Search results for: complex pain

Authors: Trisha S. Malhotra

Abstract:

While there exist frameworks to study the induction, manifestation, duration and general nature of emotions like shame, guilt, embarrassment and pride in humans, the same cannot be said for other species. This is because such 'complex' emotions have situational inductions and manifestations that supposedly vary due to differences between and within different species' ethology. This paper looks at the socio-adaptive functions of guilt to posit why this emotion might be observed across varying species. Primarily, the experimental paradigm of guilt-assessment in domesticated dogs is critiqued for lack of ethological consideration in its measurement and analysis. It is argued that a paradigm for guilt-assessment should measure the species-specific prosocial approach behavior instead of the immediate feedback of the 'guilty'. Finally, it is asserted that the origin of guilt is subjective and if it must be studied across a plethora of species, its definition must be tailored to fit accordingly.

Keywords: guilt, assessment, dogs, prosocial approach behavior, empathy, species, ethology

Procedia PDF Downloads 308

Authors: Mikhail Zimin, Svetlana Zimina, Maxim Zimin

Abstract:

Without question, the basic method of prevention of human and material losses is the provision for adequate strength of constructions. At the same time, seismic load has a stochastic character. So, at all times, there is little danger of earthquake forces exceeding the selected design load. This risk is very low, but the consequences of such events may be extremely serious. Very dangerous are also occasional mistakes in seismic zoning, soil conditions changing before temblors, and failure to take into account hazardous natural phenomena caused by earthquakes. Besides, it is known that temblors detrimentally affect the environmental situation in regions where they occur, resulting in panic and worsening various disease courses. It may lead to mistakes of personnel of hazardous production facilities like the production and distribution of gas and oil, which may provoke severe accidents. In addition, gas and oil pipelines often have long mileage and cross many perilous zones by contrast with buildings. This situation increases the risk of heavy accidents. In such cases, complex monitoring of potential earthquake localities would be relevant. Even though the number of successful real-time forecasts of earthquakes is not great, it is well in excess, such as may be under random guessing. Experimental performed time-lapse study and analysis consist of searching seismic, biological, meteorological, and light earthquake precursors, processing such data with the help of fuzzy sets, collecting weather information, utilizing a database of terrain, and computing risk of slope processes under the temblor in a given setting. Works were done in a real-time environment and broadly acceptable results took place. Observations from already in-place seismic recording systems are used. Furthermore, a look back study of precursors of known earthquakes is done. Situations before Ashkhabad, Tashkent, and Haicheng seismic events are analyzed. Fairish findings are obtained. Results of earthquake forecasts can be used for predicting dangerous natural phenomena caused by temblors such as avalanches and mudslides. They may also be utilized for prophylaxis of some diseases and their complications. Relevant software is worked out too. It should be emphasized that such control does not require serious financial expenses and can be performed by a small group of professionals. Thus, complex monitoring of potential earthquake localities, including short-term earthquake forecasts and analysis of possible hazardous consequences of temblors, may further the safety of pipeline facilities.

Keywords: risk, earthquake, monitoring, forecast, precursor

Procedia PDF Downloads 23

Authors: O. I. Nkwonta, B. Dzwairo, J. Adeyemo, A. Jaiyola, N. Sawyerr, F. Otieno

Abstract:

The effective management of water resources is of great importance to ensure the supply of water resources to support changing water requirements over a selected planning horizon and in a sustainable and cost-effective way. Essentially, the purpose of the water resources planning process is to balance the available water resources in a system with the water requirements and losses to which the system is subjected. In such situations, Water resources yield and planning model can be used to solve those difficulties. It has an advantage over other models by managing model runs, developing a representative system network, modelling incremental sub-catchments, creating a variety of standard system features, special modelling features, and run result output options.

Keywords: complex, water resources, planning, cost effective and management

Procedia PDF Downloads 573

Authors: Shuhua Lai, Kairui Chen

Abstract:

In this paper, we present a fast and efficient mesh coarsening algorithm for 3D triangular meshes. Theis approach can be applied to very complex 3D meshes of arbitrary topology and with millions of vertices. The algorithm is based on the clustering of the input mesh elements, which divides the faces of an input mesh into a given number of clusters for clustering purpose by approximating the Centroidal Voronoi Tessellation of the input mesh. Once a clustering is achieved, it provides us an efficient way to construct uniform tessellations, and therefore leads to good coarsening of polygonal meshes. With proliferation of 3D scanners, this coarsening algorithm is particularly useful for reverse engineering applications of 3D models, which in many cases are dense, non-uniform, irregular and arbitrary topology. Examples demonstrating effectiveness of the new algorithm are also included in the paper.

