Nicolae Eremia, Olga Coșeleva, Natalia Sucman, Greta Balan, Lucian Lupașcu, Tatiana Mardari, Susana Modvala, Fliur Macaev
Six samples of Moldavian honey from different regions were analyzed, physical and chemical parameters, the content of macro-, microelements, and aminoacids were determined, as well as antibacterial and antifungal activity. The antibacterial and antifungal properties were determined using the double serial dilution method. It was established that all of the samples of acacia, linden, and sunflower honey possess high antibacterial activity. The bioactivity of the samples of honey was proven to be dependent on the type and origin of honey. Sunflower honey has higher antibacterial potency than linden, but linden honey is more active than acacia. Both Gram-positive and Gram-negative bacterial species proved to be susceptible to Moldavian honey. Acacia, linden, and sunflower honey, possess high antibacterial potency against S. aureus and P. aeruginosa even at a dilution of 1:16 (2.5%). The studied samples showed weak antifungal activity against Candida albicans, with the MIC determined at 1:2 dilution (20%). For linden and sunflower honey, the antifungal activity was higher than for acacia honey. The samples with the best bioactivity (sunflower honey) contain a higher amount of free acids, had lower pH values of the honey solution, and these samples also have the highest content of OMF.
{"title":"RELATIONSHIP BETWEEN PHYSICOCHEMICAL PARAMETERS AND ANTIMICROBIAL ACTIVITY OF MOLDAVIAN HONEY","authors":"Nicolae Eremia, Olga Coșeleva, Natalia Sucman, Greta Balan, Lucian Lupașcu, Tatiana Mardari, Susana Modvala, Fliur Macaev","doi":"10.59879/zt0yo","DOIUrl":"https://doi.org/10.59879/zt0yo","url":null,"abstract":"Six samples of Moldavian honey from different regions were analyzed, physical and chemical parameters, the content of macro-, microelements, and aminoacids were determined, as well as antibacterial and antifungal activity. The antibacterial and antifungal properties were determined using the double serial dilution method. It was established that all of the samples of acacia, linden, and sunflower honey possess high antibacterial activity. The bioactivity of the samples of honey was proven to be dependent on the type and origin of honey. Sunflower honey has higher antibacterial potency than linden, but linden honey is more active than acacia. Both Gram-positive and Gram-negative bacterial species proved to be susceptible to Moldavian honey. Acacia, linden, and sunflower honey, possess high antibacterial potency against S. aureus and P. aeruginosa even at a dilution of 1:16 (2.5%). The studied samples showed weak antifungal activity against Candida albicans, with the MIC determined at 1:2 dilution (20%). For linden and sunflower honey, the antifungal activity was higher than for acacia honey. The samples with the best bioactivity (sunflower honey) contain a higher amount of free acids, had lower pH values of the honey solution, and these samples also have the highest content of OMF.","PeriodicalId":49454,"journal":{"name":"Sylwan","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135911144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
After Covid-19 passed, Indonesia's economic situation has not recovered, so there is still a lot of unemployment and job switching. Reduced income leads to lifestyle changes. This research used an online survey method using bit.ly from May to mid-August 2023. The data required are secondary data from literature and online data. Samples were taken using simple random sampling as many as 529 respondents. After Covid-19 was revealed, there was a 65.8% job change and there was a 53.3% decrease in income. Lifestyles between generations are different after Covid-19, the factors that significantly different are hanging out, recording expenses, doing saving, carrying out healthy and environmental education. In addition, there is an awareness of healthy living and protecting the environment, especially in generations Y and Z. This research is used full for producers and stakeholders in developing business strategies, so there is business continuity and for government in formulating policies to improve community welfare and protect the environment
{"title":"LIFESTYLE CHANGES BETWEEN GENERATIONS POST COVID 19","authors":"Yosini Deliana,, Lucyana Trimo, Azhar El Hami","doi":"10.59879/wz7dm","DOIUrl":"https://doi.org/10.59879/wz7dm","url":null,"abstract":"After Covid-19 passed, Indonesia's economic situation has not recovered, so there is still a lot of unemployment and job switching. Reduced income leads to lifestyle changes. This research used an online survey method using bit.ly from May to mid-August 2023. The data required are secondary data from literature and online data. Samples were taken using simple random sampling as many as 529 respondents. After Covid-19 was revealed, there was a 65.8% job change and there was a 53.3% decrease in income. Lifestyles between generations are different after Covid-19, the factors that significantly different are hanging out, recording expenses, doing saving, carrying out healthy and environmental education. In addition, there is an awareness of healthy living and protecting the environment, especially in generations Y