu K. Y. Putra, Kusharisupeni Djokosujono

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Background/Objective: Body Mass Index (BMI) serves various purposes, including measuring the prevalence of obesity in a population, and also in formulating a patient’s diet at a hospital, and can be calculated with the equation = body weight (kg)/body height (m)². However, the BMI of an individual with difficulties in carrying their weight or standing up straight can not necessarily be measured. The aim of this study was to form a prediction model for the BMI of young adult students of Public Health Faculty of University of Indonesia. Subject/Method: This study used a cross sectional design, with a total sample of 132 respondents, consisted of 58 males and 74 females aged 21- 30. The dependent variable of this study was BMI, and the independent variables consisted of sex and anthropometric measurements, which included ulna length, arm length, tibia length, knee height, mid-upper arm circumference, and calf circumference. Anthropometric information was measured and recorded in a single sitting. Simple and multiple linear regression analysis were used to create the prediction equation for BMI. Results: The male respondents had an average BMI of 24.63 kg/m² and the female respondents had an average of 22.52 kg/m². A total of 17 variables were analysed for its correlation with BMI. Bivariate analysis showed the variable with the strongest correlation with BMI was Mid-Upper Arm Circumference/√Ulna Length (MUAC/√UL) (r = 0.926 for males and r = 0.886 for females). Furthermore, MUAC alone also has a very strong correlation with BMI (r = 0,913 for males and r = 0,877 for females). Prediction models formed from either MUAC/√UL or MUAC alone both produce highly accurate predictions of BMI. However, measuring MUAC/√UL is considered inconvenient, which may cause difficulties when applied on the field. Conclusion: The prediction model considered most ideal to estimate BMI is: Male BMI (kg/m²) = 1.109(MUAC (cm)) – 9.202 and Female BMI (kg/m²) = 0.236 + 0.825(MUAC (cm)), based on its high accuracy levels and the convenience of measuring MUAC on the field.

Keywords: body mass index, mid-upper arm circumference, prediction model, ulna length

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Authors: Jessica Gu, Yu Chen

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Knowledge Management (KM) is undoubtable crucial to organizational value creation, learning, and adaptation. Although the rapidly growing KM domain has been fueled with full-fledged methodologies and technologies, studies on KM evolution that bridge the organizational performance and adaptation to the organizational environment are still rarely attempted. In particular, creation (or generation) and diffusion (or share/exchange) of knowledge are of the organizational primary concerns on the problem-solving perspective, however, the optimized distribution of knowledge creation and diffusion endeavors are still unknown to knowledge workers. This research proposed an agent-based model of knowledge creation and diffusion in an organization, aiming at elucidating how the intertwining knowledge flows at microscopic level lead to optimized organizational performance at macroscopic level through evolution, and exploring what exogenous interventions by the policy maker and endogenous adjustments of the knowledge workers can better cope with different environmental conditions. With the developed model, a series of simulation experiments are conducted. Both long-term steady-state and time-dependent developmental results on organizational performance, network and structure, social interaction and learning among individuals, knowledge audit and stocktaking, and the likelihood of choosing knowledge creation and diffusion by the knowledge workers are obtained. One of the interesting findings reveals a non-monotonic phenomenon on organizational performance under turbulent environment while a monotonic phenomenon on organizational performance under a stable environment. Hence, whether the environmental condition is turbulence or stable, the most suitable exogenous KM policy and endogenous knowledge creation and diffusion choice adjustments can be identified for achieving the optimized organizational performance. Additional influential variables are further discussed and future work directions are finally elaborated. The proposed agent-based model generates evidence on how knowledge worker strategically allocates efforts on knowledge creation and diffusion, how the bottom-up interactions among individuals lead to emerged structure and optimized performance, and how environmental conditions bring in challenges to the organization system. Meanwhile, it serves as a roadmap and offers great macro and long-term insights to policy makers without interrupting the real organizational operation, sacrificing huge overhead cost, or introducing undesired panic to employees.

