Search results for: clinical prediction rule

Authors: Mohammad R. Jalali, Mohammad M. Jalali

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The earliest theories of sloshing waves and solitary waves based on potential theory idealisations and irrotational flow have been extended to be applicable to more realistic domains. To this end, the computational fluid dynamics (CFD) methods are widely used. Three-dimensional CFD methods such as Navier-Stokes solvers with volume of fluid treatment of the free surface and Navier-Stokes solvers with mappings of the free surface inherently impose high computational expense; therefore, considerable effort has gone into developing depth-averaged approaches. Examples of such approaches include Green–Naghdi (GN) equations. In Cartesian system, GN velocity profile depends on horizontal directions, x-direction and y-direction. The effect of vertical direction (z-direction) is also taken into consideration by applying weighting function in approximation. GN theory considers the effect of vertical acceleration and the consequent non-hydrostatic pressure. Moreover, in GN theory, the flow is rotational. The present study illustrates the application of GN equations to propagation of sloshing waves and solitary waves. For this purpose, GN equations solver is verified for the benchmark tests of Gaussian hump sloshing and solitary wave propagation in shallow basins. Analysis of the free surface sloshing of even harmonic components of an initial Gaussian hump demonstrates that the GN model gives predictions in satisfactory agreement with the linear analytical solutions. Discrepancies between the GN predictions and the linear analytical solutions arise from the effect of wave nonlinearities arising from the wave amplitude itself and wave-wave interactions. Numerically predicted solitary wave propagation indicates that the GN model produces simulations in good agreement with the analytical solution of the linearised wave theory. Comparison between the GN model numerical prediction and the result from perturbation analysis confirms that nonlinear interaction between solitary wave and a solid wall is satisfactorilly modelled. Moreover, solitary wave propagation at an angle to the x-axis and the interaction of solitary waves with each other are conducted to validate the developed model.

Keywords: Green–Naghdi equations, nonlinearity, numerical prediction, sloshing waves, solitary waves

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Authors: Man-Yun Liu, Emily Chia-Yu Su

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Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

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Authors: Fatima Faraz

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BACKGROUND: While Artificial intelligence (AI) provides new opportunities across a wide variety of industries, healthcare is no exception. AI can lead to advancements in how the healthcare system functions and improves the quality of patient care. Developing countries like Pakistan are lagging in the implementation of AI-based solutions in healthcare. This demands increased knowledge and AI literacy among health care professionals. OBJECTIVES: To assess the level of awareness among medical students and faculty about AI in preparation for teaching AI basics and data science applications in clinical practice in an integrated medical curriculum. METHODS: An online 15-question semi-structured questionnaire, previously tested and validated, was delivered among participants through convenience sampling. The questionnaire composed of 3 parts: participant’s background knowledge, AI awareness, and attitudes toward AI applications in medicine. RESULTS: A total of 182 students and 39 faculty members from Rawalpindi Medical University, Pakistan, participated in the study. Only 26% of students and 46.2% of faculty members responded that they were aware of AI topics in clinical medicine. The major source of AI knowledge was social media (35.7%) for students and professional talks and colleagues (43.6%) for faculty members. 23.5% of participants answered that they personally had a basic understanding of AI. Students and faculty (60.1%) were interested in AI in patient care and teaching domain. These findings parallel similar published AI survey results. CONCLUSION: This survey concludes interest among students and faculty in AI developments and technology applications in healthcare. Further studies are required in order to correctly fit AI in the integrated modular curriculum of medical education.

Keywords: medical education, data science, artificial intelligence, curriculum

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Authors: Abdulfatah Al-Jaradi, Marzoq Ali Odhah, Abdulnasser A. Haza’a

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Background: Antenatal care can be defined as the care provided by skilled healthcare professionals to pregnant women and adolescent girls to ensure the best health conditions for both mother and baby during pregnancy. The components of ANC include risk identification; prevention and management of pregnancy-related or concurrent diseases; and health education and health promotion. The aim of this study: to assess the knowledge, attitude, and practice of pregnant women regarding antenatal care. Methodology: A descriptive KAP study was conducting in public hospitals in Sana'a City-Yemen. The study population was included all pregnant women that intended to the prenatal department and clinical outpatient department, the final sample size was 371 pregnant women, a self-administered questionnaire was used to collect the data, statistical package for social sciences SPSS was used to data analysis. The results: Most (79%) of pregnant women were had correct answers in total knowledge regarding antenatal care, and about two-thirds (67%) of pregnant women were had performance practice regarding antenatal care and two-third (68%) of pregnant women were had a positive attitude. Conclusions & Recommendations: We concluded that a significant association between overall knowledge and practice level toward antenatal care and demographic characteristics of pregnant women, women (residence place, level of education, did your husband support you in attending antenatal care and place of delivery of the last baby), at (P-value ≤ 0.05). We recommended more education and training courses, lecturers and education sessions in clinical facilitators focused ANC, which relies on evidence-based interventions provided to women during pregnancy by skilled healthcare providers such as midwives, doctors, and nurses.

Keywords: antenatal care, knowledge, practice, attitude, pregnant women

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Authors: Sonal Sethi, Mukesh Yadav, Abhimanyu Gupta

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The upcoming field of radiogenomics has the potential to upgrade the role of imaging in lung cancer management by noninvasive characterization of tumor histology and genetic microenvironment. Receptor positivity like epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) genotyping are critical in lung adenocarcinoma for treatment. As conventional identification of receptor positivity is an invasive procedure, we analyzed the features on non-invasive computed tomography (CT), which predicts the receptor positivity in lung adenocarcinoma. Retrospectively, we did a comprehensive study from 77 proven lung adenocarcinoma patients with CT images, EGFR and ALK receptor genotyping, and clinical information. Total 22/77 patients were receptor-positive (15 had only EGFR mutation, 6 had ALK mutation, and 1 had both EGFR and ALK mutation). Various morphological characteristics and metastatic distribution on CT were analyzed along with the clinical information. Univariate and multivariable logistic regression analyses were used. On multivariable logistic regression analysis, we found spiculated margin, lymphangitic spread, air bronchogram, pleural effusion, and distant metastasis had a significant predictive value for receptor mutation status. On univariate analysis, air bronchogram and pleural effusion had significant individual predictive value. Conclusions: Receptor positive lung cancer has characteristic imaging features compared with nonreceptor positive lung adenocarcinoma. Since CT is routinely used in lung cancer diagnosis, we can predict the receptor positivity by a noninvasive technique and would follow a more aggressive algorithm for evaluation of distant metastases as well as for the treatment.

