Search results for: pharmacological management

Authors: R. N. Pateriya, T. K. Bhattacharya

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In India, rice-wheat cropping system occupies the major area and contributes about 40% of the country’s total food grain production. It is necessary that production of rice and wheat must keep pace with growing population. However, various factors such as degradation in natural resources, shift in cropping pattern, energy constraints etc. are causing reduction in the productivity of these crops. Seedbed for rice after wheat is difficult to prepare due to presence of straw and stubbles, and require excessive tillage operations to bring optimum tilth. In addition, delayed sowing and transplanting of rice is mainly due to poor crop residue management, multiplicity of tillage operations and non-availability of the power source. With increasing concern for fuel conservation and energy management, farmers might wish to estimate the best cultivation system for more productivity. The widest spread method of tilling land is ploughing with mould board plough. However, with the mould board plough upper layer of soil is neither always loosened at the desired extent nor proper mixing of different layers are achieved. Therefore, additional operations carried out to improve tilth. The farmers are becoming increasingly aware of the need for minimum tillage by minimizing the use of machines. Soil management can be achieved by using the combined active-passive tillage machines. A study was therefore, undertaken in wheat-harvested field to study the impact of conventional and modified tillage practices on paddy crop cultivation. Tillage treatments with tractor as a power source were selected during the experiment. The selected level of tillage treatments of tractor machinery management were (T1:- Direct Sowing of Rice), (T2:- 2 to 3 harrowing and no Puddling with manual transplanting), (T3:- 2 to 3 harrowing and Puddling with paddy harrow with manual transplanting), (T4:- 2 to 3 harrowing and Puddling with Rotavator with manual transplanting). The maximum output was obtained with treatment T1 (7.85 t/ha)) followed by T4 (6.4 t/ha), T3 (6.25 t/ha) and T2 (6.0 t/ha)) respectively.

Keywords: crop residues, cropping system, minimum tillage, yield

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Authors: Julius M. Ndambuki, Gislar E. Kifanyi, Samuel N. Odai, Charles Gyamfi

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Conjunctive management of surface and groundwater resources is a challenging task due to the spatial and temporal variability nature of hydrology as well as hydrogeology of the water storage systems. Surface water-groundwater hydrogeology is highly uncertain; thus it is imperative that this uncertainty is explicitly accounted for, when managing water resources. Various methodologies have been developed and applied by researchers in an attempt to account for the uncertainty. For example, simulation-optimization models are often used for conjunctive water resources management. However, direct application of such an approach in which all realizations are considered at each iteration of the optimization process leads to a very expensive optimization in terms of computational time, particularly when the number of realizations is large. The aim of this paper, therefore, is to introduce and apply an efficient approach referred to as Retrospective Optimization Approximation (ROA) that can be used for optimizing conjunctive use of surface water and groundwater over a multiple hydrogeological model simulations. This work is based on stochastic simulation-optimization framework using a recently emerged technique of sample average approximation (SAA) which is a sampling based method implemented within the Retrospective Optimization Approximation (ROA) approach. The ROA approach solves and evaluates a sequence of generated optimization sub-problems in an increasing number of realizations (sample size). Response matrix technique was used for linking simulation model with optimization procedure. The k-means clustering sampling technique was used to map the realizations. The methodology is demonstrated through the application to a hypothetical example. In the example, the optimization sub-problems generated were solved and analysed using “Active-Set” core optimizer implemented under MATLAB 2014a environment. Through k-means clustering sampling technique, the ROA – Active Set procedure was able to arrive at a (nearly) converged maximum expected total optimal conjunctive water use withdrawal rate within a relatively few number of iterations (6 to 7 iterations). Results indicate that the ROA approach is a promising technique for optimizing conjunctive water use of surface water and groundwater withdrawal rates under hydrogeological uncertainty.

Keywords: conjunctive water management, retrospective optimization approximation approach, sample average approximation, uncertainty

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Authors: T. Botelho de Sousa, F. Raphael Cabral Furtado, O. Eduardo da Silva Ferri, A. Batista, W. Augusto Varella, C. Eduardo Pinto, J. Mimar Santa Cruz Yabarrena, S. Gibran Ruwer, F. Müller Guerrini, L. Adalberto Philippsen Júnior

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Lean Supply Chain Management (LSCM) is an emerging research field in Operations Management (OM). As a strategic model that focuses on reduced cost and waste with fulfilling the needs of customers, LSCM attracts great interest among researchers and practitioners. The purpose of this paper is to present an overview of Lean Supply Chains literature, based on bibliometric analysis through 57 papers published in indexed journals by SCOPUS and/or Web of Science databases. The results indicate that the last three years (2015, 2016, and 2017) were the most productive on LSCM discussion, especially in Supply Chain Management and International Journal of Lean Six Sigma journals. India, USA, and UK are the most productive countries; nevertheless, cross-country studies by collaboration among researchers were detected, by social network analysis, as a research practice, appearing to play a more important role on LSCM studies. Despite existing limitation, such as limited indexed journal database, bibliometric analysis helps to enlighten ongoing efforts on LSCM researches, including most used technical procedures and collaboration network, showing important research gaps, especially, for development countries researchers.