Keywords: knowledge creation, knowledge diffusion, agent-based modeling, organizational performance, decision making evolution

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Authors: Sung-Hee Nam, Kwang-Gill Lee, You-Young Jo, HaeYong Kweon

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Entomopathogenic fungi is a Cordyceps species that is isolated from dead silkworm and cicada. Fungi on cicadas were described in old Chinese medicinal books and From ancient times, vegetable wasps and plant worms were widely known to have active substance and have been studied for pharmacological use. Among many fungi belonging to the genus Cordyceps, Cordyceps sinensis have been demonstrated to yield natural products possessing various biological activities and many bioactive components. Generally, It is commonly used to replenish the kidney and soothe the lung, and for the treatment of fatigue. Due to their commercial and economic importance, the demand for Cordyceps has been rapidly increased. However, a supply of Cordyceps specimen could not meet the increasing demand because of their sole dependence on field collection and habitat destruction. Because it is difficult to obtain many insect hosts in nature and the edibility of host insect needs to be verified in a pharmacological aspect. Recently, this setback was overcome that P. tenuipes was able to be cultivated in a large scale using silkworm as host. Pharmacological effects of P. tenuipes cultured on silkworm such as strengthening immune function, anti-fatigue, anti-tumor activity and controlling liver etc have been proved. They are widely commercialized. In this study, we attempted to establish a method for stable growth inhibition of P. tenuipes on silkworm hosts and an optimal condition for synnemata formation. To determine optimum culturing conditions, temperature and light conditions were varied. The length and number of synnemata was highest at 25℃ temperature and 100~300 lux illumination. On an average, the synnemata of wild P. tenuipes measures 70 ㎜ in length and 20 in number; those of the cultured strain were relatively shorter and more in number. The number of synnemata may have increased as a result of inoculating the host with highly concentrated conidia, while the length may have decreased due to limited nutrition per individual. It is not able that changes in light illumination cause morphological variations in the synnemata. However, regulation of only light and temperature could not produce stromata like perithecia, asci, and ascospores. Yamanaka reported that although a complete fruiting body can be produced under optimal culture conditions, it should be regarded as synnemata because it does not develop into an ascoma bearing ascospores.

Keywords: paecilomyces tenuipes, entomopathogenic fungi, silkworm larva, bombyx mori

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Authors: Soumaya Mrabet, Taieb Ach, Imen Akkari, Amira Atig, Neirouz Ghannouchi, Koussay Ach, Elhem Ben Jazia

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Introduction: Celiac disease (CD) is an immune-mediated small intestinal disorder that occurs in genetically susceptible people. It is significantly associated with other autoimmune disorders represented mainly by type 1 diabetes and autoimmune dysthyroidism. The aim of our study is to determine the prevalence and the type of the various autoimmune diseases associated with CD in adult patients. Material and methods: This is a retrospective study including patients diagnosed with CD, explored in Internal Medicine, Gastroenterology and Endocrinology and Diabetology Departments of the Farhat Hached University Hospital, between January 2005 and January 2016. The diagnosis of CD was confirmed by serological tests and duodenal biopsy. The screening of autoimmune diseases was based on physical examination, biological and serological tests. Results: Sixty five patients with a female predominance were included, 48women (73.8%) and 17 men (26.2%). The mean age was 31.8 years (17-75). A family history of CD or other autoimmune diseases was present in 5 and 10 patients respectively. Clinical presentation of CD was made by recurrent abdominal pain in 49 cases, diarrhea in 29 cases, bloating in 17 cases, constipation in 25 cases and vomiting in 8 cases. Autoimmune diseases associated with CD were found in 30 cases (46.1%): type 1 diabetes in 15 patients attested by the positivity of anti-GAD antibodies in 11 cases and anti-IA2 in 4 cases, Hashimoto thyroiditis in 8 cases confirmed by the positivity of anti-TPO antibodies, Addison's disease in 2 patients, Anemia of Biermer in 2 patients, autoimmune hepatitis, Systemic erythematosus lupus, Gougerot Sjögren syndrome, rheumatoid arthritis, Vitiligo and antiphospholipid syndrome in one patient each. CD was associated with more than one autoimmune disease defining multiple autoimmune syndrome in 2 female patients. The first patient had Basedow disease, Addison disease and type 1 diabetes. The second patient had systemic erythematosus lupus and Gougerot Sjögren syndrome. Conclusion: In our study autoimmune diseases were associated with CD in 46.1% of cases and were dominated by diabetes and dysthroidism. After establishing the diagnosis of CD the search of associated autoimmune diseases is necessary in order to avoid any therapeutic delay which can alter the prognosis of the patient.