Keywords: lung cancer, multidisciplinary cancer care, oncologic imaging, radiobiology

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Authors: Thakur Pushpawati, Singh Vinita, Agrawal Sarita, Mohapatra Eli

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Polycystic ovary syndrome (PCOS) is a disease of endocrine and frequently encountered in women in their reproductive period, and it is characterized by clinical features of anovulation, clinical and biochemical features of hyperandrogenism, and PCOS morphology on ultrasonographic examination. In Indian scenario, only a few studies are available on the correlation of serum 25-dihydroxy vitamin D3 level and insulin level. The present study is a prospective case-control study and aims to estimate the concentration of serum 25-dihydroxy vitamin D3 and insulin resistance and determine the association of serum 25-dihydroxy vitamin D3 with insulin resistance in PCOS women of 18-40 years age group. In this study, the primary objective is to estimate the concentration of 25-dihydroxy vitamin D3, insulin, glycaemic status, calcium and phosphorus levels in 18-40 year age women with polycystic ovary syndrome and to compare these parameters with age and BMI matched healthy control of same age group women. The secondary objective is to determine the association between 25-dihydroxy vitamin D3 concentration and insulin resistance among PCOS cases in 18-40 years age group women. This study was carried on at outpatient Department of Obstetrics & Gynaecology, Aiims Raipur. It took one year from the date of approval. In case, 32 women were diagnosed (Diagnosed PCOS cases as per Rotterdoms criteria among women of 18-40 years of age), as control group 32 women of 18-40 years of age were diagnosed As a result, serum insulin level was elevated among PCOS women along with 25-dihydroxy vitamin D3 deficiency.Conclude up, PCOS is more common in the age group of 20-40 years. There is a strong correlation between vitamin D deficiency and insulin resistance among PCOS patients.

Keywords: vitamin D, insulin resistance, PCOS, reproductive age group

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Authors: M. Khordadmehr, V. R. Ranjbar, R. Norouzi, M. Zeinoddin

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Coccidiosis is recognized as a serious parasitic disease problem limiting quail industry recently. But the data on incidence, clinical signs, species of coccidia and pathological changes in Japanese quail are rare, especially in Iran in spite of the significant improvement of commercial quail breeding in this country in recent decades. Therefore, in the present paper was studied natural infection of quail coccidiosis in three commercial rearing farms with 80% morbidity and 3% mortality rate. For this purpose, fecal sample, oocyst examination, and morphological study were performed beside necropsy, histopathology, and PCR to confirm the diagnosis. In the affected birds, clinical signs included brown diarrhea, weakness, and pale face. In the fecal examination, three species of the genus Eimeria were identified including E. uzura, E. bateri, and E. tsunodai. At necropsy, the main gross lesions were edema, congestion and small blood spots in the small intestine. In histopathologic examination, endogenous stages of the parasites associated with hyperplasia of the intestinal glands, mild congestion, infiltration of mononuclear cells, and edema were observed in the intestine. The molecular study using BSEF and BSER specific primers confirmed the presence of the genus Eimeria in the affected birds. Interestingly, phylogenetic analysis showed relatively high bootstrap values in Japanese quail Eimeria with E. acervuline and E. maxima strains in the chicken. The present study is the first phylogenetic findings on Eimeria of quail which could be valuable for further research on Japanese quail coccidiosis.

Keywords: coccidiosis, Japanese Quail, pathomorphology, phylogenetic analysis

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Authors: Yael Rieder, Yael Gilboa, S. O. Adva, Efrat Halevi, Ronnie Tepper

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Background: Operation of ultrasound equipment is a core skill for many clinical specialties. As part of the training program at -Simultech- a simulation center for Ob\Gyn at the Meir Medical Center, Israel, teaching how to operate ultrasound equipment requires dealing with misunderstandings of spatial and 3D orientation, failure of the operator to hold a transducer correctly, and limited ability to evaluate the data on the screen. We have developed a platform intended to endow physicians and sonographers with clinical and operational skills of obstetric ultrasound. Simultech's simulations are focused on medical knowledge, risk management, technology operations and physician-patient communication. The simulations encompass extreme work conditions. Setup: Between eight and ten of the eight hundred and fifty physicians and sonographers of the Clalit health services from seven hospitals and eight community centers across Israel, participate in individual Ob/Gyn training sessions each week. These include Ob/Gyn specialists, experts, interns, and sonographers. Innovative teaching and training methodologies: The six-hour training program includes: (1) An educational computer program that challenges trainees to deal with medical questions based upon ultrasound pictures and films. (2) Sophisticated hands-on simulators that challenge the trainees to practice correct grip of the transducer, elucidate pathology, and practice daily tasks such as biometric measurements and analysis of sonographic data. (3) Participation in a video-taped simulation which focuses on physician-patient communications. In the simulation, the physician is required to diagnose the clinical condition of a hired actress based on the data she provides and by evaluating the assigned ultrasound films accordingly. Giving ‘bad news’ to the patient may put the physician in a stressful situation that must be properly managed. (4) Feedback at the end of each phase is provided by a designated trainer, not a physician, who is specially qualified by Ob\Gyn senior specialists. (5) A group exercise in which the trainer presents a medico-legal case in order to encourage the participants to use their own experience and knowledge to conduct a productive ‘brainstorming’ session. Medical cases are presented and analyzed by the participants together with the trainer's feedback. Findings: (1) The training methods and content that Simultech provides allows trainees to review their medical and communications skills. (2) Simultech training sessions expose physicians to both basic and new, up-to-date cases, refreshing and expanding the trainee's knowledge. (3) Practicing on advanced simulators enables trainees to understand the sonographic space and to implement the basic principles of ultrasound. (4) Communications simulations were found to be beneficial for trainees who were unaware of their interpersonal skills. The trainer feedback, supported by the recorded simulation, allows the trainee to draw conclusions about his performance. Conclusion: Simultech was found to contribute to physicians at all levels of clinical expertise who deal with ultrasound. A break in daily routine together with attendance at a neutral educational center can vastly improve performance and outlook.

