Search results for: signal classification

Authors: Kanika Gupta, Ashok Kumar

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Biofilms are dense, highly hydrated cell clusters that are irreversibly attached to a substratum, to an interface or to each other, and are embedded in a self-produced gelatinous matrix composed of extracellular polymeric substances. Research in biofilm field has become very significant, as biofilm has shown high mechanical resilience and resistance to antibiotic treatment and constituted as a significant problem in both healthcare and other industry related to microorganisms. The massive information both stated and hidden in the biofilm literature are growing exponentially therefore it is not possible for researchers and practitioners to automatically extract and relate information from different written resources. So, the current work proposes and discusses the use of text mining techniques for the extraction of information from biofilm literature corpora containing 34306 documents. It is very difficult and expensive to obtain annotated material for biomedical literature as the literature is unstructured i.e. free-text. Therefore, we considered unsupervised approach, where no annotated training is necessary and using this approach we developed a system that will classify the text on the basis of growth and development, drug effects, radiation effects, classification and physiology of biofilms. For this, a two-step structure was used where the first step is to extract keywords from the biofilm literature using a metathesaurus and standard natural language processing tools like Rapid Miner_v5.3 and the second step is to discover relations between the genes extracted from the whole set of biofilm literature using pubmed.mineR_v1.0.11. We used unsupervised approach, which is the machine learning task of inferring a function to describe hidden structure from 'unlabeled' data, in the above-extracted datasets to develop classifiers using WinPython-64 bit_v3.5.4.0Qt5 and R studio_v0.99.467 packages which will automatically classify the text by using the mentioned sets. The developed classifiers were tested on a large data set of biofilm literature which showed that the unsupervised approach proposed is promising as well as suited for a semi-automatic labeling of the extracted relations. The entire information was stored in the relational database which was hosted locally on the server. The generated biofilm vocabulary and genes relations will be significant for researchers dealing with biofilm research, making their search easy and efficient as the keywords and genes could be directly mapped with the documents used for database development.

Keywords: biofilms literature, classifiers development, text mining, unsupervised learning approach, unstructured data, relational database

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Authors: Bader Eddin Al Asali, N. Srinivasa Reddy

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Cities are dynamic in nature and are characterized by concentration of people, infrastructure, services and markets, which offer opportunities for production and consumption. Often growth and development in urban areas is not systematic, and is directed by number of factors like natural growth, land prices, housing availability, job locations-the central business district (CBD’s), transportation routes, distribution of resources, geographical boundaries, administrative policies, etc. One sided spatial and geographical development in cities leads to the unequal spatial distribution of population and jobs, resulting in high transportation activity. City development can be measured by the parameters such as urban size, urban form, urban shape, and urban structure. Urban Size is the city size and defined by the population of the city, and urban form is the location and size of the economic activity (CBD) over the geographical space. Urban shape is the geometrical shape of the city over which the distribution of population and economic activity occupied. And Urban Structure is the transport network within which the population and activity centers are connected by hierarchy of roads. Among the urban land-use systems transportation plays significant role and is one of the largest energy consuming sector. Transportation interaction among the land uses is measured in Passenger-Km and mean trip length, and is often used as a proxy for measurement of energy consumption in transportation sector. Among the trips generated in cities, work trips constitute more than 70 percent. Work trips are originated from the place of residence and destination to the place of employment. To understand the role of urban parameters on transportation interaction, theoretical cities of different size and urban specifications are generated through building block exercise using a specially developed interactive C++ programme and land use transportation modeling is carried. The land-use transportation modeling exercise helps in understanding the role of urban parameters and also to classify the cities for their urban form, structure, and shape. Muscat the capital city of Oman underwent rapid urbanization over the last four decades is taken as a case study for its classification. Also, a pilot survey is carried to capture urban travel characteristics. Analysis of land-use transportation modeling with field data classified Muscat as a linear city with polycentric CBD. Conclusions are drawn suggestion are given for policy making for the sustainability of Muscat City.

Keywords: land-use transportation, transportation modeling urban form, urban structure, urban rule parameters

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Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

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Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

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Authors: Irina Belozerova

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In the recent years, the number of crimes against peace and humanity has constantly been increasing. The development of the international community is inseparably connected to the compliance with the law which protects the rights and interests of citizens in all of their manifestations. The provisions of the law of criminal procedure are no exception. The rights of the victims of genocide, of the war crimes and the crimes against humanity, require particular attention. These crimes fall within the jurisdiction of the International Criminal Court governed by the Rome Statute of the International Criminal Court. These crimes have the following features. First, any such crime has a mass character and therefore requires specific regulation in the international criminal law and procedure and the national criminal law and procedure of different countries. Second, the victims of such crimes are usually children, women and old people; the entire national, ethnic, racial or religious groups are destroyed. These features influence the classification of victims by the age criterion. Article 68 of the Rome Statute provides for protection of the safety, physical and psychological well-being, dignity and privacy of victims and witnesses and thus determines the procedural status of these persons. However, not all the persons whose rights have been violated by the commission of these crimes acquire the status of victims. This is due to the fact that such crimes affect a huge number of persons and it is impossible to mention them all by name. It is also difficult to assess the entire damage suffered by the victims. While assessing the amount of damages it is essential to take into account physical and moral harm, as well as property damage. The procedural status of victims thus gains an exclusive character. In order to determine the full extent of the damage suffered by the victims it is necessary to collect sufficient evidence. However, it is extremely difficult to collect the evidence that would ensure the full and objective protection of the victims’ rights. While making requests for the collection of evidence, the International Criminal Court faces the problem of protection of national security information. Religious beliefs and the family life of victims are of great importance. In some Islamic countries, it is impossible to question a woman without her husband’s consent which affects the objectivity of her testimony. Finally, the number of victims is quantified by hundreds and thousands. The assessment of these elements demands time and highly qualified work. These factors justify the creation of a mechanism that would help to collect the evidence and establish the truth in the international criminal proceedings. This mechanism will help to impose a just and appropriate punishment for the persons accused of having committed a crime, since, committing the crime, criminals could not misunderstand the outcome of their criminal intent.

Keywords: crimes against humanity, evidence in international criminal proceedings, international criminal proceedings, protection of victims

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Authors: Olivine Lo

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Small- and Medium-Sized Enterprises (SMEs) consist of a broad variety of businesses, ranging from small grocery shops to manufacturing concerns. Some are dynamic and innovative, while others are more traditional. The definition of SMEs varies by country but is most determined by the number of employees, though business assets and sales revenues are alternative measures. There are eight main types of SME industries in Hong Kong: garment, electronics, plastics, metal and machinery, trading and logistics, building, manufacturing, and service industries. Information exchange is a key goal of human communication, and communicators have used a variety of media to maintain relationships through traditional face-to-face interactions and written forms like letters and faxes. With the advancement of mediated-interpersonal communication media from telephone to synchronic online tools like email, instant messaging, voice messaging, and video conferencing for sustaining relationships, particularly enabling geographically distanced relationships. Although these synchronous tools are gaining popularity, they are facilitating relationship maintenance in everyday life and complementing rather than replacing the more conventional face-to-face interactions. This study will test if there are any variances in effects by industry type among Hong Kong SMEs. The competitiveness of the business environment refers to the competition faced by a business within its particular industry. The more intense the competition in a given sector, the greater the potential for strategic uses of specific needs in a business. Both internal organization characteristics and external environments may affect firm performance and financial resources. The level of competitiveness within an industry will be a more reliable indicator to show how Hong Kong SMEs are striving to achieve their business goals using different techniques in their communication media preferences, rather than mere classification by industry type. This study thus divides the competitiveness of the business environment into internal and external: (1) the internal environment competition is the inherent competitiveness of the products or services provided by the SMEs, whereas (2) the external environment competition includes the economic and political realities and competitors joining the market. This study will test various organizational characteristics and competitiveness of the business environment to predict entrepreneurs’ communication media preferences.

