Search results for: harmony search algorithms

Authors: Suleman Maliha, Suleman Sidra

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Obstructive sleep apnea (OSA) is a sleep disorder that can result in behavioral and psychomotor impairments in children. The classical treatment modalities for OSA have been continuous positive airway pressure and adenotonsillectomy. However, orthodontic intervention through rapid maxillary expansion (RME) has also been commonly used to manage skeletal transverse maxillary discrepancies. Aim and objectives: The aim of this study is to determine the efficacy of rapid maxillary expansion in paediatric patients with obstructive sleep apnea by assessing pre and post-treatment mean apnea-hypopnea index (AHI) and oxygen saturations. Methodology: Literature was identified through a rigorous search of the Embase, Pubmed, and CINAHL databases. Articles published from 2012 onwards were selected. The inclusion criteria consisted of patients aged 18 years and under with no systemic disease, adenotonsillar surgery, or hypertrophy who are undergoing RME with AHI measurements before and after treatment. In total, six suitable papers were identified. Results: Three studies assessed patients pre and post-RME at 12 months. The first study consisted of 15 patients with an average age of 7.5 years. Following treatment, they found that RME resulted in both higher oxygen saturations (+ 5.3%) and improved AHI (- 4.2 events). The second study assessed 11 patients aged 5–8 years and also noted improvements, with mean AHI reduction from 6.1 to 2.4 and oxygen saturations increasing from 93.1% to 96.8%. The third study reviewed 14 patients aged 6–9 years and similarly found an AHI reduction from 5.7 to 4.4 and an oxygen saturation increase from 89.8% to 95.5%. All modifications noted in these studies were statistically significant. A long-term study reviewed 23 patients aged 6–12 years post-RME treatment on an annual basis for 12 years. They found that the mean AHI reduced from 12.2 to 0.4, with improved oxygen saturations from 78.9% to 95.1%. Another study assessed 19 patients aged 9-12 years at two months into RME and four months post-treatment. Improvements were also noted at both stages, with an overall reduction of the mean AHI from 16.3 to 0.8 and an overall increase in oxygen saturations from 77.9% to 95.4%. The final study assessed 26 children aged 7-11 years on completion of individual treatment and found an AHI reduction from 6.9 to 5.3. However, the oxygen saturation remained stagnant at 96.0%, but this was not clinically significant. Conclusion: Overall, the current evidence suggests that RME is a promising treatment option for paediatric patients with OSA. It can provide efficient and conservative treatment; however, early diagnosis is crucial. As there are various factors that could be contributing to OSA, it is important that each case is treated on its individual merits. Going forward, there is a need for more randomized control trials with larger cohorts being studied. Research into the long-term effects of RME and potential relapse amongst cases would also be useful.

Keywords: orthodontics, sleep apnea, maxillary expansion, review

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Authors: Saradiya Mukherjee

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Background: Indian Muslims, compared to their counterparts in other religions, generally do not fare well on many yardsticks related to socio-economic progress and the same is true with maternal health care utilization. Due to low age at marriage a major percentage of child birth is ascribed to young (15-24 years) Muslim mothers in, which pose serious concerns on the maternal health care of Young Married Muslim women (YMMW). A thorough search of past literature on Muslim women’s health and health care reveals that studies in India have mainly focused on religious differences in fertility levels and contraceptive use while the research on the determinants of maternal health care utilization among Muslim women are lacking in India. Data and Methods: Retrieving data from the National Family Health Survey -3 (2005-06) this study attempts to assess the level of utilization and factors effecting three key maternal health indicators (full ANC, safe delivery and PNC) among YMMW (15-24 years) in India. The key socio-economic and demographic variables taken as independent or predictor variables in the study was guided by existing literature particularly for India. Bi-variate analysis and chi square test was applied and variables which were found to be significant were further included in binary logistic regression. Results: The findings of the study reveal abysmally low levels of utilization for all three indicators i.e. full ANC, safe delivery and PNC of maternal health care included in the study. Mother’s education, mass media exposure, women’s autonomy, birth order, economic status wanted status of child and region of residence were found to be significant variables effecting maternal health care utilization among YMMW. Multivariate analysis reveals that no mass media exposure, lower autonomy, education, poor economic background, higher birth order and unintended pregnancy are some of the reasons behind low maternal health care utilization. Conclusion: Considering the low level of safe maternal health care utilization and its proximate determinants among YMMW the study suggests educating Muslim girls, promoting family planning use, involving media and collaboration between religious leader and health care system could be some important policy level interventions to address the unmet need of maternity services among YMMW.

Keywords: young Muslim women, religion, socio-economic condition, antenatal care, delivery, post natal care

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Authors: Anders Schou Simonsen, Kim Sorensen, Thomas Condra

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Wet scrubbers are used for flue gas desulfurization by injecting water directly into the flue gas stream from a set of sprayers. The water droplets will flow freely inside the scrubber, and flow down along the scrubber walls as a thin wall film while reacting with the gas phase to remove SO₂. This complex multiphase phenomenon can be divided into three main contributions: the continuous gas phase, the liquid droplet phase, and the liquid wall film phase. This study proposes a complete model, where all three main contributions are taken into account and resolved using OpenFOAM for the continuous gas phase, and MATLAB for the liquid droplet and wall film phases. The 3D continuous gas phase is composed of five species: CO₂, H₂O, O₂, SO₂, and N₂, which are resolved along with momentum, energy, and turbulence. Source terms are present for four species, energy and momentum, which are affecting the steady-state solution. The liquid droplet phase experiences breakup, collisions, dynamics, internal chemistry, evaporation and condensation, species mass transfer, energy transfer and wall film interactions. Numerous sub-models have been implemented and coupled to realise the above-mentioned phenomena. The liquid wall film experiences impingement, acceleration, atomization, separation, internal chemistry, evaporation and condensation, species mass transfer, and energy transfer, which have all been resolved using numerous sub-models as well. The continuous gas phase has been coupled with the liquid phases using source terms by an approach, where the two software packages are couples using a link-structure. The complete CFD model has been verified using 16 experimental tests from an existing scrubber installation, where a gradient-based pattern search optimization algorithm has been used to tune numerous model parameters to match the experimental results. The CFD model needed to be fast for evaluation in order to apply this optimization routine, where approximately 1000 simulations were needed. The results show that the complex multiphase phenomena governing wet scrubbers can be resolved in a single model. The optimization routine was able to tune the model to accurately predict the performance of an existing installation. Furthermore, the study shows that a coupling between OpenFOAM and MATLAB is realizable, where the data and source term exchange increases the computational requirements by approximately 5%. This allows for exploiting the benefits of both software programs.