Keywords: medical training, simulations, ultrasound, Simultech

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Authors: Karima Boukhadia

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In the present study, the subsonic flow in an asymmetrical diffuser was simulated numerically using code CFX 11.0 and its generator of grid ICEM CFD. Two models of turbulence were tested: K- ε and K- ω SST. The results obtained showed that the K- ε model singularly over-estimates the speed value close to the wall and that the K- ω SST model is qualitatively in good agreement with the experimental results of Buice and Eaton 1997. They also showed that the separation and reattachment of the fluid on the tilted wall strongly depends on its angle of inclination and that the length of the zone of separation increases with the angle of inclination of the lower wall of the diffuser.

Keywords: asymmetric diffuser, separation, reattachment, tilt angle, separation zone

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Authors: Sabrina Ladjama, Aicha Rizi, Azzedine Abbaci

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In this work, we use the crossover model to formulate a comprehensive fundamental equation of state for the thermodynamic properties for several n-alkanes in the critical region that extends to the classical region. This equation of state is constructed on the basis of comparison of selected measurements of pressure-density-temperature data, isochoric and isobaric heat capacity. The model can be applied in a wide range of temperatures and densities around the critical point for n-heptane. It is found that the developed model represents most of the reliable experimental data accurately.

Keywords: crossover model, critical region, fundamental equation, n-heptane

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Authors: Rekab Djabri Hamza, Daoud Salah

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We report first-principles calculations of structural and magnetic properties of TmAs compound in zinc blende(B3) and CsCl(B2), structures employing the density functional theory (DFT) within the local density approximation (LDA). We use the full potential linear muffin-tin orbitals (FP-LMTO) as implemented in the LMTART-MINDLAB code (Calculation). Results are given for lattice parameters (a), bulk modulus (B), and its first derivatives(B’) in the different structures NaCl (B1) and CsCl (B2). The most important result in this work is the prediction of the possibility of transition; from cubic rocksalt (NaCl)→ CsCl (B2) (32.96GPa) for TmAs. These results use the LDA approximation.

Keywords: LDA, phase transition, properties, DFT

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Authors: Malalage Mudara Peiris

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Objectives of the study are: the biosynthesis of silver nanoparticles (AgNPs) using Escherichia coli, Acinetobacter baumannii and Staphylococcus aureus, characterization of silver nanoparticles and determination of antimicrobial activity against E. coli, P. aeruginosa, S. aureus, MRSA, and C. Albicans. Methods: E. coli (ATCC 25922), A. baumanii (clinical strain), S. aureus (clinical strain) cultured in nutrient broth medium were used for biosynthesis of AgNPs. Culture conditions (AgNO3 concentration, pH, incubation time and temperature) were optimized. Characterization of synthesized NPs was done by UV-Visible spectroscopy. The antimicrobial activity of the synthesized NPs was studied using the good diffusion assay against E. coli, S. aureus, MRSA (Methicillin-resistant Staphylococcus aureus), P. aeruginosa and C. Albicans. Results: All the selected bacteria produced silver nanoparticles at alkaline pH above 0.3 g/L AgNO3 concentration. The optimum reaction temperature was 60oC. According to the UV-Visible spectroscopy, the maximum absorbance was found to be around 420 - 430 nm indicating the presence of AgNPs. According to the good diffusion results, AgNPs produced by S. aureus resulted in the larger zone of inhibition (ZOI) against the selected pathogens, while AgNPs produced by E. coli showed comparatively smaller ZOI. In general, biosynthesized AgNPs were highly effective against gram-negative bacteria compared to gram-positive bacterial and fungal species. Conclusions: Green AgNPs produced by each bacterium show antimicrobial activity against the selected pathogens. AgNPs produced by S. aureus are the most effective NPs among tested AgNPs, while AgNPs produced by E. coli are the least effective. Further characterization of NPs is required to study the physical properties of silver NPs.

Keywords: green nanotechnology, silver nanoparticles, bacteria, antimicrobial activity

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Authors: I. Ramalho, S. Campos, M. Dias

