Search results for: VAS – visual analogue score

Authors: Mohammadreza Mojtahedi

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Rapid urbanization presents multifaceted challenges, including environmental degradation and public health concerns. As the inevitability of urban sprawl continues, it becomes essential to devise strategies to alleviate its pressures on natural ecosystems and elevate socio-economic benchmarks within cities. This research investigates urban agriculture's economic contributions, emphasizing its pivotal role in food provisioning and export potential. Adopting a descriptive-analytical approach, field survey data was primarily collected via questionnaires. The tool's validity was affirmed by expert opinions, and its reliability secured by achieving a Cronbach's alpha score over 0.70 from 30 preliminary questionnaires. The research encompasses Neishabour's populace of 264,375, extracting a sample size of 384 via Cochran's formula. Findings reveal the significance of urban agriculture in food supply and its potential for exports, underlined by a p-value < 0.05. Neishabour's urban farming can augment the export of organic commodities, fruits, vegetables, ornamental plants, and foster product branding. Moreover, it supports the provision of fresh produce, bolstering dietary quality. Urban agriculture further impacts urban development metrics—enhancing environmental quality, job opportunities, income levels, and aesthetics, while promoting rainwater utilization. Popular cultivations include peaches, Damask roses, and poultry, tailored to available spaces. Structural equation modeling indicates urban agriculture's overarching influence, accounting for a 56% variance, predominantly in food sufficiency and export proficiency.

Keywords: urban agriculture, food supply, export potential, urban development, environmental health, structural equation modeling

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Authors: Parisa Mansour

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Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

Procedia PDF Downloads 63

Authors: Hui-Chi Huang, Su-Ju Yang, Ching-Wei Lin, Jui-Yao Tsai, Liang-Yiang

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Background: Evidence exists that pneumonia is a frequently encountered complication after stroke which is associated with a higher rate of mortality and increased long-term disability Purpose: To determine the predictors associated with the risk of one-year disability in acute stroke. Methods: Data for this longitudinal follow-up study were extracted from a tertiary referral medical center’s stroke registry database in Northern Taipei. Eligible patients with acute stroke admitted to the hospital and completed a one-year follow up were recruited for analysis. Favorable outcome was defined as a modified Rankin Scale score ≤ 2. SAS version 9.2 was used for the multivariable regression analyses to examine the factors correlated with the one-year disability in stroke patients. Results: From January 2012 to December 2013, a total of 1373 (mean age: 70.49±15.4 years, 913(66.5%) males) consecutively administered acute stroke patients were recruited. Overall, the rate of one-year disability was 37.20%(404/1086) in those without post-stroke pneumonia. It increased to 82.93 %(238/287) in patients developed post-stroke pneumonia. Factors associated with increased risk of disability were age ≧ 75(OR= 4.845, p<.0001), female /gender (OR=1.568, p =.0062), previous stroke (OR= 1.868, p = <. 0001) ,dementia (OR= 2.872, p =.0047), ventilator use (OR= 4.653, p <. 0001),age ≧ 75 /pneumonia (OR=1.236, p <. 0001) , ICU admission (OR=3.314, p <.0001) , nasogastric tube insertion (OR= 4.28, p <.0001), speech therapy (OR= 1.79, p =.0142), urinary tract infection (OR= 1.865, p =.0018), estimated glomerular filtration rate (eGFR > 60 )(OR= 0.525, p= .0029), Admission NIHSS >11 (OR= 2.101, p = .0099), Length of hospitalization > 30(d) (OR= 5.182, p <.0001). Conclusion: Older age, severe neurological deficit, complications, rehabilitation intervention, length of hospitalization >30(d), and cognitive impairment were significantly associated with Post-stroke functional impairment, especially those with post-stroke pneumonia. These findings could open new avenues in the management of stroke patients.

Keywords: stroke, risk, pneumonia, disability

Procedia PDF Downloads 229

Authors: Somaye Ghafarpour, Kamran Yazdanbakhsh, Mohamad Reza Zarbakhsh, Simin Hosseinian, Samira Ghafarpour

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Unsatisfactory sleep quality is one of the most common complications of pregnancy, which can predispose mothers to postpartum depression, requiring implementing effective psychological interventions to prevent and modify behaviors accentuating sleep problems. This study was a randomized clinical controlled trial with a pre-test/post-test design aiming to investigate the effectiveness of sleep behavioral interventions during the third trimester of pregnancy on sleep quality and postpartum depression. A total of 50 pregnant mothers in the 26-30 weeks of pregnancy suffering from sleep problems (based on the score obtained from the Pittsburgh Sleep Questionnaire) were randomized into two groups (control and intervention, n= 25 per group). The data were collected using interviews, the Pittsburgh Sleep Quality Index (PSQI), and the Edinburgh Postnatal Depression Scale (EPDS) were used. The participants in the intervention group received eight 60-minute sessions of combinational training for behavioral therapy techniques. At the end of the intervention and four weeks after delivery, sleep quality and postpartum depression were evaluated. Considering that the Kolmogorov Smirnov test confirmed the normal distribution of the data, the independent t-test and analysis of covariance were used to analyze the data, showing that the behavioral interventions were effective on the overall sleep quality after delivery (p=0.001); however, no statistically significant effects were observed on postpartum depression, the sub-scales of sleep disorders, and daily functioning (p>0.05). Considering the potential effectiveness of behavioral interventions in improving sleep quality and alleviating insomnia symptoms, it is recommended to implement such measures as an effective intervention to prevent or treat these problems during prenatal and postnatal periods.