Keywords: desulfurization, discrete phase, scrubber, wall film

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Authors: Neringa Bagdonaite

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Study Aims: The current study aimed to systematically analyse various research done in the area of female post-traumatic stress disorder (PTSD) and alcohol abuse, and to critically review these results on the basis of theoretical models as well as answer following questions: (I) What is the reciprocal relationship between PTSD and problem alcohol use among females; (II) What are the moderating/mediating factors of this relationship? Methods: The computer bibliographic databases Ebsco, Scopus, Springer, Web of Science, Medline, Science Direct were used to search for scientific articles. Systematic analyses sample consisted of peer-reviewed, English written articles addressing mixed gender and female PTSD and alcohol abuse issues from Jan 2012 to May 2017. Results: Total of 1011 articles were found in scientific databases related to searched keywords of which 29 met the selection criteria and were analysed. The results of longitudinal studies indicate that (I) various trauma, especially interpersonal trauma exposure in childhood is linked with increased risk of revictimization in later life and problem alcohol use; (II) revictimization in adolescence or adulthood, rather than victimization in childhood has a greater impact on the onset and progression of problematic alcohol use in adulthood. Cross-sectional and epidemiological studies also support significant relationships between female PTSD and problem alcohol use. Regards to the negative impact of alcohol use on PTSD symptoms results are yet controversial; some evidence suggests that alcohol does not exacerbate symptoms of PTSD over time, while others argue that problem alcohol use worsens PTSD symptoms and is linked to chronicity of both disorders, especially among women with previous alcohol use problems. Analysis of moderating/mediating factors of PTSD and problem alcohol use revealed, that higher motives/expectancies, specifically distress coping motives for alcohol use significantly moderates the relationship between PTSD and problematic alcohol use. Whereas negative affective states mediate relationship between symptoms of PTSD and alcohol use, but only among woman with alcohol use problems already developed. Conclusions: Interpersonal trauma experience, especially in childhood and its reappearance in lifetime is linked with PTSD symptoms and problem drinking among women. Moreover, problem alcohol use can be both a cause and a consequence of trauma and PTSD, and if used for coping it, increases the likelihood of chronicity of both disorders. In order to effectively treat both disorders, it’s worthwhile taking into account this dynamic interplay of women's PTSD symptoms and problem drinking.

Keywords: female, trauma, post-traumatic stress disorder, problem alcohol use, systemic analysis

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Authors: Marion G. Ben-Jacob, David Wang

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There is a mathematics requirement for entry level college and university students, especially those who plan to study STEM (Science, Technology, Engineering and Mathematics). Most of them take College Algebra, and to continue their studies, they need to succeed in this course. Different pedagogical strategies are employed to promote the success of our students. There is, of course, the Traditional Method of teaching- lecture, examples, problems for students to solve. The Emporium Model, another pedagogical approach, replaces traditional lectures with a learning resource center model featuring interactive software and on-demand personalized assistance. This presentation will compare these two methods of pedagogy and the study done with its results on this comparison. Math is the foundation for science, technology, and engineering. Its work is generally used in STEM to find patterns in data. These patterns can be used to test relationships, draw general conclusions about data, and model the real world. In STEM, solutions to problems are analyzed, reasoned, and interpreted using math abilities in a assortment of real-world scenarios. This presentation will examine specific examples of how math is used in the different STEM disciplines. Math becomes practical in science when it is used to model natural and artificial experiments to identify a problem and develop a solution for it. As we analyze data, we are using math to find the statistical correlation between the cause of an effect. Scientists who use math include the following: data scientists, scientists, biologists and geologists. Without math, most technology would not be possible. Math is the basis of binary, and without programming, you just have the hardware. Addition, subtraction, multiplication, and division is also used in almost every program written. Mathematical algorithms are inherent in software as well. Mechanical engineers analyze scientific data to design robots by applying math and using the software. Electrical engineers use math to help design and test electrical equipment. They also use math when creating computer simulations and designing new products. Chemical engineers often use mathematics in the lab. Advanced computer software is used to aid in their research and production processes to model theoretical synthesis techniques and properties of chemical compounds. Mathematics mastery is crucial for success in the STEM disciplines. Pedagogical research on formative strategies and necessary topics to be covered are essential.

Keywords: emporium model, mathematics, pedagogy, STEM

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Authors: Yasmeen Jamal Alabdallat, Almutazballlah Bassam Qablan, Obada Ahmad Al Jayyousi, Ihdaa Mahmoud Bani Khalaf, Eman E. Alshial

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Background: Bipolar disorder, formerly known as manic depression, is a mental health status that leads to extreme mood swings that include emotional lows (depression) and highs (mania or hypomania). This systematic review and meta-analysis aimed to assess the safety and efficacy of lithium versus valproate among bipolar patients. Methods: A computer literature search of PubMed, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials was conducted from inception until June 2022. Studies comparing lithium versus valproate among bipolar patients were selected for the analysis, and all relevant outcomes were pooled in the meta-analysis using Review Manager Software. Results: 11 Randomized Clinical Trials were included in this meta-analysis with a total of 4159 patients. Our meta showed that lithium was superior to valproate in terms of Young Mania Rating Scale (YMRS) (MD = 0.00 with 95% CI, (-0.55 – 0.55; I2 = 0%), P = 1.00). The results of the Hamilton Depression Rating Scale (HDRS) showed that the overall effect favored the valproate treated group (MD = 1.41 with 95% CI, (-0.15 – 2.67; I2 = 0%), P = 0.03). Concerning the results of the Montgomery-Asberg Depression Rating Scale (MADRS), the results showed that the lithium was superior to valproate (MD = 0.03 with 95% CI, (-0.80 to 0.87; I2 = 40%), P = 0.94). In terms of the sexual side effect, we found that the valproate was superior to lithium (RR 1.19 with 95% CI, (0.74 to 1.91; I2 = 0%), P = 0.47). The lithium-treated group was superior in comparison to valproate treated group in terms of Abnormal Involuntary Movement Scale (AIMS) (MD = -0.03 with 95% CI (-0.38 to 0.32; I2 = 0%), P = 0.87). The lithium was more favorable in terms of Simpson-Agnes scale (MD = -0.40 with 95% CI, (-0.86 to 0.06; I2 = 0%), P = 0.09). The results of the Barnes akathisia scale showed that the overall effect of the valproate was more favorable in comparison to lithium (MD = 0.05 with 95% CI, (-0.12 to 0.22; I2 = 0%), P = 0.57). Conclusion: Our study revealed that on the scales of efficacy Lithium treated group surpassed Valproate treated group in terms of Young Mania Rating Scale (YMRS), Abnormal Involuntary Movement Scale (AIMS) and Simpson-Agnes scale, but valproate surpassed it in Barnes Akathisia scale. Furthermore, on the scales of depression Hamilton Depression Rating Scale (HDRS) showed that the overall effect favored Valproate treated group, but Lithium surpassed valproate in terms of Montgomery-Asberg Depression Rating Scale (MADRS). Valproate surpassed Lithium in terms of sexual side effects.

Keywords: bipolar, mania, bipolar-depression, sexual dysfunction, sexual side effects, treatment

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Authors: Gabriel Montague, Max Vilgalys, Catherine H. Crawford, Jorge Ortiz, Dava Newman

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There has never been so much publicly accessible atmospheric and environmental data. The possibilities of these data are exciting, but the sheer volume of available datasets represents a new challenge for researchers. The task of identifying and working with a new dataset has become more difficult with the amount and variety of available data. Datasets are often documented in ways that differ substantially from the common English used to describe the same topics. This presents a barrier not only for new scientists, but for researchers looking to find comparisons across multiple datasets or specialists from other disciplines hoping to collaborate. This paper proposes a method for addressing this obstacle: creating a knowledge graph to bridge the gap between everyday English language and the technical language surrounding these datasets. Knowledge graph generation is already a well-established field, although there are some unique challenges posed by working with Earth data. One is the sheer size of the databases – it would be infeasible to replicate or analyze all the data stored by an organization like The National Aeronautics and Space Administration (NASA) or the European Space Agency. Instead, this approach identifies topics from metadata available for datasets in NASA’s Earthdata database, which can then be used to directly request and access the raw data from NASA. By starting with a single metadata standard, this paper establishes an approach that can be generalized to different databases, but leaves the challenge of metadata harmonization for future work. Topics generated from the metadata are then linked to topics from a collection of English queries through a variety of standard and custom natural language processing (NLP) methods. The results from this method are then compared to a baseline of elastic search applied to the metadata. This comparison shows the benefits of the proposed knowledge graph system over existing methods, particularly in interpreting natural language queries and interpreting topics in metadata. For the research community, this work introduces an application of NLP to the ecological and environmental sciences, expanding the possibilities of how machine learning can be applied in this discipline. But perhaps more importantly, it establishes the foundation for a platform that can enable common English to access knowledge that previously required considerable effort and experience. By making this public data accessible to the full public, this work has the potential to transform environmental understanding, engagement, and action.