Keywords: competitiveness of business environment, small- and medium-sized enterprises, organizational characteristics, communication media preference

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Authors: John K. Avor, Choong-Koo Chang

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The transfer of electrical loads at power generation stations from Standby Auxiliary Transformer (SAT) to Unit Auxiliary Transformer (UAT) and vice versa is through a fast bus transfer scheme. Fast bus transfer is a time-critical application where the transfer process depends on various parameters, thus transfer schemes apply advance algorithms to ensure power supply reliability and continuity. In a nuclear power generation station, supply continuity is essential, especially for critical class 1E electrical loads. Bus transfers must, therefore, be executed accurately within 4 to 10 cycles in order to achieve safety system requirements. However, the main problem is that there are instances where transfer schemes scrambled due to inaccurate interpretation of key parameters; and consequently, have failed to transfer several critical loads from UAT to the SAT during main generator trip event. Although several techniques have been adopted to develop robust transfer schemes, a combination of Artificial Neural Network and Fuzzy Systems (Neuro-Fuzzy) has not been extensively used. In this paper, we apply the concept of Neuro-Fuzzy to determine plant operating mode and dynamic prediction of the appropriate bus transfer algorithm to be selected based on the first cycle of voltage information. The performance of Sequential Fast Transfer and Residual Bus Transfer schemes was evaluated through simulation and integration of the Neuro-Fuzzy system. The objective for adopting Neuro-Fuzzy approach in the bus transfer scheme is to utilize the signal validation capabilities of artificial neural network, specifically the back-propagation algorithm which is very accurate in learning completely new systems. This research presents a combined effect of artificial neural network and fuzzy systems to accurately interpret key bus transfer parameters such as magnitude of the residual voltage, decay time, and the associated phase angle of the residual voltage in order to determine the possibility of high speed bus transfer for a particular bus and the corresponding transfer algorithm. This demonstrates potential for general applicability to improve reliability of the auxiliary power distribution system. The performance of the scheme is implemented on APR1400 nuclear power plant auxiliary system.

Keywords: auxiliary power system, bus transfer scheme, fuzzy logic, neural networks, reliability

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Authors: X. Wang

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Timely and accurate information on urban building damage caused by earthquake is important basis for disaster assessment and emergency relief. Very high resolution (VHR) remotely sensed imagery containing abundant fine-scale information offers a large quantity of data for detecting and assessing urban building damage in the aftermath of earthquake disasters. However, the accuracy obtained using spectral features alone is comparatively low, since building damage, intact buildings and pavements are spectrally similar. Therefore, it is of great significance to detect urban building damage effectively using multi-source data. Considering that in general height or geometric structure of buildings change dramatically in the devastated areas, a novel multi-stage urban building damage detection method, using bi-temporal spectral, height and corner information, was proposed in this study. The pre-event height information was generated using stereo VHR images acquired from two different satellites, while the post-event height information was produced from airborne LiDAR data. The corner information was extracted from pre- and post-event panchromatic images. The proposed method can be summarized as follows. To reduce the classification errors caused by spectral similarity and errors in extracting height information, ground surface, shadows, and vegetation were first extracted using the post-event VHR image and height data and were masked out. Two different types of building damage were then extracted from the remaining areas: the height difference between pre- and post-event was used for detecting building damage showing significant height change; the difference in the density of corners between pre- and post-event was used for extracting building damage showing drastic change in geometric structure. The initial building damage result was generated by combining above two building damage results. Finally, a post-processing procedure was adopted to refine the obtained initial result. The proposed method was quantitatively evaluated and compared to two existing methods in Port au Prince, Haiti, which was heavily hit by an earthquake in January 2010, using pre-event GeoEye-1 image, pre-event WorldView-2 image, post-event QuickBird image and post-event LiDAR data. The results showed that the method proposed in this study significantly outperformed the two comparative methods in terms of urban building damage extraction accuracy. The proposed method provides a fast and reliable method to detect urban building collapse, which is also applicable to relevant applications.

Keywords: building damage, corner, earthquake, height, very high resolution (VHR)

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Authors: Ella Tyuryumina, Alexey Neznanov

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This study is an attempt to obtain reliable data on the natural history of breast cancer growth. We analyze the opportunities for using classical mathematical models (exponential and logistic tumor growth models, Gompertz and von Bertalanffy tumor growth models) to try to describe growth of the primary tumor and the secondary distant metastases of human breast cancer. The research aim is to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoMPaS and corresponding software. We are interested in: 1) modelling the whole natural history of the primary tumor and the secondary distant metastases; 2) developing adequate and precise CoMPaS which reflects relations between the primary tumor and the secondary distant metastases; 3) analyzing the CoMPaS scope of application; 4) implementing the model as a software tool. The foundation of the CoMPaS is the exponential tumor growth model, which is described by determinate nonlinear and linear equations. The CoMPaS corresponds to TNM classification. It allows to calculate different growth periods of the primary tumor and the secondary distant metastases: 1) ‘non-visible period’ for the primary tumor; 2) ‘non-visible period’ for the secondary distant metastases; 3) ‘visible period’ for the secondary distant metastases. The CoMPaS is validated on clinical data of 10-years and 15-years survival depending on the tumor stage and diameter of the primary tumor. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer growth models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. The CoMPaS model and predictive software: a) fit to clinical trials data; b) detect different growth periods of the primary tumor and the secondary distant metastases; c) make forecast of the period of the secondary distant metastases appearance; d) have higher average prediction accuracy than the other tools; e) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoMPaS: the number of doublings for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases. The CoMPaS enables, for the first time, to predict ‘whole natural history’ of the primary tumor and the secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on the primary tumor sizes. Summarizing: a) CoMPaS describes correctly the primary tumor growth of IA, IIA, IIB, IIIB (T1-4N0M0) stages without metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and inception of the secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, metastases in lymph nodes, primary tumor, survival

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Authors: J. Ritonja

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The biochemical technology has been developing extremely fast since the middle of the last century. The main reason for such development represents a requirement for large production of high-quality biologically manufactured products such as pharmaceuticals, foods, and beverages. The impact of the biochemical industry on the world economy is enormous. The great importance of this industry also results in intensive development in scientific disciplines relevant to the development of biochemical technology. In addition to developments in the fields of biology and chemistry, which enable to understand complex biochemical processes, development in the field of control theory and applications is also very important. In the paper, the control for the biochemical reactor for the milk fermentation was studied. During the fermentation process, the biophysical quantities must be precisely controlled to obtain the high-quality product. To control these quantities, the bioreactor’s stirring drive and/or heating system can be used. Available commercial biochemical reactors are equipped with open loop or conventional linear closed loop control system. Due to the outstanding parameters variations and the partial nonlinearity of the biochemical process, the results obtained with these control systems are not satisfactory. To improve the fermentation process, the self-tuning adaptive control system was proposed. The use of the self-tuning adaptive control is suggested because the parameters’ variations of the studied biochemical process are very slow in most cases. To determine the linearized mathematical model of the fermentation process, the recursive least square identification method was used. Based on the obtained mathematical model the linear quadratic regulator was tuned. The parameters’ identification and the controller’s synthesis are executed on-line and adapt the controller’s parameters to the fermentation process’ dynamics during the operation. The use of the proposed combination represents the original solution for the control of the milk fermentation process. The purpose of the paper is to contribute to the progress of the control systems for the biochemical reactors. The proposed adaptive control system was tested thoroughly. From the obtained results it is obvious that the proposed adaptive control system assures much better following of the reference signal as a conventional linear control system with fixed control parameters.

