Search results for: comparing partitions

Authors: Arya Farjand

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The Nihewan Basin is a critical region in order to understand the Plio-Pleistocene paleoenvironment and its fauna in Northern China. The rich fossiliferous, fluvial-lacustrine sediments around the Nihewan Village hosted the specimens known as the Classic Nihewan Fauna. The primary excavations in the early 1920-30s produced more than 2000 specimens housed in Tianjin and Paris Museum. Nevertheless, the exact locality of excavations, fossil beds, and the reliable ages remained ambiguous until recent paleomagnetic studies and extensive work in conjunction sites. In this study, for the first time, we successfully relocated some of the original excavation sites. We reexamined more than 1500 specimens held in Tianjin Museum and cited their locality numbers and properties. During the field-season of 2017-2019, we visited the Xiashagou Valley. By reading the descriptions of the original site, utilization of satellite pictures, and comparing them with the current geomorphology of the area, we ensured the exact location of 26 of these sites and 17 fossil layers. Furthermore, by applying the latest technologies, such as GPS, Compass, digital barometers, laser measurer, and Abney level, we ensured the accuracy of the measurement. We surveyed 133-meter thickness of the deposits. Ultimately by applying the available Paleomagnetic data for this section, we estimated the ages of different horizons. The combination of our new data and previously published researches present a unique age control for the Classic Nihewan Fauna. These findings prove the hypothesis in which the Classic Nihewan Fauna belongs to different horizons, ranging from before Reunion up to after Olduvai earth geomagnetic field excursion (2.2-1.7 Mya).

Keywords: classic Nihewan basin fauna, Olduvai excursion, Pleistocene, stratigraphy

Procedia PDF Downloads 141

Authors: Jungbin Lim, Bohee Kang, Heelim Lee, Sunjin Kim, GeumHee Choi, Jae-Suk Jung, Suk Ji

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Nonsurgical periodontal therapies have, for several decades, been the basis of periodontal treatment concepts. The aim of this paper is to investigate the effectiveness of non-surgical periodontal therapy according to the severity of periodontitis disease. Methods: Retrospective data of patients who visited Department of periodontics in Ajou University Medical Center from 2016 to 2022 were collected. Among the patients, those who took full mouth examination of clinical parameters and non-surgical periodontal therapy were chosen for this study. Selected patients were divided into initial, moderate, and severe periodontitis based on severity and complexity of management (2018 World Workshop EFP/AAP consensus). Recall visits with clinical periodontal examination were scheduled for 1,2,3 months or 1,3,6 months after the treatment. The results were evaluated by recordings of mean probing pocket depth (mean PD), mean clinical attachment levels (mean CAL), bleeding on probing (BOP%), mean gingival index (mean GI), mean regression, mean sulcus bleeding index (mean SBI), mean plaque scores (mean PI). All statistical analyses were performed with R software, version 4.3.0. A level of significance, P<0.05, was considered to be statistically significant. Results: A total of 92 patients were included in this study. 15 patients were diagnosed as initial periodontitis, 14 moderate periodontitis, and 63 severe periodontitis. The all parameters except for mean recession decreased over time in all groups. The amount of mean PD decreased were the greatest in severe periodontitis group followed by moderate and initial, which was found to be statistically significant. The changes of mean PD were 0.15±0.05 mm, 0.37±0.06 mm, and 1.01±0.07 mm (initial, moderate, and severe, respectively, P<0.001). When comparing before and after treatment, the reductions in BOP(%), mean GI, mean SBI, and mean PI were statistically significant. Conclusion: All patients who received non-surgical periodontal therapy showed periodontal healing in terms of improvements in clinical parameters, and it was greater in the severe group.

Keywords: periodontology, clinical periodontology, oral treatment, comprehensive preventive dentistry, non-surgical periodontal therapy

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Authors: Nico Rosamilia

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The study evaluates the importance of non-financial disclosure practices for regulators, investors, businesses, and markets. It aims to create a sector-specific set of indicators for environmental, social, and governance (ESG) performances alternative to the ratings of the agencies. The existing literature extensively studies the implementation of ESG rating systems. Conversely, this study has a twofold outcome. Firstly, it should generalize incentive systems and governance policies for ESG and sustainable principles. Therefore, it should contribute to the EU Sustainable Finance Disclosure Regulation. Secondly, it concerns the market and the investors by highlighting successful sustainable investing. Indeed, the study contemplates the effect of ESG adoption practices on corporate value. The research explores the asset pricing angle in order to shed light on the fragmented argument on the finance of ESG. Investors may be misguided about the positive or negative effects of ESG on performances. The paper proposes a different method to evaluate ESG performances. By comparing the results of a traditional econometric approach (Lasso) with a machine learning algorithm (Random Forest), the study establishes a set of indicators for ESG performance. Therefore, the research also empirically contributes to the theoretical strands of literature regarding model selection and variable importance in a finance framework. The algorithms will spit out sector-specific indicators. This set of indicators defines an alternative to the compounded scores of ESG rating agencies and avoids the possible offsetting effect of scores. With this approach, the paper defines a sector-specific set of indicators to standardize ESG disclosure. Additionally, it tries to shed light on the absence of a clear understanding of the direction of the ESG effect on corporate value (the problem of endogeneity).