Keywords: earth metadata, knowledge graphs, natural language processing, question-answer systems

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Authors: Cledinaldo A. Dias, Isabela C. Santos, Marcus V. S. Siqueira

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In the contemporary globalization, the competitiveness generated in the search of new markets aiming at the growth of productivity and, consequently, of profits, implies the redefinition of productive processes and new forms of work organization. As a result of this structuring, unemployment, labor force turnover and the increase in outsourcing and informal work occur. Considering the different relationships and working conditions of outsourced employees, this study aims to identify the most present stressors among outsourced service providers from a Federal Institution of Higher Education in Brazil. To reach this objective, a descriptive exploratory study with a quantitative approach was carried out. The qualitative approach was chosen to provide an in-depth analysis of the occupational conditions of outsourced workers since this method seeks to focus on the social as a world of investigated meanings and the language or speech of each subject as the object of this approach. The survey was conducted in the city of Montes Claros - Minas Gerais (Brazil) and involved eighty workers from companies hired by the institution, including armed security guards, porters, cleaners, drivers, gardeners, and administrative assistants. The choice of professionals obeyed non-probabilistic criteria for convenience or accessibility. Data collection was performed by means of a structured questionnaire composed of sixty questions, in a Likert-type frequency interval scale format, in order to identify potential organizational stressors. The results obtained evidence that the stress factors pointed out by the workers are, in most cases, a determining factor due to the low productive performance at work. Amongst the factors associated with stress, the ones that stood out most were those related to organizational communication failures, the incentive to competition, lack of expectations of professional growth, insecurity and job instability. Based on the results, the need for greater concern and organizational responsibility with the well-being and mental health of the outsourced worker and the recognition of their physical and psychological limitations, and care that goes beyond the functional capacity for the work. Specifically for the preservation of mental health, physical and quality of life, it is concluded that it is necessary for the professional to be inserted in the external world that favors it internally since this set is complemented so that the individual remains in balance and obtain satisfaction in your work.

Keywords: occupational health, outsourced, organizational studies, stressors

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Authors: Maciej Zasuwa, Grzegorz Ptasinski, Antoni Kopyt

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Nowadays flight simulators offer tremendous possibilities for safe and cost-effective pilot training, by utilization of powerful, computational tools. Due to technology outpacing methodology, vast majority of training related work is done by human instructors. It makes assessment not efficient, and vulnerable to instructors’ subjectivity. The research presents an Objective Assessment Tool (gOAT) developed at the Warsaw University of Technology, and tested on SW-4 helicopter flight simulator. The tool uses database of the predefined manoeuvres, defined and integrated to the virtual environment. These were implemented, basing on Aeronautical Design Standard Performance Specification Handling Qualities Requirements for Military Rotorcraft (ADS-33), with predefined Mission-Task-Elements (MTEs). The core element of the gOAT enhanced algorithm that provides instructor a new set of information. In details, a set of objective flight parameters fused with report about psychophysical state of the pilot. While the pilot performs the task, the gOAT system automatically calculates performance using the embedded algorithms, data registered by the simulator software (position, orientation, velocity, etc.), as well as measurements of physiological changes of pilot’s psychophysiological state (temperature, sweating, heart rate). Complete set of measurements is presented on-line to instructor’s station and shown in dedicated graphical interface. The presented tool is based on open source solutions, and flexible for editing. Additional manoeuvres can be easily added using guide developed by authors, and MTEs can be changed by instructor even during an exercise. Algorithm and measurements used allow not only to implement basic stress level measurements, but also to reduce instructor’s workload significantly. Tool developed can be used for training purpose, as well as periodical checks of the aircrew. Flexibility and ease of modifications allow the further development to be wide ranged, and the tool to be customized. Depending on simulation purpose, gOAT can be adjusted to support simulator of aircraft, helicopter, or unmanned aerial vehicle (UAV).

Keywords: automated assessment, flight simulator, human factors, pilot training

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Authors: Emma Plante, Charles Ekwunwa, Diego Illanes

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Introduction: Serum Sickness-Like Reaction (SSLR) is an inflammatory immune response characterized by a rash, polyarthralgias, and fever. SSLR usually occurs in response to a new medication (most commonly antibiotics, anticonvulsants, or antiinflammatory agents) and is believed to involve the formation of drug-specific immune complexes. Here we present a case of a 16-year-old female patient who developed an SSLR in response to the D-mannose-containing over-the-counter supplement, Uqora, used to promote bladder health. Methodology: The methodology for this study included a thorough literature search for other cases of SSLR associated with D-Mannose containing products. Data collection was performed through a review of the patient’s medical record, including history, physical examination, relevant laboratory results, and treatment plan. Findings: A 16-year-old female with a history of overactive bladder and anemia presented with a diffuse urticarial rash, headaches, joint pain, and swelling for three days. Her medications included oral contraceptive pills, iron, mirabegron, UQora, and a probiotic. Physical examination revealed a diffuse urticarial rash, and her musculoskeletal exam revealed swelling and tenderness in her wrists. Her CBC, basic metabolic panel, liver function panel, lyme titers, and urinalysis were all within normal limits. The patient was referred to an allergist, who diagnosed her with SSLR. All medications were discontinued, and she was treated with a 7-day course of prednisone and cetirizine. Her symptoms resolved, and her medications were slowly resumed sequentially over several months. However, UQora triggered a recurrence of her symptoms, and it was identified as the culprit medication. Consequently, UQora was permanently discontinued, and the patient has remained symptom-free. Conclusion: This case report describes the first documented case of SSLR caused by UQora (active ingredient D-mannose). D-Mannose is a monosaccharide found in many plants and fruits, and it is commonly used to prevent urinary tract infections. While the clinical features and timeline, in this case, were typical of SSLR, UQora as the trigger was highly unusual. Clinicians should be aware of the diverse triggers of SSLR and the importance of prompt identification and management to enhance patient safety. It is possible D-mannose was not the trigger, and further research is necessary to better understand the potential therapeutic applications of D-mannose, as well as the potential risks and interactions.