Keywords: Lean Supply Chains, Bibliometric Study, SCOPUS, Web of Science

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Authors: Chevon Fernando, Banuka Athuraliya

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The purpose of this research is to provide a solution to the students’ time management, which usually becomes an issue because students must study and manage their personal commitments. "TimeTune," an AI-based study planner that provides an opportunity to maneuver study timeframes by incorporating modern machine learning algorithms with calendar applications, is unveiled as the ideal solution. The research is focused on the development of LSTM models that connect to the Google Calendar API in the process of developing learning paths that would be fit for a unique student's daily life experience and study history. A key finding of this research is the success in building the LSTM model to predict optimal study times, which, integrating with the real-time data of Google Calendar, will generate the timetables automatically in a personalized and customized manner. The methodology encompasses Agile development practices and Object-Oriented Analysis and Design (OOAD) principles, focusing on user-centric design and iterative development. By adopting this method, students can significantly reduce the tension associated with poor study habits and time management. In conclusion, "TimeTune" displays an advanced step in personalized education technology. The fact that its application of ML algorithms and calendar integration is quite innovative is slowly and steadily revolutionizing the lives of students. The excellence of maintaining a balanced academic and personal life is stress reduction, which the applications promise to provide for students when it comes to managing their studies.

Keywords: personalized learning, study planner, time management, calendar integration

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Authors: Maariyah Irfan

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Intro: Current cardiovascular (CV) care faces challenges such as low budgets and high hospital admission rates. This review aims to evaluate Big Data in CV healthcare management through the use of wearable devices in atrial fibrillation (AF) detection. AF may present intermittently, thus it is difficult for a healthcare professional to capture and diagnose a symptomatic rhythm. Methods: The iRhythm ZioPatch, AliveCor portable electrocardiogram (ECG), and Apple Watch were chosen for review due to their involvement in controlled clinical trials, and their integration with smartphones. The cost-effectiveness and AF detection of these devices were compared against the 12-lead ambulatory ECG (Holter monitor) that the NHS currently employs for the detection of AF. Results: The Zio patch was found to detect more arrhythmic events than the Holter monitor over a 2-week period. When patients presented to the emergency department with palpitations, AliveCor portable ECGs detected 6-fold more symptomatic events compared to the standard care group over 3-months. Based off preliminary results from the Apple Heart Study, only 0.5% of participants received irregular pulse notifications from the Apple Watch. Discussion: The Zio Patch and AliveCor devices have promising potential to be implemented into the standard duty of care offered by the NHS as they compare well to current routine measures. Nonetheless, companies must address the discrepancy between their target population and current consumers as those that could benefit the most from the innovation may be left out due to cost and access.

Keywords: atrial fibrillation, big data, cardiovascular healthcare management, wearable devices

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: T. Spiegel, J. Siegmann, C. F. Durach

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Challenges resulting from an international and dynamic business environment are increasingly being passed on from manufacturing companies to external service providers. Especially providers of complex, customer-specific industry services have to cope with continuously changing requirements. This is particularly true for contract logistics service providers. They are forced to develop efficient and highly flexible structures and strategies to meet their customer’s needs. One core element they have to focus on is the reorganization of their service development and sales process. Based on an action research approach, this study develops and tests a concept to streamline tender management for contract logistics service providers. The concept of modularized service architecture is deployed in order to derive a practice-oriented approach for the modularization of complex service portfolios and the design of customized quotes. These findings are evaluated regarding their applicability in other service sectors and practical recommendations are given.

Keywords: contract logistics, modularization, service development, tender management

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Authors: Hind Bouami, Patrick Millot

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Medication dispensing system is a life-critical system whose failure may result in preventable adverse events leading to longer patient stays in hospitals or patient death. Automation has led to great improvements in life-critical systems as it increased safety, efficiency, and comfort. However, critical risks related to medical organization complexity and automated solutions integration can threaten drug dispensing security and performance. Knowledge about the system’s complexity aspects and human machine parameters to control for automated equipment’s security and performance will help operators to secure their automation process and to optimize their system’s reliability. In this context, this study aims to document the operator’s situation awareness about automation risks and parameters involved in automation security and performance. Our risk management approach has been deployed in the North Luxembourg hospital center’s pharmacy, which is equipped with automated drug dispensing systems since 2009. With more than 4 million euros of gains generated, North Luxembourg hospital center’s success story was enabled by the management commitment, pharmacy’s involvement in the implementation and improvement of the automation project, and the close collaboration between the pharmacy and Sinteco’s firm to implement the necessary innovation and organizational actions for automated solutions integration security and performance. An analysis of the actions implemented by the hospital and the parameters involved in automated equipment’s integration security and performance has been made. The parameters to control for automated equipment’s integration security and performance are human aspects (6.25%), technical aspects (50%), and human-machine interaction (43.75%). The implementation of an anthropocentric analysis system before automation would have prevented and optimized the control of risks related to automation.