Keywords: behavioral interventions, sleep quality, postpartum depression, pregnancy, delivery

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Authors: Sishen Wang

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Chinese rural industry development is the major task currently during rapid urbanization. Development of potentiality assessment, evaluate the overall suitability of each village for further industrial development, could offer reference for policy makers, especially considering the limited data available in Chinese rural regions. The study focuses on 157 official villages in Fuliang County and evaluates their development potentiality by their topography, transportation condition, population, income of villagers, infrastructure and environmental conditions. Land cover changes for Fuliang county and surrounding areas of each village is also investigated for reference. The final development potentiality of each village was calculated by adding different weighted scores of different categories. Besides, inverse distance weighting (IDW) images for both final score of development potentiality and each factor were made and compared to help to understand the final result. The study found that village in the southern and northern regions have higher development potentiality than villages in the eastern and western regions, mainly because of higher income of villagers, good accessibilities and a large amount of population size. In addition, the Fuliang county was divided into five regions based on final result and policy reference for the development of each region were put forward individually. In addition, three suggestions were made for better local development potentiality: Firstly, the transportation accessibility needs to be improved in the northern regions by building more public transit system there. Secondly, the environmental conditions and infrastructure conditions in the eastern region of the county need some improvement. Thirdly, some encouragement and job opportunities should beset up in the western regions to attract labor force to move in and settle down.

Keywords: development potentiality, Fuliang GIS-Based, GIS, official village

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Authors: Ranojoy Dutta, Adam Barker

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Multifamily residential buildings are increasingly being built with large glazed areas to provide tenants with greater daylight and outdoor views. However, traditional double-glazed window assemblies can lead to significant thermal discomfort from high radiant temperatures as well as increased cooling energy use to address solar gains. Dynamic glazing provides an effective solution by actively controlling solar transmission to maintain indoor thermal comfort, without compromising the visual connection to outdoors. This study uses thermal simulations across three Canadian cities (Toronto, Vancouver and Montreal) to verify if dynamic glazing along with operable windows and ceiling fans can maintain the indoor operative temperature of a prototype southwest facing high-rise apartment unit within the ASHRAE 55 adaptive comfort range for a majority of the year, without any mechanical cooling. Since this study proposes the use of natural ventilation for cooling and the typical building life cycle is 30-40 years, the typical weather files have been modified based on accepted global warming projections for increased air temperatures by 2050. Results for the prototype apartment confirm that thermal discomfort with dynamic glazing occurs only for less than 0.7% of the year. However, in the baseline scenario with low-E glass there are up to 7% annual hours of discomfort despite natural ventilation with operable windows and improved air movement with ceiling fans.

Keywords: electrochromic glazing, multi-family housing, passive cooling, thermal comfort, natural ventilation

Procedia PDF Downloads 102

Authors: Fatemeh Rezaei, Mohammad H. Yarmohammadian, Masoud Ferdosi, Abbas Haghshnas

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Background: Failure Modes and Effect Analysis is now having known as the main methods of risk assessment and the accreditation requirements for many organizations. The Risk Priority Number (RPN) approach is generally preferred, especially for its easiness of use. Indeed it does not require statistical data, but it is based on subjective evaluations given by the experts about the Occurrence (O i), the Severity (Si) and the Detectability (D i) of each cause of failure. Methods: This study is a quantitative – qualitative research. In terms of qualitative dimension, method of focus groups with inductive approach is used. To evaluate the results of the qualitative study, quantitative assessment was conducted to calculate RPN score. Results; We have studied patient’s journey process in surgery ward and the most important phase of the process determined Transport of the patient from the holding area to the operating room. Failures of the phase with the highest priority determined by defining inclusion criteria included severity (clinical effect, claim consequence, waste of time and financial loss), occurrence (time- unit occurrence and degree of exposure to risk) and preventability (degree of preventability and defensive barriers) and quantifying risks priority criteria in the context of RPN index. Ability of improved RPN reassess by root cause (RCA) analysis showed some variations. Conclusions: Finally, It could be concluded that understandable criteria should have been developed according to personnel specialized language and communication field. Therefore, participation of both technical and clinical groups is necessary to modify and apply these models.

Keywords: failure mode, effects analysis, risk priority number(RPN), health system, risk assessment

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Authors: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health-related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores to text, ranging from positive, neutral, and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing and tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial, and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced, and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process and substituting the Naive Bayes for a deep learning neural network model.

Keywords: sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model

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Authors: Soumaya Mrabet, Imen Akkari, Amira Atig, Elhem Ben Jazia