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Introduction: Endometriosis may play a role in the pathogenesis of ovarian cancer (OC), however, the risk and prognosis have not been well established. The association between these two pathologies could have an important impact on prevention and early diagnosis of OC. Objective: To analyze the prevalence of endometriosis associated ovarian cancer and related clinical, epidemiological and histopathological issues. Design: We conducted a retrospective case series analysis of patients diagnosed with endometriosis and ovarian cancer in the Gynecology Department of Coimbra University Hospital Center since 2006 to 2015. Methods: We collected data from women diagnosed with ovarian cancer, with anatomopathology records reporting findings of endometriosis in ovarian cancer patients. Patients were retrieved from the pathological records and appropriate medical records were retrospectively reviewed. Statistical analysis was performed using SPSS 22.0. Results: Histological evidence of endometriosis was found in 17 out of 261 patients diagnosed with ovarian cancer (OC) (6.51%). The most usual symptoms were pelvic pain, abdominal distension, asthenia, ascites, weight loss and nausea. Mean age at diagnosis was 61.2 ± 15.1, 41-86 years old, 33.3% were pre-menopausal patients and cancer stage distribution was predominantly stage I (31.3%) and stage III (56.3%). OC occurred unilaterally in 14 patients and 2 patients were diagnosed with a synchronous ovarian and endometrial cancer. Regarding histological type, 10 OC were classified as clear cell carcinoma (CCC), 4 endometrioid carcinomas (EC) and 3 mixed type (clear cell and endometrioid). Four ovarian carcinomas presumably arose from endometriomas: 3 CCC and 1 EC. Conclusions: In accordance with previous studies, clear cell was the most common pathological type in endometriotic patients, followed by endometrioid carcinomas, and two rare synchronous ovarian and endometrial carcinomas were registered. Although endometriosis association to OC is uncommon, endometriosis should be managed with special care in order to early diagnosis.

Keywords: endometriosis, histology, observational study, ovarian cancer

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Authors: Arslan Masood Pirzada, Muhammad Naeem, Hafiz Haider Ali, Muhammad Latif, Aown Sammar Raza, Asad Hussain Bukhari, Muhammad Saqib, Muhammad Ijaz

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Cyperus rotundus (Cyperaceae), a medicinal herb, is being traditionally used as a home remedy for the treatment of various clinical conditions like diarrhea, diabetic, pyretic, inflammation, malaria, and for treating stomach and bowel disorders. Its current status is one of the most widespread, troublesome, and economically damaging agronomic weeds, growing wildly in various tropical and sub-tropical regions of the world. Tuber and rhizomes of Cyperus rotundus possess a higher concentration of active ingredients in the form of essential oils, phenolic acids, ascorbic acids and flavonoids, responsible for its remedial properties. Exploitation of any medicinal plant application depends on the crucial and comprehensive information about the therapeutic potential of a plant. Researchers have evaluated and characterized the significance of Cyperus rotundus as an anti-androgenic, anti-bacterial, anti-cancerous, anti-convulsant, anti-diabetic, anti-diarrheal, anti-genotoxic, anti-inflammatory, anti-lipidemic, anti-malarial, anti-mutagenic, anti-obesity, anti-oxidant, anti-uropathogenic, hepato-, cardio-, neuroprotective, and nootropic agent. This paper comprises a broad review to summarize the current state of knowledge about chemical constituents, potential economic uses and therapeutic aspects of Cyperus rotundus that will aid in the development of bioethanol and modern herbal medicine through latest technologies that will promote the ability of this plant in the cure of many clinical disorders.

Keywords: purple nutsedge, chemical composition, economic uses, therapeutic values, future directions

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Authors: Jill Garner, Belinda Lange, Sheila Lennon, Maayken van den Berg

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Currently, there are approximately one billion people worldwide affected by a neurological condition. Many of whom are assessed and treated by a physiotherapist in a variety of settings. There is a lack of consensus in the literature related to what is clinically assessed by physiotherapists in people with neurological conditions. This study aimed to explore assessment in people with neurological conditions, including how health care setting, experience, and therapeutic approach, may influence neurological assessment. A national survey targeted Australian physiotherapists who assess adults with neurological conditions as part of their clinical practice. The survey consisted of 39 questions and was distributed to physiotherapists through the Australian Physiotherapy Association, and Chief Allied Health Officers across Australia and advertised on the National Neurological Physiotherapy Facebook page. In total, 395 respondents consented to the survey from all states within Australia. Most respondents were female (85.4%) with a mean (SD) age of 35.7 years. Respondents reported working clinically in acute, community, outpatients, and community settings. Stroke was the most assessed condition (58.0%). There is variability in domains assessed by Australian physiotherapists, with common inclusions of balance, muscle strength, gait, falls and safety, function, goal setting, range of movement, pain, coordination, activity tolerance, postural alignment and symmetry and upper limb. There is little evidence to support what physiotherapists assess in practice, in different settings, and in different states within Australia and not enough information to develop a decision tree regarding what is important for assessment in different settings. Further research is needed to explore this area and develop a consensus around best practices.

Keywords: physiotherapy, neurological, assessment, domains

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Authors: Dina Farran, Mark Ashworth, Fiona Gaughran

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Atrial fibrillation (AF), the most prevalent cardiac arrhythmia, is associated with an increased risk of stroke, contributing to heart failure and death. In this project, we aim to improve patient safety by screening for stroke risk among people with AF and co-morbid mental illness. To do so, we started by conducting a systematic review and meta-analysis on prevalence, management, and outcomes of AF in people with Serious Mental Illness (SMI) versus the general population. We then evaluated oral anticoagulation (OAC) prescription trends in people with AF and co-morbid SMI in King’s College Hospital. We also evaluated the association between mental illness severity and OAC prescription in eligible patients in South London and Maudsley (SLaM) NHS Foundation Trust. Next, we implemented an electronic clinical decision support system (eCDSS) consisting of a visual prompt on patient electronic Personal Health Records to screen for AF-related stroke risk in three Mental Health of Older Adults wards at SLaM. Finally, we assessed the feasibility and acceptability of the eCDSS by qualitatively investigating clinicians’ perspectives of the potential usefulness of the eCDSS (pre-intervention) and their experiences and their views regarding its impact on clinicians and patients (post-intervention). The systematic review showed that people with SMI had low reported rates of AF. AF patients with SMI were less likely to receive OAC than the general population. When receiving warfarin, people with SMI, particularly bipolar disorder, experienced poor anticoagulation control compared to the general population. Meta-analysis showed that SMI was not significantly associated with an increased risk of stroke or major bleeding when adjusting for underlying risk factors. The main findings of the first observational study were that among AF patients having a high stroke risk, those with co-morbid SMI were less likely than non-SMI to be prescribed any OAC, particularly warfarin. After 2019, there was no significant difference between the two groups. In the second observational study, patients with AF and co-morbid SMI were less likely to be prescribed any OAC compared to those with dementia, substance use disorders, or common mental disorders, adjusting for age, sex, stroke, and bleeding risk scores. Among AF patients with co-morbid SMI, warfarin was less likely to be prescribed to those having alcohol or substance dependency, serious self-injury, hallucinations or delusions, and activities of daily living impairment. In the intervention, clinicians were asked to confirm the presence of AF, clinically assess stroke and bleeding risks, record risk scores in clinical notes, and refer patients at high risk of stroke to OAC clinics. Clinicians reported many potential benefits for the eCDSS, including improving clinical effectiveness, better identification of patients at risk, safer and more comprehensive care, consistency in decision making and saving time. Identified potential risks included rigidity in decision-making, overreliance, reduced critical thinking, false positive recommendations, annoyance, and increased workload. This study presents a unique opportunity to quantify AF patients with mental illness who are at high risk of severe outcomes using electronic health records. This has the potential to improve health outcomes and, therefore patients' quality of life.