and Z. This research is used full for producers and stakeholders in developing business strategies, so there is business continuity and for government in formulating policies to improve community welfare and protect the environment","PeriodicalId":49454,"journal":{"name":"Sylwan","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136009048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vehicle refinement recognition related technology research is widely used in the field of mine monitoring and management systems, road traffic command and control, etc. As researchers develop and implement the target recognition technology system based on deep learning algorithms, designing a target recognition algorithm with excellent performance is a research priority within the field of vehicle monitoring. In this paper, we propose an Efficient Net algorithm based recognition method for vehicle front-end and vehicle rear-end recognition to address the shortcomings of the current methods used for vehicle front-end and vehicle rear-end recognition, and verify the reliability of the algorithm using experiments. Algorithm systematically investigates model scaling, the backbone network makes extensive use of the MBConv structure to extract the feature maps, which cuts short the time required for model training, and the structure introduces the SE module to perform global averaging pooling operations in the channel dimension direction to enhance model performance, so that the network has the dual advantages of network model size and recognition accuracy at the same time. Based on the above findings, we improve the inverse residual module of the backbone feature extraction network EfficientNet by introducing the coordinate attention mechanism (CA) to average the spatial feature information in X-axis and Y-axis dimensions respectively, with the feature layer size and number of channels unchanged, and change the residual edge to shorten the input and output of high-dimensional channels to improve the accuracy of model feature extraction. Meanwhile, this paper introduces a depth-separable convolutional neural network and agent-normalized activation in the mobile flip-flop convolutional module to offset the two different dimensions of X-axis and Y-axis between each convolutional layer but the two main sources of non-normalization, so as to achieve the improvement of the target detection rate and accuracy.
{"title":"Lightweight and Scale Adaptive Efficient backbone Network for Recognition","authors":"Chao Wang, Kaijie Zhang, Xiaoyong Yu, Xianpeng Xiong, Aihua Zheng","doi":"10.59879/ny20e","DOIUrl":"https://doi.org/10.59879/ny20e","url":null,"abstract":"Vehicle refinement recognition related technology research is widely used in the field of mine monitoring and management systems, road traffic command and control, etc. As researchers develop and implement the target recognition technology system based on deep learning algorithms, designing a target recognition algorithm with excellent performance is a research priority within the field of vehicle monitoring. In this paper, we propose an Efficient Net algorithm based recognition method for vehicle front-end and vehicle rear-end recognition to address the shortcomings of the current methods used for vehicle front-end and vehicle rear-end recognition, and verify the reliability of the algorithm using experiments. Algorithm systematically investigates model scaling, the backbone network makes extensive use of the MBConv structure to extract the feature maps, which cuts short the time required for model training, and the structure introduces the SE module to perform global averaging pooling operations in the channel dimension direction to enhance model performance, so that the network has the dual advantages of network model size and recognition accuracy at the same time. Based on the above findings, we improve the inverse residual module of the backbone feature extraction network EfficientNet by introducing the coordinate attention mechanism (CA) to average the spatial feature information in X-axis and Y-axis dimensions respectively, with the feature layer size and number of channels unchanged, and change the residual edge to shorten the input and output of high-dimensional channels to improve the accuracy of model feature extraction. Meanwhile, this paper introduces a depth-separable convolutional neural network and agent-normalized activation in the mobile flip-flop convolutional module to offset the two different dimensions of X-axis and Y-axis between each convolutional layer but the two main sources of non-normalization, so as to achieve the improvement of the target detection rate and accuracy.","PeriodicalId":49454,"journal":{"name":"Sylwan","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136302010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gabriel T. Nunes, D. L. G. Fagundes-Triches, Susana E. Moreno, A. Honório-França, Eduardo L França, Joaquim M. da Silva