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Introduction: Primary biliary cirrhosis (PBC) is a cholestatic cholangitis of unknown etiology. It is frequently associated with autoimmune diseases, which explains their systematic screening. The aim of our study was to determine the prevalence and the type of autoimmune disorders associated with PBC and to assess their impact on the prognosis of the disease. Material and methods: It is a retrospective study over a period of 16 years (2000-2015) including all patients followed for PBC. In all these patients we have systematically researched: dysthyroidism (thyroid balance, antithyroid autoantibodies), type 1 diabetes, dry syndrome (ophthalmologic examination, Schirmer test and lip biopsy in case of Presence of suggestive clinical signs), celiac disease(celiac disease serology and duodenal biopsies) and dermatological involvement (clinical examination). Results: Fifty-one patients (50 women and one men) followed for PBC were collected. The Mean age was 54 years (37-77 years). Among these patients, 30 patients(58.8%) had at least one autoimmune disease associated with PBC. The discovery of these autoimmune diseases preceded the diagnosis of PBC in 8 cases (26.6%) and was concomitant, through systematic screening, in the remaining cases. Autoimmune hepatitis was found in 12 patients (40%), defining thus an overlap syndrome. Other diseases were Hashimoto's thyroiditis (n = 10), dry syndrome (n = 7), Gougerot Sjogren syndrome (n=6), celiac disease (n = 3), insulin-dependent diabetes (n = 1), scleroderma (n = 1), rheumatoid arthritis (n = 1), Biermer Anemia (n=1) and Systemic erythematosus lupus (n=1). The two groups of patients with PBC with or without associated autoimmune disorders were comparable for bilirubin levels, Child-Pugh score, and response to treatment. Conclusion: In our series, the prevalence of autoimmune diseases in PBC was 58.8%. These diseases were dominated by autoimmune hepatitis and Hashimoto's thyroiditis. Even if their association does not seem to alter the prognosis, screening should be systematic in order to institute an early and adequate management.

Keywords: autoimmune diseases, autoimmune hepatitis, primary biliary cirrhosis, prognosis

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Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

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Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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Authors: Roaa Al Sharif, Salsabil Abo Al-Azayem, Nimah Alsomali, Wjoud Alsaeed, Nawal Alshammari, Abdulaziz Alwatban, Yaseen Alrabae, Razan Orfali, Faisal Alqarni, Ahmad Alrasheedi

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from various countries have revealed that nurses possess only a basic understanding of the GCS. Regarding this matter, limited knowledge is available about the situation in Saudi Arabia. Overall, the available research suggests that there is room for improvement in the knowledge of the GCS among nurses in Saudi Arabia. Further training and education programs may be beneficial in enhancing nurses' understanding and application of the GCS in clinical practice. Objective: To determine the level of knowledge and competence in assessing the GCS among staff nurses and to identify factors that might influence their knowledge at King Fahd Medical City in Riyadh, Saudi Arabia. Methods: A descriptive, cross-sectional survey involving 199 KFMC staff nurses was conducted. Nurses were provided with a structured questionnaire, and data were collected and analyzed using SPSS version 16, employing descriptive statistics and Chi-square tests. Results: The majority, 81.4% of nurses, had an average level of knowledge in assessing the Glasgow Coma Scale (GCS). The mean score for measuring the level of knowledge among staff nurses in GCS assessment was 8.8 ± 1.826. Overall, 13.6% of respondents demonstrated good knowledge of the GCS, scoring between 11 and 15 points, while only 5% of nurses exhibited poor knowledge of the GCS assessment. There was a significant correlation between knowledge and nurses' departments (χ2(2) = 19.184, p < 0.001). χ2(2) = 19.184," representing a Chi-square statistic with 2 degrees of freedom used to test the association between categorical variables in the data analysis. Conclusion: The findings indicate that knowledge of GCS assessment among staff nurses in a single center in Saudi Arabia is moderate. Therefore, there is a need for continuous education programs to enhance their competence in using this assessment.

Keywords: Glasgow Coma Scale, brain injury, nurses’ knowledge assessment, continuous education programs

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Authors: Wissam Aljundi, Loay Daas, Yaser Abu Dail, Barbara Käsmann-Kellner, Berthold Seitz, Alaa Din Abdin

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Purpose: To investigate the effectiveness of nonsteroidal anti-inflammatory eye drops (NSAIDs) combined with oral acetazolamide for postoperative macular edema (PME) after uncomplicated phacoemulsification (PE) and to identify predictors of non-response. Methods: We analyzed data of uncomplicated PE and identified eyes with PME. First-line therapy included topical NSAIDs combined with oral acetazolamide. In case of non-response, triamcinolone was administered subtenonally. Outcome measures included best-corrected visual acuity (BCVA) and central macular thickness (CMT). Results: 94 eyes out of 9750 uncomplicated PE developed PME, of which 60 eyes were included. Follow-ups occurred 6.4±1.8, 12.5±3.7, and 18.6±6.0 weeks after diagnosis. BCVA and CMT improved significantly in all follow-ups. 40 eyes showed response to first-line therapy at first follow-up (G1). The remaining 20 eyes showed no response and required subtenon triamcinolone (G2), of which 11 eyes showed complete regression at the second follow-up and 4 eyes at the third follow-up. 5 eyes showed no response and required intravitreal injection. Multivariate linear regression model showed that diabetes mellitus (DM) and increased cumulative dissipated energy (CDE) are predictors of non-response. Conclusion: Topical NSAIDs with acetazolamide resulted in complete regression of PME in 67% of all cases. DM and increased CDE might be considered as predictors of nonresponse to this treatment.

