Search results for: social media data

Authors: Elisabeth Sundari, Anny Retnowati

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This research aims to examine the meaning of 'the best interests of the child' in Indonesia's rampant phenomenon of child marriage. The methodology used empirical and normative legal research by examining the parent's reason and the judges' considerations in granting child marriage dispensation applications. It takes data samples from judges' decisions purposively in two courts that differ in geographical and religious backgrounds to see data variation. Namely, the District Court and Religious Court of Yogyakarta City, as well as Gunung Kidul Regency, in the last three years (2020-2022). It analyses the data qualitatively to explore how judges interpreted 'the best interests of the child' in their decision. The results show that judges granted 100% of all child marriage dispensation applications filed by parents. The three reasons parents gave for applying for dispensation were that they were ashamed of having a pregnant child without being married, followed religious teachings, and obtained legal status for the baby. The judges supported those reasons by granting the dispensation application. The external factor of the child itself influenced the meaning of 'The best interests of the child' in marrying off children in Indonesia, such as cultural taboos, religious teachings, and obtaining legal status for the baby, rather than internal factors of the child, such as the will to marry, the mental and psychological readiness of the child to become a mother, as well as a wife. This research contributes to the finding that external factors, such as local culture and religion, can influence the meaning of 'the best interests of the child.'

Keywords: interests, child, Indonesia, marriage

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Authors: Sharon Truter, Ann B. Shuttleworth-Edwards

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South Africa is a developing country with significant diversity in languages spoken and quality of education available, creating challenges for fair and accurate neuropsychological assessments when most available neuropsychological tests are obtained from English-speaking developed countries. The aim of this research was to compare normative data on a spectrum of commonly used neuropsychological tests for English- and Afrikaans-speaking South Africans with relatively high quality of education and South Africans with relatively low quality of education who speak Afrikaans, Sesotho, Setswana, Sepedi, Tsonga, Venda, Xhosa or Zulu. The participants were all healthy adults aged 18-60 years, with 8-12 years of education. All the participants were tested in their first language on the following tests: two non-verbal tests (Rey Osterrieth Complex Figure Test and Bell Cancellation Test), four verbal fluency tests (category, phonemic, verb and 'any words'), one verbal learning test (Rey Auditory Verbal Leaning Test) and three tests that have a verbal component (Trail Making Test A & B; Symbol Digit Modalities Test and Digit Span). Descriptive comparisons of mean scores and standard deviations across the language groups and between the groups with relatively high versus low quality of education highlight the importance of using normative data that takes into account language and quality of education.

Keywords: cross-cultural, language, multi-lingual, neuropsychological testing, quality of education

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Authors: Salih Uzun

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The laboratory activities are seen an indispensable part of science, teaching, and learning. In this study, the aim was to identify pre-service science teachers’ perceptions related to the concept of laboratory through metaphors. It is expressed that metaphors can be used as a powerful research tool in order to understand personal perceptions. Therefore, metaphors were used with the aim of revealing a picture regarding how pre-service science teachers perceive laboratory. Within the scope of this aim, phenomenographic research design was adopted for this study and an answer was sought to the question; ‘What are pre-service science teachers’ perceptions about the concept of laboratory?’. The sample of this study was a total of 80 pre-service science teachers at various grade levels in Turkey. Participants were asked to complete the sentence; ‘Laboratory is like…; because…’. Documents including pre-service science teachers’ answers to the open-ended questions were used as data sources and the data were analysed with content analysis.

Keywords: laboratory, metaphor, phenomenology, pre-service science teachers

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Authors: Dariush Jafari, Seyed Ali Jafari

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The recommended limit for cadmium concentration in potable water is less than 0.005 mg/L. A continuous biosorption process using indigenous red seaweed, Gracilaria corticata, was performed to remove cadmium from the potable water. The process was conducted under fixed conditions and the breakthrough curves were achieved for three consecutive sorption-desorption cycles. A modeling based on Artificial Neural Network (ANN) was employed to fit the experimental breakthrough data. In addition, a simplified semi empirical model, Thomas, was employed for this purpose. It was found that ANN well described the experimental data (R2>0.99) while the Thomas prediction were a bit less successful with R2>0.97. The adjusted design parameters using the nonlinear form of Thomas model was in a good agreement with the experimentally obtained ones. The results approve the capability of ANN to predict the cadmium concentration in potable water.