Keywords: adaptive control, biochemical reactor, linear quadratic regulator, recursive least square identification

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Authors: Matheus Madureira Matos, Alexandre Rodrigues Farias

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Magnetic Resonance Imaging (MRI) is a vital imaging technique used in both clinical and pre-clinical areas to obtain detailed anatomical and functional information. However, MRI scans can be expensive, time-consuming, and often require the use of anesthetics to keep animals still during the imaging process. Anesthetics are commonly administered to animals undergoing MRI scans to ensure they remain still during the imaging process. However, prolonged or repeated exposure to anesthetics can have adverse effects on animals, including physiological alterations and potential toxicity. Minimizing the duration and frequency of anesthesia is, therefore, crucial for the well-being of research animals. In recent years, various sampling trajectories have been investigated to reduce the number of MRI measurements leading to shorter scanning time and minimizing the duration of animal exposure to the effects of anesthetics. Compressed sensing (CS) and sampling trajectories, such as cartesian, spiral, and radial, have emerged as powerful tools to reduce MRI data while preserving diagnostic quality. This work aims to apply CS and cartesian, spiral, and radial sampling trajectories for the reconstruction of MRI of the abdomen of mice sub-sampled at levels below that defined by the Nyquist theorem. The methodology of this work consists of using a fully sampled reference MRI of a female model C57B1/6 mouse acquired experimentally in a 4.7 Tesla MRI scanner for small animals using Spin Echo pulse sequences. The image is down-sampled by cartesian, radial, and spiral sampling paths and then reconstructed by CS. The quality of the reconstructed images is objectively assessed by three quality assessment techniques RMSE (Root mean square error), PSNR (Peak to Signal Noise Ratio), and SSIM (Structural similarity index measure). The utilization of optimized sampling trajectories and CS technique has demonstrated the potential for a significant reduction of up to 70% of image data acquisition. This result translates into shorter scan times, minimizing the duration and frequency of anesthesia administration and reducing the potential risks associated with it.

Keywords: compressed sensing, magnetic resonance, sampling trajectories, small animals

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Authors: N. Khursheed, M. Fatima, S. Jamal, A. Raza, S. Rattani, Q. Ahsan, A. Rasheed, M. Jawed

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Introduction: Antibiotics are among the commonly prescribed medicines to treat bacterial infections. Their misuse intensifies resistance, and overuse incurs heavy losses to the healthcare system in terms of increased treatment costs and enhanced disease burden. Studies show that 40% of empirically used antibiotics are irrationally utilized. The objective of this study was to evaluate prescribing pattern of antibiotics at six public sector tertiary care hospitals across Pakistan. Methods: A multicenter cross-sectional point prevalence survey (PPS) was conducted in selected wards of six public sector tertiary care hospitals in Pakistan as part of the Clinical Engagement program by Fleming Fund Country Grant Pakistan in collaboration with Indus Hospital & Health Network (IHHN) from February to March 2021, these included Jinnah Postgraduate Medical Center and Dr. Ruth K. M. Pfau Civil Hospital from Karachi, Sheikh Zayed Hospital Lahore, Nishtar Medical University Hospital Multan, Medical Teaching Institute Hayatabad Medical Complex Peshawar, and Provincial Headquarters Hospital Gilgit. WHO PPS methodology was used for data collection (Hospital, ward, and patient level data was collected). Data was entered into the open-source Kobo Collect application and was analyzed using SPSS (version 22.0). Findings: Medical records of 837 in-patients were surveyed, of which the prevalence of antibiotics use was 78.5%. The most commonly prescribed antimicrobial was Ceftriaxone (21.7%) which is categorized in the Watch group of WHO AWaRe Classification, followed by Metronidazole (17.3%), Cefoperazone/Sulbactam (8.4%), Co-Amoxiclav (6.3%) and Piperacillin/Tazobactam (5.9%). The antibiotics were prescribed largely for surgical prophylaxis (36.7%), followed by community-acquired infections (24.7%). One antibiotic was prescribed to 46.7%, two to 39.9%, and three or more to 12.5 %. Two of six (30%) hospitals had functional drug and therapeutic committees, three (50%) had infection prevention and control committees, and one facility had an antibiotic formulary. Conclusion: Findings demonstrate high consumption of broad-spectrum antimicrobials and emphasizes the importance of expanding the antimicrobial stewardship program. Mentoring clinical teams will help to rationalize antimicrobial use.

Keywords: antimicrobial resistance, antimicrobial stewardship, point prevalence survey, antibiotics

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Authors: Ankit Tyagi, Reet Kamal Tiwari, Naveen James

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Landslide is the major geo-environmental problem of Himalaya because of high ridges, steep slopes, deep valleys, and complex system of streams. They are mainly triggered by rainfall and earthquake and causing severe damage to life and property. In Uttarakhand, the Tehri reservoir rim area, which is situated in the lesser Himalaya of Garhwal hills, was selected for landslide hazard zonation (LHZ). The study utilized different types of data, including geological maps, topographic maps from the survey of India, Landsat 8, and Cartosat DEM data. This paper presents the use of a weighted overlay method in LHZ using fourteen causative factors. The various data layers generated and co-registered were slope, aspect, relative relief, soil cover, intensity of rainfall, seismic ground shaking, seismic amplification at surface level, lithology, land use/land cover (LULC), normalized difference vegetation index (NDVI), topographic wetness index (TWI), stream power index (SPI), drainage buffer and reservoir buffer. Seismic analysis is performed using peak horizontal acceleration (PHA) intensity and amplification factors in the evaluation of the landslide hazard index (LHI). Several digital image processing techniques such as topographic correction, NDVI, and supervised classification were widely used in the process of terrain factor extraction. Lithological features, LULC, drainage pattern, lineaments, and structural features are extracted using digital image processing techniques. Colour, tones, topography, and stream drainage pattern from the imageries are used to analyse geological features. Slope map, aspect map, relative relief are created by using Cartosat DEM data. DEM data is also used for the detailed drainage analysis, which includes TWI, SPI, drainage buffer, and reservoir buffer. In the weighted overlay method, the comparative importance of several causative factors obtained from experience. In this method, after multiplying the influence factor with the corresponding rating of a particular class, it is reclassified, and the LHZ map is prepared. Further, based on the land-use map developed from remote sensing images, a landslide vulnerability study for the study area is carried out and presented in this paper.

Keywords: weighted overlay method, GIS, landslide hazard zonation, remote sensing

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Authors: Mernoosh Abouzari, Shahrokh Sahraei

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Electronic government is a way for governments to use new technology that provides people with the necessary facilities for proper access to government information and services, improving the quality of services and providing broad opportunities to participate in democratic processes and institutions. That leads to providing the possibility of easy use of information technology in order to distribute government services to the customer without holidays, which increases people's satisfaction and participation in political and economic activities. The expansion of e-government services and its movement towards intelligentization has the ability to re-establish the relationship between the government and citizens and the elements and components of the government. Electronic government is the result of the use of information and communication technology (ICT), which by implementing it at the government level, in terms of the efficiency and effectiveness of government systems and the way of providing services, tremendous commercial changes are created, which brings people's satisfaction at the wide level will follow. The main level of electronic government services has become objectified today with the presence of artificial intelligence systems, which recent advances in artificial intelligence represent a revolution in the use of machines to support predictive decision-making and Classification of data. With the use of deep learning tools, artificial intelligence can mean a significant improvement in the delivery of services to citizens and uplift the work of public service professionals while also inspiring a new generation of technocrats to enter government. This smart revolution may put aside some functions of the government, change its components, and concepts such as governance, policymaking or democracy will change in front of artificial intelligence technology, and the top-down position in governance may face serious changes, and If governments delay in using artificial intelligence, the balance of power will change and private companies will monopolize everything with their pioneering in this field, and the world order will also depend on rich multinational companies and in fact, Algorithmic systems will become the ruling systems of the world. It can be said that currently, the revolution in information technology and biotechnology has been started by engineers, large economic companies, and scientists who are rarely aware of the political complexities of their decisions and certainly do not represent anyone. Therefore, it seems that if liberalism, nationalism, or any other religion wants to organize the world of 2050, it should not only rationalize the concept of artificial intelligence and complex data algorithm but also mix them in a new and meaningful narrative. Therefore, the changes caused by artificial intelligence in the political and economic order will lead to a major change in the way all countries deal with the phenomenon of digital globalization. In this paper, while debating the role and performance of e-government, we will discuss the efficiency and application of artificial intelligence in e-government, and we will consider the developments resulting from it in the new world and the concepts of governance.