Keywords: postoperative macular edema, intravitreal injection, cumulative energy, irvine gass syndrome, pseudophakie

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Authors: Amit Kumar, Rajdeep Chakrabarty, Ganesh Gupta

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This paper illustrates the detailed accreditation process of Accreditation Board of Engineering and Technology (ABET) for accrediting engineering and Technology programs. ABET is a non-governmental agency that accredits engineering and technology, applied and natural sciences, and computing sciences programs. ABET was founded on 10th May 1932 and was founded by Institute of Electrical and Electronics Engineering. International industries accept ABET accredited institutes having the highest standards in their academic programs. In this accreditation, there are eight criteria in general; criterion 1 describes the student outcome evaluations, criteria 2 measures the program's educational objectives, criteria 3 is the student outcome calculated from the marks obtained by students, criteria 4 establishes continuous improvement, criteria 5 focus on curriculum of the institute, criteria 6 is about faculties of this institute, criteria 7 measures the facilities provided by the institute and finally, criteria 8 focus on institutional support towards staff of the institute. In this paper, we focused on the calculative part of each criterion with equations and suitable examples, the files and documentation required for each criterion, and the total workflow of the process. The references and the values used to illustrate the calculations are all taken from the samples provided at ABET's official website. In the final section, we also discuss the criterion-wise score weightage followed by evaluation with timeframe and deadlines.

Keywords: Engineering Accreditation Committee, Computing Accreditation Committee, performance indicator, Program Educational Objective, ABET Criterion 1 to 7, IEEE, National Board of Accreditation, MOOCS, Board of Studies, stakeholders, course objective, program outcome, articulation, attainment, CO-PO mapping, CO-PO-SO mapping, PDCA cycle, degree certificates, course files, course catalogue

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Authors: Bingqing Xu, Wenxing Shuai

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This study investigates the priming effects of different Chinese compound words by native Mandarin speakers. There are lots of homonym, polysemy, and synonym in Chinese. However, it is unclear which kind of words have the biggest priming effect. Native Mandarin speakers were tested in a visual-word lexical decision experiment. The stimuli, which are all two-character compound words, consisted of two parts: primes and targets. Five types of relationships were used in all stimuli: morphologically related condition, in which the prime and the target contain the same morpheme; orthographically related condition, in which the target and the prime contain the different morpheme with the same form; phonologically related condition, in which the target and the prime contain the different morpheme with the same phonology; semantically related condition, in which the target and the prime contain the different morpheme with similar meanings; totally unrelated condition. The time since participants saw the target to respond was recorded. Analyses on reaction time showed that the average reaction time of morphologically related targets was much shorter than others, suggesting the morphological priming effect is the biggest. However, the reaction time of the phonologically related conditions was the longest, even longer than unrelated conditions. According to scatter plots analyses, 86.7% of participants had priming effects in morphologically related conditions, only 20% of participants had priming effects in phonologically related conditions. These results suggested that morphologically related conditions had the biggest priming effect. The orthographically and semantically related conditions also had priming effects, whereas the phonologically related conditions had few priming effects.

Keywords: priming effect, morphology, phonology, semantics, orthography

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Authors: Berna Yaylalı, Isin Can Traunmüller

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This paper explores the emergent bottom-up practices in the fields of architecture and urban design within comparative perspectives of two cities. As a temporary, easily affordable intervention that gives the possibility of transforming neglected spaces into vibrant public spaces, tactical urbanism, together with creative place-making strategies, presents alternative ways of creating sustainable developments in derelict and underused areas. This study examines the potential of social and physical developments through a reading of case studies of two creative spatial practices: a pop-up garden transformed from an unused derelict space in Favoriten, Vienna, and an urban community garden in Kuzguncuk, Istanbul. Two cities are chosen according to their multicultural population and diversity. Istanbul was selected as a design city by UNESCO Creative Cities Network in 2017, and Vienna was declared an open and livable city by its local government. This research will use media archives and reports, interviews with locals and local governments, site observations, and visual recordings as methods to provide a critical reading on creative public spaces from the view of local users in these neighborhoods. Reflecting on these emergent ways, this study aims at discussing the production process of tactile urbanism with the practices of locals and the decision-making process with cases from İstanbul and Vienna. The comparison between their place-making strategies in tactical urbanism will give important insights for future developments.

Keywords: creative city, tactical urbanism, neglected area, public space

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Authors: Nur Nadhirah Rusyda Rosnan, Nursuhaili Najwa Masrol, Nurul Fatiha MD Nor, Mohammad Zafrullah Mohammad Salim, Sim Choon Cheak

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Accurate inventories of oil palm planted areas are crucial for plantation management as this would impact the overall economy and production of oil. One of the technological advancements in the oil palm industry is semi-automated palm counting, which is replacing conventional manual palm counting via digitizing aerial imagery. Most of the semi-automated palm counting method that has been developed was limited to mature palms due to their ideal canopy size represented by satellite image. Therefore, immature palms were often left out since the size of the canopy is barely visible from satellite images. In this paper, an approach using a morphological filter and high-resolution satellite image is proposed to detect immature palm trees. This approach makes it possible to count the number of immature oil palm trees. The method begins with an erosion filter with an appropriate window size of 3m onto the high-resolution satellite image. The eroded image was further segmented using watershed segmentation to delineate immature palm tree regions. Then, local minimum detection was used because it is hypothesized that immature oil palm trees are located at the local minimum within an oil palm field setting in a grayscale image. The detection points generated from the local minimum are displaced to the center of the immature oil palm region and thinned. Only one detection point is left that represents a tree. The performance of the proposed method was evaluated on three subsets with slopes ranging from 0 to 20° and different planting designs, i.e., straight and terrace. The proposed method was able to achieve up to more than 90% accuracy when compared with the ground truth, with an overall F-measure score of up to 0.91.

