Search results for: performance criteria

Authors: Palash Kumar Mollick, Leire Olazar, Laura Santamaria, Pablo Comendador, Gartzen Lopez, Martin Olazar

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Average calorific value of a mixure of waste plastic is approximately 38 MJ/kg. Present work aims to extract maximum possible energy from a mixure of waste plastic using a DC thermal plasma in a spouted bed reactor. Plasma pyrolysis and steam reforming process has shown a potential to generate hydrogen from plastic with much below of legal limit of producing dioxins and furans as the carcinogenic gases. A spouted bed pyrolysis rector can continuously process plastic beads to produce organic volatiles, which later react with steam in presence of catalyst to results in syngas. lasma being the fourth state of matter, can carry high impact electrons to favour the activation energy of any chemical reactions. Computational Fluid Dynamic (CFD) simulation using COMSOL Multiphysics software has been performed to evaluate performance of a plasma spouted bed reactor in producing contamination free hydrogen as a green energy from waste plastic beads. The simulation results will showcase a design of a plasma spouted bed reactor for converting plastic waste into green hydrogen in a single step process. The high temperature hydrodynamics of spouted bed with plastic beads and the corresponding temperature distribution inside the reaction chamber will be critically examined for it’s near future installation of demonstration plant.

Keywords: green hydrogen, plastic waste, synthetic gas, pyrolysis, steam reforming, spouted bed, reactor design, plasma, dc palsma, cfd simulation

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Authors: Nouf Al Harthi

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Venous thromboembolism (VTE) is one of the most common causes of hospital-related deaths in critically ill patients. Guidelines recommended VTE prophylaxis with standardized, fixed doses for most patients. The underweight population has limited data to guide the appropriate drug and dosing regimen. The aim of this study was to describe the pattern of VTE prophylaxis dose regimens for underweighted critically ill adult patients and the prevalence of associated VTE and bleeding. This study is a retrospective cohort study, conducted in King Abdulaziz Medical City, Saudi Arabia. It included all critical patients admitted to the intensive care units and were above 14 years old with weight less than 50 kg or BMI of 18.5 kg/m2 or less and were on heparin as VTE prophylaxis for more than 72 hours from January 2016 until January 2020. After screening 270 patients, only 40 patients were included in this study according to our inclusion and exclusion criteria. Only 6 patients (15%) received VTE prophylaxis as an adjusted dose of heparin 2500 U Q12, while the rest of the patients were taking standard dosing of heparin, 5000 U Q12 was given to 21 (52.50%) patients and 5000 U Q8 was given to 13 (32.50%) patients. None of the adjusted doses developed any complications such as VTE or bleeding. There was no significant difference compared with the standard dose group. This study focused on describing the pattern of heparin doses as VTE prophylaxis in underweight patients. We also compared the standard dosing and adjusted dosage of VTE prophylaxis on underweight patients and any complications. There was no significant difference in the complication’s outcome or benefits between the two groups.

Keywords: venous thromboembolism prophylaxis, heparin, underweight patients, adult, critical care units

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: deep learning, artificial neural networks, energy price forecasting, turkey

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Authors: Reiner-Ace P. Mateo, Vince Paolo F. Obille

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The traditional method of classifying the potential mineral resources requires a significant amount of time and money. In this paper, an alternative way to classify potential mineral resources with GIS application in Surigao del Sur. The three (3) analog map data inputs integrated to GIS are geologic map, topographic map, and land cover/vegetation map. The indicators used in the classification of potential nickel laterite integrated from the analog map data inputs are a geologic indicator, which is the presence of ultramafic rock from the geologic map; slope indicator and the presence of plateau edges from the topographic map; areas of forest land, grassland, and shrublands from the land cover/vegetation map. The potential mineral of the area was classified from low up to very high potential. The produced mineral potential classification map of Surigao del Sur has an estimated 4.63% low nickel laterite potential, 42.15% medium nickel laterite potential, 43.34% high nickel laterite potential, and 9.88% very high nickel laterite from its ultramafic terrains. For the validation of the produced map, it was compared with known occurrences of nickel laterite in the area using a nickel mining tenement map from the area with the application of remote sensing. Three (3) prominent nickel mining companies were delineated in the study area. The generated potential classification map of nickel-laterite in Surigao Del Sur may be of aid to the mining companies which are currently in the exploration phase in the study area. Also, the currently operating nickel mines in the study area can help to validate the reliability of the mineral classification map produced.

Keywords: mineral potential classification, nickel laterites, GIS, remote sensing, Surigao del Sur

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Authors: S. Jonsson, D. Millard, C. Bokhove

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Smartphones are ubiquitous and frequently used as learning tools, which makes the design of educational apps an important area of research. A key issue is designing apps to encourage engagement while maintaining a focus on the educational aspects of the app. Flow experience is a promising method for addressing this issue, which refers to a mental state of cognitive absorption and positive emotion. Flow experience has been shown to be associated with positive emotion and increased learning performance. Studies have shown that immediate feedback is an antecedent to Flow. This experiment investigates the effect of immediate feedback on Flow experience. An app teaching Spanish phrases was developed, and 30 participants completed both a 10min session with immediate feedback and a 10min session with delayed feedback. The app contained a task where the user assembles Spanish phrases by pressing bricks with Spanish words. Immediate feedback was implemented by incorrect bricks recoiling, while correct brick moved to form part of the finished phrase. In the delayed feedback condition, the user did not know if the bricks they pressed were correct until the phrase was complete. The level of Flow experienced by the participants was measured after each session using the Flow Short Scale. The results showed that higher levels of Flow were experienced in the immediate feedback session. It was also found that 14 of the participants indicated that the demands of the task were ‘just right’ in the immediate feedback session, while only one did in the delayed feedback session. These results have implications for how to design educational technology and opens up questions for how Flow experience can be used to increase performance and engagement.