Breast cancer is a multifactorial disease resulting from genetic, immunological, and environmental interactions. Among environmental factors, it is known that diet plays a key role in cancer etiology. In addition, there is evidence that human milk may confer long-term benefits, such as reducing the risk of developing cancer. In breast cancer, macrophages represent one of the main components of the immune infiltrate. These cells contribute to the progression and spread of tumors, but studies suggest that these cells can be reprogrammed to act as a potent antitumor immune response. In addition to the mechanisms involved in the interaction between immune system cells and tumor progression, studies have related the use of plants as an alternative for tumor immunotherapy, among which the Cerrado bryophytes stand out. Thus, this study aimed to evaluate Lejeunea cancellata extract as a modulating agent in breast cancer (MCF-7) tumor cell lines and human colostrum. Therefore, the natural extract of Lejeunea cancellata was prepared, and from this, immunophenotyping assays, cytokine dosage, and data analysis were performed. There was an increase in the secretion of the inflammatory cytokines IL-1 and IL-8 in the groups cocultured with MCF-7 in the presence of Lejeunea cancellata. Furthermore, a decrease in the expression of CD14 (macrophages), CD163, CD197+ and CD86+ (M1 macrophages), and CD197- and CD86+ (M2 macrophages) is observed in colostrum cells when they were treated with Lejeunea cancellata in coculture with MCF-7 cells. These findings indicate that colostrum macrophages differentiate into two phenotypes, M1 and M2. When cocultured with MCF-7 breast tumor cells, the bryophyte Lejeunea cancellata reduces the percentage of both macrophage phenotypes. This data suggests that the bryophyte can inhibit the formation of inflammatory infiltrates caused by M1 macrophages in the tumor microenvironment and the progression of M2 macrophages that promote tumorigenesis.
{"title":"Lejeunea Cancellata as a modulating agent in breast cancer (MCF-7) tumor cell lines and human colostrum","authors":"Gabriel T. Nunes, D. L. G. Fagundes-Triches, Susana E. Moreno, A. Honório-França, Eduardo L França, Joaquim M. da Silva","doi":"10.59879/jqnvx","DOIUrl":"https://doi.org/10.59879/jqnvx","url":null,"abstract":"Breast cancer is a multifactorial disease resulting from genetic, immunological, and environmental interactions. Among environmental factors, it is known that diet plays a key role in cancer etiology. In addition, there is evidence that human milk may confer long-term benefits, such as reducing the risk of developing cancer. In breast cancer, macrophages represent one of the main components of the immune infiltrate. These cells contribute to the progression and spread of tumors, but studies suggest that these cells can be reprogrammed to act as a potent antitumor immune response. In addition to the mechanisms involved in the interaction between immune system cells and tumor progression, studies have related the use of plants as an alternative for tumor immunotherapy, among which the Cerrado bryophytes stand out. Thus, this study aimed to evaluate Lejeunea cancellata extract as a modulating agent in breast cancer (MCF-7) tumor cell lines and human colostrum. Therefore, the natural extract of Lejeunea cancellata was prepared, and from this, immunophenotyping assays, cytokine dosage, and data analysis were performed. There was an increase in the secretion of the inflammatory cytokines IL-1 and IL-8 in the groups cocultured with MCF-7 in the presence of Lejeunea cancellata. Furthermore, a decrease in the expression of CD14 (macrophages), CD163, CD197+ and CD86+ (M1 macrophages), and CD197- and CD86+ (M2 macrophages) is observed in colostrum cells when they were treated with Lejeunea cancellata in coculture with MCF-7 cells. These findings indicate that colostrum macrophages differentiate into two phenotypes, M1 and M2. When cocultured with MCF-7 breast tumor cells, the bryophyte Lejeunea cancellata reduces the percentage of both macrophage phenotypes. This data suggests that the bryophyte can inhibit the formation of inflammatory infiltrates caused by M1 macrophages in the tumor microenvironment and the progression of M2 macrophages that promote tumorigenesis.","PeriodicalId":49454,"journal":{"name":"Sylwan","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71244281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohd. Faheem Khan, Kush Shrivastava, Rakesh Sarkar, Qazi Mohammad Sajid Jamal
Plant bionics is a possible way to improve the natural plant system to handle the problem of urbanization, population explosion, food insecurity and for the betterment of human health safety and environment. Plant bionics is a specialized interdisciplinary science, which revolutionize the traditional plant research. This approach may also play a major role in replacement or modification of characters and functions of natural plant systems. Roots, stems, leaves and vascular networking system of plants are responsible for transmitting the chemical signals, metabolic activities, growth and functional activities. Now scientists are able to explore the unlimited possibilities of carbon nanotubes in biological and medical applications. Carbon nanotubes can append peptides, sugars, lipids DNA and RNA. These biologically transformed conjugates can be very handy to tackle the problem of reducing natural resources and medical treatments. The present article depicts the infinite possibilities of plant bionics for the betterment of human being.