Keywords: atrial fibrillation, stroke, mental health conditions, electronic clinical decision support systems

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Authors: Usman Qamar, Younus Javed

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Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and rough-sets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.

Keywords: rough-sets, classification, feature selection, entropy, outliers, frequent itemset mining

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Authors: Muhammad Usman

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Pattern extraction has been done in past to extract hidden and interesting patterns from large datasets. Recently, advancements are being made in these techniques by providing the ability of multi-level mining, effective dimension reduction, advanced evaluation and visualization support. This paper focuses on reviewing the current techniques in literature on the basis of these parameters. Literature review suggests that most of the techniques which provide multi-level mining and dimension reduction, do not handle mixed-type data during the process. Patterns are not extracted using advanced algorithms for large datasets. Moreover, the evaluation of patterns is not done using advanced measures which are suited for high-dimensional data. Techniques which provide visualization support are unable to handle a large number of rules in a small space. We present a theoretical model to handle these issues. The implementation of the model is beyond the scope of this paper.

Keywords: association rule mining, data mining, data warehouses, visualization of association rules

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Authors: Pomozova Kseniia, Gorlachev Gennadiy, Chernyaev Aleksandr, Golanov Andrey

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In clinical practice, and especially in stereotactic radiosurgery planning, the significance of diffusion-weighted imaging (DWI) is growing. This makes the existence of software capable of quickly processing and reliably visualizing diffusion data, as well as equipped with tools for their analysis in terms of different tasks. We are developing the «MRDiffusionImaging» software on the standard C++ language. The subject part has been moved to separate class libraries and can be used on various platforms. The user interface is Windows WPF (Windows Presentation Foundation), which is a technology for managing Windows applications with access to all components of the .NET 5 or .NET Framework platform ecosystem. One of the important features is the use of a declarative markup language, XAML (eXtensible Application Markup Language), with which you can conveniently create, initialize and set properties of objects with hierarchical relationships. Graphics are generated using the DirectX environment. The MRDiffusionImaging software package has been implemented for processing diffusion magnetic resonance imaging (dMRI), which allows loading and viewing images sorted by series. An algorithm for "masking" dMRI series based on T2-weighted images was developed using a deformable surface model to exclude tissues that are not related to the area of interest from the analysis. An algorithm of distortion correction using deformable image registration based on autocorrelation of local structure has been developed. Maximum voxel dimension was 1,03 ± 0,12 mm. In an elementary brain's volume, the diffusion tensor is geometrically interpreted using an ellipsoid, which is an isosurface of the probability density of a molecule's diffusion. For the first time, non-parametric intensity distributions, neighborhood correlations, and inhomogeneities are combined in one segmentation of white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) algorithm. A tool for calculating the coefficient of average diffusion and fractional anisotropy has been created, on the basis of which it is possible to build quantitative maps for solving various clinical problems. Functionality has been created that allows clustering and segmenting images to individualize the clinical volume of radiation treatment and further assess the response (Median Dice Score = 0.963 ± 0,137). White matter tracts of the brain were visualized using two algorithms: deterministic (fiber assignment by continuous tracking) and probabilistic using the Hough transform. The proposed algorithms test candidate curves in the voxel, assigning to each one a score computed from the diffusion data, and then selects the curves with the highest scores as the potential anatomical connections. White matter fibers were visualized using a Hough transform tractography algorithm. In the context of functional radiosurgery, it is possible to reduce the irradiation volume of the internal capsule receiving 12 Gy from 0,402 cc to 0,254 cc. The «MRDiffusionImaging» will improve the efficiency and accuracy of diagnostics and stereotactic radiotherapy of intracranial pathology. We develop software with integrated, intuitive support for processing, analysis, and inclusion in the process of radiotherapy planning and evaluating its results.

Keywords: diffusion-weighted imaging, medical imaging, stereotactic radiosurgery, tractography

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Authors: Vinod Kumar Jaysaval, Prateek Agarwal

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Performance prediction of airborne radar is a challenging and cumbersome task in clutter scenario for different types of targets. A generalized model requires to predict the performance of Radar for air targets as well as ground moving targets. In this paper, we propose a generalized model to bring out the performance of airborne radar for different Pulsed Repetition Frequency (PRF) as well as different type of targets. The model provides a platform to bring out different subsystem parameters for different applications and performance requirements under different types of clutter terrain.