Keywords: feedback timing, flow experience, L2 language learning, mobile learning

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Authors: Erika Humphreys

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The effectiveness of treating anxiety with Reiki is explored within ten quantitative studies. The methodology utilized for a critical appraisal and systematic review of the literature is explained with inclusion and exclusion criteria. The theoretical framework for the project is grounded in the work of Hildegard Peplau, whose nursing theory based on the therapeutic use of self is foundational for Reiki implementation. A thorough critique of the literature is conducted for key components of robustness and believability. This critique is conducted using a structured guide addressing synthesized strengths and weaknesses of the body of literature. A synthesis of the literature explores the findings of the studies. This synthesis reports on Reiki’s effectiveness in treating anxiety within a variety of patient settings and populations, its effect on subscales of anxiety, physiological manifestations of anxiety, and pain associated with anxiety. Cultural considerations affecting Reiki’s potential effectiveness are discussed. Gaps in the literature are examined, including the studies’ narrow sample population, lack of participant exclusionary factors for controlled outcome data, and the lack of studies across time. Implications for future research are discussed with recommendations for expanded research that includes a broader variety of settings, age groups, and patient diagnoses, including anxiety disorders, for research data that is transferable. Implications for further practice for the advanced practice registered nurse (APRN) are explored, with the potential benefits for both providers and patients, including improved patient satisfaction and expansion of provider treatment modalities.

Keywords: Reiki, anxiety, complementary alternative medicine, pandemic

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Authors: Anil P. Dewani, Ravindra L. Bakal, Anil V. Chandewar

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Present work demonstrates the applicability of high-performance liquid chromatography (HPLC) with UV detection for the determination of malondialdehyde as malondialdehyde-thiobarbituric acid complex (MDA-TBA) in-vivo in rats. The HPLC-UV method for MDA-TBA was achieved by isocratic mode on a reverse-phase C18 column (250mm×4.6mm) at a flow rate of 1.0mLmin−1 followed by UV detection at 278 nm. The chromatographic conditions were optimized by varying the concentration and pH followed by changes in percentage of organic phase optimal mobile phase consisted of mixture of water (0.2% Triethylamine pH adjusted to 2.3 by ortho-phosphoric acid) and acetonitrile in ratio (80:20 % v/v). The retention time of MDA-TBA complex was 3.7 min. The developed method was sensitive as limit of detection and quantification (LOD and LOQ) for MDA-TBA complex were (standard deviation and slope of calibration curve) 110 ng/ml and 363 ng/ml respectively. The method was linear for MDA spiked in plasma and subjected to derivatization at concentrations ranging from 100 to 1000 ng/ml. The precision of developed method measured in terms of relative standard deviations for intra-day and inter-day studies was 1.6–5.0% and 1.9–3.6% respectively. The HPLC method was applied for monitoring MDA levels in rats subjected to chronic treatment of ciprofloxacin (CFL) (5mg/kg/day) for 21 days. Results were compared by findings in control group rats. Mean peak areas of both study groups was subjected for statistical treatment to unpaired student t-test to find p-values. The p value was < 0.001 indicating significant results and suggesting increased MDA levels in rats subjected to chronic treatment of CFL of 21 days.

Keywords: MDA, TBA, ciprofloxacin, HPLC-UV

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Authors: Lavanya Ratnabala, Robinroy Peter, E. Y. A. Charles

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This research paper addresses the challenges of exploration and navigation in unknown environments from an evolutionary swarm robotics perspective. Path formation plays a crucial role in enabling cooperative swarm robots to accomplish these tasks. The paper presents a method called the sub-goal-based path formation, which establishes a path between two different locations by exploiting visually connected sub-goals. Simulation experiments conducted in the Argos simulator demonstrate the successful formation of paths in the majority of trials. Furthermore, the paper tackles the problem of inter-collision (traffic) among a large number of robots engaged in path formation, which negatively impacts the performance of the sub-goal-based method. To mitigate this issue, a task allocation strategy is proposed, leveraging local communication protocols and light signal-based communication. The strategy evaluates the distance between points and determines the required number of robots for the path formation task, reducing unwanted exploration and traffic congestion. The performance of the sub-goal-based path formation and task allocation strategy is evaluated by comparing path length, time, and resource reduction against the A* algorithm. The simulation experiments demonstrate promising results, showcasing the scalability, robustness, and fault tolerance characteristics of the proposed approach.