Keywords: Automated drug delivery systems, Hospitals, Human-centered automated system, Risk management

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Authors: Mijoh A. Gbededo, Kapila Liyanage, Ilias Oraifige

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Decision making for sustainable manufacturing design and management requires critical considerations due to the complexity and partly conflicting issues of economic, social and environmental factors. Although there are tools capable of assessing the combination of one or two of the sustainability factors, the frameworks have not adequately integrated all the three factors. Case study and review of existing simulation applications also shows the approach lacks integration of the sustainability factors. In this paper we discussed the development of a simulation based framework for support of a holistic assessment of sustainable manufacturing design and management. To achieve this, a strategic approach is introduced to investigate the strengths and weaknesses of the existing decision supporting tools. Investigation reveals that Discrete Event Simulation (DES) can serve as a rock base for other Life Cycle Analysis frameworks. Simio-DES application optimizes systems for both economic and competitive advantage, Granta CES EduPack and SimaPro collate data for Material Flow Analysis and environmental Life Cycle Assessment, while social and stakeholders’ analysis is supported by Analytical Hierarchy Process, a Multi-Criteria Decision Analysis method. Such a common and integrated framework creates a platform for companies to build a computer simulation model of a real system and assess the impact of alternative solutions before implementing a chosen solution.

Keywords: discrete event simulation, life cycle sustainability analysis, manufacturing, sustainability

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Authors: Bernabeo R. Alberto

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Unmanned aerial vehicles (UAV) platforms or remotely piloted aircraft system (Rpas) - with dedicated sensors - are fundamental support to the planning, running, and control of the territory in which public safety is or may be at risk for post-disaster assessments such as flooding or landslides, for searching lost people, for crime and accident scene photography, for assisting traffic control at major events, for teaching geography, history, natural science and all those subjects that require a continuous cyclical process of observation, evaluation and interpretation. Through the use of proximal remote sensing information related to anthropic landscape and nature integration, there is an opportunity to improve knowledge and management decision-making for the safeguarding of the environment, for farming, wildlife management, land management, mapping, glacier monitoring, atmospheric monitoring, for the conservation of archeological, historical, artistic and architectural sites, allowing an exact delimitation of the site in the territory. This paper will go over many different mission types. Within each mission type, it will give a broad overview to familiarize the reader but not make them an expert. It will also give detailed information on the payloads and other testing parameters the Unmanned Aerial Vehicles (UAV) use to complete a mission. The project's goal is to improve satellite maps about the stress of the plants, air quality monitoring, and related health issues.

Keywords: proximal remote sensing, remotely piloted aircraft system, risk, safety, unmanned aerial vehicle

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Authors: Oluwagbenga O. Isaac Orimoogunje, Omolola Helen Oshosanya

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The study examined land management in a typical watershed in southwestern Nigeria with a view to ascertaining its impact on land suitability analysis for rice cultivation and production. The study applied the analytical hierarchy process (AHP), weighted overlay analysis (WOA), multi-criteria decision-making techniques, and suitability map calculations within a Geographic Information System environment. Five main criteria were used, and these include climate, topography, soil fertility, macronutrients, and micronutrients. A consistency ratio (CR) of 0.067 was obtained for rice cultivation. The results showed that 95% of the land area is suitable for rice cultivation, with pH units ranging between 4.6 and 6.0, organic matter of 1.4–2.5 g kg-1 and base saturation of more than 80%. The study concluded that the Ofiki watershed is a potential site for large-scale rice cultivation in a sustainable capacity.

Keywords: land management, land characteristics, land suitability, rice production, watershed

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Authors: Han Gul Lee

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When water treatments utilities are designed, an initial construction site risk assessment is conducted. This helps us to understand general safety risks that each utility needs to be complemented in the designing stage. Once it’s built, an additional risk reassessment process secures and supplements its disaster management and response plan. Because of its constantly changing surroundings with city renovation and developments, the degree of various risks that each facility has to face changes. Therefore, to improve the preparedness for spill incidents or disasters, emergency managers should run spill simulations with the available scientific technologies. This research used a two-dimensional flow routing model to simulate its spill disaster scenario based on its digital elevation model (DEM) collected with drone technologies. The results of the simulations can help emergency managers to supplement their response plan with concrete situational awareness in advance. Planning based on this simulation model minimizes its potential loss and damage when an incident like earthquakes man-made disaster happens, which could eventually be a threat in a public health context. This pilot research provides an additional paradigm to increase the preparedness to spill disasters. Acknowledgment: This work was supported by Korea Environmental Industry & Technology Institute (KEITI) through Environmental R&D Project on the Disaster Prevention of Environmental Facilities Program funded by Korea Ministry of Environment (MOE) (No.202002860001).

Keywords: risk assessment, disaster management, water treatment utilities, situational awareness, drone technologies

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Authors: Baobao Li

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Operational risk covers all operations of commercial banks and has a close relationship with the bank’s internal control. But in the commercial banks' management practice, internal control is always separated from the operational risk measurement. With the increasing of operational risk events in recent years, operational risk is paid more and more attention by regulators and banks’ managements. The paper first discussed the relationship between internal control and operational risk management and used CVaR-POT model to measure operational risk, and then put forward a modified measurement method (to use operational risk assessment results to modify the measurement results of the CVaR-POT model). The paper also analyzed the necessity and rationality of this method. The method takes into consideration the influence of internal control, improves the accuracy and effectiveness of operational risk measurement and save the economic capital for commercial banks, avoiding the drawbacks of using some mainstream models one-sidedly.