Keywords: airborne radar, blind zone, clutter, probability of detection

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Authors: Chiu-Wen Chang, I-Yun Chang, Wei-Ting Chen, Hui-Ping Ho, Ruei-Hun Chang, Joh-Jong Huang

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Kaohsiung City is located in the tropical region where has Aedes aegypti and Aedes albopictus distributed; once the virus invades, it’s can easily trigger local epidemic. Besides, Kaohsiung City has a world-class airport and harbor, trade and tourism are close and frequently with every country, especially with the Southeast Asian countries which also suffer from dengue. Therefore, Kaohsiung City faces the difficult challenge of dengue every year. The objectives of this study was to enhance dengue clinical care, border management and vector surveillance in Kaohsiung City by establishing an larger scale, innovatively and more coordinated dengue prevention and control strategies in 2016, including (1) Integrated medical programs: facilitated 657 contract medical institutions, widely set up NS1 rapid test in clinics, enhanced triage and referrals system, dengue case daily-monitoring management (2) Border quarantine: comprehensive NS1 screening for foreign workers and fisheries when immigration, hospitalization and isolation for suspected cases, health education for high risk groups (foreign students, other tourists) (3) Mosquito control: Widely use Gravitrap to monitor mosquito density in environment, use NS1 rapid screening test to detect community dengue virus (4) Health education: create a dengue app for people to immediately inquire the risk map and nearby medical resources, routine health education to all districts to strengthen public’s dengue knowledge, neighborhood cleaning awards program. The results showed that after new integration of dengue prevention and control strategies fully implemented in Kaohsiung City, the number of confirmed cases in 2016 declined to 342 cases, the majority of these cases are the continuation epidemic in 2015; in fact, only two cases confirmed after the 2016 summer. Besides, the dengue mortality rate successfully decreased to 0% in 2016. Moreover, according to the reporting rate from medical institutions in 2014 and 2016, it dropped from 27.07% to 19.45% from medical center, and it decreased from 36.55% to 29.79% from regional hospital; however, the reporting rate of district hospital increased from 11.88% to 15.87% and also increased from 24.51% to 34.89% in general practice clinics. Obviously, it showed that under the action of strengthening medical management, it reduced the medical center’s notification ratio and improved the notification ratio of general clinics which achieved the great effect of dengue clinical management and dengue control.

Keywords: dengue control, integrated control strategies, clinical management, NS1

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Authors: Lea Stein, Sabine Rösner, Alessandra Lo Giudice, Beate Ditzen, Tewes Wischmann

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For many couples bearing children is a consistent life goal; however, it cannot always be fulfilled. Undergoing infertility treatment does not guarantee pregnancies and live births. Couples have to deal with miscarriages and sometimes even discontinue infertility treatment. Significant medical predictors for the outcome of infertility treatment have yet to be fully identified. To further our understanding, a cross-sectional five-year follow-up survey was undertaken, in which 95 women and 82 men that have been treated at the Women’s Hospital of Heidelberg University participated. Binary logistic regressions, parametric and non-parametric methods were used for our sample to determine the relevance of biological (infertility diagnoses, maternal and paternal age) and lifestyle factors (smoking, drinking, over- and underweight) on the outcome of infertility treatment (clinical pregnancy, live birth, miscarriage, dropout rate). During infertility treatment, 72.6% of couples became pregnant and 69.5% were able to give birth. Suffering from miscarriages 27.5% of couples and 20.5% decided to discontinue an unsuccessful fertility treatment. The binary logistic regression models for clinical pregnancies, live births and dropouts were statistically significant for the maternal age, whereas the paternal age in addition to maternal and paternal BMI, smoking, infertility diagnoses and infections, showed no significant predicting effect on any of the outcome variables. The results confirm an effect of maternal age on infertility treatment, whereas the relevance of other medical predictors remains unclear. Further investigations should be considered to increase our knowledge of medical predictors.

Keywords: advanced maternal age, assisted reproductive technology, female factor, male factor, medical predictors, infertility treatment, reproductive medicine

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Authors: Lok Bahadur Shrestha, Narayan Raj Bhattarai, Basudha Khanal

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Introduction: Coagulase-negative staphylococci (CoNS) are the normal commensal of human skin and mucous membranes. The study was carried out to study the prevalence of CoNS among clinical isolates, to characterize them up to species level and to compare the three conventional methods for detection of biofilm formation. Objectives: to characterize the clinically significant coagulase-negative staphylococci up to species level, to compare the three phenotypic methods for the detection of biofilm formation and to study the antimicrobial susceptibility pattern of the isolates. Methods: CoNS isolates were obtained from various clinical samples during the period of 1 year. Characterization up to species level was done using biochemical test and study of biofilm formation was done by tube adherence, congo red agar, and tissue culture plate method. Results: Among 71 CoNS isolates, seven species were identified. S. epidermidis was the most common species followed by S. saprophyticus, S. haemolyticus. Antimicrobial susceptibility pattern of CoNS documented resistance of 90% to ampicillin. Resistance to cefoxitin and ceftriaxone was observed in 55% of the isolates. We detected biofilm formation in 71.8% of isolates. The sensitivity of tube adherence method was 82% while that of congo red agar method was 78%. Conclusion: Among 71 CoNS isolated, S. epidermidis was the most common isolates followed by S. saprophyticus and S. haemolyticus. Biofilm formation was detected in 71.8% of the isolates. All of the methods were effective at detecting biofilm-producing CoNS strains. Biofilm former strains are more resistant to antibiotics as compared to biofilm non-formers.