Keywords: swarm, path formation, task allocation, Argos, exploration, navigation, sub-goal

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Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: Ayman Othman, Tallat Ali

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The successive increase of generated waste materials like glass has led to many environmental problems. Using crushed waste glass in hot mix asphalt paving has been though as an alternative to landfill disposal and recycling. This paper discusses the possibility of utilizing crushed waste glass, as a part of fine aggregate in hot mix asphalt in Egypt. This is done through evaluation of the mechanical properties of asphalt concrete mixtures mixed with waste glass and determining the appropriate glass content that can be adapted in asphalt pavement. Four asphalt concrete mixtures with various glass contents, namely; 0%, 4%, 8% and 12% by weight of total mixture were studied. Evaluation of the mechanical properties includes performing Marshall stability, indirect tensile strength, fracture energy and unconfined compressive strength tests. Laboratory testing had revealed the enhancement in both compressive strength and Marshall stability test parameters when the crushed glass was added to asphalt concrete mixtures. This enhancement was accompanied with a very slight reduction in both indirect tensile strength and fracture energy when glass content up to 8% was used. Adding more than 8% of glass causes a sharp reduction in both indirect tensile strength and fracture energy. Testing results had also shown a reduction in the optimum asphalt content when the waste glass was used. Measurements of the heat loss rate of asphalt concrete mixtures mixed with glass revealed their ability to hold heat longer than conventional mixtures. This can have useful application in asphalt paving during cold whether or when a long period of post-mix transportation is needed.

Keywords: waste glass, hot mix asphalt, mechanical performance, indirect tensile strength, fracture energy, compressive strength

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Authors: Davies Obaromi, Qin Yongsong, James Ndege, Azeez Adeboye, Akinwumi Odeyemi

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The basic model usually used in disease mapping, is the Besag, York and Mollie (BYM) model and which combines the spatially structured and spatially unstructured priors as random effects. Bayesian Conditional Autoregressive (CAR) model is a disease mapping method that is commonly used for smoothening the relative risk of any disease as used in the Besag, York and Mollie (BYM) model. This model (CAR), which is also usually assigned as a prior to one of the spatial random effects in the BYM model, successfully uses information from adjacent sites to improve estimates for individual sites. To our knowledge, there are some unrealistic or counter-intuitive consequences on the posterior covariance matrix of the CAR prior for the spatial random effects. In the conventional BYM (Besag, York and Mollie) model, the spatially structured and the unstructured random components cannot be seen independently, and which challenges the prior definitions for the hyperparameters of the two random effects. Therefore, the main objective of this study is to construct and utilize an extended Bayesian spatial CAR model for studying tuberculosis patterns in the Eastern Cape Province of South Africa, and then compare for flexibility with some existing CAR models. The results of the study revealed the flexibility and robustness of this alternative extended CAR to the commonly used CAR models by comparison, using the deviance information criteria. The extended Bayesian spatial CAR model is proved to be a useful and robust tool for disease modeling and as a prior for the structured spatial random effects because of the inclusion of an extra hyperparameter.

Keywords: Besag2, CAR models, disease mapping, INLA, spatial models

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Authors: K. Yuki, R. Tsuji, K. Takai, S. Aramaki, R. Kibushi, N. Unno, K. Suzuki

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A small cold plate with uni-directional porous copper is proposed for cooling power electronics such as an on-vehicle inverter with the heat generation of approximately 500 W/cm2. The uni-directional porous copper with the pore perpendicularly orienting the heat transfer surface is soldered to a grooved heat transfer surface. This structure enables the cooling liquid to evaporate in the pore of the porous copper and then the vapor to discharge through the grooves. In order to minimize the cold plate, a double flow channel concept is introduced for the design of the cold plate. The cold plate consists of a base plate, a spacer, and a vapor discharging plate, totally 12 mm in thickness. The base plate has multiple nozzles of 1.0 mm in diameter for the liquid supply and 4 slits of 2.0 mm in width for vapor discharging, and is attached onto the top surface of the porous copper plate of 20 mm in diameter and 5.0 mm in thickness. The pore size is 0.36 mm and the porosity is 36 %. The cooling liquid flows into the porous copper as an impinging jet flow from the multiple nozzles, and then the vapor, which is generated in the pore, is discharged through the grooves and the vapor slits outside the cold plate. A heated test section consists of the cold plate, which was explained above, and a heat transfer copper block with 6 cartridge heaters. The cross section of the heat transfer block is reduced in order to increase the heat flux. The top surface of the block is the grooved heat transfer surface of 10 mm in diameter at which the porous copper is soldered. The grooves are fabricated like latticework, and the width and depth are 1.0 mm and 0.5 mm, respectively. By embedding three thermocouples in the cylindrical part of the heat transfer block, the temperature of the heat transfer surface ant the heat flux are extrapolated in a steady state. In this experiment, the flow rate is 0.5 L/min and the flow velocity at each nozzle is 0.27 m/s. The liquid inlet temperature is 60 °C. The experimental results prove that, in a single-phase heat transfer regime, the heat transfer performance of the cold plate with the uni-directional porous copper is 2.1 times higher than that without the porous copper, though the pressure loss with the porous copper also becomes higher than that without the porous copper. As to the two-phase heat transfer regime, the critical heat flux increases by approximately 35% by introducing the uni-directional porous copper, compared with the CHF of the multiple impinging jet flow. In addition, we confirmed that these heat transfer data was much higher than that of the ordinary single impinging jet flow. These heat transfer data prove high potential of the cold plate with the uni-directional porous copper from the view point of not only the heat transfer performance but also energy saving.