Keywords: commercial banks, internal control, operational risk, risk measurement

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Authors: Siriporn Okonogi, Pimpak Phumat, Sakornrat Khongkhunthian

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Piper betle has been extensively reported for various pharmacological effects including antimicrobial activity. 4-Allylpyrocatechol (AC) is a principle active compound found in P. betle. However, AC has a problem of solubility in water. The aims of the present study were to prepare AC loaded polymeric micelles for enhancing its water solubility and to evaluate its anti-biofilm activity against oral phathogenic bacteria. AC was loaded in polymeric micelles (PM) of Pluronic F127 by using thin film hydration method to obtain AC loaded PM (PMAC). The results revealed that AC in the form of PMAC possessed high water solubility. PMAC particles were characterized using a transmission electron microscope and photon correlation spectroscopy. Determination of entrapment efficiency (EE) and loading capacity (LC) of PMAC was done by using high-performance liquid chromatography. The highest EE (86.33 ± 14.27 %) and LC (19.25 ± 3.18 %) of PMAC were found when the weight ratio of polymer to AC was 4 to 1. At this ratio, the particles showed spherical in shape with the size of 38.83 ± 1.36 nm and polydispersity index of 0.28 ± 0.10. Zeta potential of the particles is negative with the value of 16.43 ± 0.55 mV. Crystal violet assay and confocal microscopy were applied to evaluate the effects of PMAC on Streptococcus mutans biofilms using chlorhexidine (CHX) as a positive control. PMAC contained 1.5 mg/mL AC could potentially inhibit (102.01 ± 9.18%) and significantly eradicate (85.05 ± 2.03 %) these biofilms (p < 0.05). Comparison with CHX, PMAC showed slightly similar biofilm inhibition but significantly stronger biofilm eradication (p < 0.05) than CHX. It is concluded that PMAC can enhance water solubility and anti-biofilm activity of AC.

Keywords: pluronic, polymeric micelles, solubility, 4-allylpyrocathecol, Streptococcus mutans, anti-biofilm

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Authors: Abiodun Afolabi, Rufus Adesoji Adedoyin

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This study investigated and compared the effects of gym-based exercise programme (GEBP) and audio-visual guided home-based exercise programme (AVGHBEP) on selected Anthropometric variables (Weight (W), Body Mass Index (BMI), Waist Circumference (WC), Hip Circumference (HC), Thigh Circumference (TC), Waist-Hip-Ratio (WHR), Waist-Height-Ratio (WHtR), Waist-Thigh-Ratio (WTR), Biceps Skinfold Thickness (BSFT), Triceps Skinfold Thickness (TSFT), Suprailliac Skinfold Thickness (SISFT), Subscapular Skinfold Thickness (SSSFT) and Percent Body Fat (PBF)); and Cardiovasular variables (Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP) and Heart Rate (HR)) of overweight and obese students of Federal College of Education (Special), Oyo, Oyo State, Nigeria, with a view to providing information and evidence for GBEP and AVGHBEP in reducing overweight and obesity for promoting cardiovascular fitness. Eighty overweight and obese students (BMI ≥ 25 Kg/m²) were involved in this pretest-posttest quasi experimental study. Participants were randomly assigned into GBEP (n = 40) and AVGBBEP (n = 40) groups. Anthropometric and cardiovascular variables were measured using a weighing scale, height meter, tape measure, skinfold caliper and electronic sphygmomanometer following standard protocols. GBEP and AVGHBEP were implemented following a circuit training (aerobic and resistance training) pattern with a duration of 40-60 minutes, thrice weekly for twelve weeks. GBEP consisted of gymnasium supervised exercise programme while AVGHBEP is a Visual Display guided exercise programme conducted at the home setting. Data were analyzed by Descriptive and Inferential Statistics. The mean ages of the participants were 22.55 ± 2.55 and 23.65 ± 2.89 years for the GBEP group and AVGHBEP group, respectively. Findings showed that in the GBEP group, there were significant reductions in anthropometric variables and adiposity measures of Weight, BMI, BSFT, TSFT, SISFT, SSSFT, WC, HC, TC, WHtR, and PBF at week 12 of the study. Similarly, in the AVGHBEP group, there were significant reductions in Weight, BMI, BSFT, TSFT, SISFT, SSSFT, WC, HC, TC, WHtR and PBF at the 12th week of intervention. Comparison of the effects of GEBP and AVGHBEP on anthropometric variables and measures of adiposity showed that there was no significant difference between the two groups in weight, BMI, BSFT, TSFT, SISFT, SSSFT, WC, HC, TC, WHR, WHtR, WTR and PBF between the two groups at week 12 of the study. Furthermore, findings on the effects of exercise on programmes on cardiovascular variables revealed that significant reductions occurred in SBP in GBEP group and AVGHBEP group respectively. Comparison of the effects of GBEP and AVGHBEP on cardiovascular variables showed that there was no significant difference in SBP, DBP and HR between the two groups at week 12 of the study. It was concluded that the Audio-Visual Guided Home-based Exercise Programme was as effective as the Gym-Based Exercise Programme in causing a significant reduction in anthropometric variables and body fat among college students who are overweight and obese over a period of twelve weeks. Both Gymnasium-Based Exercise Programme and Audio-Visual Guided Home-Based Exercise Programme led to significant reduction in Systolic Blood Pressure over a period of weeks. Audio-Visual Guided Home-Based Exercise Programme can, therefore, be used as an alternative therapy in the non-pharmacological management of people who are overweight and obese.