Keywords: coarsening, mesh clustering, shape approximation, mesh simplification

Procedia PDF Downloads 380

Authors: Pin-Ling Yin, Dung-Ying Lin

Abstract:

Satellites play an important role in our daily lives, from monitoring the Earth's environment and providing real-time disaster imagery to predicting extreme weather events. As technology advances and demands increase, the tasks undertaken by satellites have become increasingly complex, with more stringent resource management requirements. A common challenge in satellite mission scheduling is the limited availability of resources, including onboard memory, ground station accessibility, and satellite power. In this context, efficiently scheduling and managing the increasingly complex satellite missions under constrained resources has become a critical issue that needs to be addressed. The core of Satellite Onboard Activity Planning (SOAP) lies in optimizing the scheduling of the received tasks, arranging them on a timeline to form an executable onboard mission plan. This study aims to develop an optimization model that considers the various constraints involved in satellite mission scheduling, such as the non-overlapping execution periods for certain types of tasks, the requirement that tasks must fall within the contact range of specified types of ground stations during their execution, onboard memory capacity limits, and the collaborative constraints between different types of tasks. Specifically, this research constructs a mixed-integer programming mathematical model and solves it with a commercial optimization package. Simultaneously, as the problem size increases, the problem becomes more difficult to solve. Therefore, in this study, a heuristic algorithm has been developed to address the challenges of using commercial optimization package as the scale increases. The goal is to effectively plan satellite missions, maximizing the total number of executable tasks while considering task priorities and ensuring that tasks can be completed as early as possible without violating feasibility constraints. To verify the feasibility and effectiveness of the algorithm, test instances of various sizes were generated, and the results were validated through feedback from on-site users and compared against solutions obtained from a commercial optimization package. Numerical results show that the algorithm performs well under various scenarios, consistently meeting user requirements. The satellite mission scheduling algorithm proposed in this study can be flexibly extended to different types of satellite mission demands, achieving optimal resource allocation and enhancing the efficiency and effectiveness of satellite mission execution.

Keywords: mixed-integer programming, meta-heuristics, optimization, resource management, satellite mission scheduling

Procedia PDF Downloads 25

Authors: Maryam Firouzmandi, Moosa Miri

Abstract:

Smile is considered to be one of the most effective methods of influencing people. Increasing numbers of patients are requesting cosmetic dental procedures to achieve the perfect smile. Based on the patient’s age, oral and facial characteristics, and the dentist’s expertise, different concepts of treatment would be available. Orthodontics is the most conservative and the ideal treatment alternative for crowded anterior teeth; however, it may be rejected by patients due to occupational limitations of time, physical discomfort including pain and functional limitations, psychological discomfort, and appearance during treatment. In addition, orthodontic treatment will not resolve deficits of contour and color of the anterior teeth. In consequence, patients may demand restorative techniques to resolve their anterior mal-alignment instead, often called "instant orthodontics". Following its introduction, however, adhesive dentistry has suffered at times from overuse. Creating short-term attractive smiles at the expense of long-term dental health and optimal tooth biomechanics by using cosmetic techniques should not be considered an ethical approach. The objective of this narrative review was to investigate the literature for guidelines with regard to decision making and treatment planning for anterior tooth mal-alignment. In this regard, indications of orthodontic, restorative, combination of both treatments, and adjunctive periodontal surgery were discussed in clinical cases to achieve a proportional smile. Restorative modalities would include disking, cosmetic contouring, veneers, and crowns and were compared with limited or comprehensive orthodontic options. A rapid review was also presented on pros and cons of snap on smile to mask malalignments. Diagnostic tools such as mock up, wax up, and digital smile design were also considered to achieve more conservative and functional treatments with respect to biologic factors.