Keywords: serum sickness-like reaction, d-mannose, hypersensitivity reaction, urticaria

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Authors: S. Arias

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New housing developments and the technological changes that this implies, adapt the styles of living of its residents, as well as new family structures and forms of work due to the particular needs of a specific group of people which involves different techniques of dealing with, organize, equip and use a particular territory. Currently, own their own space is increasingly important and the cities are faced with the challenge of providing the opportunity for such demands, as well as energy, water and waste removal necessary in the process of construction and occupation of new human settlements. Until the day of today, not has failed to give full response to these demands and needs, resulting in cities that grow without control, badly used land, avenues and congested streets. Buildings and dwellings have an important impact on the environment and on the health of the people, therefore environmental quality associated with the comfort of humans to the sustainable development of natural resources. Applied to architecture, this concept involves the incorporation of new technologies in all the constructive process of a dwelling, changing customs of developers and users, what must be a greater effort in planning energy savings and thus reducing the emissions Greenhouse Gases (GHG) depending on the geographical location where it is planned to develop. Since the techniques of occupation of the territory are not the same everywhere, must take into account that these depend on the geographical, social, political, economic and climatic-environmental circumstances of place, which in modified according to the degree of development reached. In the analysis that must be undertaken to check the degree of sustainability of the place, it is necessary to make estimates of the energy used in artificial air conditioning and lighting. In the same way is required to diagnose the availability and distribution of the water resources used for hygiene and for the cooling of artificially air-conditioned spaces, as well as the waste resulting from these technological processes. Based on the results obtained through the different stages of the analysis, it is possible to perform an energy audit in the process of proposing recommendations of sustainability in architectural spaces in search of energy saving, rational use of water and natural resources optimization. The above can be carried out through the development of a sustainable building code in develop technical recommendations to the regional characteristics of each study site. These codes would seek to build bases to promote a building regulations applicable to new human settlements looking for is generated at the same time quality, protection and safety in them. This building regulation must be consistent with other regulations both national and municipal and State, such as the laws of human settlements, urban development and zoning regulations.

Keywords: building regulations, housing, sustainability, technology

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Authors: Amal G. Kurian

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The use of mathematical modeling has seen a considerable boost in recent times with the development of many advanced algorithms and mathematical modeling capabilities. The advantages this method has over other methods are that they are much closer to standard physics theories and thus represent a better theoretical model. They take lesser solving time and have the ability to change various parameters for optimization, which is a big advantage, especially in automotive industry. This thesis work focuses on a thorough investigation of the effects of vehicle speed and road roughness on a heavy commercial vehicle ride and structural dynamic responses. Since commercial vehicles are kept in operation continuously for longer periods of time, it is important to study effects of various physical conditions on the vehicle and its user. For this purpose, various experimental as well as simulation methodologies, are adopted ranging from experimental transfer path analysis to various road scenario simulations. To effectively investigate and eliminate several causes of unwanted responses, an efficient and robust technique is needed. Carrying forward this motivation, the present work focuses on the development of a mathematical model of a 4-axle configuration heavy commercial vehicle (HCV) capable of calculating responses of the vehicle on different road PSD inputs and vehicle speeds. Outputs from the model will include response transfer functions and PSDs and wheel forces experienced. A MATLAB code will be developed to implement the objectives in a robust and flexible manner which can be exploited further in a study of responses due to various suspension parameters, loading conditions as well as vehicle dimensions. The thesis work resulted in quantifying the effect of various physical conditions on ride comfort of the vehicle. An increase in discomfort is seen with velocity increase; also the effect of road profiles has a considerable effect on comfort of the driver. Details of dominant modes at each frequency are analysed and mentioned in work. The reduction in ride height or deflection of tire and suspension with loading along with load on each axle is analysed and it is seen that the front axle supports a greater portion of vehicle weight while more of payload weight comes on fourth and third axles. The deflection of the vehicle is seen to be well inside acceptable limits.

Keywords: mathematical modeling, HCV, suspension, ride analysis

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Authors: Claudia Cabezas-Zabala, Jairo Lindarte-Artunduaga, Carlos Mario Zuluaga-Dominguez

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Amaranth is an emerging pseudocereal rich in such essential nutrients as protein and dietary fiber, which was employed as an ingredient in the formulation of crackers to evaluate the rheological performance and sensory acceptability of the obtained food. A completely randomized factorial design was used with two factors: (A) ratio of wheat and amaranth flour used in the preparation of the dough, in proportion 90:10 and 80:20 (% w/w) and (B) two levels of inulin addition of 8.4% and 16.7 %, having two control doughs made from amaranth and wheat flour, respectively. Initially, the functional properties of the formulations mentioned were measured, showing no significant differences in the water absorption capacity (WAC) and swelling power (SP), having mean values between 1.66 and 1.81 g/g for WAC and between 1.75 and 1.86 g/g for SP, respectively. The amaranth flour had the highest water holding capacity (WHR) of 8.41 ± 0.15 g/g and emulsifying activity (EA) of 74.63 ± 1.89 g/g. Moreover, the rheological behavior, measured through the use of farinograph, extensograph, Mixolab, and falling index, showed that the formulation containing 20% of amaranth flour and 7.16% of inulin had a rheological behavior similar to the control produced exclusively with wheat flour, being the former, the one selected for the preparation of crackers. For this formulation, the farinograph showed a mixing tolerance index of 11 UB, indicating a strong and cohesive dough; likewise, the Mixolab showed dough reaches stability at 6.47 min, indicating a good resistance to mixing. On the other hand, the extensograph exhibited a dough resistance of 637 UB, as well as extensibility of 13.4 mm, which corresponds to a strong dough capable of resisting the laminate. Finally, the falling index was 318 s, which indicates the crumb will retain enough air to enhance the crispness of a characteristic cracker. Finally, a sensory consumer test did not show significant differences in the evaluation of aroma between the control and the selected formulation, while this latter had a significantly lower rating in flavor. However, a purchase intention of 70 % was observed among the population surveyed. The results obtained in this work give perspectives for the industrial use of amaranth in baked goods. Additionally, amaranth has been a product typically linked to indigenous populations in the Andean South American countries; therefore, the search for diversification and alternatives of use for this pseudocereal has an impact on the social and economic conditions of such communities. The technological versatility and nutritional quality of amaranth is an advantage for consumers, favoring the consumption of healthy products with important contributions of dietary fiber and protein.

Keywords: amaranth, crackers, rheology, pseudocereals, kneaded products

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Authors: Neeraj Vij, Christian Leber, Kenneth Schmidt

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Introduction: Total knee arthroplasty is a common procedure. It is well known that the biomechanics of the knee do not fully return to their normal state. Motion analysis has been used to study the biomechanics of the knee after total knee arthroplasty. The purpose of this scoping review is to summarize the current use of gait analysis in total knee arthroplasty and to identify the preoperative motion analysis parameters for which a systematic review aimed at determining the reliability and validity may be warranted. Materials and Methods: This IRB-exempt scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist strictly. Five search engines were searched for a total of 279 articles. Articles underwent a title and abstract screening process followed by full-text screening. Included articles were placed in the following sections: the role of gait analysis as a research tool for operative decisions, other research applications for motion analysis in total knee arthroplasty, gait analysis as a tool in predicting radiologic outcomes, gait analysis as a tool in predicting clinical outcomes. Results: Eleven articles studied gait analysis as a research tool in studying operative decisions. Motion analysis is currently used to study surgical approaches, surgical techniques, and implant choice. Five articles studied other research applications for motion analysis in total knee arthroplasty. Other research applications for motion analysis currently include studying the role of the unicompartmental knee arthroplasty and novel physical therapy protocols aimed at optimizing post-operative care. Two articles studied motion analysis as a tool for predicting radiographic outcomes. Preoperative gait analysis has identified parameters than can predict postoperative tibial component migration. 15 articles studied motion analysis in conjunction with clinical scores. Conclusions: There is a broad range of applications within the research domain of total knee arthroplasty. The potential application is likely larger. However, the current literature is limited by vague definitions of ‘gait analysis’ or ‘motion analysis’ and a limited number of articles with preoperative and postoperative functional and clinical measures. Knee adduction moment, knee adduction impulse, total knee range of motion, varus angle, cadence, stride length, and velocity have the potential for integration into composite clinical scores. A systematic review aimed at determining the validity, reliability, sensitivities, and specificities of these variables is warranted.