Keywords: cooling, cold plate, uni-porous media, heat transfer

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Authors: Gaurav Kumar Sinha

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The oil refining industry, significant in its energy consumption and carbon emissions, faces increasing pressure to reduce its environmental footprint. This article explores the application of energy efficiency and sustainability analytics as crucial tools for reducing carbon emissions in oil refineries. Through a comprehensive review of current practices and technologies, this study highlights innovative analytical approaches that can significantly enhance energy efficiency. We focus on the integration of advanced data analytics, including machine learning and predictive modeling, to optimize process controls and energy use. These technologies are examined for their potential to not only lower energy consumption but also reduce greenhouse gas emissions. Additionally, the article discusses the implementation of sustainability analytics to monitor and improve environmental performance across various operational facets of oil refineries. We explore case studies where predictive analytics have successfully identified opportunities for reducing energy use and emissions, providing a template for industry-wide application. The challenges associated with deploying these analytics, such as data integration and the need for skilled personnel, are also addressed. The paper concludes with strategic recommendations for oil refineries aiming to enhance their sustainability practices through the adoption of targeted analytics. By implementing these measures, refineries can achieve significant reductions in carbon emissions, aligning with global environmental goals and regulatory requirements.

Keywords: energy efficiency, sustainability analytics, carbon emissions, oil refineries, data analytics, machine learning, predictive modeling, process optimization, greenhouse gas reduction, environmental performance

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Authors: Xiao-Dong Wang, Wei-Mon Yan

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The flow field design in the bipolar plates affects the performance of the proton exchange membrane (PEM) fuel cell. This work adopted a combined optimization procedure, including a simplified conjugate-gradient method and a completely three-dimensional, two-phase, non-isothermal fuel cell model, to look for optimal flow field design for a single serpentine fuel cell of size 9×9 mm with five channels. For the direct solution, the two-fluid method was adopted to incorporate the heat effects using energy equations for entire cells. The model assumes that the system is steady; the inlet reactants are ideal gases; the flow is laminar; and the porous layers such as the diffusion layer, catalyst layer and PEM are isotropic. The model includes continuity, momentum and species equations for gaseous species, liquid water transport equations in the channels, gas diffusion layers, and catalyst layers, water transport equation in the membrane, electron and proton transport equations. The Bulter-Volumer equation was used to describe electrochemical reactions in the catalyst layers. The cell output power density Pcell is maximized subjected to an optimal set of channel heights, H1-H5, and channel widths, W2-W5. The basic case with all channel heights and widths set at 1 mm yields a Pcell=7260 Wm-2. The optimal design displays a tapered characteristic for channels 1, 3 and 4, and a diverging characteristic in height for channels 2 and 5, producing a Pcell=8894 Wm-2, about 22.5% increment. The reduced channel heights of channels 2-4 significantly increase the sub-rib convection and widths for effectively removing liquid water and oxygen transport in gas diffusion layer. The final diverging channel minimizes the leakage of fuel to outlet via sub-rib convection from channel 4 to channel 5. Near-optimal design without huge loss in cell performance but is easily manufactured is tested. The use of a straight, final channel of 0.1 mm height has led to 7.37% power loss, while the design with all channel widths to be 1 mm with optimal channel heights obtained above yields only 1.68% loss of current density. The presence of a final, diverging channel has greater impact on cell performance than the fine adjustment of channel width at the simulation conditions set herein studied.

Keywords: optimization, flow field design, simplified conjugate-gradient method, serpentine flow field, sub-rib convection

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Authors: Li-Hsueh Chen

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Efficient operation is more and more important for managers of hotels. Unlike the manufacturing industry, hotels cannot store their products. In addition, many hotels provide room service, and food and beverage service simultaneously. When efficiencies of hotels are evaluated, the internal structure should be considered. Hence, based on the operational characteristics of hotels, this study proposes a DEA model to simultaneously assess the efficiencies among the room production division, food and beverage production division, room service division and food and beverage service division. However, not only the enhancement of efficiency but also the adjustment of scale can improve the performance. In terms of the adjustment of scale, scale elasticity or returns to scale can help to managers to make decisions concerning expansion or contraction. In order to construct a reasonable approach to measure the efficiencies and scale elasticities of hotels, this study builds an alternative variable-returns-to-scale-based two-stage network DEA model with the combination of parallel and series structures to explore the scale elasticities of the whole system, room production division, food and beverage production division, room service division and food and beverage service division based on the data of international tourist hotel industry in Taiwan. The results may provide valuable information on operational performance and scale for managers and decision makers.

Keywords: efficiency, scale elasticity, network data envelopment analysis, international tourist hotel

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Authors: Adem Öğüt, M. Tahir Demirsel

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Rapid changes and developments today, besides the opportunities and facilities they offer to the organization, may also be a source of danger and difficulties due to the uncertainty. In order to take advantage of opportunities and to take the necessary measures against possible uncertainties, organizations must always follow the changes and developments that occur in the business environment and develop flexible structures and strategies for the alternative cases. Perceived environmental uncertainty is an outcome of managers’ perceptions of the combined complexity, instability and unpredictability in the organizational environment. An environment that is perceived to be complex, changing rapidly, and difficult to predict creates high levels of uncertainty about the appropriate organizational responses to external circumstances. In an uncertain and complex environment, organizations experiencing cutthroat competition may be successful by developing their corporate entrepreneurial ability. Corporate entrepreneurship is a process that includes many elements such as innovation, creating new business, renewal, risk-taking and being predictive. Successful corporate entrepreneurship is a critical factor which has a significant contribution to gain a sustainable competitive advantage, to renew the organization and to adapt the environment. In this context, the objective of this study is to investigate the effect of perceived environmental uncertainty of managers on corporate entrepreneurship performance. The research was conducted on 222 business executives in one of the major industrial zones of Turkey, Konya Organized Industrial Zone (KOS). According to the results, it has been observed that there is a positive statistically significant relationship between perceived environmental uncertainty and corporate entrepreneurial activities.