Keywords: crowding, misalignment, veneer, crown, orthodontics

Procedia PDF Downloads 116

Authors: C. Mayr, J. Periya, A. Kariminezhad

Abstract:

In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

Procedia PDF Downloads 246

Authors: Yifan Dong, Xincheng Pu

Abstract:

Rural settlements originate from the accumulation of residential building elements, and their agglomeration forms the settlement pattern and defines the relationship between the settlement and the inside and outside. The settlement boundary is an important part of the settlement pattern. Compared with the simplification of the urban settlement boundary, the settlement of the country is more complex, fuzzy and uncertain, and then presents a rich and diverse boundary morphological phenomenon. In this paper, China traditional rural settlements plane boundary as the research object, using fractal theory and fractal dimension method, quantitative analysis of planar shape boundary settlement, and expounds the research for the architectural design, ancient architecture protection and renewal and development and the significance of the protection of settlements.

Keywords: rural settlement, border, fractal, quantification

Procedia PDF Downloads 249

Authors: Yaser E. Hawas, Md. Didarul Alam

Abstract:

Rollover crashes are complex events entailing interactions of driver, road, vehicle, and environmental factors. The primary objective of this paper is to present an empirical approach that can be used to characterise the rollover crashes and to identify some of the important factors that may lead to rollovers. Among the studied factors are the vehicle types and the rollover occurrence rate after hitting various barrier types. The carried analysis indicated that 71% of the rollover crashes occurred after impact and the type of rollover initiation is “trip/turn over” (nearly 50%). It was also found that light trucks (LTVs) vehicles are more likely to rollover than the sedan vehicles. Barrier impacts are associated with increased incidence of rollover.

Keywords: empirical, hitting barrier, in-depth crash investigation, rollover, severe crash

Procedia PDF Downloads 372

Authors: T. Alghamdi, G. Alaghband

Abstract:

In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution Neural Network, Edges, Face Recognition , Support Vector Machine.

Procedia PDF Downloads 154

Authors: Parastoo Parhizkar, Jaber Yaghini, Omid Fakheran

Abstract:

Background: Third molar surgery is often associated with postoperative problems which cause serious impediments on daily activities and quality of life. Steroidal anti-inflammatory drugs may decrease these common post-operative complications. The purpose of this review is evaluating the available evidence regarding the efficacy of corticosteroids used as adjunctive therapy for patients undergoing third molar surgery. Methods: PubMed, Google scholar, Scopus, web of science, clinicaltrials.gov, scirus.com, Cochrane central register for controlled trials, LILACS, OpenGrey, centerwatch, isrctn, who.int and ebsco were searched without restrictions regarding the year of publication. Randomized clinical trials assessing patient-reported outcomes in patients undergoing surgical therapy, were eligible for inclusion. Study quality was assessed using the CONSORT-checklist. No meta-analysis was performed. Results: A total of twelve Randomized Clinical Trials were included in this study. Methylprednisolone and Dexamethasone may decrease postoperative side effects such as pain, trismus and edema. Based on the results both of them could improve patients’ satisfaction, and there is no significant difference between these two types of corticosteroids regarding the patient centered outcomes (p > 0.05). Intralesional and intravenous injection of Dexamethasone showed an equivalent result, with statistically significant better results (P < 0.05) in comparison with the oral treatment. Conclusion: various types of corticosteroids can enhance the patient’s satisfaction following third molar surgery. However, there is no significant difference between Dexamethasone, Prednisolone and Methylprednisolone groups in this regard. Comparing the various administration routs, local injection of Dexamethasone is quite simple, painless and cost-effective adjunctive therapy with better drug efficacy.

Keywords: third molar surgery, corticosteroids, patient-reported outcomes, health related quality of life

Procedia PDF Downloads 202

Authors: Mualla McManus, Jenna Luche Thaye

Abstract:

World Health Organisation International Classification of Disease codes were created to define disease including infections in order to guide and educate diagnosticians. Most infectious diseases such as syphilis are clearly defined by their ICD 10 codes and aid/help to educate the clinicians in syphilis diagnosis and treatment globally. However, current ICD 10 codes for relapsing fever Borreliosis and Lyme disease are less clearly defined and can impede appropriate diagnosis especially if the clinician is not familiar with the symptoms of these infectious diseases. This is despite substantial number of scientific articles published in peer-reviewed journals about relapsing fever and Lyme disease. In the USA there are estimated 380,000 people annually contacting Lyme disease, more cases than breast cancer and 6x HIV/AIDS cases. This represents estimated 0.09% of the USA population. If extrapolated to the global population (7billion), 0.09% equates to 63 million people contracting relapsing fever or Lyme disease. In many regions, the rate of contracting some form of infection from tick bite may be even higher. Without accurate and appropriate diagnostic codes, physicians are impeded in their ability to properly care for their patients, leaving those patients invisible and marginalized within the medical system and to those guiding public policy. This results in great personal hardship, pain, disability, and expense. This unnecessarily burdens health care systems, governments, families, and society as a whole. With accurate diagnostic codes in place, robust data can guide medical and public health research, health policy, track mortality and save health care dollars. Better defined ICD codes are the way forward in educating the diagnosticians about relapsing fever and Lyme diseases.

Keywords: WHO ICD codes, relapsing fever, Lyme diseases, World Health Organisation

Procedia PDF Downloads 193

Authors: Abhishek Pandey

Abstract:

Ibuprofen and Acetaminophen is widely used as prescription & non-prescription medicine. Ibuprofen mainly used in the treatment of mild to moderate pain related to headache, migraine, postoperative condition and in the management of spondylitis, osteoarthritis and rheumatoid arthritis. Acetaminophen is used as an analgesic and antipyretic drug. Ibuprofen having high tendency of sticking to punches of tablet punching machine while Acetaminophen is not ordinarily compressible to tablet formulation because Acetaminophen crystals are very hard and brittle in nature and fracture very easily when compressed producing capping and laminating tablet defects therefore wet granulation method is used to make them compressible. The aim of study was to prepare Ibuprofen and Acetaminophen tablets by direct compression and top spray granulation technique. In this Investigation tablets were prepared by using directly compressible grade excipients. Dibasic calcium phosphate, lactose anhydrous (DCL21), microcrystalline cellulose (Avicel PH 101). In order to obtain best or optimized formulation, nine different formulations were generated among them batch F7, F8, F9 shows good results and within the acceptable limit. Formulation (F7) selected as optimize product on the basis of dissolution study. Furtherly, directly compressible granules of both drugs were prepared by using top spray granulation technique in fluidized bed processor equipment and compressed .In order to obtain best product process optimization was carried out by performing four trials in which various parameters like inlet air temperature, spray rate, peristaltic pump rpm, % LOD, properties of granules, blending time and hardness were optimized. Batch T3 coined as optimized batch on the basis physical & chemical evaluation. Finally formulations prepared by both techniques were compared.

Keywords: direct compression, top spray granulation, process optimization, blending time

Procedia PDF Downloads 363

Authors: Nuruddeen Usman, Ahmad Muhammad Ibrahim

Abstract:

Management of construction logistics at construction sites becomes increasingly complex with rising construction volume, which made it relatively inefficient in the developing nations even with the technological advancement. The objective of this research is to conceptually synthesise the approaches and challenges befall in the course of construction logistic management, with the aim to proffer possible solution to it. Therefore, this study appraised the glitches associated with both conventional and technological methods of construction logistic management that result in its inefficiency. Thus, this investigation found that, both conventional and the technological issues were due to certain obstacles that affect the construction logistic management which resulted into delays, accidents, fraudulent activities, time and cost overrun. Therefore, this study has developed a framework that might bring a lasting solution to the challenges of construction logistic management.

Keywords: construction, conventional, logistic, technological

Procedia PDF Downloads 554

Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

Procedia PDF Downloads 83

Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

Procedia PDF Downloads 95

Authors: G. Khamooshian

Abstract:

One of the main points of application of the mechanisms of the series and parallel is the subject of managing them. The control of this mechanism and similar mechanisms is one that has always been the intention of the scholars. On the other hand, modeling the behavior of the system is difficult due to the large number of its parameters, and it leads to complex equations that are difficult to solve and eventually difficult to control. In this paper, a six-linkage robot has been presented that could be used in different areas such as medical robots. Using these robots needs a robust control. In this paper, the system equations are first found, and then the system conversion function is written. A new controller has been designed for this robot which could be used in other parallel robots and could be very useful. Parallel robots are so important in robotics because of their stability, so methods for control of them are important and the robust controller, especially in parallel robots, makes a sense.