Keywords: ESG ratings, non-financial information, value of firms, sustainable finance

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Authors: Syrine Bassi

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Sound symbolism has been able to give us an exciting new tool to target consumers’ brand perception. It acts on a subconscious level making them less likely to reject the implicit message delivered by the sound of the brand name. Most of the research conducted in the field was focused on the English language as it is the language used for international branding campaigns and global companies. However, more research is examining the sound symbolism in other languages and comparing it to the English language findings. Besides, researchers have been able to study luxury brand names and spot out the patterns used in them to provoke luxury and sophistication. It stands to a reason to connect the luxury brand names and the local language’s sound effects since a considerable number of these brands are promoting the origin of the Maison, therefore, have names in foreign languages. This study was established around the Hungarian luxury brand names. It aims to spot out the patterns used in these names that connect to the previous findings of luxury sound effects and also the differences. We worked with a non-Hungarian speaking sample who had some basic knowledge of the language just to make sure they were able to correctly pronounce the names. The results have shown both similarities and differences when it comes to perceiving luxury based on the brand name. As the Hungarian language can be qualified as a saturated language, consonant wise, it was easy to feed the luxury feeling only by using designers' names, however, some complicated names were too difficult and repulsive to consider as luxurious. On the other hand, oversimplifying some names did not convey the desired image as it was too simple and easy. Overall, some sounds have been proved to be linked to luxury as the literature suggests, the difficulty of pronunciation has also proved effective since it highlights the distant feeling consumers crave when looking for luxury. These results suggest that sound symbolism can set up an aura of luxury when used properly, leveraging each languages’ convenient assets.

Keywords: hungarian language, linguistics, luxury brands, sound symbolism

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Authors: Carmela Perta

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Among the studies flourished in the field of historical sociolinguistics, mainly in the strand devoted to English history, during its Medieval and early modern phases, multilingual texts had been analysed using theories and models coming from contact linguistics, thus applying synchronic models and approaches to the past. This is true also in the case of contact phenomena which would transcend the writing level involving the language systems implicated in contact processes to the point of perceiving a new variety. This is the case for medieval administrative-commercial texts in which, according to some Scholars, the degree of fusion of Anglo-Norman, Latin and middle English is so high a mixed code emerges, and there are recurrent patterns of mixed forms. Interesting is a collection of multilingual business writings by John Balmayn, an Englishman overseeing a large shipment in Tuscany, namely the Cantelowe accounts. These documents display various analogies with multilingual texts written in England in the same period; in fact, the writer seems to make use of the above-mentioned patterns, with Middle English, Latin, Anglo-Norman, and the newly added Italian. Applying an atomistic yet dynamic approach to the study of contact phenomena, we will investigate these documents, trying to explore the nature of the switching forms they contain from an intra-writer variation perspective. After analysing the accounts and the type of multilingualism in them, we will take stock of the assumed mixed code nature, comparing the characteristics found in this genre with modern assumptions. The aim is to evaluate the possibility to consider the switching forms as core elements of a mixed code, used as professional variety among merchant communities, or whether such texts should be analysed from a switching perspective.

Keywords: historical sociolinguistics, historical code switching, letters, medieval england

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Authors: Amir Reza Heydari, Yaser Jenab

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Coronary artery disease, a common cardiovascular disease, is attributed to the accumulation of cholesterol-based plaques in the coronary arteries, leading to atherosclerosis. This disease is associated with risk factors such as smoking, hypertension, diabetes, and elevated cholesterol levels, contributing to severe clinical consequences, including acute coronary syndromes and myocardial infarction. Treatment approaches such as from lifestyle interventions to surgical procedures like percutaneous coronary intervention and coronary artery bypass surgery. These interventions often employ stents, including bare-metal stents (BMS), drug-eluting stents (DES), and bioresorbable vascular scaffolds (BVS), each with its advantages and limitations. Computational tools have emerged as critical in optimizing stent designs and assessing their performance. The aim of this study is to provide an overview of the computational methods of studies based on the finite element (FE) method in the field of coronary stenting and discuss the potential for development and clinical application of stent devices. Additionally, the importance of assessing the ability of computational models is emphasized to represent real-world phenomena, supported by recent guidelines from the American Society of Mechanical Engineers (ASME). Validation processes proposed include comparing model performance with in vivo, ex-vivo, or in vitro data, alongside uncertainty quantification and sensitivity analysis. These methods can enhance the credibility and reliability of in silico simulations, ultimately aiding in the assessment of coronary stent designs in various clinical contexts.

Keywords: atherosclerosis, materials, restenosis, review, validation

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Authors: Kamyar Maleki Bagherabadi, Torstein Aarseth Bø, Truls Flatberg, Olve Mo

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Hydrogen fuel cells and batteries are one of the promising solutions aligned with carbon emission reduction goals for the marine sector. However, the higher installation and operation costs of hydrogen-based systems compared to conventional diesel gensets raise questions about the appropriate hydrogen tank size, energy, and fuel consumption estimations. Ship designers need methodologies and tools to calculate energy and fuel consumption for different component sizes to facilitate decision-making regarding feasibility and performance for retrofits and design cases. The aim of this work is to compare three alternative modeling approaches for the estimation of energy and fuel consumption with various hydrogen tank sizes, battery capacities, and load-sharing strategies. A fishery vessel is selected as an example, using logged load demand data over a year of operations. The modeled power system consists of a PEM fuel cell, a diesel genset, and a battery. The methodologies used are: first, an energy-based model; second, considering load variations during the time domain with a rule-based Power Management System (PMS); and third, a load variations model and dynamic PMS strategy based on optimization with perfect foresight. The errors and potentials of the methods are discussed, and design sensitivity studies for this case are conducted. The results show that the energy-based method can estimate fuel and energy consumption with acceptable accuracy. However, models that consider time variation of the load provide more realistic estimations of energy and fuel consumption regarding hydrogen tank and battery size, still within low computational time.