Keywords: ANN, biosorption, cadmium, packed-bed, potable water

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Authors: Nuo Xu, Sijing Chen

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Background: Childbirth is considered a critical traumatic event throughout our lives, positively or negatively impacting the mother's physiology, psychology, and even the whole family. Adverse birth experiences, such as labor pain, anxiety, and fear can negatively impact the mother. Studies had shown that the immersive nature of VR can distract attention from pain and increase focus on interventions for pain relief. However, the existing studies that applied VR to maternal delivery were still in their infancy and showed disparate results, and the small sample size is not representative, so this review analyzed the effects of VR in labor, such as on maternal pain and anxiety, with a view to providing a basis for future applications. Search strategy: We searched Pubmed, Embase, Web of Science, the Cochrane Library, CINAHL, China National Knowledge Infrastructure, Wan-Fang database from the building to November 17, 2021. Selection Criteria: Randomized controlled trials (RCTs) that intervened the pregnant women aged 18-35 years with gestational >34 weeks and without complications with VR technology were contained within this review. Data Collection and Analysis: Two researchers completed the study selection, data extraction, and assessment of study quality. For quantitative data we used MD or SMD, and RR (risk ratio) for qualitative data. Random-effects model and 95% confidence interval (95% CI) were used. Main Results: 12 studies were included. Using VR could relieve pain during labor (MD=-1.81, 95% CI (-2.04, -1.57), P< 0.00001) and active period (SMD=-0.41, 95% CI (-0.68, -0.14), P= 0.003), reduce anxiety (SMD=-1.39, 95% CI (-1.99, -0.78), P< 0.00001) and improve satisfaction (RR = 1.32; 95% CI (1.10, 1.59); P = 0.003), but the effect on the duration of first (SMD=-1.12, 95% CI (-2.38, 0.13), P=0.08) and second (SMD=-0.22, 95% CI (-0.67, 0.24), P=0.35) stage of labor was not statistically significant. Conclusions: Compared with conventional care, VR technology can relieve labor pain and anxiety and improve satisfaction. However, extensive experimental validation is still needed.

Keywords: virtual reality, delivery, labor pain, anxiety, meta-analysis, systematic review

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Authors: Fareena Alladin

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In the Caribbean, issues of food security, health and taste are intricately linked, seen most clearly in the increasing incidence of lifestyle diseases among children coupled with a taste for high calorie and Westernized diets. In order to fully appreciate this link, the role of nutrition environments must be examined. To this end, the present study incorporates tenets of Bourdieu’s social constructivist theory with the Community Nutrition Environment Model. The aim of this study was to examine the relationships between availability of and access to healthy/unhealthy foods within nutrition environments, namely the household and school, and the development of taste preferences for healthy/unhealthy foods among primary school children in a selected educational district in Trinidad and Tobago. A cross-sectional survey of 400 children between the ages of 9 and 11 years was conducted. Data analysis was conducted using SPSS 24. Results indicated that availability of healthy food at home was positively correlated with preference for vegetables, and negatively correlated with preference for salty snacks and fast food. The availability of unhealthy food within the home was found to be negatively correlated with preference for vegetables and positively correlated with preference for salty snacks. Access to unhealthy foods at school had a positive correlation with preference for fast food. These findings highlight the role of the food environment in shaping taste preferences, and point to the need for interrogating the centrality of food security concerns in emerging health concerns of Caribbean countries. Such interrogations are a necessary part of the development of research agendas, and policy formulation and implementation.

Keywords: food security, nutrition environment, taste preference, Trinidad and Tobago

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Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

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The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

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Authors: Okike Benjamin, Garba E J. D.

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Encryption is used to conceal information from prying eyes. Presently, information and data encryption are common due to the volume of data and information in transit across the globe on daily basis. Image encryption is yet to receive the attention of the researchers as deserved. In other words, video and multimedia documents are exposed to unauthorized accessors. The authors propose image encryption using matrix transpose. An algorithm that would allow image encryption is developed. In this proposed image encryption technique, the image to be encrypted is split into parts based on the image size. Each part is encrypted separately using matrix transpose. The actual encryption is on the picture elements (pixel) that make up the image. After encrypting each part of the image, the positions of the encrypted images are swapped before transmission of the image can take place. Swapping the positions of the images is carried out to make the encrypted image more robust for any cryptanalyst to decrypt.