Keywords: corporate entrepreneurship, entrepreneurship, industrial zone, perceived environmental uncertainty, uncertainty

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Authors: Mrinalini Amritkar, Disha Patil, Swapna Kulkarni, Sukratu Barve, Suresh Gosavi

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Micro-mixers play an important role in the lab-on-a-chip applications and micro total analysis systems to acquire the correct level of mixing for any given process. The mixing process can be classified as active or passive according to the use of external energy. Literature of microfluidics reports that most of the work is done on the models of steady laminar flow; however, the study of unsteady laminar flow is an active area of research at present. There are wide applications of this, out of which, we consider nanoparticle synthesis in micro-mixers. In this work, we have developed a model for unsteady flow to study the mixing performance of a passive micro mixer for reactants used for such synthesis. The model is developed in Finite Volume Method (FVM)-based software, OpenFOAM. The model is tested by carrying out the simulations at Re of 0.5. Mixing performance of the micro-mixer is investigated using simulated concentration values of mixed species across the width of the micro-mixer and calculating the variance across a line profile. Experimental validation is done by passing dyes through a Y shape micro-mixer fabricated using polydimethylsiloxane (PDMS) polymer and comparing variances with the simulated ones. Gold nanoparticles are later synthesized through the micro-mixer and collected at two different times leading to significantly different size distributions. These times match with the time scales over which reactant concentrations vary as obtained from simulations. Our simulations could thus be used to create design aids for passive micro-mixers used in nanoparticle synthesis.

Keywords: Lab-on-chip, LOC, micro-mixer, OpenFOAM, PDMS

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Authors: Junya Kouwa, Shinsuke Matsuno, Chihiro Inoue, Takehiro Himeno, Toshinori Watanabe

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Bi-propellant thrusters use impinging jet atomization to atomize liquid fuel and oxidizer. Atomized propellants are mixed and combusted due to auto-ignitions. Therefore, it is important for a prediction of thruster’s performance to simulate the primary atomization phenomenon; especially, the local mixture ratio can be used as indicator of thrust performance, so it is useful to evaluate it from numerical simulations. In this research, we propose a numerical method for considering bi-liquid and the mixture and install it to CIP-LSM which is a two-phase flow simulation solver with level-set and MARS method as an interfacial tracking method and can predict local mixture ratio distribution downstream from an impingement point. A new parameter, beta, which is defined as the volume fraction of one liquid in the mixed liquid within a cell is introduced and the solver calculates the advection of beta, inflow and outflow flux of beta to a cell. By validating this solver, we conducted a simple experiment and the same simulation by using the solver. From the result, the solver can predict the penetrating length of a liquid jet correctly and it is confirmed that the solver can simulate the mixing of liquids. Then we apply this solver to the numerical simulation of impinging jet atomization. From the result, the inclination angle of fan after the impingement in the bi-liquid condition reasonably agrees with the theoretical value. Also, it is seen that the mixture of liquids can be simulated in this result. Furthermore, simulation results clarify that the injecting condition affects the atomization process and local mixture ratio distribution downstream drastically.

Keywords: bi-propellant thrusters, CIP-LSM, free-surface flow simulation, impinging jet atomization

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Authors: José Manue Carvalho Vieira, Mariana Magalhães, Elizabeth Serra

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The Port Wine industry is essential to Portugal because it carries a tangible cultural heritage and for social and economic reasons. Positioned as a luxury product, brands need to pay more attention to the new generation's habits, preferences, languages, and sensory perceptions. Healthy lifestyles, anti-alcohol campaigns, and digitalisation of their buying decision process need to be better understood to understand the wine market in the future. The purpose of this study is to clarify the sensory perception gap between Port Wine descriptors promotion and the new generation's perceptions to help wineries to align their strategies. Based on the interpretivist approach - multiple methods and techniques (mixed-methods), different world views and different assumptions, and different data collection methods and analysis, this research integrated qualitative semi-structured interviews, Port Wine promotion contents, and social media perceptions mined by Sentiment Analysis Enginius algorithm. Findings confirm that Port Wine CEOs' strategies, brands' promotional content, and social perceptions are not sufficiently aligned. The central insight for Port Wine brands' managers is that there is a long and continuous work of understanding and associating their descriptors with the most relevant perceptual values and criteria of their targets to reposition (when necessary) and sustainably revitalise their brands. Finally, this study hypothesised a sensory gap that leads to a decrease in consumption, trying to find recommendations on how to transform it into an advantage for a better attraction towards the young age group (18-25).

Keywords: port wine, consumer habits, sensory gap analysis, wine marketing

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Authors: Cathy T. Mpanga Kowet, Aghaegbuna Obinna U. Ozumba

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This study examined and identified the inconsistencies, relationships, gaps and recurring themes in literature regarding the relationship between procurement strategies employed in the construction projects for sustainable buildings and realization of sustainability goals. A systematic literature review of studies on the relationship between various procurement strategies and attainment of sustainability outcomes was conducted. Using specific terms, papers published between 2002 and 2018 were identified and screened according to an inclusion and exclusion criteria. Current findings reveal that, although the attainment of sustainability goals is achievable with both traditional and contemporary procurement strategies, only projects delivered using modern procurement strategies are capable of meeting and exceeding targeted sustainability objectives. However, traditional procurement strategy remains the preferred method for most green building construction projects. The results suggest implications for decision makers in considering the impact of selected procurement strategies on targeted sustainability goals, in the early stages of sustainable building construction projects. The study shows that there is a gap between the reported appropriate procurement strategies and what is being practiced currently. Theoretically, the study expands on the literature on adoption and diffusion of contemporary procurement strategies, by consolidating existing studies to highlight the current gaps. While the study is at the literature review stage, deductions will serve as basis for field work involving empirical data.