Keywords: fuel cell, battery, hydrogen, hybrid power system, power management system

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Authors: Boutemak Khalida, Dahmani Siham

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Garden cress (Lepidium Sativum L.) belonging to the family Brassicaceae, is edible growing annual herb. Its various parts (roots, leaves and seeds) have been used to treat various human ailments. Its seed extracts have been screened for various biological activities like hypotensive, antimicrobial, bronchodilator, hypoglycaemic and antianemic. The aim of the present study is to optimize the process parameters (cellulase concentration and incubation time) of enzymatic pre-treatment of the garden cress seeds and to evaluate the effect of cellulase pre-treatment of the crushed seeds on the oil yield, physico-chemical properties and antibacterial activity and comparing to non-enzymatic method. The optimum parameters of cellulase pre-treatment were as follows: cellulase of 0,1% w/w and incubation time of 2h. After enzymatic pre-treatment, the oil was extracted by n-hexane for 1.5 h, the oil yield was 4,01% for cellulase pre-treatment as against 10,99% in the control sample. The decrease in yield might be caused a result of mucilage. Garden cress seeds are covered with a layer of mucilage which gels on contact with water. At the same time, the antibacterial activity was carried out using agar diffusion method against 4 food-borne pathogens (Escherichia coli, Salmonella typhi,Staphylococcus aureus, Bacillus subtilis). The results showed that bacterial strains are very sensitive to the oil with cellulase pre-treatment. Staphylococcus aureus is extremely sensitive with the largest zone of inhibition (40 mm), Escherichia coli and salmonella typhi had a very sensitive to the oil with a zone of inhibition (26 mm). Bacillus subtilizes is averagely sensitive which gave an inhibition of 16 mm. But it does not exhibit sensivity to the oil without enzymatic pre-treatment with a zone inhibition (< 8 mm). Enzymatic pre-treatment could be useful for antimicrobial activity of the oil, and hold a good potential for use in food and pharmaceutical industries.

Keywords: Lepidium sativum L., cellulase, enzymatic pretreatment, antibacterial activity.

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Authors: Clesse C., Lighezzolo-Alnot J., De Lavergne S.

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Considered as the most common surgical procedure worldwide, episiotomy can be defined as an incision around the vulva performed to enlarge it, in the aim of preventing the traumatic rupture of the perineum during childbirth. Rather mediatized, this practice raises many questions in the field of mental health, relayed by different users and health professionals. Today, is topicality is moderately hectic since many queries about the prophylactic exercise of episiotomy are subject to a relative consensus, particularly since WHO advocated in 1996 that only 10% of childbirths should involve an episiotomy. This indicator appeared after the publication of numerous results from randomized clinical trials. Unfortunately, these papers seem mostly centered about somatic impacts of episiotomy. From the side of psychological studies, they mostly integrate a major clinical methodological bias, especially considering that every primiparous woman is identical to the others face to the experience of parturition. In the aim to fill this lack of knowledge, we developed a longitudinal research starting in the 7th month of pregnancy and ending one year after delivery. We are studying in a comparative way different possible psychological consequences inherent to the use of episiotomy. To do this, we use a standardized methodology which combines semi-structured clinical interviews (IRMAG, IRMAN ...), free clinical interviews, a projective test (Rorschach) and five questionnaires (QIC, EPDS, CPQ WOMBLSQ4, SF36). Therefore, we can comprehend with shrewdness the question of psychic impacts of episiotomy in a qualitative and quantitative way by comparing it to other obstetric interventions. In this paper, we will present the first results obtained about a population of twenty-two primiparous women by focusing on body image, sexuality, quality of life, depressive affects, post-traumatic stress disorder and investment of the maternal role. Finally, we will consider the different implications and perspectives of this research which could improve the public health policies in the field of perinatal care.

Keywords: assessment, episiotomy, mental health, psychical impacts

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Authors: Wanying Xie

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Under the background of the increasing Sino-US trade friction, the two nations pay more attention to the medias’ words. This paper mainly studies the causality, effectiveness, and influence of discourse construction between traditional media and social media. Based on the Network Agenda Setting theory, a kind of associative memory pattern in Psychology, who focuses on how media affect audiences’ cognition of issues and attributes, as well as the significance of the relation between people and matters. The date of the sample chosen in this paper ranges from March 23, 2018, to April 30, 2019. A total of 395 Tweets of Donald Trump are obtained, and 731 related reports are collected from the mainstream American newspapers including New York Times, the Washington Post and the Washington Street, by using Factiva and other databases. The sample data are processed by MAXQDA while the media discourses are analyzed by SPSS and Cite Space, with an aim to study: 1) whether the inter-media discourse construction exists; 2) which media (traditional media V.S. social media) is dominant; 3) the causality between two media. The results show: 1) the discourse construction between three American mainstream newspapers and Donald Trump's Twitter is proved in some periods; 2) the dominant position is extremely depended on the events; 3) the causality between two media is decided by many reasons. New media technology shortens the time of agenda-setting effect to one day or less. By comparing the specific relation between the three major American newspapers and Donald Trump’s Twitter, whose popularity and influence could be reflected. Hopefully, this paper could enable readers to have a more comprehensive understanding of the international media language and political environment.

Keywords: discourse construction, media language, network agenda-setting theory, sino-us trade friction

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Authors: Soheila Sadeghi

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In construction projects, predicting project performance metrics accurately is essential for effective management and successful delivery. However, conventional methods often depend on fixed baseline plans, disregarding the evolving nature of project progress and external influences. To address this issue, we introduce a distinct approach based on machine learning to forecast key performance indicators, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category within an urban road reconstruction project. Our proposed model leverages time series forecasting techniques, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance by analyzing historical data and project progress. Additionally, the model incorporates external factors, including weather patterns and resource availability, as features to improve forecast accuracy. By harnessing the predictive capabilities of machine learning, our performance forecasting model enables project managers to proactively identify potential deviations from the baseline plan and take timely corrective measures. To validate the effectiveness of the proposed approach, we conduct a case study on an urban road reconstruction project, comparing the model's predictions with actual project performance data. The outcomes of this research contribute to the advancement of project management practices in the construction industry by providing a data-driven solution for enhancing project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, schedule variance, earned value management

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Authors: Mariana Roberta Ribeiro, Isabela de Cássia Caramello, Roberto Saverio Souza Costa