Keywords: image encryption, matrices, pixel, matrix transpose

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Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

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This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

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Authors: Fernando Araujo, Sandra Cardoso, Fátima Fonseca, Sandra Cavaca

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A debureaucratization strategy for the Portuguese Health Service was assumed by the Executive Board of the SNS, in deep articulation with the Shared Services of the Ministry of Health. Two of the main dimensions were focused on sick leaves (SL), that transform primary health care (PHC) in administrative institutions, limiting access to patients. The self-declaration of illness (SDI) project, through the National Health Service Contact Centre (SNS24), began on May 1, 2023, and has already resulted in the issuance of more than 300,000 SDI without the need to allocate resources from the National Health Service (NHS). This political decision allows each citizen, in a maximum 2 times/year, and 3 days each time, if ill, through their own responsibility, report their health condition in a dematerialized way, and by this way justified the absence to work, although by Portuguese law in these first three days, there is no payment of salary. Using a digital approach, it is now feasible without the need to go to the PHC and occupy the time of the PHC only to obtain an SL. Through this measure, bureaucracy has been reduced, and the system has been focused on users, improving the lives of citizens and reducing the administrative burden on PHC, which now has more consultation times for users who need it. The second initiative, which began on March 1, 2024, allows the SL to be issued in emergency departments (ED) of public hospitals and in the health institutions of the social and private sectors. This project is intended to allow the user who has suffered a situation of acute urgent illness and who has been observed in an ED of a public hospital or in a private or social entity no longer need to go to PHC only to apply for the respective SL. Since March 1, 54,453 SLs have been issued, 242 in private or social sector institutions and 6,918 in public hospitals, of which 134 were in ED and 47,292 in PHC. This approach has proven to be technically robust, allows immediate resolution of problems and differentiates the performance of doctors. However, it is important to continue to qualify the proper functioning of the ED, preventing non-urgent users from going there only to obtain SL. Thus, in order to make better use of existing resources, it was operationalizing this extension of its issuance in a balanced way, allowing SL to be issued in the ED of hospitals only to critically ill patients or patients referred by INEM, SNS24, or PHC. In both cases, an intense public campaign was implemented to explain the way it works and the benefits for patients. In satisfaction surveys, more than 95% of patients and doctors were satisfied with the solutions, asking for extensions to other areas. The administrative simplification agenda of the NHS continues its effective development. For the success of this debureaucratization agenda, the key factors are effective communication and the ability to reach patients and health professionals in order to increase health literacy and the correct use of NHS.

Keywords: debureaucratization strategy, self-declaration of illness, sick leaves, SNS24

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Authors: Ahmed. A. Hossam Eldin, Karim H. Youssef, Kareem M. AboRas

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Recent current rapid industrial development and energy shortage are essential problems, which face most of the developing countries. Moreover, increased prices of fossil fuel and advanced energy conversion technology lead to the need for renewable energy resources. A study, modelling and simulation of an outdoor micro scale stand alone wind turbine was carried out. For model validation an experimental study was applied. In this research the aim was to clarify effects of real outdoor operating conditions and the instantaneous fluctuations of both wind direction and wind speed on the actual produced power. The results were compared with manufacturer’s data. The experiments were carried out in Borg Al-Arab, Alexandria. This location is on the north Western Coast of Alexandria. The results showed a real max output power for outdoor micro scale wind turbine, which is different from manufacturer’s value. This is due to the fact that the direction of wind speed is not the same as that of the manufacturer’s data. The measured wind speed and direction by the portable metrological weather station anemometer varied with time. The blade tail response could not change the blade direction at the same instant of the wind direction variation. Therefore, designers and users of micro scale wind turbine stand alone system cannot rely on the maker’s name plate data to reach the required power.

Keywords: micro-turbine, wind turbine, inverters, renewable energy, hybrid system

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Authors: Siddhartha Khare, Nitish Kr Boro, Omm Animesh Mishra

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Recent food price hikes may signal the end of an era of predictable global grain crop plenty due to climate change, population expansion, and dietary changes. Food consumption will treble in 20 years, requiring enormous production expenditures. Climate and the atmosphere changed owing to rainfall and seasonal cycles in the past decade. India's tropical agricultural relies on evapotranspiration and monsoons. In places with limited resources, the global environmental change affects agricultural productivity and farmers' capacity to adjust to changing moisture patterns. Motivated by these difficulties, satellite remote sensing might be combined with near-surface imaging data (smartphones, UAVs, and PhenoCams) to enable phenological monitoring and fast evaluations of field-level consequences of extreme weather events on smallholder agriculture output. To accomplish this technique, we must digitally map all communities agricultural boundaries and crop kinds. With the improvement of satellite remote sensing technologies, a geo-referenced database may be created for rural Indian agriculture fields. Using AI, we can design digital agricultural solutions for individual farms. Main objective is to Geo-enable each farm along with their seasonal crop information by combining Artificial Intelligence (AI) with satellite and near-surface data and then prepare long term crop monitoring through in-depth field analysis and scanning of fields with satellite derived vegetation indices. We developed an AI based algorithm to understand the timelapse based growth of vegetation using PhenoCam or Smartphone based images. We developed an android platform where user can collect images of their fields based on the android application. These images will be sent to our local server, and then further AI based processing will be done at our server. We are creating digital boundaries of individual farms and connecting these farms with our smart phone application to collect information about farmers and their crops in each season. We are extracting satellite-based information for each farm from Google earth engine APIs and merging this data with our data of tested crops from our app according to their farm’s locations and create a database which will provide the data of quality of crops from their location.