Keywords: immature palm count, oil palm, precision agriculture, remote sensing

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Authors: Amir Zeb, Shailima Rampogu, Minky Son, Ayoung Baek, Sang H. Yoon, Keun W. Lee

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Neurotoxic insults activate calpain, which in turn produces truncated p25 from p35. p25 forms hyperactivated Cdk5/p25 complex, and thereby induces severe neuropathological aberrations including hyperphosphorylated tau, neuroinflammation, apoptosis, and neuronal death. Inhibition of Cdk5/p25 complex alleviates aberrant phosphorylation of tau to mitigate AD pathology. PHA-793887 and Roscovitine have been investigated as selective inhibitors of Cdk5/p25 with IC50 values 5nM and 160nM, respectively, but their mechanistic studies remain unknown. Herein, computational simulations have explored the binding mode and interaction mechanism of PHA-793887 and Roscovitine with Cdk5/p25. Docking results suggested that PHA-793887 and Rsocovitine have occupied the ATP-binding site of Cdk5 and obtained highest docking (GOLD) score of 66.54 and 84.03, respectively. Furthermore, molecular dynamics (MD) simulation demonstrated that PHA-793887 and Roscovitine established stable RMSD of 1.09 Å and 1.48 Å with Cdk5/p25, respectively. Profiling of polar interactions suggested that each inhibitor formed hydrogen bonds (H-bond) with catalytic residues of Cdk5 and could remain stable throughout the molecular dynamics simulation. Additionally, binding free energy calculation by molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) suggested that PHA-793887 and Roscovitine had lowest binding free energies of -150.05 kJ/mol and -113.14 kJ/mol, respectively with Cdk5/p25. Free energy decomposition demonstrated that polar energy by H-bond between the Glu81 of Cdk5 and PHA-793887 is the essential factor to make PHA-793887 highly selective towards Cdk5/p25. Overall, this study provided substantial evidences to explore mechanistic interactions of the selective inhibitors of Cdk5/p25 and could be used as fundamental considerations in the development of structure-based selective inhibitors of Cdk5/p25.

Keywords: Cdk5/p25 inhibition, molecular modeling of Cdk5/p25, PHA-793887 and roscovitine, selective inhibition of Cdk5/p25

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Authors: Hasibul Kabir, Samin Shahriar Tokey, Md. Tofazzal Hossain

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One of the most necessary things in the present time is raising social awareness about global warming and climate change among the people. Though many types of mediums and techniques have been used to teach people about this global phenomenon, there are still more effective ways to reach people with useful information about global warming. As many traditional methods to teach people about global warming and climate change did not work well, video games were overdue. To learn how effective a video game can be in this regard, we developed a Video game, "Historia's Nightmare," that teaches people about Global warming and climate change. The game was designed to entertain people and give them an idea about the reasons and consequences of global warming and climate change while not being like traditional educational games. The game threw a mini quiz consisting of two MCQs based on the information shown in the game, where a gamer had to pass the quiz to reach the next level. We published the game on different platforms to let all types of people play and complete our experiment effectively. The game continuously communicated with our server to send data about gamers' performance. We observed the data, including the participants' performance, time spent, quiz score, and the in-game feedback on a regular basis, and finally came to a verdict. In our experiment, we have found that most participants positively accepted the game and learned something new. The participants who spent more on our game performed better in both quiz and the game. Our experiment's result demonstrates that video games can be a great way to teach people something, particularly to raise social awareness about global warming and climate change. It also demonstrates that the game can be a significant element in education and learning improvement.

Keywords: video game, global warming, social awareness, climate change, education, feedback

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Authors: Abeer A. Aljohani

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COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred to as coronavirus, which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. This research aims to predict COVID-19 disease in its initial stage to reduce the death count. Machine learning (ML) is nowadays used in almost every area. Numerous COVID-19 cases have produced a huge burden on the hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease is based on the symptoms and medical history of the patient. This research presents a unique architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard UCI dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques to the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and the principal component analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, receiver operating characteristic (ROC), and area under curve (AUC). The results depict that decision tree, random forest, and neural networks outperform all other state-of-the-art ML techniques. This achieved result can help effectively in identifying COVID-19 infection cases.

Keywords: supervised machine learning, COVID-19 prediction, healthcare analytics, random forest, neural network

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Authors: Larry Turkish

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Introduction: The NBA is an example of mediocrity and this will be evident in the following paper. The study examines and evaluates the characteristics of the NBA champions. As divisions and playoff teams increase, there is an increase in the probability that the champion originates from the mediocre category. Since it’s inception in 1947, the league has been mediocre and continues to this day. Why does a professional league allow any team with a less than 50% winning percentage into the playoffs? As long as the finances flow into the league, owners will not change the current algorithm. The objective of this paper is to determine if the regular season has meaning in finding an NBA champion. Statistical Analysis: The data originates from the NBA website. The following variables are part of the statistical analysis: Rank, the rank of a team relative to other teams in the league based on the regular season win-loss record; Winning Percentage of a team based on the regular season; Divisions, the number of divisions within the league and Playoff Teams, the number of playoff teams relative to a particular season. The following statistical applications are applied to the data: Pearson Product-Moment Correlation, Analysis of Variance, Factor and Regression analysis. Conclusion: The results indicate that the divisional structure and number of playoff teams results in a negative effect on the winning percentage of playoff teams. It also prevents teams with higher winning percentages from accessing the playoffs. Recommendations: 1. Teams that have a winning percentage greater than 1 standard deviation from the mean from the regular season will have access to playoffs. (Eliminates mediocre teams.) 2. Eliminate Divisions (Eliminates weaker teams from access to playoffs.) 3. Eliminate Conferences (Eliminates weaker teams from access to the playoffs.) 4. Have a balanced regular season schedule, (Reduces the number of regular season games, creates equilibrium, reduces bias) that will reduce the need for load management.