Keywords: green buildings construction, procurement method, procurement strategy, sustainability objectives, sustainability outcomes

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Authors: Mohammad Abdullah Almalki

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Background: Despite the frequent usage of ankle arthroscopy, there is limited medical literature regarding its indications, patterns of admissions, surgical outcomes, and associated complicated at Saudi Arabia. Hence, this study would highlight the surgical outcomes of such surgical approach that will assist orthopedic surgeons to detect which surgical procedure needs to be done as well as to help them regarding their diagnostic workups. Methods: At the Orthopedic Division of King Abdul‑Aziz Medical City in Riyadh and through a cross‑sectional design and convenient sampling techniques, the present study had recruited 20 subjects who fulfill the inclusion and exclusion criteria between 2016 and 2018. Data collection was carried out by a questionnaire designed and revised by an expert panel of health professionals. Results: Twenty patients were reviewed (11M and 9F) with an average age of 40.1 ± 12.2. Only 30% of the patients (5M, 1F) have no comorbidity, but 70% of patients (7M, 8F) were having at least one comorbidity. The most common indications were osteochondritis dissecans (n = 7, 35%), ankle fracture without dislocation (n = 4, 20%), and tibiotalar impingement (n = 3, 15%). Patients recorded pain in all cases (100%). The top four symptoms after pain were instability (30%, n = 6), muscle weakness (15%, n = 3) swelling (15%, n = 3), and stiffness (5%, n = 1). Two‑third of cases reached to their full healthy status and toe‑touch weight‑bearing was seen in two patients (10%). Conclusion: Ankle arthroscopy improved the rehabilitation rates in our tertiary care center. In addition, the surgical outcomes are favorable in our hospital since it has a very short length of stay, unexpended surgery, and fewest physiotherapy sessions.

Keywords: ankle, arthroscopy, indications, patterns

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Authors: M. Rodionov, Z. Dedovets

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The article describes the theoretical concept of teaching secondary school students proof demonstration skills in mathematics. It describes in detail different levels of mastery of the concept of proof-which correspond to Piaget’s idea of there being three distinct and progressively more complex stages in the development of human reflection. Lessons for each level contain a specific combination of the visual-figurative components and deductive reasoning. It is vital at the transition point between levels to carefully and rigorously recalibrate teaching to reflect the development of more complex reflective understanding. This can apply even within the same age range, since students will develop at different speeds and to different potential. The authors argue that this requires an aware and adaptive approach to lessons to reflect this complexity and variation. The authors also contend that effective teaching which enables students to properly understand the implementation of proof arguments must develop specific competences. These are: understanding of the importance of completeness and generality in making a valid argument; being task focused; having an internalised locus of control and being flexible in approach and evaluation. These criteria must be correlated with the systematic application of corresponding methodologies which are best likely to achieve success. The particular pedagogical decisions which are made to deliver this objective are illustrated by concrete examples from the existing secondary school mathematics courses. The proposed theoretical concept formed the basis of the development of methodological materials which have been tested in 47 secondary schools.

Keywords: education, teaching of mathematics, proof, deductive reasoning, secondary school

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Authors: Ghanim A. Bekr

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Project success is what must be done for the project to be acceptable to the client, stakeholders and end-users who will be affected by the project. The study of project success and the critical success factors (CSFs) are the means adopted to improve the effectiveness of project. This research is conducted to make an attempt to identify which variables influence the success of project implementation. This study has selected, through an extensive literature review and interviews, (83) factors categorized in (7) groups that the questionnaire respondents were asked to score. The responses from 66 professionals with an average of 15 years of experience in different types of construction projects in Jordan were collected and analyzed using SPSS and most important factors for success for various success criteria are presented depending on the relative importance index to rank the categories. The research revealed the significant groups of factors are: Client related factors, Contractor’s related factors, Project Manager (PM) related factors, and Project management related factors. In addition the top ten sub factors are: Assertion of the client towards short time of the project, availability of skilled labor, Assertion of the client towards high level of the quality, capability of the client in taking risk, previous experience of the PM in similar projects, previous experience of the contractor in similar projects, decision making by the client/ the client’s representative at the right time, assertion of client towards low cost of project, experience in project management in previous projects, and flow of the information among parties. The results would be helpful to construction project professionals in taking proactive measures for successful completion of construction projects in Jordan.

Keywords: construction projects, critical success factors, Jordan, project success

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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Authors: Pallavi Kishore, Mariam Aslam