Keywords: electronic government, artificial intelligence, information and communication technology., system

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Authors: Hannele Kuusisto, Paivi Makila, Ursula Hyrkkanen

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Introduction: There have been arguments about the skills university students should have when graduated. Current trends argue that as well as the specific job-related skills the graduated students need problem-solving, interaction and networking skills as well as self-management skills. Skills required in working life are also considered in the Finnish national project called VALTE (short for 'prepared for working life'). The project involves 11 Finnish school organizations. As one result of this project, a five-credit independent online course in study and job engagement as well as in study and job crafting was developed at Turku University of Applied Sciences. The aim of the oral or e-poster presentation is to present the online course developed in the project. The purpose of this abstract is to present the development work of the online course and the feedback received from the pilots. Method: As the University of Turku is the leading partner of the VALTE project, the collaborative education platform ViLLE (https://ville.utu.fi, developed by the University of Turku) was chosen as the online platform for the course. Various exercise types with automatic assessment were used; for example, quizzes, multiple-choice questions, classification exercises, gap filling exercises, model answer questions, self-assessment tasks, case tasks, and collaboration in Padlet. In addition, the free material and free platforms on the Internet were used (Youtube, Padlet, Todaysmeet, and Prezi) as well as the net-based questionnaires about the study engagement and study crafting (made with Webropol). Three teachers with long teaching experience (also with job crafting and online pedagogy) and three students working as trainees in the project developed the content of the course. The online course was piloted twice in 2017 as an elective course for the students at Turku University of Applied Sciences, a higher education institution of about 10 000 students. After both pilots, feedback from the students was gathered and the online course was developed. Results: As the result, the functional five-credit independent online course suitable for students of different educational institutions was developed. The student feedback shows that students themselves think that the developed online course really enhanced their job and study crafting skills. After the course, 91% of the students considered their knowledge in job and study engagement as well as in job and study crafting to be at a good or excellent level. About two-thirds of the students were going to exploit their knowledge significantly in the future. Students appreciated the variability and the game-like feeling of the exercises as well as the opportunity to study online at the time and place they chose themselves. On a five-point scale (1 being poor and 5 being excellent), the students graded the clarity of the ViLLE platform as 4.2, the functionality of the platform as 4.0 and the easiness of operating as 3.9.

Keywords: job crafting, job engagement, online course, study crafting, study engagement

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Authors: Jitendra Pratap, Jonathan Sivyer

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Introduction: Dual energy/Spectral CT scanning permits simultaneous acquisition of two x-ray spectra datasets and can complement radiological diagnosis by allowing tissue characterisation (e.g., uric acid vs. non-uric acid renal stones), enhancing structures (e.g. boost iodine signal to improve contrast resolution), and quantifying substances (e.g. iodine density). However, the latter showed inconsistent results between the 2 main modes of dual energy scanning (i.e. dual source vs. dual layer). Therefore, the present study aimed to determine which technology is more accurate in quantifying iodine density. Methods: Twenty vials with known concentrations of iodine solutions were made using Optiray 350 contrast media diluted in sterile water. The concentration of iodine utilised ranged from 0.1 mg/ml to 1.0mg/ml in 0.1mg/ml increments, 1.5 mg/ml to 4.5 mg/ml in 0.5mg/ml increments followed by further concentrations at 5.0 mg/ml, 7mg/ml, 10 mg/ml and 15mg/ml. The vials were scanned using Dual Energy scan mode on a Siemens Somatom Force at 80kV/Sn150kV and 100kV/Sn150kV kilovoltage pairing. The same vials were scanned using Spectral scan mode on a Philips iQon at 120kVp and 140kVp. The images were reconstructed at 5mm thickness and 5mm increment using Br40 kernel on the Siemens Force and B Filter on Philips iQon. Post-processing of the Dual Energy data was performed on vendor-specific Siemens Syngo VIA (VB40) and Philips Intellispace Portal (Ver. 12) for the Spectral data. For each vial and scan mode, the iodine concentration was measured by placing an ROI in the coronal plane. Intraclass correlation analysis was performed on both datasets. Results: The iodine concentrations were reproduced with a high degree of accuracy for Dual Layer CT scanner. Although the Dual Source images showed a greater degree of deviation in measured iodine density for all vials, the dataset acquired at 80kV/Sn150kV had a higher accuracy. Conclusion: Spectral CT scanning by the dual layer technique has higher accuracy for quantitative measurements of iodine density compared to the dual source technique.

Keywords: CT, iodine density, spectral, dual-energy

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Authors: Felix Schumann, Giorgia Carratta, Tobias Dauth, Liv Jaeckel

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In the last few decades, the rapid growth of the use and disposal of plastic items has led to their overaccumulation in the environment. As a result, plastic pollution has become a subject of global concern. Today plastics are used as raw materials in almost every industry. While the recognition of the ecological, social, and economic impact of plastics in academic research is on the rise, the potential role of the ‘plastic industry’ in dealing with such issues is still largely underestimated. Therefore, the literature on sustainable plastic management is still nascent and fragmented. Working towards sustainability requires a fundamental shift in the way companies employ plastics in their day-to-day business. For that reason, the applicability of the business model concept has recently gained momentum in environmental research. Business model innovation is increasingly recognized as an important driver to re-conceptualize the purpose of the firm and to readily integrate sustainability in their business. It can serve as a starting point to investigate whether and how sustainability can be realized under industry- and firm-specific circumstances. Yet, there is no comprehensive view in the plastic industry on how firms start refining their business models to embed sustainability in their operations. Our study addresses this gap, looking primarily at the industrial sectors responsible for the production of the largest amount of plastic waste today: plastic packaging, consumer goods, construction, textile, and transport. Relying on the archetypes of sustainable business models and applying them to the aforementioned sectors, we try to identify companies’ current strategies to make their business models more sustainable. Based on the thematic clustering, we can develop an integrative framework for the plastic industry. The findings are underpinned and illustrated by a variety of relevant plastic management solutions that the authors have identified through a systematic literature review and analysis of existing, empirically grounded research in this field. Using the archetypes, we can promote options for business model innovations for the most important sectors in which plastics are used. Moreover, by linking the proposed business model archetypes to the plastic industry, our research approach guides firms in exploring sustainable business opportunities. Likewise, researchers and policymakers can utilize our classification to identify best practices. The authors believe that the study advances the current knowledge on sustainable plastic management through its broad empirical industry analyses. Hence, the application of business model archetypes in the plastic industry will be useful for shaping companies’ transformation to create and deliver more sustainability and provides avenues for future research endeavors.