Keywords: association, autoimmune thyroiditis, celiac disease, diabetes

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Authors: C. S. Subhashini, H. L. Premaratne

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Landslides are the most recurrent and prominent disaster in Sri Lanka. Sri Lanka has been subjected to a number of extreme landslide disasters that resulted in a significant loss of life, material damage, and distress. It is required to explore a solution towards preparedness and mitigation to reduce recurrent losses associated with landslides. Artificial Neural Networks (ANNs) and Hidden Markov Model (HMMs) are now widely used in many computer applications spanning multiple domains. This research examines the effectiveness of using Artificial Neural Networks and Hidden Markov Model in landslides predictions and the possibility of applying the modern technology to predict landslides in a prominent geographical area in Sri Lanka. A thorough survey was conducted with the participation of resource persons from several national universities in Sri Lanka to identify and rank the influencing factors for landslides. A landslide database was created using existing topographic; soil, drainage, land cover maps and historical data. The landslide related factors which include external factors (Rainfall and Number of Previous Occurrences) and internal factors (Soil Material, Geology, Land Use, Curvature, Soil Texture, Slope, Aspect, Soil Drainage, and Soil Effective Thickness) are extracted from the landslide database. These factors are used to recognize the possibility to occur landslides by using an ANN and HMM. The model acquires the relationship between the factors of landslide and its hazard index during the training session. These models with landslide related factors as the inputs will be trained to predict three classes namely, ‘landslide occurs’, ‘landslide does not occur’ and ‘landslide likely to occur’. Once trained, the models will be able to predict the most likely class for the prevailing data. Finally compared two models with regards to prediction accuracy, False Acceptance Rates and False Rejection rates and This research indicates that the Artificial Neural Network could be used as a strong decision support system to predict landslides efficiently and effectively than Hidden Markov Model.

Keywords: landslides, influencing factors, neural network model, hidden markov model

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Authors: Surinder Pal, Ajay Gupta, Johny Khajuria

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Casting simulation helps visualize mold filling and casting solidification; predict related defects like cold shut, shrinkage porosity and hard spots; and optimize the casting design to achieve the desired quality with high yield. Flow and solidification of molten metals are, however, a very complex phenomenon that is difficult to simulate correctly by conventional computational techniques, especially when the part geometry is intricate and the required inputs (like thermo-physical properties and heat transfer coefficients) are not available. Simulation software is based on the process of modeling a real phenomenon with a set of mathematical formulas. It is, essentially, a program that allows the user to observe an operation through simulation without actually performing that operation. Simulation software is used widely to design equipment so that the final product will be as close to design specs as possible without expensive in process modification. Simulation software with real-time response is often used in gaming, but it also has important industrial applications. When the penalty for improper operation is costly, such as airplane pilots, nuclear power plant operators, or chemical plant operators, a mockup of the actual control panel is connected to a real-time simulation of the physical response, giving valuable training experience without fear of a disastrous outcome. The all casting simulation software has own requirements, like magma cast has only best for crack simulation. The latest generation software Auto CAST developed at IIT Bombay provides a host of functions to support method engineers, including part thickness visualization, core design, multi-cavity mold design with common gating and feeding, application of various feed aids (feeder sleeves, chills, padding, etc.), simulation of mold filling and casting solidification, automatic optimization of feeders and gating driven by the desired quality level, and what-if cost analysis. IIT Bombay has developed a set of applications for the foundry industry to improve casting yield and quality. Casting simulation is a fast and efficient solution for process for advanced tool which is the result of more than 20 years of collaboration with major industrial partners and academic institutions around the world. In this paper the process of casting simulation is studied.