Keywords: motion analysis, joint replacement, patient-reported outcomes, knee surgery

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Authors: Gunnar Oskarsson, Irena Georgsdottir

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Tourism has been growing incredibly fast during the past years, including the cruise industry, which is gaining increasing popularity among various groups of travelers. It is a challenging task for companies serving cruise ship passengers with local products and services at the point of destination to reach them in due time with information about their offerings, as well learning how to adapt their offerings and messages to the type of customers arriving on each particular occasion. Although some research has been conducted in this sphere, there is still limited knowledge about many specifics within this sector of the tourist industry. The objective of this research is to examine one of these, with the main goal of studying the segmentation of cruise passengers and to learn about marketing practices directed towards them. A qualitative research method, based on in-depth interviews, was used, as this provides an opportunity to gain insight into the participants’ perspectives. Interviews were conducted with 10 respondents from different companies in the tourist industry in Iceland, who interact with cruise passengers on a regular basis in their work environment. The main objective was to gain an understanding of what distinguishes different customer groups, or segments, in this industry, and of the marketing approaches directed towards them. The main findings reveal that participants note the strongest difference between cruise passengers of different nationalities, passengers coming on different ships (size and type), and passengers arriving at different times of the year. A drastic difference was noticed between nationalities in four main segments, American, British, Other European, and Asian customers, although some of these segments could be divided into even further sub-segments. Other important differencing factors were size and type of ships, quality or number of stars on the ship, and travelling time of the year. Companies serving cruise ship passengers, as well as the customers themselves, could benefit if the offerings of services were designed specifically for particular segments within the industry. Concerning marketing towards cruise passengers, the results indicate that it is carried out almost exclusively through the Internet using; a reliable website and, search engine optimization. Marketing is also by word-of-mouth. This research can assist practitioners by offering a deeper understanding of the approaches that may be effective in marketing local products and services to cruise ship passengers, based on their segmentation and by identifying effective ways to reach them. The research, furthermore, provides a valuable contribution to marketing knowledge for the benefit of an increasingly important market segment in a fast growing tourist industry.

Keywords: capabilities, global integration, internationalisation, SMEs

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Authors: Ella Tyuryumina, Alexey Neznanov

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Finding algorithms to predict the growth of tumors has piqued the interest of researchers ever since the early days of cancer research. A number of studies were carried out as an attempt to obtain reliable data on the natural history of breast cancer growth. Mathematical modeling can play a very important role in the prognosis of tumor process of breast cancer. However, mathematical models describe primary tumor growth and metastases growth separately. Consequently, we propose a mathematical growth model for primary tumor and primary metastases which may help to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoM-IV and corresponding software. We are interested in: 1) modelling the whole natural history of primary tumor and primary metastases; 2) developing adequate and precise CoM-IV which reflects relations between PT and MTS; 3) analyzing the CoM-IV scope of application; 4) implementing the model as a software tool. The CoM-IV is based on exponential tumor growth model and consists of a system of determinate nonlinear and linear equations; corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and primary metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for primary metastases; 3) ‘visible period’ for primary metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer 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. Thus, the CoM-IV model and predictive software: a) detect different growth periods of primary tumor and primary metastases; b) make forecast of the period of primary metastases appearance; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of BC and facilitate optimization of diagnostic tests. The following are calculated by CoM-IV: the number of doublings for ‘nonvisible’ and ‘visible’ growth period of primary metastases; tumor volume doubling time (days) for ‘nonvisible’ and ‘visible’ growth period of primary metastases. The CoM-IV enables, for the first time, to predict the whole natural history of primary tumor and primary metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-IV describes correctly primary tumor and primary distant metastases growth of IV (T1-4N0-3M1) stage with (N1-3) or without regional metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and manifestation of primary metastases.

Keywords: breast cancer, exponential growth model, mathematical modelling, primary metastases, primary tumor, survival

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Authors: Sanjay Rathee, Arti Kashyap

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Extraction of useful information from large datasets is one of the most important research problems. Association rule mining is one of the best methods for this purpose. Finding possible associations between items in large transaction based datasets (finding frequent patterns) is most important part of the association rule mining. There exist many algorithms to find frequent patterns but Apriori algorithm always remains a preferred choice due to its ease of implementation and natural tendency to be parallelized. Many single-machine based Apriori variants exist but massive amount of data available these days is above capacity of a single machine. Therefore, to meet the demands of this ever-growing huge data, there is a need of multiple machines based Apriori algorithm. For these types of distributed applications, MapReduce is a popular fault-tolerant framework. Hadoop is one of the best open-source software frameworks with MapReduce approach for distributed storage and distributed processing of huge datasets using clusters built from commodity hardware. However, heavy disk I/O operation at each iteration of a highly iterative algorithm like Apriori makes Hadoop inefficient. A number of MapReduce-based platforms are being developed for parallel computing in recent years. Among them, two platforms, namely, Spark and Flink have attracted a lot of attention because of their inbuilt support to distributed computations. Earlier we proposed a reduced- Apriori algorithm on Spark platform which outperforms parallel Apriori, one because of use of Spark and secondly because of the improvement we proposed in standard Apriori. Therefore, this work is a natural sequel of our work and targets on implementing, testing and benchmarking Apriori and Reduced-Apriori and our new algorithm ReducedAll-Apriori on Apache Flink and compares it with Spark implementation. Flink, a streaming dataflow engine, overcomes disk I/O bottlenecks in MapReduce, providing an ideal platform for distributed Apriori. Flink's pipelining based structure allows starting a next iteration as soon as partial results of earlier iteration are available. Therefore, there is no need to wait for all reducers result to start a next iteration. We conduct in-depth experiments to gain insight into the effectiveness, efficiency and scalability of the Apriori and RA-Apriori algorithm on Flink.

Keywords: apriori, apache flink, Mapreduce, spark, Hadoop, R-Apriori, frequent itemset mining

Procedia PDF Downloads 265

Authors: Claudio Lamilla, Andrés Santos, Vicente Llanquinao, Jocelyn Hermosilla, Leticia Barrientos

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The industry in general is very interested in improving and optimizing industrial processes in order to reduce the costs involved in obtaining raw materials and production. Thus, an interesting and cost-effective alternative is the incorporation of bioactive metabolites in such processes, being an example of this enzymes which catalyze efficiently a large number of enzymatic reactions of industrial and biotechnological interest. In the search for new sources of these active metabolites, Antarctica is one of the least explored places on our planet where the most drastic cold conditions, salinity, UVA-UVB and liquid water available are present, features that have shaped all life in this very harsh environment, especially bacteria that live in different Antarctic ecosystems, which have had to develop different strategies to adapt to these conditions, producing unique biochemical strategies. In this work the production of cellulolytic enzymes of seven bacterial strains isolated from marine sediments at different sites in the Antarctic was evaluated. Isolation of the strains was performed using serial dilutions in the culture medium at M115°C. The identification of the strains was performed using universal primers (27F and 1492R). The enzyme activity assays were performed on R2A medium, carboxy methyl cellulose (CMC)was added as substrate. Degradation of the substrate was revealed by adding Lugol. The results show that four of the tested strains produce enzymes which degrade CMC substrate. The molecular identifications, showed that these bacteria belong to the genus Streptomyces and Pseudoalteromonas, being Streptomyces strain who showed the highest activity. Only some bacteria in marine sediments have the ability to produce these enzymes, perhaps due to their greater adaptability to degrade at temperatures bordering zero degrees Celsius, some algae that are abundant in this environment and have cellulose as the main structure. The discovery of new enzymes adapted to cold is of great industrial interest, especially for paper, textiles, detergents, biofuels, food and agriculture. These enzymes represent 8% of industrial demand worldwide and is expected to increase their demand in the coming years. Mainly in the paper and food industry are required in extraction processes starch, protein and juices, as well as the animal feed industry where treating vegetables and grains helps improve the nutritional value of the food, all this clearly puts Antarctic microorganisms and their enzymes specifically as a potential contribution to industry and the novel biotechnological applications.