{"title":"PLANT BIONICS: A STEP TOWARDS SUSTAINABLE FUTURE DEVELOPMENT IN AREA OF PLANT SCIENCE","authors":"Mohd. Faheem Khan, Kush Shrivastava, Rakesh Sarkar, Qazi Mohammad Sajid Jamal","doi":"10.59879/lwihd","DOIUrl":"https://doi.org/10.59879/lwihd","url":null,"abstract":"Plant bionics is a possible way to improve the natural plant system to handle the problem of urbanization, population explosion, food insecurity and for the betterment of human health safety and environment. Plant bionics is a specialized interdisciplinary science, which revolutionize the traditional plant research. This approach may also play a major role in replacement or modification of characters and functions of natural plant systems. Roots, stems, leaves and vascular networking system of plants are responsible for transmitting the chemical signals, metabolic activities, growth and functional activities. Now scientists are able to explore the unlimited possibilities of carbon nanotubes in biological and medical applications. Carbon nanotubes can append peptides, sugars, lipids DNA and RNA. These biologically transformed conjugates can be very handy to tackle the problem of reducing natural resources and medical treatments. The present article depicts the infinite possibilities of plant bionics for the betterment of human being.","PeriodicalId":49454,"journal":{"name":"Sylwan","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135610012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, there have been significant advancements in the utilization of machine learning, incorporating data mining and deep learning techniques, for the analysis of chest X-ray images. These methods play a vital role as decision support tools, aiding radiologists in expediting the diagnostic process. Chest X-ray (CXR) images have proven their value in diagnosing and monitoring various pulmonary diseases, such as COVID-19 and Pneumonia and Tuberculosis. This study aims to detect these lung diseases by applying deep learning method. To achieve this, we applied Convolutional Neural Network (CNN) and Transfer (VGG16) models in the publicly available dataset comprising 7135 CXR images. The obtained results show the effectiveness of deep learning in detecting lung diseases, as well as the importance of coloring CXR images to increase the accuracy of disease detection.
{"title":"DETECTION OF LUNG DISEASES FROM COLORIZED CHEST X-RAY IMAGES USING DEEP LEARNING","authors":"Sibel Senan, Razan Almnawer","doi":"10.59879/ffow3","DOIUrl":"https://doi.org/10.59879/ffow3","url":null,"abstract":"In recent years, there have been significant advancements in the utilization of machine learning, incorporating data mining and deep learning techniques, for the analysis of chest X-ray images. These methods play a vital role as decision support tools, aiding radiologists in expediting the diagnostic process. Chest X-ray (CXR) images have proven their value in diagnosing and monitoring various pulmonary diseases, such as COVID-19 and Pneumonia and Tuberculosis. This study aims to detect these lung diseases by applying deep learning method. To achieve this, we applied Convolutional Neural Network (CNN) and Transfer (VGG16) models in the publicly available dataset comprising 7135 CXR images. The obtained results show the effectiveness of deep learning in detecting lung diseases, as well as the importance of coloring CXR images to increase the accuracy of disease detection.","PeriodicalId":49454,"journal":{"name":"Sylwan","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135610172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Suminartika, Y. Deliana, D. Rochdiani, L. Trimo, Yadi Heryadi
Environmental problems must be addressed properly, one of which is by producing and consuming organic products. Although it is currently impossible to meet the demand of organic products in the world, it can at least reduce environmental problems. Consumer knowledge of a sustainable environment is seen from the knowledge of green products, Green Finance, Green Living, Green Transportation, Green Producers, Green Consumers, Green Communication , Green Institutions and Green Creativity. The purpose of this study is to see the perception and consumer behavior of organic products in supporting a sustainable environment. The study was conducted in June – October 2022 with 183 respondents using simple random sampling. The consumer criteria are consumers who often buy from these three organic commodities in daily shopping patterns and the data is analyzed with Multidimensioan Scalling (MDS). The results showed that consumer perceptions of sustainable environmental trends say that organic vegetables and chickens have similarities, then rice and organic vegetables. While rice and organic chicken have no similarities. Consumer behavior that is oriented towards being environmentally friendly is revealed that consumers in buying organic rice consider many factors including green products, green producers, green communication, and green institutions. As for organic chicken factor green consumer, and green creativity. Furthermore, for organic vegetables, only green finance. Thus, consumers in buying organic rice consider many factors compared to buying organic chicken and vegetables. This indicates that knowledge of sustainable environment still needs to be conveyed to the community considering that rice is a staple food in Indonesia and also other countries in the world.