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Currently, one of the most important environmental problems is soil degradation. This wear is the result of inadequate agricultural practices, with water erosion as the main agent. As the runoff water is concentrated in certain points, it can reach a more advanced stage, which are the gullies. In view of this, the objective of this work was to evaluate which methodology is most suitable for the purpose of elaborating a project for the recovery of a gully, relating work time, data reliability, and the final cost. The work was carried out on a rural road in Monte Alto - SP, where there is 0.30 hectares of area under the influence of a gully. For the evaluation, an aerophotogrammetric survey was used with RPA, with georeferenced points, and with a GNSS L1/L2 receiver. To assess the importance of georeferenced points, there was a comparison of altimetric data using the support points with altimetric data using only the aircraft's internal GPS. Another method used was the survey by conventional topography, where coordinates were collected by total station and L1/L2 Geodetic GPS receiver. Statistical analysis was performed using analysis of variance (ANOVA) using the F test (p<0.05), and the means between treatments were compared using the Tukey test (p<0.05). The results showed that the surveys carried out by aerial photogrammetry and by conventional topography showed no significant difference for the analyzed parameters. Considering the data presented, it is possible to conclude that, when comparing the parameters of accuracy, the final volume of the gully, and cost, for the purpose of elaborating a project for the recovery of a gully, the methodologies of aerial photogrammetric survey and conventional topography do not differ significantly. However, when working time, use of labor, and project detail are compared, the aerial photogrammetric survey proves to be more viable.

Keywords: drones, erosion, soil conservation, technology in agriculture

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Authors: Jisong Ryu, Woosik Lee, Yonggu Jang

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The paper discusses the process of establishing a reliable test bed for verifying the usability of Ground Penetrating Radar (GPR) exploration equipment based on an integrated underground spatial map in Korea. The aim of this study is to construct a test bed consisting of metal and non-metal pipelines to verify the performance of GPR equipment and improve the accuracy of the underground spatial integrated map. The study involved the design and construction of a test bed for metal and non-metal pipe detecting tests. The test bed was built in the SOC Demonstration Research Center (Yeoncheon) of the Korea Institute of Civil Engineering and Building Technology, burying metal and non-metal pipelines up to a depth of 5m. The test bed was designed in both vehicle-type and cart-type GPR-mounted equipment. The study collected data through the construction of the test bed and conducting metal and non-metal pipe detecting tests. The study analyzed the reliability of GPR detecting results by comparing them with the basic drawings, such as the underground space integrated map. The study contributes to the improvement of GPR equipment performance evaluation and the accuracy of the underground spatial integrated map, which is essential for urban planning and construction. The study addressed the question of how to verify the usability of GPR exploration equipment based on an integrated underground spatial map and improve its performance. The study found that the test bed is reliable for verifying the performance of GPR exploration equipment and accurately detecting metal and non-metal pipelines using an integrated underground spatial map. The study concludes that the establishment of a test bed for verifying the usability of GPR exploration equipment based on an integrated underground spatial map is essential. The proposed Korean-style test bed can be used for the evaluation of GPR equipment performance and support the construction of a national non-metal pipeline exploration equipment performance evaluation center in Korea.

Keywords: Korea-style GPR testbed, GPR, metal pipe detecting, non-metal pipe detecting

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Authors: Ji-Hoon Byeon, Kwon-Hee Lee

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Strainer filter serves to block the inflow of impurities while mixed fluid is entering or exiting the piping. The filter of the strainer has a perforated structure, so that the pressure drop and the velocity change necessarily occur when the mixed fluid passes through the filter. It is possible to predict the pressure drop and velocity change of the strainer by numerical analysis by implementing all the perforated plates. However, if the size of the perforated plate exceeds a certain size, it is difficult to perform the numerical analysis, and sometimes we cannot guarantee its accuracy. In this study, we tried to predict the pressure drop and velocity change by using the porous media technique to obtain the equivalent resistance without actual implementation of the perforation shape of the strainer. Ansys-CFX, a commercial software, is used to perform the numerical analysis. The analysis procedure is as follows. Firstly, the unit pattern of the perforated plate is modeled, and the pressure drop is analyzed by varying the velocity by symmetry of the wall surface. Secondly, since the equation for obtaining resistance is a quadratic equation of pressure having unknown velocity, the viscous resistance and the inertia resistance of the perforated plate are obtained from the relationship between pressure and speed. Thirdly, by using the calculated resistance values, the values are substituted into the flat plate implemented as a two-dimensional porous media, and the accuracy is verified by comparing the pressure drop and the velocity change. Fourthly, the pressure drop and velocity change in the whole strainer are analyzed by using the resistance values obtained on the perforated plate in the actual whole strainer model. Using the porous media technique, it is found that pressure drop and velocity change can be predicted in relatively short time without modeling the overall shape of the filter. Acknowledgements: This work was supported by the Valve Center from the Regional Innovation Center(RIC) Program of Ministry of Trade, Industry & Energy (MOTIE).

Keywords: strainer, porous media, CFD, numerical analysis

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Authors: Radovan Cobanovic, Milica Rankov-Sicar

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The fresh cake is in the group of perishable food which cannot be kept a long period of time. The study of sustainability has been done in order to extend the shelf-life of the product which was 10 days. According to the plan of sustainability, it was defined that 5 samples had to be stored for 20 days at max +8°C and analyzed every 5th day from the day of reception until the 20th day. The shelf life of cake has expired during the study of sustainability in the period between 10th and 20th day of analyses. Cake samples were subjected to sensory analysis (appearance, odor, taste, color, aroma) and bacteriological analysis (Listeria monocytogenes, Salmonella spp. and Enterobacteriaceae) according to Serbian state regulation. All analysis were tested according to ISO methodology: sensory analysis ISO 6658, Listeria monocytogenes ISO 11290-1, Salmonella spp ISO 6579, and Enterobacteriaceae ISO 21258-2. Analyses showed that after ten days of storage at a temperature defined by the manufacturers and within the product's shelf life, the cake did not have any noticeable changes in sensory characteristics. Smell and taste are unaffected there was no presence of strange smell or taste. As far as microbiological analyses are concerned, neither one pathogen was detected and number of Enterobacteriaceae was at level less than 102 cfu/g. After expiry of shelf life in a period of 15th and 20th day of storage, the sensory analysis showed the presence of strange sour-milky smell and rancid taste. Concerning microbiological analyses, there still were not positive results for pathogen microorganisms but the number of Enterobacteriaceae was at level more than 103cfu/g. Reviewing the results of sensory analysis indicates that it is not recommended to extend the shelf-life of the product comparing to the already defined shelf-life because occurred changes may adversely affect the consumer desire for the choice of this product.