Keywords: antarctic, bacteria, biotechnological, cellulolytic enzymes

Procedia PDF Downloads 275

Authors: Farah Amalina Mohamed Affandi, Redhwan Ahmad Al-Naggar, Seok Mui Wang, Thanikasalam Kathiresan

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Gestational choriocarcinoma is a condition in which there is an abnormal growth or a tumor inside the women’s uterus after conception. It is a type of gestational trophoblastic disease which is relatively rare and malignant. The current epidemiological data of this disease are inadequate. The purposes of this study are to examine the epidemiology of choriocarcinoma and their risk factors based on all available population-based and hospital-based data of the disease. In this study, we searched The MEDLINE and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases using the keywords ‘choriocarcinoma’, ‘gestational’, ‘gestational choriocarcinoma’ and ‘epidemiology’. We included only human studies published in English between 1995 and 2015 to ensure up to date evidence. Case studies, case reports, animal studies, letters to the editor, news, and review articles were excluded. Retrieved articles were screened in three phases. In the first phase, any articles that did not match the inclusion criteria based solely on titles were excluded. In the second phase, the abstracts of remaining articles were screened thoroughly; any articles that did not meet our inclusion criteria were excluded. In the final phase, full texts of the remaining articles were read and assessed to exclude articles that did not meet the inclusion criteria or any articles that fulfilled the exclusion criteria. Duplicates articles were also removed. Systematic reviews and meta-analysis were excluded. Extracted data were summarized in table and figures descriptively. The reference lists of included studies were thoroughly reviewed in search for other relevant studies. A total of ten studies met all the selection criteria. Nine were retrospective studies and one was cohort study. Total numbers of 4563 cases of choriocarcinoma were reviewed from several countries which are Korea, Japan, South Africa, USA, New Mexico, Finland, Turkey, China, Brazil and The Netherlands. Different studies included different range of age with their mean age of 28.5 to 30.0 years. All studies investigated on the disease’s incidence rate, only two studies examined on the risk factors or associations of the disease. Approximately 20% of the studies showed a reduction in the incidence of choriocarcinoma while the other 80% showed inconsistencies in rate. Associations of age, fertility age, occupations and socio-demographic with the status remains unclear. There is limited information on the epidemiological aspects of gestational choriocarcinoma. The observed results indicated there was a decrease in the incidence rate of gestational choriocarcinoma globally. These could be due to the reduction in the incidence of molar pregnancy and the efficacy of the treatment, mainly by chemotherapy.

Keywords: epidemiology, gestational choriocarcinoma, incidence, prevalence, risk factor

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Authors: S. Cheng, C. Catallo

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Introduction: Canada's healthcare and social services systems are failing high risk, vulnerable older adults. Care for vulnerable older Canadians (65 and older) is not optimal in Canada. It does not address the care needs of vulnerable, high risk adults using a holistic approach. Given the growing aging population, and the care needs for seniors with complex conditions is one of the highest in Canada's health care system, there is a sense of urgency to optimize care. Integration of health and social services is an emerging trend in Canada when compared to European countries. There is no common and universal understanding of healthcare and social services integration within the country. Consequently, a clear understanding and definition of integrated health and social services are absent in Canada. Objectives: A study was undertaken to develop a case definition for integrated health and social care initiatives that serve older adults, which was then tested against three Canadian integrated initiatives. Methodology: A limited literature review was undertaken to identify common characteristics of integrated health and social care initiatives that serve older adults, and comprised both scientific and grey literature, in order to develop a case definition. Three Canadian integrated initiatives that are located in the province of Ontario, were identified using an online search and a screening process. They were surveyed to determine if the literature-based integration definition applied to them. Results: The literature showed that there were 24 common healthcare and social services integration characteristics that could be categorized into ten themes: 1) patient-care approach; 2) program goals; 3) measurement; 4) service and care quality; 5) accountability and responsibility; 6) information sharing; 7) Decision-making and problem-solving; 8) culture; 9) leadership; and 10) staff and professional interaction. The three initiatives showed agreement on all the integration characteristics except for those characteristics associated with healthcare and social care professional interaction, collaborative leadership and shared culture. This disagreement may be due to several reasons, including the existing governance divide between the healthcare and social services sectors within the province of Ontario that has created a ripple effect in how professions in the two different sectors interact. In addition, the three initiatives may be at maturing levels of integration, which may explain disagreement on the characteristics associated with leadership and culture. Conclusions: The development of a case definition for healthcare and social services integration that incorporates common integration characteristics can act as a useful instrument in identifying integrated healthcare and social services, particularly given the emerging and evolutionary state of this phenomenon within Canada.

Keywords: Canada, case definition, healthcare and social services integration, integration, seniors health, services delivery

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Authors: Anna Bak-Klimek, Emily Spencer, Siew Lee, Karen Campbell, Wendy McInally

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Background & Significance: Over half of Teenagers and Young Adults (TYAs) say that they experience psychological distress after cancer diagnosis and TYAs with cancer are at higher risk of developing distress compared to other age groups. Despite this there are no age-appropriate interventions to help TYAs manage distress and there is a lack of conceptual understanding of what causes distress in this population group. This makes it difficult to design a targeted, developmentally appropriate intervention. This review aims to identify the key determinants of distress in TYAs affected by cancer and to propose an integrative model of cancer-related distress for TYAs. Method: A literature search was performed in Cochrane Database of Systematic Reviews, MEDLINE, PsycINFO, CINAHL, EMBASE and PsycArticles in May-June, 2022. Quantitative literature was systematically reviewed on the relationship between psychological distress experienced by TYAs affected by cancer and a wide range of factors i.e. individual (demographic, psychological, developmental, and clinical factors) and contextual (social/environmental) factors. Evidence was synthesized and correlates were categorized using the Biopsychosocial Model. The full protocol is available from PROSPERO (CRD42022322069) Results: Thirty eligible quantitative studies met criteria for the review. A total of twenty-six studies were cross-sectional, three were longitudinal and one study was a case control study. The evidence on the relationship between the socio-demographic, illness and treatment-related factors and psychological distress is inconsistent and unclear. There is however consistent evidence on the link between psychological factors and psychological distress. For instance, the use of cognitive and defence coping, negative meta-cognitive beliefs, less optimism, a lack of sense of meaning and lower resilience levels were significantly associated with higher psychological distress. Furthermore, developmental factors such as poor self-image, identity issues and perceived conflict were strongly associated with higher distress levels. Conclusions: The current review suggests that psychological and developmental factors such as ineffective coping strategies, poor self-image and identity issues may play a key role in the development of psychological distress in TYAs affected by cancer. The review proposes a Positive Developmental Psychology Model of Distress for Teenagers and Young Adults affected by cancer. The review highlights that implementation of psychological interventions that foster optimism, improve resilience and address self-image may result in reduced distress in TYA’s with cancer.