Keywords: artificial intelligence, satellite remote sensing, crop monitoring, android and web application

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Authors: Leila Rashidian, Mina Rajabali

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Industrialization has made progress and comfort for human beings in many aspects. It is not only achievement for the global environment but also factor for destruction and disruption of the Earth's climate. In this study, we used LARS.WG model and down scaling of general circulation climate model HADCM-3 daily precipitation amounts, minimum and maximum temperature and daily sunshine hours. These data are provided by the meteorological organization for Caspian Sea coastal station such as Anzali, Manjil, Rasht, Lahijan and Astara since their establishment is from 1982 until 2010. According to the IPCC scenarios, including series A1b, A2, B1, we tried to simulate data from 2010 to 2040. The rainfall pattern has changed. So we have a rainfall distribution inappropriate in different months.

Keywords: climate change, Lars.WG, HADCM3, Gillan province, climatic parameters, A2 scenario

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Authors: Leila Rashidian, Abbas Ebrahimi

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The development of industrial activities, increase in fossil fuel consumption, vehicles, destruction of forests and grasslands, changes in land use, and population growth have caused to increase the amount of greenhouse gases especially CO₂ in the atmosphere in recent decades. This has led to global warming and climate change. In the present paper, we have investigated the trend of climate change according to the data simulation during the time interval of 2010-2030 in the Fars province. In this research, the daily climatic parameters such as maximum and minimum temperature, precipitation and number of sunny hours during the 1977-2008 time interval for synoptic stations of Shiraz and Abadeh and during 1995-2008 for Lar stations and also the output of HADCM₃ model in 2010-2030 time interval have been used based on the A₂ propagation scenario. The results of the model show that the average temperature will increase by about 1 degree centigrade and the amount of precipitation will increase by 23.9% compared to the observational data. In conclusion, according to the temperature increase in this province, the amount of precipitation in the form of snow will be reduced and precipitations often will occur in the form of rain. This 1-degree centigrade increase during the season will reduce production by 6 to 10% because of shortening the growing period of wheat.

Keywords: climate change, Lars WG, HADCM3, Gillan province, climatic parameters, A2 scenario

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Authors: Darren Edwards, Thomas Pinna

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Background: Interoception and heart rate variability have been found to predict outcomes of mental health and well-being. However, these have usually been investigated independently of one another. Objectives: This review aimed to explore the associations between interoception and heart rate variability (HRV) with emotion regulation (ER) and ER strategies within the existing literature and utilizing systematic review methodology. Methods: The process of article retrieval and selection followed the preferred reporting items for systematic review and meta-analyses (PRISMA) guidelines. Databases PsychINFO, Web of Science, PubMed, CINAHL, and MEDLINE were scanned for papers published. Preliminary inclusion and exclusion criteria were specified following the patient, intervention, comparison, and outcome (PICO) framework, whilst the checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies (CHARMS) framework was used to help formulate the research question, and to critically assess for bias in the identified full-length articles. Results: 237 studies were identified after initial database searches. Of these, eight studies were included in the final selection. Six studies explored the associations between HRV and ER, whilst three investigated the associations between interoception and ER (one of which was included in the HRV selection too). Overall, the results seem to show that greater HRV and interoception are associated with better ER. Specifically, high parasympathetic activity largely predicted the use of adaptive ER strategies such as reappraisal, and better acceptance of emotions. High interoception, instead, was predictive of effective down-regulation of negative emotions and handling of social uncertainty, there was no association with any specific ER strategy. Conclusions: Awareness of one’s own bodily feelings and vagal activation seem to be of central importance for the effective regulation of emotional responses.