Keywords: confectionary product, extension of shelf life, sensory and microbiological analyses, sustainability

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Authors: Zeinab Gharibi, B. Stoevesandt, J. Peinke

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Long term surface erosion of wind turbine blades, especially at the leading edge, impairs aerodynamic performance; therefore, lowers efficiency of the blades mostly in the high-speed rotor tip regions. Blade protection provides significant improvements in annual energy production, reduces costly downtime, and protects the integrity of the blades. However, this protection still influences the aerodynamic behavior, and broadband noise caused by interaction between the impinging turbulence and blade’s leading edge. This paper presents an extensive numerical aeroacoustics approach by investigating the sound power spectra of the eroded and coated NACA 64-618 wind turbine airfoil and evaluates aeroacoustics improvements after the protection procedure. Using computational fluid dynamics (CFD), different quasi 2D numerical grids were implemented and special attention was paid to the refinement of the boundary layers. The noise sources were captured and decoupled with acoustic propagation via the derived formulation of Curle’s analogy implemented in OpenFOAM. Therefore, the noise spectra were compared for clean, coated and eroded profiles in the range of chord-based Reynolds number (1.6e6 ≤ Re ≤ 11.5e6). Angle of attack was zero in all cases. Verifications were conducted for the clean profile using available experimental data. Sensitivity studies for the far-field were done on different observational positions. Furthermore, beamforming studies were done simulating an Archimedean spiral microphone array for far-field noise directivity patterns. Comparing the noise spectra of the coated and eroded geometries, results show that, coating clearly improves aerodynamic and acoustic performance of the eroded airfoil.

Keywords: computational fluid dynamics, computational aeroacoustics, leading edge, OpenFOAM

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Authors: Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy

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Fake news and false information are big challenges of all types of media, especially social media. There is a lot of false information, fake likes, views and duplicated accounts as big social networks such as Facebook and Twitter admitted. Most information appearing on social media is doubtful and in some cases misleading. They need to be detected as soon as possible to avoid a negative impact on society. The dimensions of the fake news datasets are growing rapidly, so to obtain a better result of detecting false information with less computation time and complexity, the dimensions need to be reduced. One of the best techniques of reducing data size is using feature selection method. The aim of this technique is to choose a feature subset from the original set to improve the classification performance. In this paper, a feature selection method is proposed with the integration of K-means clustering and Support Vector Machine (SVM) approaches which work in four steps. First, the similarities between all features are calculated. Then, features are divided into several clusters. Next, the final feature set is selected from all clusters, and finally, fake news is classified based on the final feature subset using the SVM method. The proposed method was evaluated by comparing its performance with other state-of-the-art methods on several specific benchmark datasets and the outcome showed a better classification of false information for our work. The detection performance was improved in two aspects. On the one hand, the detection runtime process decreased, and on the other hand, the classification accuracy increased because of the elimination of redundant features and the reduction of datasets dimensions.

Keywords: clustering, fake news detection, feature selection, machine learning, social media, support vector machine

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Authors: A. Farhad Sadri, B. Ali Farhadi, C. Nasim Shalamzari

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Waste management is a principle of urban and environmental governance. Waste management in Tehran metropolitan requires good strategies for better governance. Using of good urban governance principles together with eight main indexes can be an appropriate base for this aim. One of the reasonable tools in this field is usage of SWOT methods which provides possibility of comparing the opportunities, threats, weaknesses, and strengths by using IFE and EFE matrixes. The results of the above matrixes, respectively 2.533 and 2.403, show that management system of Tehran metropolitan wastes has performed weak regarding to internal factors and has not have good performance regarding using the opportunities and dealing with threats. In this research, prioritizing and describing the real value of each 24 strategies in waste management in Tehran metropolitan have been surveyed considering good governance derived from Quantitative Strategic Planning Management (QSPM) by using Kolomogrof-Smirnoff by 1.549 and significance level of 0.073 in order to define normalization of final values and all of the strategies utilities and Variance Analysis of ANOVA has been calculated for all SWOT strategies. Duncan’s test results regarding four WT, ST, WO, and SO strategies show no significant difference. In addition to mean comparison by Duncan method in this research, LSD (Lowest Significant Difference test) has been used by probability of 5% and finally, 7 strategies and final model of Tehran metropolitan waste management strategy have been defined. Increasing the confidence of people with transparency of budget, developing and improving the legal structure (rule-oriented and law governance, more responsibility about requirements of private sectors, increasing recycling rates and real effective participation of people and NGOs to improve waste management (contribution) and etc, are main available strategies which have been achieved based on good urban governance management principles.