Keywords: gym-based exercises, audio-visual guided home-based exercises, anthropometric parameters, cardiovascular parameters, overweight students, obese students

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Authors: Vinayaka Gude Divya Sampath

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The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.

Keywords: deep learning, disaster management, flood prediction, urban flooding

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Authors: Bita Payami-Shabestari, Dariush Eslami

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The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory

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Authors: Emery A. Coppola Jr., Suna Cinar, Ferenc Szidarovszky

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Over-pumping of groundwater resources is a serious problem world-wide. In addition to depleting this valuable resource, hydraulically connected sensitive ecological resources like wetlands and surface water bodies are often impacted and even destroyed by over-pumping. Effectively managing groundwater in a way that satisfy human demand while preserving natural resources is a daunting challenge that will only worsen with growing human populations and climate change. As presented in this paper, a numerical flow model developed for a hypothetical but realistic groundwater/surface water system was combined with formal optimization. Response coefficients were used in an optimization management model to maximize groundwater pumping in a complex, multi-layered aquifer system while protecting against groundwater over-draft, streamflow depletion, and wetland impacts. Pumping optimization was performed for different constraint sets that reflect different resource protection preferences, yielding significantly different optimal pumping solutions. A sensitivity analysis on the optimal solutions was performed on select response coefficients to identify differences between wet and dry periods. Stochastic optimization was also performed, where uncertainty associated with changing irrigation demand due to changing weather conditions are accounted for. One of the strengths of this optimization approach is that it can efficiently and accurately identify superior management strategies that minimize risk and adverse environmental impacts associated with groundwater pumping under different hydrologic conditions.

Keywords: numerical groundwater flow modeling, water management optimization, groundwater overdraft, streamflow depletion

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Authors: Donald Kushon, Jyoti Pillai

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Psychogenic Non-epileptic Seizure Disorder (PNES) is a challenging clinical problem for the neurologist. This study explores the benefits of on-site collaboration between psychiatry and neurology in the management of PNES. A 3 month period at a university hospital seizure clinic is described detailing specific management approaches taken as a result of this collaboration. This study describes four areas of interest: (1. After the video EEG results confirm the diagnosis of PNES, the presentation of the diagnosis of PNES to the patient. (2. The identification of co-morbid psychiatric illness (3. Treatment with specific psychotherapeutic interventions (including Cognitive Behavioral Therapy) and psychopharmacologic interventions (primarily SSRIs) and (4. Preliminary treatment outcomes.

Keywords: cognitive behavioral therapy (CBT), psychogenic non-epileptic seizure disorder (PNES), selective serotonin reuptake inhibitors (SSRIs), video electroencephalogram (VEEG)

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Authors: Luciana C. Ramos, Leandro J. Sousa, Antônio Ferreira da Silva, Valéria Gomes Oliveira Falcão, Suzana T. Cunha Lima

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The commercial production of biodiesel using microalgae demands a high-energy input for harvesting biomass, making production economically unfeasible. Methods currently used involve mechanical, chemical, and biological procedures. In this work, a flocculation system is presented as a cost and energy effective process to increase biomass production of Phaeodactylum tricornutum. This diatom is the only species of the genus that present fast growth and lipid accumulation ability that are of great interest for biofuel production. The algae, selected from the Bank of Microalgae, Institute of Biology, Federal University of Bahia (Brazil), have been bred in tubular reactor with photoperiod of 12 h (clear/dark), providing luminance of about 35 μmol photons m^-2s^-1, and temperature of 22 °C. The medium used for growing cells was the Conway medium, with addition of silica. The seaweed growth curve was accompanied by cell count in Neubauer camera and by optical density in spectrophotometer, at 680 nm. The precipitation occurred at the end of the stationary phase of growth, 21 days after inoculation, using two methods: centrifugation at 5000 rpm for 5 min, and electro-flocculation at 19 EPD and 95 W. After precipitation, cells were frozen at -20 °C and, subsequently, lyophilized. Biomass obtained by electro-flocculation was approximately four times greater than the one achieved by centrifugation. The benefits of this method are that no addition of chemical flocculants is necessary and similar cultivation conditions can be used for the biodiesel production and pharmacological purposes. The results may contribute to improve biodiesel production costs using marine microalgae.

Keywords: biomass, diatom, flocculation, microalgae

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Authors: Krishnan Manickavasagam, Manikandan Shanmugam

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Clean and abundant renewable energy sources (RES) such as solar energy is seen as the best solution to replace conventional energy source. Unpredictable power generation is a major issue in the penetration of solar energy, as power generated is governed by the irradiance received. Controlling the power generated from solar PV (SPV) panels to battery and load is a challenging task. In this paper, power flow control from SPV to load and energy storage device (ESD) is controlled by a fuzzy decision support system (FDSS) on the availability of solar irradiation. The results show that FDSS implemented with the energy management system (EMS) is capable of managing power within the area, and if excess power is available, then shared with the neighboring area.