Keywords: alignment, mediocrity, regression, z-score

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Authors: Abraham O. Olaniyi, Oluyemi Oke, Atilade Otunla

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The structural performance of bridges decreases progressively throughout their service life due to many contributing factors (fatigue, carbonation, fire incidents etc.). Around the world, numerous bridges have attained their estimated service life and many have approached this limit. The structural integrity assessment of the burnt composite bridge located at CH57+450, Koita village along Abuja-Abaji-Lokoja road, Nigeria, is presented as a case study and shall be forthwith referred to as the 'Koita bridge' in this paper. From the technical evaluation, the residual compressive strength of the concrete piers was found to be below 16.0 N/mm2. This value is very low compared to the expected design value of 30.0 N/mm2. The pier capping beam at pier location 1 has a very low residual compressive strength. The cover to the reinforcement of certain capping beams has an outline of reinforcement which signifies poor concrete cover and the mean compressive strength is also less than 20.0 N/mm2. The steel girder indicated black colouration as a result of the fire incident without any significant structural defect like buckling or warping of the steel section. This paper reviews the structural integrity assessment and repair methodology of the Koita bridge; a composite bridge damaged by fire, highlighting the various challenges of limited obtainable guidance documents about the bridge. The objectives are to increase the understanding of processes and versatile equipment required to test and assess a fire-damaged bridge in order to improve the quality of structural appraisal and rehabilitation; thus, eliminating the prejudice associated with current visual inspection techniques.

Keywords: assessment, bridge, rehabilitation, sustainability

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Authors: Syed Asif Hassan, Syed Atif Hassan

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Multidrug-resistant Tuberculosis (MDR-TB) is an infection caused by the resistant strains of Mycobacterium tuberculosis that do not respond either to isoniazid or rifampicin, which are the most important anti-TB drugs. The increase in the occurrence of a drug-resistance strain of MTB calls for an intensive search of novel target-based therapeutics. In this context LprG (Rv1411c) a lipoprotein from MTB plays a pivotal role in the immune evasion of Mtb leading to survival and propagation of the bacterium within the host cell. Therefore, a machine learning method will be developed for generating a computational model that could predict for a potential anti LprG activity of the novel antituberculosis compound. The present study will utilize dataset from PubChem database maintained by National Center for Biotechnology Information (NCBI). The dataset involves compounds screened against MTB were categorized as active and inactive based upon PubChem activity score. PowerMV, a molecular descriptor generator, and visualization tool will be used to generate the 2D molecular descriptors for the actives and inactive compounds present in the dataset. The 2D molecular descriptors generated from PowerMV will be used as features. We feed these features into three different classifiers, namely, random forest, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model based on the accuracy of predicting novel antituberculosis compound with an anti LprG activity. Additionally, the efficacy of predicted active compounds will be screened using SMARTS filter to choose molecule with drug-like features.

Keywords: antituberculosis drug, classifier, machine learning, molecular descriptors, prediction

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Authors: Jolanta Jonak, Sylvia Tolczyk

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Students demonstrate various learning preferences and learning styles that range from visual, auditory to kinesthetic preferences. These learning preferences are further impacted by individual cognitive make up that characterizes itself in linguistic strengths, logical- special, inter-or intra- personal, just to name a few. Students from culturally and linguistically diverse backgrounds (CLD) have an increased risk of being misunderstood by many school systems and even medical personnel. CLD students are influenced by many factors (like acculturation and experience) that may impact their achievements and functioning levels. CLD students who develop initial or basic interpersonal communication proficiency skills in the target language are even at a higher risk for being suspected of learning disability when they are underachieving academically. Research indicates that large numbers of students arenot provided the type of education and types of supports they need in order to be successful in an academicenvironment. Multiple research findings indicate that significant numbers of school staff self-reports that they do not feel adequately prepared to work with CLD students. It is extremely important for the school staff, especially school psychologists, who often are the first experts that are consulted, to be educated about overlapping symptoms and settle differences between learning difference and disability. It is equally important for medical personnel, mainly pediatricians, psychologists, and psychiatrists, to understand the subtle differences to avoid inaccurate opinions. Having the knowledge, school staff can avoid unnecessary referrals for special education evaluations and avoid inaccurate decisions about the presence of a disability. This presentation will illustrate distinctions based on research between learning differences and disabilities, how to recognize them, and how to assess for them.