Keywords: waste, strategy, environmental management, urban good governance, SWOT

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Authors: Shuyu Zhang

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The waterfront historical district, as a type of historical districts on the verge of waters such as the sea, lake, and river, have a relatively special urban form. In the past preservation and renewal of traditional historic districts, there have been many discussions on the land range, and the waterfront and marginal spaces are easily overlooked. However, the waterfront space of the historic districts, as a cultural landscape heritage combining historical buildings and landscape elements, has strong ecological and sustainable values. At the same time, Suzhou and Venice, as sister water cities in history, have more waterfront spaces that can be compared in urban form and other levels. Therefore, this paper focuses on the waterfront historic districts in Venice and Suzhou, establishes quantitative evaluation indicators for environmental perception, makes analogies, and promotes the renewal and activation of the entire historical district by improving the spatial quality and vitality of the waterfront area. First, this paper uses multi-source data for analysis, such as Baidu Maps and Google Maps API to crawl the street view of the waterfront historic districts, uses machine learning algorithms to analyze the proportion of cultural landscape elements such as green viewing rate in the street view pictures, and uses space syntax software to make quantitative selectivity analysis, so as to establish environmental perception evaluation indicators for the waterfront historic districts. Finally, by comparing and summarizing the waterfront historic districts in Venice and Suzhou, it reveals their similarities and differences, characteristics and conclusions, and hopes to provide a reference for the heritage preservation and renewal of other waterfront historic districts.

Keywords: waterfront historical district, cultural landscape, perception, multi-source Data

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Authors: Titanilla Komenda

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Human-machine-collaboration defines a direct interaction between humans and machines to fulfil specific tasks. Those so-called collaborative machines are used without fencing and interact with humans in predefined workspaces. Even though, human-machine-collaboration enables a flexible adaption to variable degrees of freedom, industrial applications are rarely found. The reasons for this are not technical progress but rather limitations in planning processes ensuring safety for operators. Until now, humans and machines were mainly considered separately in the planning process, focusing on ergonomics and system performance respectively. Within human-machine-collaboration, those aspects must not be seen in isolation from each other but rather need to be analysed in interaction. Furthermore, a simulation model is needed that can validate the system performance and ensure the safety for the operator at any given time. Following on from this, a holistic simulation model is presented, enabling a simulative representation of collaborative tasks – including both, humans and machines. The presented model does not only include a geometry and a motion model of interacting humans and machines but also a numerical behaviour model of humans as well as a Boole’s probabilistic sensor model. With this, error scenarios can be simulated by validating system behaviour in unplanned situations. As these models can be defined on the basis of Failure Mode and Effects Analysis as well as probabilities of errors, the implementation in a collaborative model is discussed and evaluated regarding limitations and simulation times. The functionality of the model is shown on industrial applications by comparing simulation results with video data. The analysis shows the impact of considering human factors in the planning process in contrast to only meeting system performance. In this sense, an optimisation function is presented that meets the trade-off between human and machine factors and aids in a successful and safe realisation of collaborative scenarios.

Keywords: human-machine-system, human-robot-collaboration, safety, simulation

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Authors: Yujie Wei

Abstract:

Twitter uses a variety of narrative methods (e.g., messages, featured videos, music, and actual events) to strengthen its cultivation effect. Consumers are receiving mass-produced brand stores or images made by brand managers according to strict market specifications. Drawing on the cultivation theory, this quantitative research investigates how following a brand on Twitter for 12 weeks can cultivate their attitude toward the brand and influence their purchase intentions. We conducted three field experiments on Twitter to test the cultivation effects of following a brand for 12 weeks on consumer attitude toward the followed brand. The cultivation effects were measured by comparing the changes in consumer attitudes before and after they have followed a brand over time. The findings of our experiments suggest that when consumers are exposed to a brand’s stable, pervasive, and recurrent tweets on Twitter for 12 weeks, their attitude toward a brand can be significantly changed, which confirms the cultivating effects on consumer attitude. Also, the results indicate that branding activities on Twitter, when properly implemented, can be very effective in changing consumer attitudes toward a brand, increasing the purchase intentions, and increasing their willingness to spread the word-of-mouth for the brand on social media. The cultivation effects are moderated by brand type and consumer age. The research provides three major marketing implications. First, Twitter marketers should create unique content to engage their brand followers to change their brand attitude through steady, cumulative exposure to the branding activities on Twitter. Second, there is a significant moderating effect of brand type on the cultivation effects, so Twitter marketers should align their branding content with the brand type to better meet the needs and wants of consumers for different types of brands. Finally, Twitter marketers should adapt their tweeting strategies according to the media consumption preferences of different age groups of their target markets. This empirical research proves that content is king.

Keywords: tweeting, cultivation theory, consumer brand attitude, purchase intentions, word-of-mouth

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Authors: Choukri Lekbir, Mira Mokhtari

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Hydrogen-Materials interaction and mechanisms can be modeled at nano scale by quantum methods. In this work, the effect of hydrogen on the electronic properties of a cluster material model «nickel» has been studied by using of density functional theoretical (DFT) method. Two types of clusters are optimized: Nickel and hydrogen-nickel system. In the case of nickel clusters (n = 1-6) without presence of hydrogen, three types of electronic structures (neutral, cationic and anionic), have been optimized according to three basis sets calculations (B3LYP/LANL2DZ, PW91PW91/DGDZVP2, PBE/DGDZVP2). The comparison of binding energies and bond lengths of the three structures of nickel clusters (neutral, cationic and anionic) obtained by those basis sets, shows that the results of neutral and anionic nickel clusters are in good agreement with the experimental results. In the case of neutral and anionic nickel clusters, comparing energies and bond lengths obtained by the three bases, shows that the basis set PBE/DGDZVP2 is most suitable to experimental results. In the case of anionic nickel clusters (n = 1-6) with presence of hydrogen, the optimization of the hydrogen-nickel (anionic) structures by using of the basis set PBE/DGDZVP2, shows that the binding energies and bond lengths increase compared to those obtained in the case of anionic nickel clusters without the presence of hydrogen, that reveals the armor effect exerted by hydrogen on the electronic structure of nickel, which due to the storing of hydrogen energy within nickel clusters structures. The comparison between the bond lengths for both clusters shows the expansion effect of clusters geometry which due to hydrogen presence.