Keywords: business models, environmental economics, plastic management, plastic pollution, sustainability

Procedia PDF Downloads 99

Authors: Ahmed O. Apampa, Yinusa A. Jimoh

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The potential economic viability and environmental benefits of using a biomass waste, such as corn cob ash (CCA) as pozzolan in stabilizing soils for road pavement construction in a sub-tropical region was investigated. Corn cob was obtained from Maya in South West Nigeria and processed to ash of characteristics similar to Class C Fly Ash pozzolan as specified in ASTM C618-12. This was then blended with ordinary Portland cement in the CCA:OPC ratios of 1:1, 1:2 and 2:1. Each of these blends was then mixed with lateritic soil of ASHTO classification A-2-6(3) in varying percentages from 0 – 7.5% at 1.5% intervals. The soil-CCA-Cement mixtures were thereafter tested for geotechnical index properties including the BS Proctor Compaction, California Bearing Ratio (CBR) and the Unconfined Compression Strength Test. The tests were repeated for soil-cement mix without any CCA blending. The cost of the binder inputs and optimal blends of CCA:OPC in the stabilized soil were thereafter analyzed by developing algorithms that relate the experimental data on strength parameters (Unconfined Compression Strength, UCS and California Bearing Ratio, CBR) with the bivariate independent variables CCA and OPC content, using Matlab R2011b. An optimization problem was then set up minimizing the cost of chemical stabilization of laterite with CCA and OPC, subject to the constraints of minimum strength specifications. The Evolutionary Engine as well as the Generalized Reduced Gradient option of the Solver of MS Excel 2010 were used separately on the cells to obtain the optimal blend of CCA:OPC. The optimal blend attaining the required strength of 1800 kN/m2 was determined for the 1:2 CCA:OPC as 5.4% mix (OPC content 3.6%) compared with 4.2% for the OPC only option; and as 6.2% mix for the 1:1 blend (OPC content 3%). The 2:1 blend did not attain the required strength, though over a 100% gain in UCS value was obtained over the control sample with 0% binder. Upon the fact that 0.97 tonne of CO2 is released for every tonne of cement used (OEE, 2001), the reduced OPC requirement to attain the same result indicates the possibility of reducing the net CO2 contribution of the construction industry to the environment ranging from 14 – 28.5% if CCA:OPC blends are widely used in soil stabilization, going by the results of this study. The paper concludes by recommending that Nigeria and other developing countries in the sub-tropics with abundant stock of biomass waste should look in the direction of intensifying the use of biomass waste as fuel and the derived ash for the production of pozzolans for road-works, thereby reducing overall green house gas emissions and in compliance with the objectives of the United Nations Framework on Climate Change.

Keywords: corn cob ash, biomass waste, lateritic soil, unconfined compression strength, CO2 emission

Procedia PDF Downloads 373

Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yaokai Liu, Xinhong Wang, Yongsheng Zhou

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Performances analysis of remote sensing sensor is required to pursue a range of scientific research and application objectives. Laboratory analysis of any remote sensing instrument is essential, but not sufficient to establish a valid inflight one. In this study, with the aid of the in situ measurements and corresponding image of three-gray scale permanent artificial target, the in-flight radiometric performances analyses (in-flight radiometric calibration, dynamic range and response linearity, signal-noise-ratio (SNR), radiometric resolution) of self-developed short-wave infrared (SWIR) camera are performed. To acquire the inflight calibration coefficients of the SWIR camera, the at-sensor radiances (L_i) for the artificial targets are firstly simulated with in situ measurements (atmosphere parameter and spectral reflectance of the target) and viewing geometries using MODTRAN model. With these radiances and the corresponding digital numbers (DN) in the image, a straight line with a formulation of L = G × DN + B is fitted by a minimization regression method, and the fitted coefficients, G and B, are inflight calibration coefficients. And then the high point (L_H) and the low point (L_L) of dynamic range can be described as L_H= (G × DN_H + B) and L_L= B, respectively, where DN_H is equal to 2ⁿ − 1 (n is the quantization number of the payload). Meanwhile, the sensor’s response linearity (δ) is described as the correlation coefficient of the regressed line. The results show that the calibration coefficients (G and B) are 0.0083 W·sr⁻¹m⁻²µm⁻¹ and −3.5 W·sr⁻¹m⁻²µm⁻¹; the low point of dynamic range is −3.5 W·sr⁻¹m⁻²µm⁻¹ and the high point is 30.5 W·sr⁻¹m⁻²µm⁻¹; the response linearity is approximately 99%. Furthermore, a SNR normalization method is used to assess the sensor’s SNR, and the normalized SNR is about 59.6 when the mean value of radiance is equal to 11.0 W·sr⁻¹m⁻²µm⁻¹; subsequently, the radiometric resolution is calculated about 0.1845 W•sr^-1m^-2μm^-1. Moreover, in order to validate the result, a comparison of the measured radiance with a radiative-transfer-code-predicted over four portable artificial targets with reflectance of 20%, 30%, 40%, 50% respectively, is performed. It is noted that relative error for the calibration is within 6.6%.

Keywords: calibration and validation site, SWIR camera, in-flight radiometric calibration, dynamic range, response linearity

Procedia PDF Downloads 270

Authors: Elif Tugce Aksun Tumerkan

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Fluorescent proteins (FPs) have become very popular since green fluorescent protein discovered from crystal jellyfish. It is known that Anthozoa species have a wide range of chromophore organisms, and the initial crystal structure for non-fluorescent chromophores obtained from the reef-building coral has been determined. There are also differently coloured pigments in non-bioluminescent Anthozoa zooxanthellate and azooxanthellate which are frequently members of the GFP-like protein family. The development of fluorescent proteins (FPs) and their applications is an outstanding example of basic science leading to practical biotechnological and medical applications. Fluorescent proteins have several applications in science and are used as important indicators in molecular biology and cell-based research. With rising interest in cell biology, FPs have used as biosensor indicators and probes in pharmacology and cell biology. Using fluorescent proteins in genetically encoded metabolite sensors has many advantages than chemical probes for metabolites such as easily introduced into any cell or organism in any sub-cellular localization and giving chance to fixing to fluoresce of different colours or characteristics. There are different factors effects to signalling mechanism when they used as a biosensor. While there are wide ranges of research have been done on the significance and applications of fluorescent proteins, the cell signalling response of FPs and target cell are less well understood. In this study, it was aimed to clarify the response of adaptive mechanisms of coral species such as pH, temperature and symbiotic relationship and target cells properties on the signalling capacity. Corals are a rich natural source of fluorescent proteins that change with environmental conditions such as light, heat stress and injury. Adaptation mechanism of coral species to these types of environmental variations is important factor due to FPs properties have affected by this mechanism. Since fluorescent proteins obtained from nature, their own ecological property like the symbiotic relationship is observed very commonly in coral species and living conditions have the impact on FPs efficiency. Target cell properties also have an effect on signalling and visualization. The dynamicity of detector that used for reading fluorescence and the level of background fluorescence are key parameters for the quality of the fluorescent signal. Among the factors, it can be concluded that coral species adaptive characteristics have the strongest effect on FPs signalling capacity.

Keywords: biosensor, cell biology, environmental conditions, fluorescent protein, sea anemone

Procedia PDF Downloads 170

Authors: M. Abderrahmane Mograne, Didier Laux, Jean-Yves Ferrandis

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Rheological characterizations of complex liquids like polymer solutions present an important scientific interest for a lot of researchers in many fields as biology, food industry, chemistry. In order to establish master curves (elastic moduli vs frequency) which can give information about microstructure, classical rheometers or viscometers (such as Couette systems) are used. For broadband characterization of the sample, temperature is modified in a very large range leading to equivalent frequency modifications applying the Time Temperature Superposition principle. For many liquids undergoing phase transitions, this approach is not applicable. That is the reason, why the development of broadband spectroscopic methods around room temperature becomes a major concern. In literature many solutions have been proposed but, to our knowledge, there is no experimental bench giving the whole rheological characterization for frequencies about a few Hz (Hertz) to many MHz (Mega Hertz). Consequently, our goal is to investigate in a nondestructive way in very broadband frequency (A few Hz – Hundreds of MHz) rheological properties using longitudinal ultrasonic waves (L waves), a unique experimental bench and a specific container for the liquid: a test tube. More specifically, we aim to estimate the three viscosities (longitudinal, shear and bulk) and the complex elastic moduli (M*, G* and K*) respectively longitudinal, shear and bulk moduli. We have decided to use only L waves conditioned in two ways: bulk L wave in the liquid or guided L waves in the tube test walls. In this paper, we will present first results for very low frequencies using the ultrasonic tracking of a falling ball in the test tube. This will lead to the estimation of shear viscosity from a few mPa.s to a few Pa.s (Pascal second). Corrections due to the small dimensions of the tube will be applied and discussed regarding the size of the falling ball. Then the use of bulk L wave’s propagation in the liquid and the development of a specific signal processing in order to assess longitudinal velocity and attenuation will conduct to the longitudinal viscosity evaluation in the MHz frequency range. At last, the first results concerning the propagation, the generation and the processing of guided compressional waves in the test tube walls will be discussed. All these approaches and results will be compared to standard methods available and already validated in our lab.