Keywords: special education, learning disability, differentiation, differences

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Authors: Salman Amur Alhajri

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Purpose: This paper explores the art of contemporary Arabic calligraphy in Oman. It explains the aesthetic features of Arabic calligraphy as a unique icon of Islamic art. This paper also explores the profile of one Omani artist, Salman Alhajri, as an example of Omani artists who have developed unique styles in this art stream. Methodology and approach: The paper is based on a theoretical study using a descriptive and case-study approach. Omani artists are fascinated by the art forms of Arabic calligraphy, which combine both spiritual meaning and aesthetic beauty. Artist Salman Alhajri is an example of a contemporary Arabic artist who uses Arabic calligraphy as the main theme in his art. Dr. Alhajri is trying to introduce the beauty of Arabic letters from a new aesthetic point of view. He also aims to create unusual visual effects that viewers can easily interact with. Even though words and phrases appear in Alhajri’s artwork, they are not conveying direct meanings: viewers can create their own meaning or expressions from them by appreciating the compositions of the artwork. Results: Arabic writing is directly related to the identity of Omani artists and their cultural background. This paper shows how the beauty of Arabic letters comes from its indefinite possibilities in designing calligraphic expressions, even within a single word, because letters can be stretched and transformed in various ways to create different compositions. Omani artists are interested in employing new media applications in this kind of practice to find new techniques for creating artwork based on Arabic writing. It is really important for all Omani artists to practice this art style because Arabic calligraphy and its flexibility introduce infinite possibilities that involve further exploration and investigation.

Keywords: Islamic art, contemporary Arabic calligraphy, new techniques, Omani artist

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Authors: Emmanuel Iyamuremye, Irenee Ndayambaje

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This study investigated the influence of Concrete Pictorial Abstract (CPA) teaching approach on mathematics achievement based on a sample of eighth-grade students (N = 10,345) from the Rwandan Lower Secondary School quasi-experimental study with pre-test and post-test control group of 2019 (RLSQES19). Key aspects studied included mathematics concept understanding and mathematics concept retention and how these are influenced by teacher's teaching approach. Specifically, the study aimed to a.) investigate students' concept understanding and concept retention in mathematics when exposed to CPA approach and to those exposed to non-CPA approach before and after the intervention, and b.) ascertain the significant difference between the performance of the students exposed to CPA approach and those exposed to non-CPA approach in terms of post-test scores and retention test scores. Two groups (control and experimental) undergone pre-test, post-test, and retention test. The assignment of control and experimental group among senior two classes from 10 schools was done randomly. The materials used to determine the performance of the students is a teacher-made test. Descriptive statistics and ANCOVA were used for the analysis of the study. For determining the improvement in concept understanding of mathematics, Hakes methods of calculating gain were used to analyze the pre-test and post test score. The level of performance of the two groups in the pre-test is below average level. During the post-test and retention test, the performance of students in non-CPA group is on average level, and students in CPA group are on above average level. Hakes methods of calculating gain revealed higher significant performance in the post-test and retention test of CPA group of students than non-CPA group of students.

Keywords: concept understanding, concept retention, performance, teaching approach

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Authors: Abu Salim Mustafa

Abstract:

Rv3873 is a relatively large size protein (371 amino acids in length) and its gene is located in the immunodominant genomic region of difference (RD)1 that is present in the genome of Mycobacterium tuberculosis but deleted from the genomes of all the vaccine strains of Bacillus Calmette Guerin (BCG) and most other mycobacteria. However, when tested for cellular immune responses using peripheral blood mononuclear cells from tuberculosis patients and BCG-vaccinated healthy subjects, this protein was found to be a major stimulator of cell mediated immune responses in both groups of subjects. In order to further identify the sequence of immunodominant epitopes and explore their Human Leukocyte Antigen (HLA)-restriction for epitope recognition, 24 peptides (25-mers overlapping with the neighboring peptides by 10 residues) covering the sequence of Rv3873 were synthesized chemically using fluorenylmethyloxycarbonyl chemistry and tested in cell mediated immune responses. The results of these experiments helped in the identification of an immunodominant peptide P9 that was recognized by people expressing varying HLA-DR types. Furthermore, it was also predicted to be a promiscuous binder with multiple epitopes for binding to HLA-DR, HLA-DP and HLA-DQ alleles of HLA-class II molecules that present antigens to T helper cells, and to HLA-class I molecules that present antigens to T cytotoxic cells. In addition, the evaluation of peptide P9 using an immunogenicity predictor server yielded a high score (0.94), which indicated a greater probability of this peptide to elicit a protective cellular immune response. In conclusion, P9, a peptide with multiple epitopes and ability to bind several HLA class I and class II molecules for presentation to cells of the cellular immune response, may be useful as a peptide-based vaccine against tuberculosis.

Keywords: mycobacterium tuberculosis, PPE68, peptides, vaccine

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Authors: Mulugeta K. Tefera, Xiaolong Yang, Jian Liu

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Detection and tracking of moving objects are very important in many application contexts such as detection and recognition of people, visual surveillance and automatic generation of video effect and so on. However, the task of detecting a real shape of an object in motion becomes tricky due to various challenges like dynamic scene changes, presence of shadow, and illumination variations due to light switch. For such systems, once the moving object is detected, tracking is also a crucial step for those applications that used in military defense, video surveillance, human computer interaction, and medical diagnostics as well as in commercial fields such as video games. In this paper, an object presents in dynamic background is detected using adaptive mixture of Gaussian based analysis of the video sequences. Then the detected moving object is tracked using the region based moving object tracking and inter-frame differential mechanisms to address the partial overlapping and occlusion problems. Firstly, the detection algorithm effectively detects and extracts the moving object target by enhancing and post processing morphological operations. Secondly, the extracted object uses region based moving object tracking and inter-frame difference to improve the tracking speed of real-time moving objects in different video frames. Finally, the plotting method was applied to detect the moving objects effectively and describes the object’s motion being tracked. The experiment has been performed on image sequences acquired both indoor and outdoor environments and one stationary and web camera has been used.