Keywords: 3-RRS, 6 linkage, parallel robot, control

Procedia PDF Downloads 159

Authors: Thohidul Islam, Md. Hamidul Haque, Robin Kumar Biswas

Abstract:

Floods are one of the deadliest natural disasters which are very complex to model; however, machine learning is opening the door for more reliable and accurate flood prediction. In this research, a multilayer perceptron neural network (MLP) is developed to model the rainfall-water level relation, in a subtropical monsoon climatic region of the Bangladesh-India border. Our experiments show promising empirical results to forecast the water level for 1 day lead time. Our best performing MLP model achieves 98.7% coefficient of determination with lower model complexity which surpasses previously reported results on similar forecasting problems.

Keywords: flood forecasting, machine learning, multilayer perceptron network, regression

Procedia PDF Downloads 172

Authors: Ali Safdari-Vaighani

Abstract:

Pricing financial contracts on several underlying assets received more and more interest as a demand for complex derivatives. The option pricing under asset price involving jump diffusion processes leads to the partial integral differential equation (PIDEs), which is an extension of the Black-Scholes PDE with a new integral term. The aim of this paper is to show how basket option prices in the jump diffusion models, mainly on the Merton model, can be computed using RBF based approximation methods. For a test problem, the RBF-PU method is applied for numerical solution of partial integral differential equation arising from the two-asset European vanilla put options. The numerical result shows the accuracy and efficiency of the presented method.

Keywords: basket option, jump diffusion, ‎radial basis function, RBF-PUM

Procedia PDF Downloads 354

Authors: Flavio Campos

Abstract:

This paper describes an implementation of a STEM curriculum program using robotics as a technological resource at a private school in Brazil. Emphasized the pedagogic and didactic aspects and brings a discussion about STEM curriculum and the perspective of using robotics and the relation between curriculum, science and technologies into the learning process. The results indicate that STEM curriculum integration with robotics as a technological resource in K-12 students learning process has complex aspects, such as relation between time/space, the development of educators and the relation between robotics and other subjects. Therefore, the comprehension of these aspects could indicate some steps that we should consider when integrating STEM basis and robotics into curriculum, which can improve education for science and technology significantly.

Keywords: STEM curriculum, educational robotics, constructionist approach, education and technology

Procedia PDF Downloads 342

Authors: Andrés Gomez-Casseres, Rubén Contreras

Abstract:

In this paper, a bidirectional boost converter operated in Discontinuous Conduction Mode (DCM) is presented as a suitable power conditioning circuit for tuning of kinetic energy harvesters without the need of a battery. A nonlinear control scheme, composed by two linear controllers, is used to control the average value of the input current, enabling the synthesization of complex loads. The converter, along with the control system, is validated through SPICE simulations using the LTspice tool. The converter model and the controller transfer functions are derived. From the simulation results, it was found that the input current distortion increases with the introduced phase shift and that, such distortion, is almost entirely present at the zero-crossing point of the input voltage.

Keywords: average current control, boost converter, electrical tuning, energy harvesting

Procedia PDF Downloads 762

Authors: Olga Blasco-Blasco, Vicente Liern

Abstract:

The development of tourism since the mid-20th century has raised problems of overcrowding, indiscriminate construction in seaside areas and gentrification. Increasingly, the World Tourism Organisation and public institutions are promoting policies that encourage sustainability. From the perspective of sustainability, three types of tourism can be established: traditional tourism, sustainable tourism and sustainable impact tourism. Measuring sustainability is complex due to its multiple dimensions of different relative importance and diversity in nature. In order to try to answer this problem and to identify the benefits of applying policies that promote sustainable tourism, a decision-making analysis will be carried out through the application of a multicriteria analysis method. The proposal is applied to hotel reservations and to the evaluation and management of tourism sustainability in the Spanish Autonomous Communities.