Keywords: nondestructive measurement for liquid, piezoelectric transducer, ultrasonic longitudinal waves, viscosities

Procedia PDF Downloads 265

Authors: T. Nishimura, K. Doi, H. Fujimoto, T. Wada

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The Number of people with acquired visual impairments has increased in recent years. In specialized courses at schools for the blind and in Braille lessons offered by social welfare organizations, many people with acquired visual impairments cannot learn to read adequately Braille. One of the reasons is that the common Braille patterns for people visual impairments who already has mature Braille reading skill being difficult to read for Braille reading beginners. In addition, there is the scanty knowledge of Braille book manufacturing companies regarding what Braille patterns would be easy to read for beginners. Therefore, it is required to investigate a suitable Braille patterns would be easy to read for beginners. In order to obtain knowledge regarding suitable Braille patterns for beginners, this study aimed to elucidate the relationship between readability of paper-based Braille and its patterns. This study focused on character spacing, which readily affects Braille reading ability, to determine a suitable character spacing ratio (ratio of character spacing to dot spacing) for beginners. Specifically, considering beginners with acquired visual impairments who are unfamiliar with reading Braille, we quantitatively evaluated the effect of character spacing ratio on Braille readability through an evaluation experiment using sighted subjects with no experience of reading Braille. In this experiment, ten sighted adults took the blindfold were asked to read test piece (three Braille characters). Braille used as test piece was composed of five dots. They were asked to touch the Braille by sliding their forefinger on the test piece immediately after the test examiner gave a signal to start the experiment. Then, they were required to release their forefinger from the test piece when they perceived the Braille characters. Seven conditions depended on character spacing ratio was held (i.e., 1.2, 1.4, 1.5, 1.6, 1.8, 2.0, 2.2 [mm]), and the other four depended on the dot spacing (i.e., 2.0, 2.5, 3.0, 3.5 [mm]). Ten trials were conducted for each conditions. The test pieces are created using by NISE Graphic could print Braille adjusted arbitrary value of character spacing and dot spacing with high accuracy. We adopted the evaluation indices for correct rate, reading time, and subjective readability to investigate how the character spacing ratio affects Braille readability. The results showed that Braille reading beginners could read Braille accurately and quickly, when character spacing ratio is more than 1.8 and dot spacing is more than 3.0 mm. Furthermore, it is difficult to read Braille accurately and quickly for beginners, when both character spacing and dot spacing are small. For this study, suitable character spacing ratio to make reading easy for Braille beginners is revealed.

Keywords: Braille, character spacing, people with visual impairments, readability

Procedia PDF Downloads 285

Authors: Mussa Hussaini, Supasith Chonglerttham

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Stocks are usually classified according to their characteristics which are unique enough such that the performance of each category can be differentiated from another. The reasons behind such classifications in the financial market are sometimes financial innovation or it can also be because of finding a premium in a group of stocks with similar features. One of the major classifications in stocks market is called momentum strategy. Based on this strategy stocks are classified according to their past performances into past winners and past losers. Momentum in a stock market refers to the idea that stocks will keep moving in the same direction. In other word, stocks with rising prices (past winners stocks) will continue to rise and those stocks with falling prices (past losers stocks) will continue to fall. The performance of this classification has been well documented in numerous studies in different countries. These studies suggest that past winners tend to outperform past losers in the future. However, academic research in this direction has been limited in countries such as Thailand and to the best of our knowledge, there has been no such study in Thailand after the financial crisis of 1997. The significance of this study stems from the fact that Thailand is an open market and has been encouraging foreign investments as one of the means to enhance employment, promote economic development, and technology transfer and the main equity market in Thailand, the Stock Exchange of Thailand is a crucial channel for Foreign Investment inflow into the country. The equity market size in Thailand increased from $1.72 billion in 1984 to $133.66 billion in 1993, an increase of over 77 times within a decade. The main contribution of this paper is evidence for size category in the context of the equity market in Thailand. Almost all previous studies have focused solely on large stocks or indices. This paper extends the scope beyond large stocks and indices by including small and tiny stocks as well. Further, since there is a distinct absence of detailed academic research on momentum strategy in the Stock Exchange of Thailand after the crisis, this paper also contributes to the extension of existing literature of the study. This research is also of significance for those researchers who would like to compare the performance of this strategy in different countries and markets. In the Stock Exchange of Thailand, we examined the performance of momentum strategy from 2010 to 2014. Returns on portfolios are calculated on monthly basis. Our results on momentum strategy confirm that there is positive momentum profit in large size stocks whereas there is negative momentum profit in small size stocks during the period of 2010 to 2014. Furthermore, the equal weighted average of momentum profit of both small and large size category do not provide any indication of overall momentum profit.

Keywords: momentum strategy, past loser, past winner, stock exchange of Thailand

Procedia PDF Downloads 317

Authors: Alexandru Achim, Tamás Szűcsborus, Viktor Sasi, Ferenc Nagy, Zoltán Jambrik, Attila Nemes, Albert Varga, Călin Homorodean, Olivier F. Bertrand, Zoltán Ruzsa

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Aim: Our study aimed to establish the safety and the technical success of distal radial access for balloon aortic valvuloplasty (DR-BAV). The secondary objective was to determine the effectiveness and appropriate role of DR-BAV within half year follow-up. Methods: Clinical and angiographic data from 32 consecutive patients with symptomatic aortic stenosis were evaluated in a prospective pilot single-center study. Between 2020 and 2021, the patients were treated utilizing dual distal radial access with 6-10F compatible balloons. The efficacy endpoint was divided into technical success (successful valvuloplasty balloon inflation at the aortic valve and absence of intra- or periprocedural major complications), hemodynamic success (a reduction of the mean invasive gradient >30%), and clinical success (an improvement of at least one clinical category in the NYHA classification). The safety endpoints were vascular complications (major and minor Valve Academic Research Consortium (VARC)-2 bleeding, diminished or lost arterial pulse or the presence of any pseudo-aneurysm or arteriovenous fistula during the clinical follow-up) and major adverse events, MAEs (the composite of death, stroke, myocardial infarction, and urgent major aortic valve replacement or implantation during the hospital stay and or at one-month follow-up). Results: 32 patients (40 % male, mean age 80 ± 8,5) with severe aortic valve stenosis were included in the study and 4 patients were excluded. Technical success was achieved in all patients (100%). Hemodynamic success was achieved in 30 patients (93,75%). Invasive max and mean gradients were reduced from 73±22 mm Hg and 49±22 mm Hg to 49±19 mm Hg and 20±13 mm Hg, respectively (p = <.001). Clinical success was achieved in 29 patients (90,6%). In total, no major adverse cardiac or cerebrovascular event nor vascular complications (according to VARC 2 criteria) occurred during the intervention. All-cause death at 6 months was 12%. Conclusion: According to our study, dual distal radial artery access is a safe and effective option for balloon aortic valvuloplasty in patients with severe aortic valve stenosis and can be performed in all patients with sufficient lumen diameter. Future randomized studies are warranted to investigate whether this technique is superior to other approaches.