Keywords: CoNS, congo red agar, bloodstream infections, foreign body-related infections, tissue culture plate

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Authors: Kamal Ameis

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This study aims to further improve our understanding of the underlying mechanism of local injury that occurs after manual acupuncture needle manipulation, and that initiates the muscle regeneration process, which is essential for muscle maintenance and adaptation. Skeletal muscle is maintained by resident stem cells called muscle satellite cells. These cells are normally in quiescent state, but following muscle injury, they re-enter the cell cycle and execute a myogenic program resulting in muscle fiber regeneration. Our previous work in young rats demonstrated that acupuncture treatment induced injury that activated resident satellite (stem) cells, which leads to muscle regeneration. Skeletal muscle regeneration is an adaptive response to injury that requires a tightly orchestrated event between signaling pathways activated by growth factor and intrinsic regulatory program controlled by myogenic transcription factor. We identified several gene expressions uniquely important for muscle regeneration in response to acupuncture treatment at different time course using different biological techniques, including Immunocytochemistry, western blotting, and Real Time PCR. This study uses a novel but non-invasive model of injury induced by manual acupuncture to further our current understanding of regenerative mechanism of muscle stem cells. From a clinical perspective, this model of injury induced by manual acupuncture may be easily translatable into a clinical tool that can be used as an alternative to physical exercise for patients challenged by bed rest or forced inactivity. Finally, the knowledge gained from this research could be useful for studies of the local effects of various modalities of induced injury, such as the traditional method of healing by cupping (hijamah), which may enhanced muscle stem cells and muscle fiber regeneration.

Keywords: acupuncture, injury, regeneration, muscle stem cells

Procedia PDF Downloads 142

Authors: T. Ferreira, A. Kulkarni, C. Bretscher, K. Richter, M. Ehrlich, A. Marchini

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H-1 protoparvovirus (H-1PV) is a virus with inherent oncolytic and oncosuppressive activities while remaining non-pathogenic in humans. H-1PV was the first oncolytic parvovirus to undergo clinical testing. Results from trials in patients with glioblastoma or pancreatic carcinoma showed an excellent safety profile and first signs of efficacy. H-1PV infection is vastly dependent on cellular factors, from cell attachment and entry to viral replication and egress. Hence, we believe that the characterisation of the parvovirus life cycle would ultimately help further improve H-1PV clinical outcome. In the present study, we explored the entry pathway of H-1PV in cervical HeLa and glioma NCH125 cancer cell lines. Electron and confocal microscopy showed viral particles associated with clathrin-coated pits and vesicles, providing the first evidence that H-1PV cell entry occurs through clathrin-mediated endocytosis. Accordingly, we observed that by blocking clathrin-mediated endocytosis with hypertonic sucrose, chlorpromazine, or pitstop 2, H-1PV transduction was markedly decreased. Accordingly, siRNA-mediated knockdown of AP2M1, which retains a crucial role in clathrin-mediated endocytosis, verified the reliance of H-1PV on this route to enter HeLa and NCH125 cancer cells. By contrast, we found no evidence of viral entry through caveolae-mediated endocytosis. Indeed, pre-treatment of cells with nystatin or methyl-β-cyclodextrin, both inhibitors of caveolae-mediated endocytosis, did not affect viral transduction levels. Unexpectedly, siRNA-mediated knockdown of caveolin-1, the main driver of caveolae-mediated endocytosis, increased H-1PV transduction, suggesting caveolin-1 is a negative modulator of H-1PV infection. We also show that H-1PV entry is dependent on dynamin, a protein responsible for mediating the scission of vesicle neck and promoting further internalisation. Furthermore, since dynamin inhibition almost completely abolished H-1PV infection, makes it unlikely that H-1PV uses macropinocytosis as an alternative pathway to enter cells. After viral internalisation, H-1PV passes through early to late endosomes as observed by confocal microscopy. Inside these endocytic compartments, the acidic environment proved to be crucial for a productive infection. Inhibition of acidification of pH dramatically reduced H-1PV transduction. Besides, a fraction of H-1PV particles was observed inside LAMP1-positive lysosomes, most likely following a non-infectious route. To the author's best knowledge, this is the first study to characterise the cell entry pathways of H-1PV. Along these lines, this work will further contribute to understand H-1PV oncolytic properties as well as to improve its clinical potential in cancer virotherapy.

Keywords: clathrin-mediated endocytosis, H-1 parvovirus, oncolytic virus, virus entry

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Authors: Mukul Sharma, Madhusmita Das, Sundeep Chaitanya Vedithi

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Leprosy is a chronic human disease caused by Mycobacterium leprae, that cannot be cultured in vitro. Though treatable with multidrug therapy (MDT), recently, bacteria reported resistance to multiple antibiotics. Targeting DNA replication and repair pathways can serve as the foundation of developing new anti-leprosy drugs. Due to the absence of an axenic culture medium for the propagation of M. leprae, studying cellular processes, especially those belonging to DNA repair pathways, is challenging. Genomic understanding of M. Leprae harbors several protein-coding genes with no previously assigned function known as 'hypothetical proteins'. Here, we report identification and expression of known and hypothetical DNA repair genes from a human skin biopsy and mouse footpads that are involved in base excision repair, direct reversal repair, and SOS response. Initially, a bioinformatics approach was employed based on sequence similarity, identification of known protein domains to screen the hypothetical proteins in the genome of M. leprae, that are potentially related to DNA repair mechanisms. Before testing on clinical samples, pure stocks of bacterial reference DNA of M. leprae (NHDP63 strain) was used to construct standard graphs to validate and identify lower detection limit in the qPCR experiments. Primers were designed to amplify the respective transcripts, and PCR products of the predicted size were obtained. Later, excisional skin biopsies of newly diagnosed untreated, treated, and drug resistance leprosy cases from SIHR & LC hospital, Vellore, India were taken for the extraction of RNA. To determine the presence of the predicted transcripts, cDNA was generated from M. leprae mRNA isolated from clinically confirmed leprosy skin biopsy specimen across all the study groups. Melting curve analysis was performed to determine the integrity of the amplification and to rule out primer‑dimer formation. The Ct values obtained from qPCR were fitted to standard curve to determine transcript copy number. Same procedure was applied for M. leprae extracted after processing a footpad of nude mice of drug sensitive and drug resistant strains. 16S rRNA was used as positive control. Of all the 16 genes involved in BER, DR, and SOS, differential expression pattern of the genes was observed in terms of Ct values when compared to human samples; this was because of the different host and its immune response. However, no drastic variation in gene expression levels was observed in human samples except the nth gene. The higher expression of nth gene could be because of the mutations that may be associated with sequence diversity and drug resistance which suggests an important role in the repair mechanism and remains to be explored. In both human and mouse samples, SOS system – lexA and RecA, and BER genes AlkB and Ogt were expressing efficiently to deal with possible DNA damage. Together, the results of the present study suggest that DNA repair genes are constitutively expressed and may provide a reference for molecular diagnosis, therapeutic target selection, determination of treatment and prognostic judgment in M. leprae pathogenesis.