Keywords: renewable energy sources, fuzzy decision support system, solar photovoltaic, energy storage device, energy management system

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Authors: Carly Madge, Melanie Zurba, Ryan Bullock

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The Boreal Forest has experienced some of the most drastic climate change-induced temperature rises in Canada, with average winter temperatures increasing by 3°C since 1948. One of the main concerns of the province of Saskatchewan, and particularly wildfire managers, is the increased risk of wildfires due to climate change. With these concerns in mind Sakaw Askiy Management Inc., a forestry corporation located in Prince Albert, Saskatchewan with operations in the Boreal Forest biome, is developing wildfire risk reduction strategies that are supported by the shareholders of the corporation as well as the stakeholders of the Prince Albert Forest Management Area (which includes citizens, hunters, trappers, cottage owners, and outfitters). In the past, wildfire management strategies implemented through harvesting have been received with skepticism by some community members of Prince Albert. Engagement of the stakeholders of the Prince Albert Management Area through the development of the wildfire risk reduction strategies aims to reduce this skepticism and rebuild some of the trust that has been lost between industry and community. This research project works with the framework of social learning, which is defined as the learning that occurs when individuals come together to form a group with the purpose of understanding environmental challenges and determining appropriate responses to them. The project evaluates the social learning processes that occur through the development of the risk reduction strategies and how the learning has allowed Sakaw to work towards implementing the strategies into their forest harvesting plans. The incorporation of wildfire risk reduction strategies works to increase the adaptive capacity of Sakaw, which in this case refers to the ability to adjust to climate change, moderate potential damages, take advantage of opportunities, and cope with consequences. Using semi-structured interviews and wildfire workshop meetings shareholders and stakeholders shared their knowledge of wildfire, their main wildfire concerns, and changes they would like to see made in the Prince Albert Forest Management Area. Interviews and topics discussed in the workshops were inductively coded for themes related to learning, adaptive capacity, areas of concern, and preferred methods of wildfire risk reduction strategies. Analysis determined that some of the learning that has occurred has resulted through social interactions and the development of networks oriented towards wildfire and wildfire risk reduction strategies. Participants have learned new knowledge and skills regarding wildfire risk reduction. The formation of wildfire networks increases access to information on wildfire and the social capital (trust and strengthened relations) of wildfire personnel. Both factors can be attributed to increases in adaptive capacity. Interview results were shared with the General Manager of Sakaw, where the areas of concern and preferred strategies of wildfire risk reduction will be considered and accounted for in the implementation of new harvesting plans. This research also augments the growing conceptual and empirical evidence of the important role of learning and networks in regional wildfire risk management efforts.

Keywords: adaptive capacity, community-engagement, social learning, wildfire risk reduction

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Authors: Richard I. Licayan, Aisle Janne B. Dagpin, Romeo M. Del Rosario, Nenita D. Palmes

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Hiptage benghalensis, Antigonon leptopus, Macroptillium atropurpureum, and Dioscorea bulbifera L. are herbal weeds that have been used by traditional healers in rural communities in the Philippines as medicine. In this study, the basic pharmacological components of the crude secondary metabolites extracted from the four herbal weeds and their in vitro antioxidant properties was investigated to provide baseline data for the possible development of these metabolites in pharmaceutical products. Qualitative screening of the secondary metabolites showed that alkaloids, tannins, saponins, steroids, and flavonoids were present in their leaf extracts. All of the plant extracts showed varied antioxidant activity. The greatest DPPH radical scavenging activity was observed in H. begnhalensis (84.64%), followed by A. leptopus (68.21%), M. atropurpureum (26.62%), and D. bulbifera L. (19.04%). The FRAP assay revealed that H. benghalensis had the highest antioxidant activity (8.32 mg/g) while ABTS assay showed that M. atropurpureum had the strongest scavenging ability of free radicals (0.0842 mg Trolox/g). The total flavonoid content (TFC) analysis showed that D. bulbifera L. had the highest TFC (420.35 mg quercetin per gram-dried material). The total phenolic content (TPC) of the four herbal weeds showed large variations, between 26.56±0.160 and 55.91±0.087 mg GAE/g dried material. The plant leaf extracts arranged in increasing values of TPC are H. benghalensis (26.565) < A. leptopus (37.29) < D. bulbifera L. (46.81) < M. atropurpureum (55.91). The obtained results may support their use in herbal medicine and as baseline data for the development of new drugs and standardized phytomedicines.