Keywords: cancer, determinant, psychological distress, teenager and young adult, theoretical model

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Authors: E. Gopi, E. Devaindran

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Objective: Non-operative management of blunt splenic trauma have started to overtake the traditional splenectomy in recent years across the grade of splenic injury. The two main non-operative methods are observation and angioembolisation. However, the post management convalescence in these groups are still being investigated. The study attempts to quantify the clinical indicators among the two in particular complications, mortalities, conversions to operative management and duration of inpatient stay. Methodology: A systematic search was done via PUBMED, MEDLINE, and EMBASE. A total of 639 articles identified and subsequently 68 articles were identified post duplicates, full text, and inclusion and exclusion criteria. Main exclusions were non-English articles without English translation, pure observational or angioembolisation articles of which no comparison data could be identified and articles looking into pure hemodynamically unstable patients. Results: 24 non randomized controlled trial, 5 clinical control trial and 39 retrospective studies analyzing a total of 23700 patients with blunt splenic trauma. Discrepancies in data were noted in the group who had observational management versus angioembolisation in particular as data was compared among the classes of splenic rupture, the protocol of management in different centers, availability of angiogram suite, and the study design. Further variability was also noted in the angioembolisation arm as the preference for treatment differs between distal versus proximal splenic artery involvement. Overall the cumulative mortality in both observational and angioembolisation group were similar, 2.78% and 5.97% respectively. The cause of death however is not directly attributed to the management itself but rather patient comorbidities, other associated injuries and conversions to splenectomy leading to post splenectomy complications. The cumulative morbidity among each group appears to be same approximately 12% in observational versus 15% in angioembolisation. However, the type of complications varies with the observational group having higher rates of inpatient stay and intrabdominal hematoma infection and angioembolisation group developing more splenic infarcts and bleeds. There were significant disparity in reporting the actual data on duration of inpatient stay and complications to allow a statistically significant quantitative analysis to be done, 15 articles however are currently being considered. Conclusions: Observational management appears to be much effective in managing lower grade splenic trauma (grade 1 and 2) where else angioembolisation appears to play a bigger role in intermediate grades (grade 3-4) in ensuring splenic function preservation. Care has to be taken however in the angioembolisation group in view of distal splenic infarct group compromising splenic function. The cumulated data of 15 articles are now being considered for a meta-analysis.

Keywords: blunt splenic trauma, conservative, non-operative, angioembolisation

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Authors: Jessica A. Hellings, Piyushkumar Jani

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Background: Systemic autoimmune disorders are increasingly implicated in neuropsychiatric illness, especially in the setting of treatment resistance in individuals of all ages. Gluten allergy in fullest extent results in celiac disease, affecting multiple organs including central nervous system (CNS). Clinicians often lack awareness of the association between neuropsychiatric illness and gluten allergy, partly since many such research studies are published in immunology and gastroenterology journals. Methods: Following a Pubmed literature search and online searches on celiac disease websites, 40 articles are critically reviewed in detail. This work reviews celiac disease, gluten intolerance and current evidence of their relationship to neuropsychiatric and systemic illnesses. The review also covers current work-up and diagnosis, as well as dietary interventions, gluten restriction outcomes, and future research directions. Results: Gluten allergy in susceptible individuals damages the small intestine, producing a leaky gut and malabsorption state, as well as allowing antibodies into the bloodstream, which attack major organs. Lack of amino acid precursors for neurotransmitter synthesis together with antibody-associated brain changes and hypoperfusion may result in neuropsychiatric illness. This is well documented; however, studies in neuropsychiatry are often small. In the large CATIE trial, subjects with schizophrenia had significantly increased antibodies to tissue transglutaminase (TTG), and antigliadin antibodies, both significantly greater gluten antibodies than in control subjects. On later follow up, TTG-6 antibodies were identified in these subjects’ brains but not in their intestines. Significant evidence mostly from small studies also exists for gluten allergy and celiac-related depression, anxiety disorders, attention-deficit/hyperactivity disorder, autism spectrum disorders, ataxia, and epilepsy. Dietary restriction of gluten resulted in remission in several published cases, including for treatment-resistant schizophrenia. Conclusions: Ongoing and larger studies are needed of the diagnosis and treatment efficacy of the gluten-free diet in neuropsychiatric illness. Clinicians should ask about the patient history of anemia, hypothyroidism, irritable bowel syndrome and family history of benefit from the gluten-free diet, not limited to but especially in cases of treatment resistance. Obtaining gluten antibodies by a simple blood test, and referral for gastrointestinal work-up in positive cases should be considered.

Keywords: celiac, gluten, neuropsychiatric, translational

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Authors: Giorgio Bertolazzi, Panayiotis Benos, Michele Tumminello, Claudia Coronnello

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MicroRNAs are small non-coding RNAs that post-transcriptionally regulate the expression levels of messenger RNAs. MicroRNA regulation activity depends on the recognition of binding sites located on mRNA molecules. ComiR (Combinatorial miRNA targeting) is a user friendly web tool realized to predict the targets of a set of microRNAs, starting from their expression profile. ComiR incorporates miRNA expression in a thermodynamic binding model, and it associates each gene with the probability of being a target of a set of miRNAs. ComiR algorithms were trained with the information regarding binding sites in the 3’UTR region, by using a reliable dataset containing the targets of endogenously expressed microRNA in D. melanogaster S2 cells. This dataset was obtained by comparing the results from two different experimental approaches, i.e., inhibition, and immunoprecipitation of the AGO1 protein; this protein is a component of the microRNA induced silencing complex. In this work, we tested whether including coding region binding sites in the ComiR algorithm improves the performance of the tool in predicting microRNA targets. We focused the analysis on the D. melanogaster species and updated the ComiR underlying database with the currently available releases of mRNA and microRNA sequences. As a result, we find that the ComiR algorithm trained with the information related to the coding regions is more efficient in predicting the microRNA targets, with respect to the algorithm trained with 3’utr information. On the other hand, we show that 3’utr based predictions can be seen as complementary to the coding region based predictions, which suggests that both predictions, from 3'UTR and coding regions, should be considered in a comprehensive analysis. Furthermore, we observed that the lists of targets obtained by analyzing data from one experimental approach only, that is, inhibition or immunoprecipitation of AGO1, are not reliable enough to test the performance of our microRNA target prediction algorithm. Further analysis will be conducted to investigate the effectiveness of the tool with data from other species, provided that validated datasets, as obtained from the comparison of RISC proteins inhibition and immunoprecipitation experiments, will be available for the same samples. Finally, we propose to upgrade the existing ComiR web-tool by including the coding region based trained model, available together with the 3’UTR based one.