{"title":"THE PERCEPTION AND CONSUMER BEHAVIOR OF ORGANIC PRODUCTS IN SUPPORTING A SUSTAINABLE ENVIRONMENT","authors":"E. Suminartika, Y. Deliana, D. Rochdiani, L. Trimo, Yadi Heryadi","doi":"10.59879/kupcu","DOIUrl":"https://doi.org/10.59879/kupcu","url":null,"abstract":"Environmental problems must be addressed properly, one of which is by producing and consuming organic products. Although it is currently impossible to meet the demand of organic products in the world, it can at least reduce environmental problems. Consumer knowledge of a sustainable environment is seen from the knowledge of green products, Green Finance, Green Living, Green Transportation, Green Producers, Green Consumers, Green Communication , Green Institutions and Green Creativity. The purpose of this study is to see the perception and consumer behavior of organic products in supporting a sustainable environment. The study was conducted in June – October 2022 with 183 respondents using simple random sampling. The consumer criteria are consumers who often buy from these three organic commodities in daily shopping patterns and the data is analyzed with Multidimensioan Scalling (MDS). The results showed that consumer perceptions of sustainable environmental trends say that organic vegetables and chickens have similarities, then rice and organic vegetables. While rice and organic chicken have no similarities. Consumer behavior that is oriented towards being environmentally friendly is revealed that consumers in buying organic rice consider many factors including green products, green producers, green communication, and green institutions. As for organic chicken factor green consumer, and green creativity. Furthermore, for organic vegetables, only green finance. Thus, consumers in buying organic rice consider many factors compared to buying organic chicken and vegetables. This indicates that knowledge of sustainable environment still needs to be conveyed to the community considering that rice is a staple food in Indonesia and also other countries in the world.","PeriodicalId":49454,"journal":{"name":"Sylwan","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71244326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fatma Khalifa Elsayed, Nashwa Karam Abo Bakr, Shrooq Gharamallah Alzahrani
Gender Identity Disorder GID has negative psychological and social effects on individuals and society, its spread has led to the emergence of strange behaviors in the Arab community in general, and in school and university settings. For Arab societies, including Saudi Arabia, there is insufficient information on the prevalence of GID. The study attempted to determine the prevalence rates of GID, and the difference in GID using some demographic variables (age, economic status, Gregorian ordinal number of family members), determine the difference between abused and non-abused women. the GID Scale was used on a sample of (799) Saudi Women’s, their ages ranged between (18-29) with an average age of 75.24, a standard deviation of 37.9. The result showed prevalence of gender identity disorder according to the age variable24.75, In terms of economic level, the average prevalence of GID was 24.75, Regarding the Gregorian order, it showed that the mean prevalence of gender identity disorder was 24.75, In terms of family size, it showed that the mean prevalence of GID was 24.75, In addition to that there are no significant differences between abused and non-abused women, both in the overall degree of gender identity disorder and in the subdimensions.