Keywords: DNA repair, human biopsy, hypothetical proteins, mouse footpads, Mycobacterium leprae, qPCR

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Authors: Maimona A. E. Elimam, Suhair Rehan, Miskelyemen A. Elmekki, Mogahid M. Elhassan

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Staphylococcus aureus (Staph. aureus), a major cause of potentially life-threatening infections acquired in healthcare and community settings, has developed resistance to most classes of antimicrobial agents as determined by the dramatic increase. The present study aimed to determine the prevalence of MRSA, and VRSA in patients with different clinical manifestations in Khartoum state. The study population (n, 426) were males and females with different age categories, suffering either from wound infections (105), ear infections (121), or UTI (101), in addition to nasal carriers of medical staff (100). Cultures, Gram staining, and other biochemical tests were performed for conventional identification. Modified Kirby-Bauer disk diffusion method was applied and DNA was extracted from MRSA and VRSA isolates and PCR was then performed for amplification of arc, mecA, VanA, and VanB genes. The results confirmed the existence of Staph. aureus in 49/426 (11.5%) cases among which MRSA were isolated from 34/49 (69.4%) when modified Kirby-Bauer disk diffusion method was applied. Ten out of these 34 MRSA were confirmed as VRSA by cultures on BHI agar containing 6μg/ml vancomycin according to NCCLS criteria. PCR revealed that out of the 34 MRSA isolates, 26 were mecA positive (76.5%) while 8 (23.5%) were arcC positive. No vanA or VanB genes were detected. Molecular method confirmed the results for MRSA through the presence of either arcC or mecA genes while it failed to approve the occurrence of VRSA since neither VanA or VanB genes were detected. Thus, VRSA may be attributed to other factors.

Keywords: antibiotic resistance, Staphylococcus aureus, VRSA, MRSA, Khartoum, Sudan

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Authors: Ali Kazemi

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Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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Authors: Sahand Hamed Moeel Ardebil, Zohreh Taebi Noghondari, Mahmood Reza Ghorban Sabbagh

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Gillian Flynn’s Gone Girl, depicts a society in which, as a result of media dominance, the reality is very precarious and difficult to grasp. In Gone Girl, reality and image of reality represented on TV, are challenging to differentiate. Along with reality, individuals’ agency and independence before media and the capitalist rule are called in to question in the novel. In order to expose the unstable nature of reality and an individual’s complicated relationship with media, this study has deployed the ideas of Marxist-media theorist Guy Debord (1931-1992). In his book Society of the Spectacle (1966), Debord delineates a society in which images replace the objective reality, and people are incapable of making real changes. The results of the current study show that despite their efforts, Nick and Amy, the two main characters of the novel, are no more than spectators with very little agency before the media. Moreover, following Debord’s argument about the replacement of reality with images, everyone and every institution in Gone Girl projects an image that does not necessarily embody the objective reality, a fact that makes it very hard to differentiate the real from unreal.

Keywords: agency, Debord, Gone Girl, media studies, society of spectacle, reality

Procedia PDF Downloads 112

Authors: Esra Polat

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Partial Least Squares Discriminant Analysis (PLSDA) is a statistical method for classification and consists a classical Partial Least Squares Regression (PLSR) in which the dependent variable is a categorical one expressing the class membership of each observation. PLSDA can be applied in many cases when classical discriminant analysis cannot be applied. For example, when the number of observations is low and when the number of independent variables is high. When there are missing values, PLSDA can be applied on the data that is available. Finally, it is adapted when multicollinearity between independent variables is high. The aim of this study is to determine the economic and/or demographic indicators, which are effective in grouping the 28 European Union (EU) member countries and 7 candidate countries (including potential candidates Bosnia and Herzegovina (BiH) and Kosova) by using the data set obtained from database of the World Bank for 2014. Leaving the political issues aside, the analysis is only concerned with the economic and demographic variables that have the potential influence on country’s eligibility for EU entrance. Hence, in this study, both the performance of PLSDA method in classifying the countries correctly to their pre-defined groups (candidate or member) and the differences between the EU countries and candidate countries in terms of these indicators are analyzed. As a result of the PLSDA, the value of percentage correctness of 100 % indicates that overall of the 35 countries is classified correctly. Moreover, the most important variables that determine the statuses of member and candidate countries in terms of economic indicators are identified as 'external balance on goods and services (% GDP)', 'gross domestic savings (% GDP)' and 'gross national expenditure (% GDP)' that means for the 2014 economical structure of countries is the most important determinant of EU membership. Subsequently, the model validated to prove the predictive ability by using the data set for 2015. For prediction sample, %97,14 of the countries are correctly classified. An interesting result is obtained for only BiH, which is still a potential candidate for EU, predicted as a member of EU by using the indicators data set for 2015 as a prediction sample. Although BiH has made a significant transformation from a war-torn country to a semi-functional state, ethnic tensions, nationalistic rhetoric and political disagreements are still evident, which inhibit Bosnian progress towards the EU.

Keywords: classification, demographic indicators, economic indicators, European Union, partial least squares discriminant analysis

Procedia PDF Downloads 274