Keywords: binding energies, bond lengths, density functional theoretical, geometry optimization, hydrogen energy, nickel cluster

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Authors: Maryam Kakavand, Samira Entezari, Sara Khoshjamalfekri, Raghad Mimar

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The objective of this study is 1) to compare elite female and beginner taekwondo players in terms of plantar pressure distribution, vertical ground reaction force, contact area, mean pressure, and right and left longitudinal arches, and 2) to compare preferred and non-preferred limbs among elite players. To the best of authors’ knowledge, as of yet, there is no information available about the plantar pressure distribution and arch index among taekwondo players. Material and Methods: An analytical-comparative research method is applied. Therefore seven elite athletes and eight novice athletes were selected. The emed-C50 platform was used to assess plantar pressure distribution, vertical ground reaction force, contact area, mean pressure of different areas, and planter longitudinal arch in a second step protocol. Independent t-test and dependent t-test were used at a level of 0.05 to compare the elites and beginners' right and left feet, and preferred and non-preferred limbs among elite athletes, respectively. Results: In comparing the right and left limbs of elite and beginner groups, findings indicate that there is only a significant difference in the mean pressure of the first metatarsal of the right foot. Findings also showed a significant difference in the contact area of the toes 3, 4, 5 regions between elites’ preferred and non-preferred limbs. However, no significant difference was found between the two groups’ right and left limbs and elites’ preferred and non-preferred limbs in terms of pressure distribution, vertical ground reaction force, and arch index. Conclusion: It seems that taekwondo exercises have affected pressure distribution patterns among advanced players causing some differences in their planter pressure distribution pattern when compared to that of beginners. Therefore, taekwondo exercises may be a factor contributing to asymmetry performance in preferred and non-preferred limbs.

Keywords: planter pressure, arch index, taekwondo, elite

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Authors: Sameh A. S. Thabit Alariqi

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Food is widely packaged with plastic materials to prevent microbial contamination and spoilage. Ionizing radiation is widely used to sterilize the food-packaging materials. Sterilization by γ-radiation causes degradation for the plastic packaging materials such as embrittlement, stiffening, softening, discoloration, odour generation, and decrease in molecular weight. Many antioxidants can prevent γ-degradation but most of them are toxic. The migration of antioxidants to its environment gives rise to major concerns in case of food packaging plastics. In this attempt, we have aimed to utilize synergistic mixtures of stabilizers which are approved for food-contact applications. Ethylene-propylene-diene terpolymer (EPDM) have been melt-mixed with hindered amine stabilizers (HAS), phenolic antioxidants and organo-phosphites (hydroperoxide decomposer). Results were discussed by comparing the stabilizing efficiency of mixtures with and without phenol system. Among phenol containing systems where we mostly observed discoloration due to the oxidation of hindered phenol, the combination of secondary HAS, tertiary HAS, organo-phosphite and hindered phenol exhibited improved stabilization efficiency than single or binary additive systems. The mixture of secondary HAS and tertiary HAS, has shown antagonistic effect of stabilization. However, the combination of organo-phosphite with secondary HAS, tertiary HAS and phenol antioxidants have been found to give synergistic even at higher doses of -sterilization. The effects have been explained through the interaction between the stabilizers. After γ-irradiation, the consumption of oligomeric stabilizer significantly depends on the components of stabilization mixture. The effect of the organo-phosphite antioxidant on the overall stability has been discussed.

Keywords: ethylene-propylene-diene terpolymer, synergistic mixtures, gamma sterilization, gamma stabilization

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Authors: Mostafa Mjahed

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This paper concerns the control of a nonlinear system using two different methods, reference model and genetic algorithm. The quadcopter is a nonlinear unstable system, which is a part of aerial robots. It is constituted by four rotors placed at the end of a cross. The center of this cross is occupied by the control circuit. Its motions are governed by six degrees of freedom: three rotations around 3 axes (roll, pitch and yaw) and the three spatial translations. The control of such system is complex, because of nonlinearity of its dynamic representation and the number of parameters, which it involves. Numerous studies have been developed to model and stabilize such systems. The classical PID and LQ correction methods are widely used. If the latter represent the advantage to be simple because they are linear, they reveal the drawback to require the presence of a linear model to synthesize. It also implies the complexity of the established laws of command because the latter must be widened on all the domain of flight of these quadcopter. Note that, if the classical design methods are widely used to control aeronautical systems, the Artificial Intelligence methods as genetic algorithms technique receives little attention. In this paper, we suggest comparing two PID design methods. Firstly, the parameters of the PID are calculated according to the reference model. In a second phase, these parameters are established using genetic algorithms. By reference model, we mean that the corrected system behaves according to a reference system, imposed by some specifications: settling time, zero overshoot etc. Inspired from the natural evolution of Darwin's theory advocating the survival of the best, John Holland developed this evolutionary algorithm. Genetic algorithm (GA) possesses three basic operators: selection, crossover and mutation. We start iterations with an initial population. Each member of this population is evaluated through a fitness function. Our purpose is to correct the behavior of the quadcopter around three axes (roll, pitch and yaw) with 3 PD controllers. For the altitude, we adopt a PID controller.

Keywords: quadcopter, genetic algorithm, PID, fitness, model, control, nonlinear system

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Authors: Phakamani Xaba, Robert Huberts, Bilainu Oboirien

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The present study was aimed at developing & comparing two neural-network-based predictive models to predict shelf-life/product age of South African margarine using free fatty acid (FFA), water droplet size (D3.3), water droplet distribution (e-sigma), moisture content, peroxide value (PV), anisidine valve (AnV) and total oxidation (totox) value as input variables to the model. Brick margarine products which had varying ages ranging from fresh i.e. week 0 to week 47 were sourced. The brick margarine products which had been stored at 10 & 25 °C and were characterized. JMP and MATLAB models to predict shelf-life/ margarine age were developed and their performances were compared. The key performance indicators to evaluate the model performances were correlation coefficient (CC), root mean square error (RMSE), and mean absolute percentage error (MAPE) relative to the actual data. The MATLAB-developed model showed a better performance in all three performance indicators. The correlation coefficient of the MATLAB model was 99.86% versus 99.74% for the JMP model, the RMSE was 0.720 compared to 1.005 and the MAPE was 7.4% compared to 8.571%. The MATLAB model was selected to be the most accurate, and then, the number of hidden neurons/ nodes was optimized to develop a single predictive model. The optimized MATLAB with 10 neurons showed a better performance compared to the models with 1 & 5 hidden neurons. The developed models can be used by margarine manufacturers, food research institutions, researchers etc, to predict shelf-life/ margarine product age, optimize addition of antioxidants, extend shelf-life of products and proactively troubleshoot for problems related to changes which have an impact on shelf-life of margarine without conducting expensive trials.