Keywords: emotional regulation, vagal tone, interoception, chronic conditions, health and well-being, psychological flexibility

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Authors: Liesbeth Van Kelst, Jozefiene Jansens

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Background: All care providers within mother and child care are confronted, at some point in their career, with the care for parents who (will) lose or have lost a baby. Obtaining the correct attitude and communicating well during these difficult moments are aspects that many healthcare provides continue to struggle with. Parents still encounter well-intentioned but inappropriate communication from healthcare providers. Aim: To study how communication, both verbal and non-verbal, around the death of a baby during pregnancy, birth, or in the first ten days postnatal was experienced by parents and healthcare providers. Methods: A qualitative study using grounded theory principles was conducted. Data were collected through 22 individual face-to-face in-depth interviews with parents who had lost a baby (n = 12) and intramural caregivers, such as midwives, nurses, gynecologists and neonatologists (n=10). In the first phase, data were analyzed within each group separately (parents and healthcare providers) and in the second phase, findings from both groups were compared and analyzed according to meta-synthesis principles. Results: The themes that emerged from the data demonstrated congruent experiences between the group of the parents and the health care providers. Both strengths and weaknesses in current care were named and suggestions for appropriate communication were formulated. Conclusion: Since most health care providers only occasionally care for parents with a deceased baby, a communication tool can optimize communication between healthcare professionals and parents who lose a baby. This is very important as the words which are said at this difficult period last a lifetime in the heads of parents.

Keywords: communication, death, perinatal loss, stillbirth

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Authors: Caiwei Chen, Jianhao Li, Jiasong Zhu

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The reform and opening-up stimulated economic and technological take-off in China while resulting in massive urbanization and motorization. Wujiaochang area was set as a secondary business district in Shanghai to meet the growing demand, with the reconstruction of Wujiaochang Plaza in 2005 being a milestone of this intended urban renewal. Wujiaochang is now an economically dynamic area providing much larger traffic and transit capacity transportation-wise. However, this rebuilding has completely changed the face of the district. It is, therefore, appropriate to evaluate its impact on neighborhoods and communities while assessing the overall sustainability of such an operation. In this study, via an online questionnaire survey among local residents and daily visitors, we assess the perceptions and the estimated impact of Wujiaochang Plaza's reconstruction. We then confront these results to the 62 answers from local residents to a questionnaire collected on paper. The analysis of our data, along with observation and other forms of information -such as maps analysis or online applications (Dianping)- demonstrate major improvement in economic sustainability but also significant losses in environmental sustainability, especially in terms of active transportation. As for the social viewpoint, local residents' opinions tend to be rather positive, especially regarding traffic safety and access to consumption, despite the lack of connectivity and radical changes induced by Wujiaochang massive transformations. In general, our investigation exposes the overall positive outcomes of Wujiaochang Plaza reconstruction but also unveils major drawbacks, especially in terms of soft mobility and traffic fluidity. We gather that our approach could be of tremendous help for future major urban interventions, as such approaches in municipal regeneration are widely implemented in Chinese cities and yet still need to be thoroughly assessed in terms of sustainability.

Keywords: China's reform and opening-up, economical revitalization, neighborhood identity, sustainability assessment, urban renewal

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Authors: Sadia Bibi, Karim Ullah

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Islamic banks have excess liquidity, which needs proper management to earn a high rate of return on them to remain competitive. However, they lack assets-backed avenues and rely on a few sukuks, which led them to liquidity management issues. Financial engineering comes forward to innovate and develop instruments for the requisite financial problem. Still, they face many challenges, explored in the context of liquidity management in Islamic banks. The rigorous literature review shows that Shariah compliance, competition from the conventional banks, lack of sufficient instruments, derivatives are still not accepted as legitimate products, the inter-bank market being less developed, and no possibility of lender of last resort is the six significant constraints to financial engineering for liquidity management of Islamic banks. To further explore the problem, a multiple case study strategy is used to extend and develop the theory with the philosophical stance of social constructivism. Narrative in-depth interviews over the telephone are conducted with key personnel at treasury departments of selected banks. Data is segregated and displayed using NVivo 11 software, and the thematic analysis approach identifies themes related to the constraints. The exploration of further constraints to financial engineering for liquidity management of Islamic banks achieves the research aim. The theory is further developed by the addition of three more constraints to the theoretical framework, which are i) lack of skilled human resources, ii) lack of unified vision, and iii) lack of government support to the Islamic banks. These study findings are fruitful for the use of the government, regulatory authorities of the banking sector, the State Bank of Pakistan (Central Bank), and the product design & development division of Islamic banks to make the financial engineering process feasible and resolve liquidity management issues of Islamic banks.

Keywords: financial engineering, liquidity management, Islamic banks, shariah compliance

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Authors: Kais Nasser

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This paper tries to map the right to city, the right to just city, and describes the complications of achieving these rights in practice. It defines the right of city, its theoretical meanings, and approaches; in addition, it discusses the standards for achieving a Just City- equality, democracy, and diversity- and the complicity of ensuring them in practice. The article shows that realizing the right to city involves political, economic, social, and cultural aspects that might disturb the mission of planning a just city. Nevertheless, the article argues that the realization of the right to just city is not impossible.