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The sharp decline in oil prices that started in 2014 affected most economies in the world either positively or negatively. In some economies, particularly the oil exporting countries, the effects were felt immediately. The Gulf Cooperation Council’s (GCC henceforth) countries are oil and gas-dependent with the largest oil reserves in the world. UAE (United Arab Emirates) has been striving to diversify away from oil and expects higher non-oil growth in 2018. These two factors, falling oil prices and the economy strategizing away from oil dependence, make a compelling case to study the financial performance of various sectors in the economy. Among other sectors, the insurance sector is widely recognized as an important indicator of the health of the economy. An expanding population, surge in construction and infrastructure, increased life expectancy, greater expenditure on automobiles and other luxury goods translate to a booming insurance sector. A slow-down of the insurance sector, on the other hand, may indicate a general slow-down in the economy. Therefore, a study on the insurance sector will help understand the general nature of the current economy. This study involves calculations and comparisons of ratios pre and post the fall in oil prices in the insurance sector in the UAE. A sample of 33 companies listed on the official stock exchanges of UAE-Dubai Financial Market and Abu Dhabi Stock Exchange were collected and empirical analysis employed to study the financial performance pre and post fall in oil prices. Ratios were calculated in 5 categories: Profitability, Liquidity, Leverage, Efficiency, and Investment. The means pre- and post-fall are compared to conclude that the profitability ratios including ROSF (Return on Shareholder Funds), ROCE (Return on Capital Employed) and NPM (Net Profit Margin) have all taken a hit. Parametric tests, including paired t-test, concludes that while the fall in profitability ratios is statistically significant, the other ratios have been quite stable in the period. The efficiency, liquidity, gearing and investment ratios have not been severely affected by the fall in oil prices. This may be due to the implementation of stronger regulatory policies and is a testimony to the diversification into the non-oil economy. The regulatory authorities can use the findings of this study to ensure transparency in revealing financial information to the public and employ policies that will help further the health of the economy. The study will also help understand which areas within the sector could benefit from more regulations.

Keywords: UAE, insurance sector, ratio analysis, oil price, profitability, liquidity, gearing, investment, efficiency

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Authors: Mona Rashidirad, Hamid Salimian

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Dynamic capabilities, as the most considerable capabilities of firms in the current fast-moving economy may not be sufficient for performance improvement, but their contribution to performance is undeniable. While much of the extant literature investigates the impact of dynamic capabilities on organisational performance, little attention has been devoted to understand whether and how dynamic capabilities create value. Dynamic capabilities as the mirror of competitive strategies should enable firms to search and seize new ideas, integrate and coordinate the firm’s resources and capabilities in order to create value. A careful investigation to the existing knowledge base remains us puzzled regarding the relationship among competitive strategies, dynamic capabilities and value creation. This study thus attempts to fill in this gap by empirically investigating the impact of dynamic capabilities on value creation and the mediating impact of competitive strategy on this relationship. We aim to contribute to dynamic capability view (DCV), in both theoretical and empirical senses, by exploring the impact of dynamic capabilities on firms’ value creation and whether competitive strategy can play any role in strengthening/weakening this relationship. Using a sample of 491 firms in the UK telecommunications market, the results demonstrate that dynamic sensing, learning, integrating and coordinating capabilities play a significant role in firm’s value creation, and competitive strategy mediates the impact of dynamic capabilities on value creation. Adopting DCV, this study investigates whether the value generating from dynamic capabilities depends on firms’ competitive strategy. This study argues a firm’s competitive strategy can mediate its ability to derive value from its dynamic capabilities and it explains the extent a firm’s competitive strategy may influence its value generation. The results of the dynamic capabilities-value relationships support our expectations and justify the non-financial value added of the four dynamic capability processes in a highly turbulent market, such as UK telecommunications. Our analytical findings of the relationship among dynamic capabilities, competitive strategy and value creation provide further evidence of the undeniable role of competitive strategy in deriving value from dynamic capabilities. The results reinforce the argument for the need to consider the mediating impact of organisational contextual factors, such as firm’s competitive strategy to examine how they interact with dynamic capabilities to deliver value. The findings of this study provide significant contributions to theory. Unlike some previous studies which conceptualise dynamic capabilities as a unidimensional construct, this study demonstrates the benefits of understanding the details of the link among the four types of dynamic capabilities, competitive strategy and value creation. In terms of contributions to managerial practices, this research draws attention to the importance of competitive strategy in conjunction with development and deployment of dynamic capabilities to create value. Managers are now equipped with solid empirical evidence which explains why DCV has become essential to firms in today’s business world.

Keywords: dynamic capabilities, resource based theory, value creation, competitive strategy

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Authors: M. Devamanalan, K. Pothiraj, M. Sudhan

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In competitive market like India, there is a high demand on the equal contribution on performance and its durability aspect of any system. In General vehicle has multiple sub-systems such as powertrain, BIW, Brakes, Actuations, Suspension and Seats etc., To withstand the market challenges, the contribution of each sub-system is very vital. The malfunction of any one sub system will directly have an impact on the performance of the major system which lead to dis-satisfaction to the end user. The Powertrain system consists of several sub-systems in which clutch is one of the prime sub-systems in MT vehicles which assist for smoother gear shifts with proper clutch dis-engagement and engagement. In general, most of the vehicles will have a mechanical or semi or full hydraulic clutch release system, whereas in small Commercial Vehicles (SCV) the majorly used clutch release system is mechanical cable release system due to its lesser cost and functional requirements. The major bottle neck in the cable type clutch release system is increase in pedal effort due to hysteresis increase and Gear shifting hard due to efficiency loss / cable slackness over the mileage accumulation of the vehicle. This study is to mainly focus on how the efficiency and hysteresis change over the mileage of the vehicle occurs because of the design architecture of outer and inner cable. The study involves several cable design validation results from vehicle level and rig level through the defined cable routing and test procedures. Results are compared to evaluate the suitable cable design architecture based on better efficiency and lower hysteresis parameters at initial and end of the validation.