Keywords: antioxidant properties, total flavonoids, total phenolics, creeping herbal weeds

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Authors: Inyoung Park, Youngjoo Woo, Euiseong Seo

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With the advent of WebGL, Web apps are now able to provide high quality graphics by utilizing the underlying graphic processing units (GPUs). Despite that the Web apps are becoming common and popular, the current power management schemes, which were devised for the conventional native applications, are suboptimal for Web apps because of the additional layer, the Web browser, between OS and application. The Web browser running on a CPU issues GL commands, which are for rendering images to be displayed by the Web app currently running, to the GPU and the GPU processes them. The size and number of issued GL commands determine the processing load of the GPU. While the GPU is processing the GL commands, CPU simultaneously executes the other compute intensive threads. The actual user experience will be determined by either CPU processing or GPU processing depending on which of the two is the more demanded resource. For example, when the GPU work queue is saturated by the outstanding commands, lowering the performance level of the CPU does not affect the user experience because it is already deteriorated by the retarded execution of GPU commands. Consequently, it would be desirable to lower CPU or GPU performance level to save energy when the other resource is saturated and becomes a bottleneck in the execution flow. Based on this observation, we propose a power management scheme that is specialized for the Web app runtime environment. This approach incurs two technical challenges; identification of the bottleneck resource and determination of the appropriate performance level for unsaturated resource. The proposed power management scheme uses the CPU utilization level of the Window Manager to tell which one is the bottleneck if exists. The Window Manager draws the final screen using the processed results delivered from the GPU. Thus, the Window Manager is on the critical path that determines the quality of user experience and purely executed by the CPU. The proposed scheme uses the weighted average of the Window Manager utilization to prevent excessive sensitivity and fluctuation. We classified Web apps into three categories using the analysis results that measure frame-per-second (FPS) changes under diverse CPU/GPU clock combinations. The results showed that the capability of the CPU decides user experience when the Window Manager utilization is above 90% and consequently, the proposed scheme decreases the performance level of CPU by one step. On the contrary, when its utilization is less than 60%, the bottleneck usually lies in the GPU and it is desirable to decrease the performance of GPU. Even the processing unit that is not on critical path, excessive performance drop can occur and that may adversely affect the user experience. Therefore, our scheme lowers the frequency gradually, until it finds an appropriate level by periodically checking the CPU utilization. The proposed scheme reduced the energy consumption by 10.34% on average in comparison to the conventional Linux kernel, and it worsened their FPS by 1.07% only on average.

Keywords: interactive applications, power management, QoS, Web apps, WebGL

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Authors: Ali Mohaghar, Iman Ghasemian Sahebi, Alireza Arab

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In the last decades, increasing in human and natural disaster occurrence had very irreparable effects on human life. Hence, one of the important issues in humanitarian supply chain management is identifying and prioritizing the different risks and finding suitable solutions for encountering them at the time of disaster occurrence. This study is an attempt to provide a comprehensive review of humanitarian supply chain risks in a case study of Tehran Red Crescent Societies. For this purpose, Best-Worst method (BWM) has been used for analyzing the risks of the humanitarian supply chain. 22 risks of the humanitarian supply chain were identified based on the literature and interviews with four experts. According to BWM method, the importance of each risk was calculated. The findings showed that culture contexts, little awareness of people, and poor education system are the most important humanitarian supply chain risks. This research provides a useful guideline for managers so that they can benefit from the results to prioritize their solutions.

Keywords: Best-Worst Method, humanitarian logistics, humanitarian supply chain, risk management

Procedia PDF Downloads 310

Authors: Subhasree Majumdar, Sovan Dey, Sayari Mukherjee, Sourav Dutta, Dalia Dasgupta Mandal

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Bacterial isolates from Planococcus genus are known for the production of yellowish orange pigment that belongs to the carotenoid family. These pigments are of immense pharmacological importance as antioxidant, anticancer, eye and liver protective agent, etc. The production of this pigment in a cost effective manner is a challenging task. The present study explored paper mill sludge (PMS), a solid lignocellulosic waste generated in large quantities from pulp and paper mill industry as a substrate for carotenoid pigment production by Planococcus sp. TRC1. PMS was compared in terms of efficacy with sugarcane bagasse, which is a highly explored substrate for valuable product generation via solid state fermentation. The results showed that both the biomasses yielded the highest carotenoid during 48 hours of incubation, 31.6 mg/gm and 42.1 mg/gm for PMS and bagasse respectively. Compositional alterations of both the biomasses showed reduction in lignin, hemicellulose and cellulose content by 41%, 15%, 1% for PMS and 38%, 25% and 6% for sugarcane bagasse after 72 hours of incubation. Structural changes in the biomasses were examined by FT-IR, FESEM, and XRD which further confirmed modification of solid biomasses by bacterial isolate. This study revealed the potential of PMS to act as cheap substrate for carotenoid pigment production by Planococcus sp. TRC1, as it showed a significant production in comparison to sugarcane bagasse which gave only 1.3 fold higher production than PMS. Delignification of PMS by TRC1 during pigment production is another important finding for the reuse of this waste from the paper industry.