Keywords: right to city, placemaking, city marketing, just city

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Authors: Chek K. Loi

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The present study has two objectives. Firstly, it investigates the rhetorical strategies employed in the body paragraphs of ESL (English as a Second Language) undergraduate students’ English academic essays. Peacock’s (2002) model of the discussion section was used as the starting points in this study to investigate the rhetorical moves employed in the data. Secondly, it investigates the writing problems as perceived by these ESL students through an interview. Interview responses serve as accompanying data to the move analysis. Apart from this, students’ English academic writing problems are diagnosed. The findings have pedagogical implications in an EAP (English for Academic Purposes) classroom.

Keywords: academic essays, move analysis, pedagogical implication, rhetorical strategies

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Authors: Alok Kumar, Hari Ram, Lebin Thomas, Ved Pal Singh

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Organic solvent tolerant amylases and proteases of microbial origin are in great demand for their application in transglycosylation of water-insoluble flavanoids and in peptide synthesizing reaction in organic media. Most of the amylases and proteases are unstable in presence of organic solvent. In the present work two different bacterial strains M-11 and VP-07 were isolated from the soil sample of a dairy farm in Delhi, India, for the efficient production of extracellular amylase and protease through their screening on starch agar (SA) and skimmed milk agar (SMA) plates, respectively. Both the strains (M-11 and VP-07) were identified based on morphological, biochemical and 16S rRNA gene sequencing methods. After analysis through Ez-Taxon software, the strains M-11 and VP-07 were found to have maximum pairwise similarity of 98.63% and 100% with Bacillus subtilis subsp. inaquosorum BGSC 3A28 and Bacillus anthracis ATCC 14578 and were therefore identified as Bacillus sp. UKS1 and Bacillus sp. UKS2, respectively. Time course study of enzyme activity and bacterial growth has shown that both strains exhibited typical sigmoid growth behavior and maximum production of amylase (180 U/ml) and protease (78 U/ml) by these strains (UKS1 and UKS2) was commenced during stationary phase of growth at 24 and 20 h, respectively. Thereafter, both amylase and protease were tested for their tolerance towards organic solvents and were found to be active as well stable in p-xylene (130% and 115%), chloroform (110% and 112%), isooctane (119% and 107%), benzene (121% and 104%), n-hexane (116% and 103%) and toluene (112% and 101%, respectively). Owing to such properties, these enzymes can be exploited for their potential application in industries for organic synthesis.

Keywords: amylase, enzyme activity, industrial applications, organic solvent tolerant, protease

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Authors: Carmen Rocio Fernandez Diaz

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This paper focuses on the relevance of information and communication technologies (hereinafter referred as ‘ICTs’) as an essential part of the day-to-day life of all societies nowadays, as they offer the scenario where an immense number of behaviors are performed that previously took place in the physical world. In this context, areas of reality that have remained outside the so-called ‘information society’ are hardly imaginable. Nevertheless, it is possible to identify a means that continue to be behind this reality, and it is the penitentiary area regarding inmates rights, as security aspects in prison have already be improved by new technologies. Introducing ICTs in prisons is still a matter subject to great rejections. The study of comparative penitentiary systems worldwide shows that most of them use ICTs only regarding educational aspects of life in prison and that communications with the outside world are generally based on traditional ways. These are only two examples of the huge range of activities where ICTs can carry positive results within the prison. Those positive results have to do with the social reintegration of persons serving a prison sentence. Deprivation of liberty entails contact with the prison subculture and the harmful effects of it, causing in cases of long-term sentences the so-called phenomenon of ‘prisonization’. This negative effect of imprisonment could be reduced if ICTs were used inside prisons in the different areas where they can have an impact, and which are treated in this research, as (1) access to information and culture, (2) basic and advanced training, (3) employment, (4) communication with the outside world, (5) treatment or (6) leisure and entertainment. The content of all of these areas could be improved if ICTs were introduced in prison, as it is shown by the experience of some prisons of Belgium, United Kingdom or The United States. However, rejections to introducing ICTs in prisons obey to the fact that it could carry also risks concerning security and the commission of new offences. Considering these risks, the scope of this paper is to offer a real proposal to introduce ICTs in prison, trying to avoid those risks. This enterprise would be done to take advantage of the possibilities that ICTs offer to all inmates in order to start to build a life outside which is far from delinquency, but mainly to those inmates who are close to release. Reforming prisons in this sense is considered by the author of this paper an opportunity to offer inmates a progressive resettlement to live in freedom with a higher possibility to obey the law and to escape from recidivism. The value that new technologies would add to education, employment, communications or treatment to a person deprived of liberty constitutes a way of humanization of prisons in the 21st century.