Keywords: AGO1, coding region, Drosophila melanogaster, microRNA target prediction

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Authors: M. Sulieman, H. Arabiyat, H. Ali, K. Potiszil, I. Abbas, R. English, P. King, I. Brown, P. Drew

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Introduction: The incidence of breast ductal Carcinoma in Situ (DCIS) has been increasing; it currently represents up 20-25% of all breast carcinomas. Some aspects of DCIS management are still controversial, mainly due to the heterogeneity of its clinical presentation and of its biological and pathological characteristics. In DCIS, histological diagnosis obtained preoperatively, carries the risk of sampling error if the presence of invasive cancer is subsequently diagnosed. The mammographic extent over than 4–5 cm and the presence of architectural distortion, focal asymmetric density or mass on mammography are proven important risk factors of preoperative histological under staging. Intracystic papillary cancer (IPC) is a rare form of breast carcinoma. Despite being previously compared to DCIS it has been shown to present histologically with invasion of the basement membrane and even metastasis. SLNB – Carries the risk of associated comorbidity that should be considered when planning surgery for DCIS and IPC. Objectives: The aim of this Audit was to better define a ‘high risk’ group of patients with pre-op diagnosis of non-invasive cancer undergoing breast conserving surgery, who would benefit from sentinel node biopsy. Method: Retrospective data collection of all patients with ductal carcinoma in situ over 5 years. 636 patients identified, and after exclusion criteria applied: 394 patients were included. High risk defined as: Extensive micro-calcification >40mm OR any mass forming DCIS. IPC: Winpath search from for the term ‘papillary carcinoma’ in any breast specimen for 5 years duration;.29 patients were included in this group. Results: DCIS: 188 deemed high risk due to >40mm calcification or a mass forming (radiological or palpable) 61% of those had a mastectomy and 32% BCS. Overall, in that high-risk group - the number with invasive disease was 38%. Of those high-risk DCIS pts 85% had a SLN - 80% at the time of surgery and 5% at a second operation. For the BCS patients - 42% had SLN at time of surgery and 13% (8 patients) at a second operation. 15 (7.9%) pts in the high-risk group had a positive SLNB, 11 having a mastectomy and 4 having BCS. IPC: The provisional diagnosis of encysted papillary carcinoma is upgraded to an invasive carcinoma on final histology in around a third of cases. This has may have implications when deciding whether to offer sentinel node removal at the time of therapeutic surgery. Conclusions: We have defined a ‘high risk’ group of pts with pre-op diagnosis of non-invasive cancer undergoing BCS, who would benefit from SLNB at the time of the surgery. In patients with high-risk features; the risk of invasive disease is up to 40% but the risk of nodal involvement is approximately 8%. The risk of morbidity from SLN is up to about 5% especially the risk of lymphedema.

Keywords: breast ductal carcinoma in Situ (DCIS), intracystic papillary carcinoma (IPC), sentinel node biopsy (SLNB), high-risk, non-invasive, cancer disease

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Authors: Jonathan Gong

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: J. O. Ezekwesili-Ofili, L. I. Okorafor, S. C. Nsofor

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Diabetes mellitus is a carbohydrate metabolism disorder due to an absolute or relative deficiency of insulin secretion, action or both. Many known hypoglycaemic drugs are known to produce serious side effects. However, the search for safer and more effective agents has shifted to plant products, including foods and spices. One of such is the rhizome of Curcuma longa or turmeric, which is a spice with high medicinal value. A drawback in the use of C. longa is the poor bioavailability of curcumin, the active ingredient. It has been reported that piperine, an alkaloid present in peppers increases the bioavailability of curcumin. This work therefore investigated the hypoglycaemic and antioxidant effects of ethanolic extract of C. longa rhizomes, alone and with two pepper adjuvants in alloxan-induced diabetic rats. A total of 48 rats were divided into 6 groups of 8 rats each. Groups A–E were induced with diabetes using 150mg/kg body weight of alloxan monohydrate, while group F was normoglycaemic: Group A: Diabetic; fed with 400 mg/g body weight of turmeric extract; group B: Diabetic, fed with 400 mg/kg b. w. and 200mg/kg b. w of ethanolic extract of seeds of Piper guinensee; group C: Diabetic, fed with 400 mg/kg b. w. and 200 mg /kg b. w. of ethanolic extract of seeds of Capsicum annum var cameroun, group D: Diabetic, treated with standard drug, glibenclamide (0.3mg/kg body weight), group E: Diabetic; no treatment i.e. Positive control and group F: non diabetic, no treatment i.e. Negative control. Blood glucose levels were monitored for 14 days using a glucometer. The levels of the antioxidant enzymes; glutathione peroxidase, catalase and superoxide dismutase were also assayed in serum. The ethanolic extracts of C. longa rhizomes at the dose given (400 mg/kg b. w) significantly reduced the blood glucose levels of the diabetic rats (p<0.05) comparable to the standard drug. Co administration of extract of the peppers did not significantly increase the efficiency of the extract, although C. annum var cameroun showed greater effect, though not significantly. The antioxidant effect of the extract was significant in diabetic rats. The use of piperine-containing peppers enhanced the antioxidant effect. Phytochemical analyses of the ethanolic extract of C. longa showed the presence of alkaloids, flavonoids, steroids, saponins, tannins, glycosides, and terpenoids. These results suggest that the ethanolic extract of C. longa had antidiabetic with antioxidant effects and could thus be of benefit in the treatment and management of diabetes as well as ameliorate pro-oxidant effects that may lead to diabetic complications. However, while the addition of piperine did not affect the antidiabetic effect of C. longa, the antioxidant effect was greatly enhanced.

Keywords: antioxidant, Curcuma longa rhizome, hypoglycaemic, pepper adjuvants, piperine

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Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

Abstract:

Antimicrobial drugs have an important role in controlling illness associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing like disk diffusion are time-consuming and other method including E-test, genotyping are relatively expensive. Fourier transform infrared (FTIR) microscopy is rapid, safe, and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 550 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 85% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E. coli, FTIR, multivariate analysis, susceptibility

Procedia PDF Downloads 239

Authors: Valentina Marutyan

Abstract:

Healthcare data mining is a rapidly developing field at the intersection of technology and medicine that has the potential to change our understanding and approach to providing healthcare. Healthcare and data mining is the process of examining huge amounts of data to extract useful information that can be applied in order to improve patient care, treatment effectiveness, and overall healthcare delivery. This field looks for patterns, trends, and correlations in a variety of healthcare datasets, such as electronic health records (EHRs), medical imaging, patient demographics, and treatment histories. To accomplish this, it uses advanced analytical approaches. Predictive analysis using historical patient data is a major area of interest in healthcare data mining. This enables doctors to get involved early to prevent problems or improve results for patients. It also assists in early disease detection and customized treatment planning for every person. Doctors can customize a patient's care by looking at their medical history, genetic profile, current and previous therapies. In this way, treatments can be more effective and have fewer negative consequences. Moreover, helping patients, it improves the efficiency of hospitals. It helps them determine the number of beds or doctors they require in regard to the number of patients they expect. In this project are used models like logistic regression, random forests, and neural networks for predicting diseases and analyzing medical images. Patients were helped by algorithms such as k-means, and connections between treatments and patient responses were identified by association rule mining. Time series techniques helped in resource management by predicting patient admissions. These methods improved healthcare decision-making and personalized treatment. Also, healthcare data mining must deal with difficulties such as bad data quality, privacy challenges, managing large and complicated datasets, ensuring the reliability of models, managing biases, limited data sharing, and regulatory compliance. Finally, secret code of data mining in healthcare helps medical professionals and hospitals make better decisions, treat patients more efficiently, and work more efficiently. It ultimately comes down to using data to improve treatment, make better choices, and simplify hospital operations for all patients.

Keywords: data mining, healthcare, big data, large amounts of data

Procedia PDF Downloads 46