Keywords: mean invasive gradient, distal radial access for balloon aortic valvuloplasty (DR-BAV), aortic valve stenosis, pseudo-aneurysm, arteriovenous fistula, valve academic research consortium (VARC)-2

Procedia PDF Downloads 94

Authors: Mohammad Noor Hisham Osman, Ahmed Razman Abdul Latiff, Zaidi Mat Daud, Zulkarnain Muhamad Sori

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The problem that Malaysian auditors do not issue going concern opinion (GC opinion) to seriously financially distressed companies is still a pressing issue. Policy makers, particularly the Financial Statement Review Committee (FSRC) of Malaysian Institute of Accountant, have raised this issue as early as in 2009. Similar problem happened in the US, UK, and many developing countries. It is important for auditors to issue GC opinion properly because such opinion is one signal about the viability of a company much needed by stakeholders. There are at least two unanswered questions or research gaps in the literature on determinants of GC opinion. Firstly, is client’s probability of failure associated with GC opinion issuance? Secondly, to what extent influential owners (management, family, and institution) moderate the association between client probability of failure and GC opinion issuance. The objective of this study is, therefore, twofold; (1) To examine the extent of the relationship between the probability of client failure and the issuance of GC opinion and (2) To examine the level of management, family, and institutional ownerships moderate the association between client probability of failure and the issuance of GC opinion. This study is quantitative in nature, and the sources of data are secondary (mainly company’s annual reports). A total of four hypotheses have been developed and tested on data accumulated from annual reports of seriously financially distressed Malaysian public listed companies. Data from 2006 to 2012 on a sample of 644 observations have been analyzed using panel logistic regression. It is found that certainty (rather than probability) of client failure affects the issuance of GC opinion. In addition, it is found that only the level of family ownership does positively moderate the relationship between client probability of failure and GC opinion issuance. This study is a contribution to auditing literature as its findings can enhance our understanding about audit quality; particularly on the variables that are associated with the issuance of GC opinion. The findings of this study shed light on the roles family owners in GC opinion issuance process, and this would open ways for the researcher to suggest measures that can be used to tackle the problem of auditors do not want to issue GC opinion to financially distressed clients. The measures to be suggested can be useful to policy makers in formulating future promulgations.

Keywords: audit quality, auditing, auditor characteristics, going concern opinion, Malaysia

Procedia PDF Downloads 260

Authors: Murray L. Ireland, Kevin J. Worrall, Rebecca Mackenzie, Thaleia Flessa, Euan McGookin, Douglas Thomson

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Robotic rovers which are designed to work in extra-terrestrial environments present a unique challenge in terms of the reliability and availability of systems throughout the mission. Should some fault occur, with the nearest human potentially millions of kilometres away, detection and identification of the fault must be performed solely by the robot and its subsystems. Faults in the system sensors are relatively straightforward to detect, through the residuals produced by comparison of the system output with that of a simple model. However, faults in the input, that is, the actuators of the system, are harder to detect. A step change in the input signal, caused potentially by the loss of an actuator, can propagate through the system, resulting in complex residuals in multiple outputs. These residuals can be difficult to isolate or distinguish from residuals caused by environmental disturbances. While a more complex fault detection method or additional sensors could be used to solve these issues, an alternative is presented here. Using inverse simulation (InvSim), the inputs and outputs of the mathematical model of the rover system are reversed. Thus, for a desired trajectory, the corresponding actuator inputs are obtained. A step fault near the input then manifests itself as a step change in the residual between the system inputs and the input trajectory obtained through inverse simulation. This approach avoids the need for additional hardware on a mass- and power-critical system such as the rover. The InvSim fault detection method is applied to a simple four-wheeled rover in simulation. Additive system faults and an external disturbance force and are applied to the vehicle in turn, such that the dynamic response and sensor output of the rover are impacted. Basic model-based fault detection is then employed to provide output residuals which may be analysed to provide information on the fault/disturbance. InvSim-based fault detection is then employed, similarly providing input residuals which provide further information on the fault/disturbance. The input residuals are shown to provide clearer information on the location and magnitude of an input fault than the output residuals. Additionally, they can allow faults to be more clearly discriminated from environmental disturbances.

Keywords: fault detection, ground robot, inverse simulation, rover

Procedia PDF Downloads 308

Authors: Erine van Niekerk, Jason Holland

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In Māori culture water is considered to be the foundation of all life and has its own mana (spiritual power) and mauri (life force). Water classification for cultural values therefore includes categories like waitapu (sacred water), waimanawa-whenua (water from under the land), waipuna (freshwater springs), the relationship between water quantity and quality and the relationship between surface and groundwater. Particular rivers and lakes have special significance to iwi and hapu for their rohe (tribal areas). The Mararoa River, including its freshwater springs and wetlands, is an example of such an area. There is currently little information available about the sources, characteristics and behavior of these important water resources and this study on the water quality of the Mararoa River and adjacent freshwater springs will provide valuable information to be used in informed decisions about water management. The regional council of Southland, Environment Southland, is required to make changes under their water quality policy in order to comply with the requirements for the New National Standards for Freshwater to consult with Maori to determine strategies for decision making. This requires an approach that includes traditional knowledge combined with scientific knowledge in the decision-making process. This study provided the scientific data that can be used in future for decision making on fresh water springs combined with traditional values for this particular area. Several parameters have been tested in situ as well as in a laboratory. Parameters such as temperature, salinity, electrical conductivity, Total Dissolved Solids, Total Kjeldahl Nitrogen, Total Phosphorus, Total Suspended Solids, and Escherichia coli among others show that recorded values of all test parameters fall within recommended ANZECC guidelines and Environment Southland standards and do not raise any concerns for the water quality of the springs and the river at the moment. However, the destruction of natural areas, particularly due to changes in farming practices, and the changes to water quality by the introduction of Didymosphenia geminate (Didymo) means Māori have already lost many of their traditional mahinga kai (food sources). There is a major change from land use such as sheep farming to dairying in Southland which puts freshwater resources under pressure. It is, therefore, important to draw on traditional knowledge and spirituality alongside scientific knowledge to protect the waters of the Mararoa River and waipuna. This study hopes to contribute to scientific knowledge to preserve the cultural values of these significant waters.

Keywords: cultural values, freshwater springs, Maori, water quality

Procedia PDF Downloads 282

Authors: S. Sakhri

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Background: The use of Zoledronic acid (ZA) is an established place in the treatment of malignant tumors with a predilection for the skeleton of interest (in particular metastasis). Although the main target of Zoledronic acid was osteoclasts, there are preclinical data suggest that Zoledronic acid may have an antitumor effect on cells other than osteoclasts, including tumor cells. Antitumor activity, including the inhibition of tumor cell growth and the induction of apoptosis of tumor cells, inhibition of tumor cell adhesion and invasion, and anti-angiogenic effects have been demonstrated. Methods. From (2012 to 2014), 438 patients were included respondents the inclusion criteria, respectively. This is a prospective study over a 4 year period. Of all patients (N=438), 432 received neoadjuvant chemotherapy with Zoledronic acid. The primary end point was the pathologic complete response in advancer breast cancer stage. The secondary end point is to evaluate Clinical response according to RECIST criteria; estimate the bone density before and at the end of chemotherapy in women with locally advanced breast cancer, Toxicity Evaluation and Overall survival using Kaplan-Meier and log test. Result: The Objective response rate was 97% after (C4) with 3% stabilizations and 99, 3% of which 0.7% C8 after stabilization. The clinical complete response was 28% after C4 respectively, and 46.8% after C8, the pathologic complete response rate was 40.13% according to the classification Sataloff. We observed that the pathologic complete response rate was the most raised in the group including Her2 (luminal Her2 and Her2) the lowest in the triple negative group as classified by Sataloff. We found that the pCR is significantly higher in the age group (35-50 years) with 53.17%. Those who have more than 50 years in 2nd place with 27.7% and the lower in young woman 35 years pCR was 19%, not statistically significant, -The pCR was also in favor of the menopausal group in 51, 4%, and 48, 55% for non-menopausal women. The average duration of overall survival was also significantly in the subgroup (Luminal -Her2, Her2) compared with triple negative. It is 47.18 months in the luminal group vs. 38.95 in the triple negative group. -Was observed in our study a difference in quality of life between (C1) was the admission of the patient, and after (C8), we found an increase in general signs and a deterioration in the psychological state C1, in contrast to the C8 these general signs and mental status improves, up to 12, and 24 months. Conclusion The results of this study suggest that the addition of ZA to néoadjuvant CT has potential anti-cancer benefit in patients (Luminal -Her2, Her2) compared with triple negative with or without menopause status.