Keywords: background modeling, Gaussian mixture model, inter-frame difference, object detection and tracking, video surveillance

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Authors: Olga Plaza, Katarzyna Kosinska-Kaczynska, Stepan Feduniw, Dominika Pazdzior, Kinga Zebrowska, Katarzyna Kwiatkowska

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Introduction: The main causes of depression among pregnant women remain unclear. However, it is clear that pregnancy carries a higher risk of depression occurrence. Left untreated, prenatal depression can be a cause of serious both maternal and neonatal complications. Aim of the study: The aim of the study was to define potential risk factors of prenatal depression and to assess the frequency of its occurrence among pregnant women. Material and Methods: A prospective cross-sectional study was performed among 346 women. The self- composed questionnaire consisting of 46 questions, was distributed via the Internet between November 2017 and March 2018. The questionnaire contained the Edinburgh Postnatal Depression Scale (EPDS), in which the results of 13 and more points (out of 30) suggested possible prenatal depression. Statistical analysis was performed with Chi2 Pearson. P value < 0.05 was considered significant. Results: 37.57% (n=130) of women had a score of 13 or more points. Women with depressive symptoms (DS) reported lack of support from the partner (46.9% vs. 16.2%; p < 0.001) as well as other family members (40.8% vs. 14.4%; p < 0.001), current pregnancy being unplanned (21.5% vs. 12.5%; p=0.014) and low socio-economic status (10% vs. 0.9%; p < 0.001). Both early and advanced maternal age seemed to play a role in occurrence of DS: in women aged 17-24 40.8% declared symptoms (vs 28.7%; p < 0.01), in mothers aged ≥37 6.2% did (vs 0.5%; p < 0.001). Smoking during pregnancy was also more frequent among patients with DS (31.5% vs. 18.1%; p=0.004). Previous diagnosis of depression or other mood disorders significantly increased a chance of DS occurrence (respectively- 17.7% vs. 4.6%; p < 0.001 and 49.2% vs. 25%; p<0.001). Parental diagnosis of mood disorders and other mental disorders was also more frequent in this group of patients (respectively- 24.6% vs. 15.7%; p= 0.026 and 26.4% vs. 9.7%; p < 0.001). Only 23.8% of women with DS sought help from healthcare professionals, with 21.5% receiving pharmacological treatment. Conclusions: Pregnant women often report having DS. Evaluation of risk factors of DS and possible prenatal depression is essential in proper screening for depression among pregnant women.

Keywords: obstetrics, polish women, prenatal care, prenatal depression, risk factors

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Authors: Marko Kolakovic

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Creative industries are an important sector of growth and development of knowledge economies. They have a positive impact on employment, economic growth, export and the quality of life in the areas where they are developed. Creative sectors include architecture, design, advertising, publishing, music, film, television and radio, video games, visual and performing arts and heritage. Following the positive trends of development of creative industries on the global and European level, this paper analyzes creative industries in general and specific characteristics of creative entrepreneurship. Special focus in this paper is put on the influence of the information communication technology on the development of new creative business models and protection of the intellectual property rights. One part of the paper is oriented on the analysis of the status of creative industries and creative entrepreneurship in Croatia. The main objective of the paper is by using the statistical analysis of creative industries in Croatia and information gained during the interviews with entrepreneurs, to make conclusions about potentials and development of creative industries in Croatia. Creative industries in Croatia are at the beginning of their development and growth strategy still does not exist at the national level. Statistical analysis pointed out that in 2015 creative enterprises made 9% of all enterprises in Croatia, employed 5,5% of employed people and their share in GDP was 4,01%. Croatian creative entrepreneurs are building competitive advantage using their creative resources and creating specific business models. The main obstacles they meet are lack of business experience and impossibility of focusing on the creative activities only. In their business, they use digital technologies and are focused on export. The conclusion is that creative industries in Croatia have development potential, but it is necessary to take adequate measures to use this potential in a right way.

Keywords: creative entrepreneurship, knowledge economy, business models, intellectual property

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Authors: Tünde Tifordiána Simonyi, Tímea Harmath-Tánczos

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The primary aim of the current research is to present the significance of a multicultural perspective in clinical neuropsychology and to present the test battery of the Multicultural Neuropsychological Scale (MUNS). The method includes the MUNS screening tool that involves stimuli common to most cultures in the world. The test battery measures general cognitive functioning focusing on five cognitive domains (memory, executive function, language, visual construction, and attention) tested with seven subtests that can be utilized within a wide age range (15-89), and lower and higher education participants. It is a scale that is sensitive to mild cognitive impairments. Our study presents the first results with the Hungarian translation of MUNS on a healthy sample. The education range was 4-25 years of schooling. The Hungarian sample was recruited by snowball sampling. Within the investigated population (N=151) the age curve follows an inverted U-shaped curve regarding cognitive performance with a high load on memory. Age, reading fluency, and years of education significantly influenced test scores. The sample was tested twice within a 14-49 days interval to determine test-retest reliability, which is satisfactory. Besides the findings of the study and the introduction of the test battery, the article also highlights its potential benefits for both research and clinical neuropsychological practice. The importance of adapting, validating and standardizing the test in other languages besides the Hungarian language context is also stressed. This test battery could serve as a helpful tool in mapping general cognitive functions in psychiatric and neurological disorders regardless of the cultural background of the patients.

Keywords: general cognitive functioning, multicultural, MUNS, neuropsychological test battery

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