Keywords: casting simulation software’s, simulation technique’s, casting simulation, processes

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Authors: Oliver Ikechukwu Inyiama, Boniface Uche Ugwuanyi

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The aim of the research is to evaluate the key financial performance indicators that help both managers and their shareholders of Nigerian Banks to determine the appropriate dividend payout to their ordinary shareholders in an accounting year. Profitability, total asset, and earnings of commercial banks were selected as key performance indicators in Nigeria Banking Sector. They represent the independent variables of the study while dividend per share is the proxy for the dividend paid on ordinary shares which represent the dependent variable. The effect of profitability, total asset and earnings on dividend per share were evaluated through the ordinary least square method of multiple regression analysis. Test for normality of frequency distribution was conducted through descriptive statistics such as Jacque Bera Statistic, skewness and kurtosis. Rate of dividend payout was subsequently applied as an alternate dependent variable to test for robustness of the earlier results. The 64% adjusted R-squared of the pooled data indicates that profitability, total asset, and earnings explain the variation in dividend per share during the period under research while the remaining 36% variation in dividend per share could be explained by changes in other variables not captured by this study as well as the error term. The study concentrated on four leading Nigeria Commercial Banks namely; First Bank of Nigeria Plc, GTBank Plc, United Bank for Africa Plc and Zenith International Bank Plc. Dividend per share was found to be positively affected by total assets and earnings of the commercial banks. However, profitability which was proxied by profit after tax had a negative effect on dividend per share. The implication of the findings is that commercial banks in Nigeria pay more dividend when they are having a dwindling fortune in order to retain the confidence of the shareholders provided their gross earnings and size is on the increase. Therefore, the management and board of directors of Nigeria commercial banks should apply decent marketing strategies to enhance earnings through investment in profitable ventures for an improved dividend payout rate.

Keywords: assets, banks, indicators, performance, profitability, shares

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Authors: Hala M. El-hanbuli, Mohammed F. Darweesh

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The incidence rates of any tumor vary hugely with geographical location. Basal Cell Carcinoma (BCC) is one of the most common skin cancer that has many histopathologic subtypes. Objective: The aim was to study the histopathological features of BCC cases that were received in the Pathology Department, Kasr El-Aini hospital, Cairo University, Egypt during the period from Jan 2004 to Dec 2013 and to evaluate the clinical characters through the patient data available in the request sheets. Methods: Slides and data of BCC cases were collected from the archives of the pathology department, Kasr El-Aini hospital. Revision of all available slides and histological classification of BCC according to WHO (2006) was done. Results: A total number of 310 cases of BCC representing about 65% from the total number of malignant skin tumors examined during the 10-years duration in the department. The age ranged from 8 to 84 years, the mean age was (55.7 ± 15.5). Most of the patients (85%) were above the age of 40 years. There was a slight male predominance (55%). Ulcerated BCC was the most common gross picture (60%), followed by nodular lesion (30%) and finally the ulcerated nodule (10%). Most of the lesions situated in the high-risk sites (77%) where the nose was the most common site (35%) followed by the periocular area (22%), then periauricular (15%) and finally perioral (5%). No lesion was reported outside the head. The tumor size was less than 2 centimeters in 65% of cases, and from 2-5 centimeters in the lesions' greatest dimension in the rest of cases. Histopathological reclassification revealed that the nodular BCC was the most common (68%) followed by the pigmented nodular (18.75%). The histologic high-risk groups represented (7.5%) about half of them (3.75%) being basosquamous carcinoma. The total incidence for multiple BCC and 2nd primary was 12%. Recurrent BCC represented 8%. All of the recurrent lesions of BCC belonged to the histologic high-risk group. Conclusion: Basal Cell Carcinoma is the most common skin cancer in the 10-year survey. Histopathological diagnosis and classification of BCC cases are essential for the determination of the tumor type and its biological behavior.

Keywords: basal cell carcinoma, high risk, histopathological features, statistical analysis

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