Keywords: sustainable tourism, multicriteria analysis, flexible optimization, composite indicators

Procedia PDF Downloads 311

Authors: Hushyar Azari

Abstract:

Aim and background: Deep brain stimulation (DBS) is regarded as an important therapeutic choice for Parkinson's disease (PD). The two most common targets for DBS are the subthalamic nucleus (STN) and globus pallidus (GPi). This review was conducted to compare the clinical effectiveness of these two targets. Methods: A systematic literature search in electronic databases: Embase, Cochrane Library and PubMed were restricted to English language publications 2010 to 2021. Specified MeSH terms were searched in all databases. Studies which evaluated the Unified Parkinson's Disease Rating Scale (UPDRS) III were selected by meeting the following criteria: (1) compared both GPi and STN DBS; (2) had at least three months follow-up period; (3)at least five participants in each group; (4)conducted after 2010. Study quality assessment was performed using the Modified Jadad Scale. Results: 3577 potentially relevant articles were identified, of these, 3569 were excluded based on title and abstract, duplicate and unsuitable article removal. Eight articles satisfied the inclusion criteria and were scrutinized (458 PD patients). According to Modified Jadad Scale, the majority of included studies had low evidence quality which was a limitation of this review. 5 studies reported no statistically significant between-group difference for improvements in UPDRS ш scores. At the same time, there were some results in terms of pain, action tremor, rigidity, and urinary symptoms, which indicated that STN DBS might be a better choice. Regarding the adverse effects, GPi was superior. Conclusion: It is clear that other larger randomized clinical trials with longer follow-up periods and control groups are needed to decide which target is more efficient for deep brain stimulation in Parkinson’s disease and imposes fewer adverse effects on the patients. Meanwhile, STN seems more reasonable according to the results of this systematic review.

Keywords: brain stimulation, globus pallidus, Parkinson's disease, subthalamic nucleus

Procedia PDF Downloads 179

Authors: Mary Gouva, Elena Dragioti, Evangelia Kotrsotsiou

Abstract:

Family identification has the potential to play a very decisive role in psychopathology. In this study we aimed to investigate the impact of family identifications on female psychopathology. A community sample of 101 women (mean age 20.81 years, SD = 0.91 ranged 20-25) participated to the present study. The girls completed a) the Symptom Check-List Revised (SCL-90) and b) questionnaire concerning socio-demographic information and questions for family identifications. The majority of women reported that they matched to the father in terms of identifications (47.1%). Age and birth order were not contributed on family identifications (F(5) =2.188, p=.062 and F(3)=1.244, p=.299 respectively). Multivariate analysis by using MANCOVA found statistical significant associations between family identifications and domains of psychopathology as provided by SCL-90 (P<05). Our results highlight the role of identifications especially on father and female psychopathology as well as replicate the Freudian perception about the female Oedipus complex.

Keywords: family identification, psychoanalysis, psychopathology, women

Procedia PDF Downloads 324

Authors: Sven Tackenberg, Sönke Duckwitz, Andreas Petz, Christopher M. Schlick

Abstract:

This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem (RCPSP) to apply it to complex maintenance problems. The problem is to assign technicians to a team which has to process several tasks with multi-level skill requirements during a work shift. Here, several alternative activities for a task allow both, the temporal shift of activities or the reallocation of technicians and tools. As a result, switches from one valid work process variant to another can be considered and may be selected by the developed evolutionary algorithm based on the present skill level of technicians or the available tools. An additional complication of the observed scheduling problem is that the locations of the construction sites are only temporarily accessible during a day. Due to intensive rail traffic, the available time slots for maintenance and repair works are extremely short and are often distributed throughout the day. To identify efficient working periods, a first concept of a Bayesian network is introduced and is integrated into the extended RCPSP with pre-emptive and non-pre-emptive tasks. Thereby, the Bayesian network is used to calculate the probability of a maintenance task to be processed during a specific period of the shift. Focusing on the domain of maintenance of the railway infrastructure in metropolitan areas as the most unproductive implementation process at construction site, the paper illustrates how the extended RCPSP can be applied for maintenance planning support. A multi-criteria evolutionary algorithm with a problem representation is introduced which is capable of revising technician-task allocations, whereas the duration of the task may be stochastic. The approach uses a novel activity list representation to ensure easily describable and modifiable elements which can be converted into detailed shift schedules. Thereby, the main objective is to develop a shift plan which maximizes the utilization of each technician due to a minimization of the waiting times caused by rail traffic. The results of the already implemented core algorithm illustrate a fast convergence towards an optimal team composition for a shift, an efficient sequence of tasks and a high probability of the subsequent implementation due to the stochastic durations of the tasks. In the paper, the algorithm for the extended RCPSP is analyzed in experimental evaluation using real-world example problems with various size, resource complexity, tightness and so forth.