Keywords: carotenoid, lignocellulosic, paper mill sludge, Planococcus sp. TRC1, solid state fermentation, sugarcane bagasse

Procedia PDF Downloads 233

Authors: Innocent Pangapanga, Eric Mungatana

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Tropical cyclones–related floods (TCRFs) in Malawi have devastating effects on smallholder agriculture, thereby threatening the food security agenda, which is already constrained by poor agricultural innovations, low use of improved varieties, and unaffordable inorganic fertilizers, and fragmenting landholding sizes. Accordingly, households have engineered and indigenously implemented sustainable landscape management (SLM) innovations to contain the adverse effects of TCRFs on farm productivity. This study, therefore, interrogated the efficacy of SLM adoption on farm productivity under varying TCRFs, while controlling for the potential selection bias and unobservable heterogeneity through the application of the Endogenous Switching Regression Model. In this study, we further investigated factors driving SLM adoption. Substantively, we found TCRFs reducing farm productivity by 31 percent, on the one hand, and influencing the adoption of SLM innovations by 27 percent, on the other hand. The study also observed that households that interacted SLM with TCRFs were more likely to enhance farm productivity by 24 percent than their counterparts. Interestingly, the study results further demonstrated that multiple adoptions of SLM-related innovations, including intercropping, agroforestry, and organic manure, enhanced farm productivity by 126 percent, suggesting promoting SLM adoption as a package to appropriately inform existing sustainable development goals’ agricultural productivity initiatives under intensifying TCRFs in the country.

Keywords: tropical cyclones–related floods, sustainable landscape management innovations, farm productivity, endogeneity, endogenous switching regression model, panel data, smallholder agriculture

Procedia PDF Downloads 115

Authors: Lucie Jirotková, Daniel Macek, Andrea Palazzo, Veronika Malinová

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Currently, the implementation of 3D models in the construction industry is gaining popularity. Countries around the world are developing their own modelling standards and implement the use of 3D models into their individual permitting processes. Another theme that needs to be addressed are public building spaces and their subsequent maintenance, where the usage of BIM methodology is directly offered. The significant benefit of the implementation of Building Information Management is the information transfer. The 3D model contains not only the spatial representation of the item shapes but also various parameters that are assigned to the individual elements, which are easily traceable, mainly because they are all stored in one place in the BIM model. However, it is important to keep the data in the models up to date to achieve useability of the model throughout the life cycle of the building. It is now becoming standard practice to use BIM models in the construction of buildings, however, the building environment is very often neglected. Especially in large-scale development projects, the public space of buildings is often forwarded to municipalities, which obtains the ownership and are in charge of its maintenance. A 3D model of the building surroundings would include both the above-ground visible elements of the development as well as the underground parts, such as the technological facilities of water features, electricity lines for public lighting, etc. The paper shows the possibilities of a model in the field of information for the handover of premises, the following maintenance and decision making. The attributes and spatial representation of the individual elements make the model a reliable foundation for the creation of "Smart Cities". The paper analyses the current use of the BIM methodology and presents the state-of-the-art possibilities of development.

Keywords: BIM model, urban space, BIM methodology, facility management

Procedia PDF Downloads 123

Authors: Mahboubeh Varmaziar

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Depression is a significant public health concern affecting people of all ages and genders. Physical activity has been shown to have a positive effect on mental health, particularly in alleviating symptoms of depression. This study aims to explore the impact of continuous exercise on depression levels among young female athletes in Hamadan Province, Iran. In this randomized controlled trial, 72 women aged 20 to 35 years attending sports centers in Hamadan Province were selected through convenient sampling and randomly assigned to either the control or experimental group. The experimental group participated in a continuous exercise program consisting of 20 sessions over six weeks, with each session lasting 30 minutes. In contrast, the control group maintained their usual daily activities at the sports center. Both groups completed demographic and Beck Depression Inventory questionnaires. Data were analyzed using descriptive and inferential statistics, including two-way ANOVA. The results of the two-way ANOVA, after controlling for the pre-test effect, revealed a significant difference in the mean depression scores between the control and experimental groups (p < 0.001). This suggests that the continuous exercise program significantly reduced depression levels in the young female athletes. The findings suggest that continuous exercise is an effective non-pharmacological intervention for reducing depression in young female athletes. Incorporating regular physical activity into treatment plans may serve as a complementary therapy alongside conventional treatments, offering a low-risk and beneficial approach to managing depression.

Keywords: depression, exercise, female athletes, yong women

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Authors: Mohammad Amin Hamedirad, Seyed Javad Vaziri Kang Olyaei

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Project planning and control are one of the most critical issues in the management of construction projects. Traditional methods of project planning and control, such as the critical path method or Gantt chart, are not widely used for planning projects with discrete and repetitive activities, and one of the problems of project managers is planning the implementation process and optimal allocation of its resources. Massive concreting projects is also a project with discrete and repetitive activities. This study uses the concept of simulating discrete events to manage resources, which includes finding the optimal number of resources considering various limitations such as limitations of machinery, equipment, human resources and even technical, time and implementation limitations using analysis of resource consumption rate, project completion time and critical points analysis of the implementation process. For this purpose, the concept of discrete-event simulation has been used to model different stages of implementation. After reviewing the various scenarios, the optimal number of allocations for each resource is finally determined to reach the maximum utilization rate and also to reduce the project completion time or reduce its cost according to the existing constraints. The results showed that with the optimal allocation of resources, the project completion time could be reduced by 90%, and the resulting costs can be reduced by up to 49%. Thus, allocating the optimal number of project resources using this method will reduce its time and cost.

Keywords: simulation, massive concreting, discrete event simulation, resource management

Procedia PDF Downloads 147