Keywords: clutch, clutch cable, efficiency, architecture, cable routing

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Authors: Sajjad Hassanpour, Vicente A. González, Yang Zou, Jiamou Liu

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Earthquakes pose a significant threat to both structural and non-structural elements in buildings, putting human lives at risk. Effective post-earthquake evacuation is critical for ensuring the safety of building occupants. However, current design practices often neglect the integration of post-earthquake evacuation considerations into the early-stage architectural design process. To address this gap, this paper presents a novel automated internal architectural layout generation tool that optimizes post-earthquake evacuation performance. The tool takes an initial plain floor plan as input, along with specific requirements from the user/architect, such as minimum room dimensions, corridor width, and exit lengths. Based on these inputs, firstly, the tool randomly generates different architectural layouts. Secondly, the human post-earthquake evacuation behaviour will be thoroughly assessed for each generated layout using the advanced Agent-Based Building Earthquake Evacuation Simulation (AB2E2S) model. The AB2E2S prototype is a post-earthquake evacuation simulation tool that incorporates variables related to earthquake intensity, architectural layout, and human factors. It leverages a hierarchical agent-based simulation approach, incorporating reinforcement learning to mimic human behaviour during evacuation. The model evaluates different layout options and provides feedback on evacuation flow, time, and possible casualties due to earthquake non-structural damage. By integrating the AB2E2S model into the automated layout generation tool, architects and designers can obtain optimized architectural layouts that prioritize post-earthquake evacuation performance. Through the use of the tool, architects and designers can explore various design alternatives, considering different minimum room requirements, corridor widths, and exit lengths. This approach ensures that evacuation considerations are embedded in the early stages of the design process. In conclusion, this research presents an innovative automated internal architectural layout generation tool that integrates post-earthquake evacuation simulation. By incorporating evacuation considerations into the early-stage design process, architects and designers can optimize building layouts for improved post-earthquake evacuation performance. This tool empowers professionals to create resilient designs that prioritize the safety of building occupants in the face of seismic events.

Keywords: agent-based simulation, automation in design, architectural layout, post-earthquake evacuation behavior

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Authors: Martin Cai, Khadijah B. Hashim, Leng Leo, Edmund F. Tian

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Analysis of traditional Chinese medicinal (TCM) supplements has always been a laborious task, particularly in the case of multi‐ingredient formulations. Traditionally, herbal extracts are analysed using one or few markers compounds. In the recent years, however, pharmaceutical companies are introducing health supplements of TCM active ingredients to cater to the needs of consumers in the fast-paced society in this age. As such, new problems arise in the aspects of composition identification as well as quality analysis. In most cases of products or supplements formulated with multiple TCM herbs, the chemical composition, and nature of each raw material differs greatly from the others in the formulation. This results in a requirement for individual analytical processes in order to identify the marker compounds in the various botanicals. Thin-layer Chromatography (TLC) is a simple, cost effective, yet well-regarded method for the analysis of natural products, both as a Pharmacopeia-approved method for identification and authentication of herbs, and a great analytical tool for the discovery of chemical compositions in herbal extracts. Recent technical advances introduced High-Performance TLC (HPTLC) where, with the help of automated equipment and improvements on the chromatographic materials, both the quality and reproducibility are greatly improved, allowing for highly standardised analysis with greater details. Here we report an industrial consultancy project with ONI Global Pte Ltd for the analysis of LAC Liver Protector, a TCM formulation aimed at improving liver health. The aim of this study was to identify 4 key components of the supplement using HPTLC, following protocols derived from Chinese Pharmacopeia standards. By comparing the TLC profiles of the supplement to the extracts of the herbs reported in the label, this project proposes a simple and cost-effective analysis of the presence of the 4 marker compounds in the multi‐ingredient formulation by using 4 different HPTLC methods. With the increasing trend of small and medium-sized enterprises (SMEs) bringing natural products and health supplements into the market, it is crucial that the qualities of both raw materials and end products be well-assured for the protection of consumers. With the technology of HPTLC, science can be incorporated to help SMEs with their quality control, thereby ensuring product quality.

Keywords: traditional Chinese medicine supplement, high performance thin layer chromatography, active ingredients, product quality

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Authors: Ibrahim Nadeem, Mohammed Rahman, Yasser Ad-Dab’Bagh, Mahmood Akhtar

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Depression is one of the most prevalent mental illnesses and is often associated with various other medical disorders. In this review, we aim to evaluate existing systematic reviews that investigate the use of probiotics as a treatment for depressive symptoms. Five online databases were searched for relevant studies up to December 2017. Systematic reviews that included randomized controlled trials assessing the efficacy of probiotics in the treatment of depressive symptoms were included. Seven systematic reviews met the inclusion criteria. Three of these reviews conducted meta-analyses, out of which, two found probiotics to significantly improve depressive symptoms in the sample population. Two meta-analyses conducted subgroup analysis based on health status, and both found probiotics to significantly decrease depressive symptoms in patients with major depressive disorder, but only one review found it to significantly decrease in healthy patients. Another subgroup analysis was conducted based on age, and found probiotics to produce significant effects on subjects under the age of 60, but close to no effect on patients over the age of 65. Out of the four reviews that conducted qualitative analysis, three reviews concluded that probiotics have the potential to be used as a treatment. Due to the differences in clinical trials, a definitive effect of probiotics on depressive symptoms cannot be concluded. Nonetheless, probiotics seem to produce a significant therapeutic effect for subjects with pre-existing depressive symptoms. Further studies are warranted for definitive conclusions.

Keywords: depression, gut-brain axis, gut microbiota, probiotic, psychobiotic

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