Keywords: HER2+, RH+, breast cancer, tyrosine kinase

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Authors: Meera Tandan, Mohan Timilsina, Martin Cormican, Akke Vellinga

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Background: In general practice, many infections are treated empirically without microbiological confirmation. Understanding susceptibility of antimicrobials during empirical prescribing can be helpful to reduce inappropriate prescribing. This study aims to apply a prediction model using a decision tree approach to predict the antimicrobial resistance (AMR) of urinary tract infections (UTI) based on non-clinical features of patients over 65 years. Decision tree models are a novel idea to predict the outcome of AMR at an initial stage. Method: Data was extracted from the database of the microbiological laboratory of the University Hospitals Galway on all antimicrobial susceptibility testing (AST) of urine specimens from patients over the age of 65 from January 2011 to December 2014. The primary endpoint was resistance to common antimicrobials (Nitrofurantoin, trimethoprim, ciprofloxacin, co-amoxiclav and amoxicillin) used to treat UTI. A classification and regression tree (CART) model was generated with the outcome ‘resistant infection’. The importance of each predictor (the number of previous samples, age, gender, location (nursing home, hospital, community) and causative agent) on antimicrobial resistance was estimated. Sensitivity, specificity, negative predictive (NPV) and positive predictive (PPV) values were used to evaluate the performance of the model. Seventy-five percent (75%) of the data were used as a training set and validation of the model was performed with the remaining 25% of the dataset. Results: A total of 9805 UTI patients over 65 years had their urine sample submitted for AST at least once over the four years. E.coli, Klebsiella, Proteus species were the most commonly identified pathogens among the UTI patients without catheter whereas Sertia, Staphylococcus aureus; Enterobacter was common with the catheter. The validated CART model shows slight differences in the sensitivity, specificity, PPV and NPV in between the models with and without the causative organisms. The sensitivity, specificity, PPV and NPV for the model with non-clinical predictors was between 74% and 88% depending on the antimicrobial. Conclusion: The CART models developed using non-clinical predictors have good performance when predicting antimicrobial resistance. These models predict which antimicrobial may be the most appropriate based on non-clinical factors. Other CART models, prospective data collection and validation and an increasing number of non-clinical factors will improve model performance. The presented model provides an alternative approach to decision making on antimicrobial prescribing for UTIs in older patients.

Keywords: antimicrobial resistance, urinary tract infection, prediction, decision tree

Procedia PDF Downloads 255

Authors: Matthew Cardeiro, Amalia D. Ardeljan, Lexi Frankel, Dianela Prado Escobar, Catalina Molnar, Omar M. Rashid

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Introduction: Enterococci comprise the natural flora of nearly all animals and are ubiquitous in food manufacturing and probiotics. However, its role in the microbiome remains controversial. The gut microbiome has shown to play an important role in immunology and cancer. Further, recent data has suggested a relationship between gut microbiota and breast cancer. These studies have shown that the gut microbiome of patients with breast cancer differs from that of healthy patients. Research regarding enterococcus infection and its sequala is limited, and further research is needed in order to understand the relationship between infection and cancer. Enterococcus may prevent the development of breast cancer (BC) through complex immunologic and microbiotic adaptations following an enterococcus infection. This study investigated the effect of enterococcus infection and the incidence of BC. Methods: A retrospective study (January 2010- December 2019) was provided by a Health Insurance Portability and Accountability Act (HIPAA) compliant national database and conducted using a Humans Health Insurance Database. International Classification of Disease (ICD) 9th and 10th codes, Current Procedural Terminology (CPT), and National Drug Codes were used to identify BC diagnosis and enterococcus infection. Patients were matched for age, sex, Charlson Comorbidity Index (CCI), antibiotic treatment, and region of residence. Chi-squared, logistic regression, and odds ratio were implemented to assess the significance and estimate relative risk. Results: 671 out of 28,518 (2.35%) patients with a prior enterococcus infection and 1,459 out of 28,518 (5.12%) patients without enterococcus infection subsequently developed BC, and the difference was statistically significant (p<2.2x10⁻¹⁶). Logistic regression also indicated enterococcus infection was associated with a decreased incidence of BC (RR=0.60, 95% CI [0.57, 0.63]). Treatment for enterococcus infection was analyzed and controlled for in both enterococcus infected and noninfected populations. 398 out of 11,523 (3.34%) patients with a prior enterococcus infection and treated with antibiotics were compared to 624 out of 11,523 (5.41%) patients with no history of enterococcus infection (control) and received antibiotic treatment. Both populations subsequently developed BC. Results remained statistically significant (p<2.2x10-16) with a relative risk of 0.57 (95% CI [0.54, 0.60]). Conclusion & Discussion: This study shows a statistically significant correlation between enterococcus infection and a decrease incidence of breast cancer. Further exploration is needed to identify and understand not only the role of enterococcus in the microbiome but also the protective mechanism(s) and impact enterococcus infection may have on breast cancer development. Ultimately, further research is needed in order to understand the complex and intricate relationship between the microbiome, immunology, bacterial infections, and carcinogenesis.

Keywords: breast cancer, enterococcus, immunology, infection, microbiome

Procedia PDF Downloads 173

Authors: Sarah E. Nelson, Casey Weiner, Alexander Sigmon, Jun Hua, Haris I. Sair, Jose I. Suarez, Robert D. Stevens

Abstract:

Graph-theoretical information from structural connectomes indicated significant connectivity changes and improved acute prognostication in a Random Forest (RF) model in aneurysmal subarachnoid hemorrhage (aSAH), which can lead to significant morbidity and mortality and has traditionally been fraught by poor methods to predict outcome. This study’s hypothesis was that structural connectivity changes occur in canonical brain networks of acute aSAH patients, and that these changes are associated with functional outcome at six months. In a prospective cohort of patients admitted to a single institution for management of acute aSAH, patients underwent diffusion tensor imaging (DTI) as part of a multimodal MRI scan. A weighted undirected structural connectome was created of each patient’s images using Constant Solid Angle (CSA) tractography, with 176 regions of interest (ROIs) defined by the Johns Hopkins Eve atlas. ROIs were sorted into four networks: Default Mode Network, Executive Control Network, Salience Network, and Whole Brain. The resulting nodes and edges were characterized using graph-theoretic features, including Node Strength (NS), Betweenness Centrality (BC), Network Degree (ND), and Connectedness (C). Clinical (including demographics and World Federation of Neurologic Surgeons scale) and graph features were used separately and in combination to train RF and Logistic Regression classifiers to predict two outcomes: dichotomized modified Rankin Score (mRS) at discharge and at six months after discharge (favorable outcome mRS 0-2, unfavorable outcome mRS 3-6). A total of 56 aSAH patients underwent DTI a median (IQR) of 7 (IQR=8.5) days after admission. The best performing model (RF) combining clinical and DTI graph features had a mean Area Under the Receiver Operator Characteristic Curve (AUROC) of 0.88 ± 0.00 and Area Under the Precision Recall Curve (AUPRC) of 0.95 ± 0.00 over 500 trials. The combined model performed better than the clinical model alone (AUROC 0.81 ± 0.01, AUPRC 0.91 ± 0.00). The highest-ranked graph features for prediction were NS, BC, and ND. These results indicate reorganization of the connectome early after aSAH. The performance of clinical prognostic models was increased significantly by the inclusion of DTI-derived graph connectivity metrics. This methodology could significantly improve prognostication of aSAH.

Keywords: connectomics, diffusion tensor imaging, graph theory, machine learning, subarachnoid hemorrhage

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