Keywords: deprivation of freedom, information and communication technologies, imprisonment, social reintegration

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Authors: April Hueimin Lu, Liangj-Ju Yao, Jun-Tin Lin, Susan Siru Liu

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This paper discusses the application of aerial survey technology and 3D laser scanning technology in the surveying and mapping work of the settlements and slate houses of the old Taiwanese aborigines. The relics of old Taiwanese aborigines with thousands of history are widely distributed in the deep mountains of Taiwan, with a vast area and inconvenient transportation. When constructing the basic data of cultural assets, it is necessary to apply new technology to carry out efficient and accurate settlement mapping work. In this paper, taking the old Paiwan as an example, the aerial survey of the settlement of about 5 hectares and the 3D laser scanning of a slate house were carried out. The obtained orthophoto image was used as an important basis for drawing the settlement map. This 3D landscape data of topography and buildings derived from the aerial survey is important for subsequent preservation planning as well as building 3D scan provides a more detailed record of architectural forms and materials. The 3D settlement data from the aerial survey can be further applied to the 3D virtual model and animation of the settlement for virtual presentation. The information from the 3D scanning of the slate house can also be used for further digital archives and data queries through network resources. The results of this study show that, in large-scale settlement surveys, aerial surveying technology is used to construct the topography of settlements with buildings and spatial information of landscape, as well as the application of 3D scanning for small-scale records of individual buildings. This application of 3D technology, greatly increasing the efficiency and accuracy of survey and mapping work of aboriginal settlements, is much helpful for further preservation planning and rejuvenation of aboriginal cultural heritage.

Keywords: aerial survey, 3D scanning, aboriginal settlement, settlement architecture cluster, ecological landscape area, old Paiwan settlements, slat house, photogrammetry, SfM, MVS), Point cloud, SIFT, DSM, 3D model

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Authors: Hlamulo Makelane

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The study aims at providing new insights regarding research and development (R&D) public and private activities based on the national R&D survey of the past five years. The main question of the study is what role does water R&D plays on water security; to then analyze what lessons could be extracted to improve the security of water through R&D. In particular, this work concentrates on three main aspects of R&D investments: (i) the level of expenditures, (ii) the sources of funding related to water R&D, and (iii) the personnel working in the field, both for the public and private sectors. The nonlinear regression approached will be used for data analysis based on secondary data gathered from the South African nation R&D survey conducted annually by the Centre for science, technology and innovation indicators (CeSTII).

Keywords: water, R&D, investment, public sector, private sector

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Authors: Abdulnasser Ahmed Haza’a, Marzoq Ali Odhah, Saddam Ahmed Al-Ahdal, Abdulfatah Saleh Al-Jaradi, Gamil Ghaleb Alrubaiee

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Patient safety in hospitals is an essential professional indicator that should be noticed. The threat of fires is potentially the most dangerous risk that could harm patients and personnel. The aim of the study is to assess the knowledge of operating room (OR) staff toward prevention and control sources of fires. Between March 1 and March 30, 2022, data collection was done. A descriptive cross-sectional study was conducted. The sample of the study consisted of 89 OR staff from different governmental hospitals. Convenient sampling was applied to select the sample size. Official approvals were obtained from selected settings for start collection data. Data were collected using a close-ended questionnaire and tested for knowledge. This study was conducted in four governmental hospitals in Sana'a, Yemen. Most of the OR staff were male. Of these, 50.6% of them were operation technician professionals. More than two-thirds of OR staff have less than ten years of experience; 93% of OR staff had inadequate knowledge of sources of fires, and inadequate knowledge of them toward controls and prevention of fires (73%, 79.8%), respectively; 77.5% of OR staff had inadequate knowledge of prevention and control sources of fires. The study concluded that most of OR staff had inadequate knowledge of sources, controls, and prevention of fires, while 22.5% of them had adequate knowledge of prevention and control sources of fires. We recommended the implementation of training programs toward sources, controls, and prevention of fires or related workshops in their educational planning for OR staff of hospitals.

Keywords: knowledge, operation rooms staff, fires, prevention

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to preventing deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.