Keywords: maintenance management, scheduling, resource constrained project scheduling problem, genetic algorithms

Procedia PDF Downloads 231

Authors: Agostinho Antunes

Abstract:

The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: comparative genomics, adaptive evolution, bioinformatics, phylogenetics, genome mining

Procedia PDF Downloads 533

Authors: Alakija Temitope Olufunmilayo, Akinyemi, Yagba Joy

Abstract:

Hepatitis is the inflammation of the liver tissue that can cause whiteness of the eyes (Jaundice), lack of appetite, vomiting, tiredness, abdominal pain, diarrhea. Hepatitis is acute if it resolves within 6 months and chronic if it last longer than 6 months. Acute hepatitis can resolve on its own, lead to chronic hepatitis or rarely result in acute liver failure. Chronic hepatitis may lead to scarring of the liver (Cirrhosis), liver failure and liver cancer. Modelling Hepatitis B may become necessary in order to reduce its spread. So, dynamic SIR model can be used. This model consists of a system of three coupled non-linear ordinary differential equation which does not have an explicit formula solution. It is an epidemiological model used to predict the dynamics of infectious disease by categorizing the population into three possible compartments. In this study, a five-compartment dynamic model of Hepatitis B disease was proposed and developed by adding control measure of sensitizing the public called awareness. All the mathematical and statistical formulation of the model, especially the general equilibrium of the model, was derived, including the nonlinear least square estimators. The initial parameters of the model were derived using nonlinear least square embedded in R code. The result study shows that the proportion of Hepatitis B patient in the study population is 1.4 per 1,000,000 populations. The estimated Hepatitis B induced death rate is 0.0108, meaning that 1.08% of the infected individuals die of the disease. The reproduction number of Hepatitis B diseases in Nigeria is 6.0, meaning that one individual can infect more than 6.0 people. The effect of sensitizing the public on the basic reproduction number is significant as the reproduction number is reduced. The study therefore recommends that programme should be designed by government and non-governmental organization to sensitize the entire Nigeria population in order to reduce cases of Hepatitis B disease among the citizens.

Keywords: hepatitis B, modelling, non-linear ordinary differential equation, sihar model, sensitization

Procedia PDF Downloads 89

Authors: K. L. Kabemba, R. F. Sandenberg

Abstract:

The usual way to desorb gold is by elution with a hot concentrated alkaline solution of sodium cyanide. The high temperature is necessary because the dielectric constant of water decreases with increasing temperature hence the electrostatic forces between charcoal and the gold cyanide complex decreases. High alkalinity and a high concentration of cyanide are necessary for gold desorption because both OH- and CN- ions are preferentially adsorbed. The rate of elution increases with increasing anion concentration but decreases with increasing cation concentration that means the rate of elution passes through a maximum as the concentration of the eluting salt (NaCN, for example) is increased. The anion that gives the best results, the cyanide ion, decomposes fairly rapidly at elevated temperatures (40% in 6 hours, 90% in 24 hours at 95°C).

Keywords: caustic, cyanide, gold, temperature

Procedia PDF Downloads 387

Authors: Mads H. Clausen

Abstract:

Plant cell walls are structurally complex and contain a larger number of diverse carbohydrate polymers. These plant fibers are a highly valuable bio-resource and the focus of food, energy and health research. We are interested in studying the interplay of plant cell wall carbohydrates with proteins such as enzymes, cell surface lectins and antibodies. However, detailed molecular level investigations of such interactions are hampered by the heterogeneity and diversity of the polymers of interest. To circumvent this, we target well-defined oligosaccharides with representative structures that can be used for characterizing protein-carbohydrate binding. The presentation will highlight chemical syntheses of plant cell wall oligosaccharides from our group and provide examples from studies of their interactions with proteins.

Keywords: oligosaccharides, carbohydrate chemistry, plant cell walls, carbohydrate-acting enzymes

Procedia PDF Downloads 312

Authors: Xiangtuo Chen, Paul-Henry Cournéde

Abstract:

Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

Procedia PDF Downloads 231