Keywords: margarine shelf-life, predictive modelling, neural networks, oil oxidation

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Authors: Parimalakrishnan Sundararjan, Madheswaran Murugan, Dhanya Dharman, Yatindra Kumar, Sudhir Singh Gangwar, Guru Prasad Mohanta

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Antibiotic resistance AR is a global issue, India started to redress the issues of antibiotic resistance late and it plans to have: active surveillance of microbial resistance and promote appropriate use of antibiotics. The present study attempted to achieve appropriate use of antibiotics through pharmacists’ intervention at practice point. In a quasi-experimental prospective cohort study, the cases with bacteremia from four hospitals were identified during 2015 and 2016 for intervention. The pharmacists centered intervention: active screening of each prescription and comparing with the selection of antibiotics with susceptibility of the bacteria. Wherever irrationality noticed, it was brought to the notice of the treating physician for making changes. There were two groups: intervention group and control group without intervention. The active screening and intervention in 915 patients has reduced therapeutic regimen time in patients with bacteremia. The intervention group showed the decreased duration of hospital stay 3.4 days from 5.1 days. Further, multivariate modeling of patients who were in control group showed that patients in the intervention group had a significant decrease in both duration of hospital stay and infection-related mortality. Unlike developed countries, pharmacists are not active partners in patient care in India. This unique attempt of pharmacist’ invention was planned in consultation with hospital authorities which proved beneficial in terms of reducing the duration of treatment, hospital stay, and infection-related mortality. This establishes the need for a collaborative decision making among the health workforce in patient care at least for promoting rational use of antibiotics, an attempt to combat resistance.

Keywords: antibiotics resistance, intervention, bacteremia, multivariate modeling

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Authors: Shannon Hearney, Jeffrey Hoch

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Pancreatic cancer is a notoriously costly and deadly form of cancer. Many types of treatment centers exist for patients to seek care from, including high-volume centers which have shown promise to provide the highest quality of care. While it may be true that this type of center provides the best care it is unclear if that care is cost-effective. Studies in the US have confirmed that high-volume hospitals do provide higher quality of care but have shown inconsistencies in the cost-effectiveness of that care. Other studies, like those from Finland have shown that high-volume centers had lower mortality and lower costs than low-volume centers. This paper thus seeks to review the current scientific literature to better understand if high-volume centers are cost-effective in delivering care in both a European setting and in the US. A review of major reference databases such as Medline, Embase and PubMed will be conducted for cost-effectiveness studies on the surgical treatment of pancreatic cancer at high-volume centers. Possible MeSH terms to be included, but not limited to, are: “pancreatic cancer”, “cost analysis”, “cost-effectiveness”, “economic evaluation”, “pancreatic neoplasms”, “surgical”, and “high-volume”. Studies must also have been available in the English language. This review will encompass European scientific literature, as well as those in the US. Based on our preliminary findings, we anticipate high-volume hospitals to provide better care at greater costs. We anticipate that high-volume hospitals may be cost-effective in different contexts depending on the national structure of a healthcare system. Countries with more centralized and socialized healthcare may yield results that are more cost-effective. High-volume centers may differ in their cost-effectiveness of the surgical care of pancreatic cancer internationally especially when comparing those in the United States to others throughout Europe.

Keywords: cost-effectiveness analysis, economic evaluation, pancreatic cancer, scientific literature review

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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Authors: Domenica Tambasco, Riina Bray, Sophia Jaworski, Gillian Grant, Celeste Corkery

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Fibromyalgia is a chronic condition characterized by widespread musculoskeletal pain, fatigue, and reduced function. Management of symptoms include medications, physical treatments and mindfulness therapies. Myofascial Release is a modality that has been successfully applied in var-ious musculoskeletal conditions. However, to the author’s best knowledge, it is not yet recog-nized as a self-management therapy option in Fibromyalgia. In this study, we investigated whether Self-applied Myofascial Release (SMR) is associated with overall improved function and symptoms in Fibromyalgia. Methods: Eligible adult patients with a confirmed diagnosis of Fibromyalgia at Women’s College Hospital were recruited to SMR. Sessions ran for 1 hour once a week for 7 weeks, led by the same two Physiotherapists knowledgeable in this physical treat-ment modality. The main outcome measure was an overall impact score for function and symp-toms based on the validated assessment tool for Fibromyalgia, the Revised Fibromyalgia Impact Questionnaire (FIQR), measured pre and post-intervention. Both descriptive and analytical methods were applied and reported. Results: We analyzed results using a paired t-test to deter-mine if there was a statistically significant difference in mean FIQR scores between initial (pre-intervention) and final (post-intervention) scores. A clinically significant difference in FIQR was defined as a reduction in score by 10 or more points. Conclusions: Our pilot study showed that SMR appeared to be a safe and effective intervention for our Fibromyalgia participants and the overall impact on function and symptoms occurred in only 7 weeks. Further studies with larger sample sizes comparing SMR to other physical treatment modalities (such as stretching) in an RCT are recommended.

Keywords: fibromyalgia, myofascial release, physical therapy, FIQR

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