Keywords: accident risks estimation, artificial neural network, deep learning, k-mean, road safety

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Authors: Saeed M. Alshahrani

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This research integrated blockchain technology to reform medical records management in healthcare informatics. It was aimed at resolving the limitations of centralized systems by establishing a secure, decentralized, and user-centric platform. The system was architected with a sophisticated three-tiered structure, integrating advanced cryptographic methodologies, consensus algorithms, and the Fast Healthcare Interoperability Resources (HL7 FHIR) standard to ensure data security, transaction validity, and semantic interoperability. The research has profound implications for healthcare delivery, patient care, legal compliance, operational efficiency, and academic advancements in blockchain technology and healthcare IT sectors. The methodology adapted in this research comprises of Preliminary Feasibility Study, Literature Review, Design and Development, Cryptographic Algorithm Integration, Modeling the data and testing the system. The research employed a permissioned blockchain with a Practical Byzantine Fault Tolerance (PBFT) consensus algorithm and Ethereum-based smart contracts. It integrated advanced cryptographic algorithms, role-based access control, multi-factor authentication, and RESTful APIs to ensure security, regulate access, authenticate user identities, and facilitate seamless data exchange between the blockchain and legacy healthcare systems. The research contributed to the development of a secure, interoperable, and decentralized system for managing medical records, addressing the limitations of the centralized systems that were in place. Future work will delve into optimizing the system further, exploring additional blockchain use cases in healthcare, and expanding the adoption of the system globally, contributing to the evolution of global healthcare practices and policies.

Keywords: healthcare informatics, blockchain, medical records management, decentralized architecture, data security, cryptographic algorithms

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Authors: Beata Patuszynska

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Children are largely absent from Polish social discourse, a fact which is mirrored in urban planning processes. Their absence creates a vicious circle – an unfriendly urban space discourages children from going outside on their own, meaning adults do not see a need to make spaces more friendly for a group, not present. The pandemic and lockdown, with their closed schools and temporary ban on unaccompanied minors on the streets, have only reinforced this. The project – co-writing with children a book concerning their first steps into urban independence - aims at empowering children, enabling them to find their voice when it comes to urban space. The foundation for the book was data collected during research and workshops with children from Warsaw primary schools, aged 7-10 - the age they begin independent travel in the city. The project was carried out with the participation and involvement of children at each creative step. Children were (1) models: the narrator is an 7-year-old boy getting ready for urban independence. He shares his experience as well as the experience of his school friends and his 10-year-old sister, who already travels on her own. Children were (2) teachers: the book is based on authentic children’s stories and experience, along with the author’s findings from research undertaken with children. The material was extended by observations and conclusions made during the pandemic. Children were (3) reviewers: a series of draft chapters from the book underwent review by children during workshops performed in a school. The process demonstrated that all children experience similar pleasures and worries when it comes to interaction with urban space. Furthermore, they also have similar needs that need satisfying. In my article, I will discuss; (1) the advantages of creating together with children; (2) my conclusions on how to work with children in participatory processes; (3) research results: perceptions of urban space by children age 7-10, when they begin their independent travel in the city; the barriers to and pleasures derived from independent urban travel; the influence of the pandemic on children’s feelings and their behaviour in urban spaces.

Keywords: children, urban space, co-creation, participation, human rights

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Authors: Joseph Lillington, Tom Gout, Mike Harrison, Ian Farnan

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The vitrification of high-level nuclear waste within borosilicate glass and its incorporation within a multi-barrier repository deep underground is widely accepted as the preferred disposal method. However, for this to happen, any safety case will require validation that the initially localized radionuclides will not be considerably released into the near/far-field. Therefore, accurate mechanistic models are necessary to predict glass dissolution, and these should be robust to a variety of incorporated waste species and leaching test conditions, particularly given substantial variations across international waste-streams. Here, machine learning is used to predict glass material properties (viscosity, density) and glass leaching model parameters from large-scale industrial data. A variety of different machine learning algorithms have been compared to assess performance. Density was predicted solely from composition, whereas viscosity additionally considered temperature. To predict suitable glass leaching model parameters, a large simulated dataset was created by coupling MATLAB and the chemical reactive-transport code HYTEC, considering the state-of-the-art GRAAL model (glass reactivity in allowance of the alteration layer). The trained models were then subsequently applied to the large-scale industrial, experimental data to identify potentially appropriate model parameters. Results indicate that ensemble methods can accurately predict viscosity as a function of temperature and composition across all three industrial datasets. Glass density prediction shows reliable learning performance with predictions primarily being within the experimental uncertainty of the test data. Furthermore, machine learning can predict glass dissolution model parameters behavior, demonstrating potential value in GRAAL model development and in assessing suitable model parameters for large-scale industrial glass dissolution data.

Keywords: machine learning, predictive modelling, pattern recognition, radioactive waste glass

Procedia PDF Downloads 113