{"title":"Factor affecting on gender identity disorder among Saudi’s Women","authors":"Fatma Khalifa Elsayed, Nashwa Karam Abo Bakr, Shrooq Gharamallah Alzahrani","doi":"10.59879/rm7bz","DOIUrl":"https://doi.org/10.59879/rm7bz","url":null,"abstract":"Gender Identity Disorder GID has negative psychological and social effects on individuals and society, its spread has led to the emergence of strange behaviors in the Arab community in general, and in school and university settings. For Arab societies, including Saudi Arabia, there is insufficient information on the prevalence of GID. The study attempted to determine the prevalence rates of GID, and the difference in GID using some demographic variables (age, economic status, Gregorian ordinal number of family members), determine the difference between abused and non-abused women. the GID Scale was used on a sample of (799) Saudi Women’s, their ages ranged between (18-29) with an average age of 75.24, a standard deviation of 37.9. The result showed prevalence of gender identity disorder according to the age variable24.75, In terms of economic level, the average prevalence of GID was 24.75, Regarding the Gregorian order, it showed that the mean prevalence of gender identity disorder was 24.75, In terms of family size, it showed that the mean prevalence of GID was 24.75, In addition to that there are no significant differences between abused and non-abused women, both in the overall degree of gender identity disorder and in the subdimensions.","PeriodicalId":49454,"journal":{"name":"Sylwan","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71244413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many linguistic speaking inputs require more confidence to communicate effectively in higher education. Focusing on the speaking discourse perspectives aiming to meet student satisfaction in committing to speaking EFL, we customized the adopted instruments as follows: (Asakereh & Dehghannezhad, 2015) and (Oxford, 1990). The research questions are RQ1. What language input challenges do Albanian students face in the university setting while speaking EFL? RQ2. Is the EFL speaking discourse affected positively by strategies utilized in FL speaking performances? For the academic year 2022/23, the current researcher obtained qualitative data output from two instruments N=250 online questionnaires. Using the second instrument (SILL), we tested the following hypotheses: H1=students achieve satisfaction with up-to-date language input in bringing knowledge to life through continuous effective instructional practices H2=the effectiveness of the strategies used by EFL teachers toward speaking commitment needs ongoing improvement. SPSS data output reported a significant correlation between the research hypotheses. It targets the perspectives of the instructional impact of Metacognitive Strategies and Affective Strategies for increased learner autonomy. The result of this research promotes Affective Strategies to maximize learner autonomy indicating significant practical implications in the classroom to accomplish speaking goals. Concerning improvement issues in EFL speaking at higher education, commitment marks the relevance of empowering teaching speaking content.
{"title":"Re-Thinking improvement issues in EFL speaking commitment at higher education - A speaking discourse analysis perspectives","authors":"Vjollca Jonuzi","doi":"10.59879/8eqdw","DOIUrl":"https://doi.org/10.59879/8eqdw","url":null,"abstract":"Many linguistic speaking inputs require more confidence to communicate effectively in higher education. Focusing on the speaking discourse perspectives aiming to meet student satisfaction in committing to speaking EFL, we customized the adopted instruments as follows: (Asakereh & Dehghannezhad, 2015) and (Oxford, 1990). The research questions are RQ1. What language input challenges do Albanian students face in the university setting while speaking EFL? RQ2. Is the EFL speaking discourse affected positively by strategies utilized in FL speaking performances? For the academic year 2022/23, the current researcher obtained qualitative data output from two instruments N=250 online questionnaires. Using the second instrument (SILL), we tested the following hypotheses: H1=students achieve satisfaction with up-to-date language input in bringing knowledge to life through continuous effective instructional practices H2=the effectiveness of the strategies used by EFL teachers toward speaking commitment needs ongoing improvement. SPSS data output reported a significant correlation between the research hypotheses. It targets the perspectives of the instructional impact of Metacognitive Strategies and Affective Strategies for increased learner autonomy. The result of this research promotes Affective Strategies to maximize learner autonomy indicating significant practical implications in the classroom to accomplish speaking goals. Concerning improvement issues in EFL speaking at higher education, commitment marks the relevance of empowering teaching speaking content.","PeriodicalId":49454,"journal":{"name":"Sylwan","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71244677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The COVID-19 pandemic, one of the most serious public health hazards of recent times, led to a high number of hospitalisations. The pressure on intensive care units has been significant. In many countries, including Iceland, there was a need to increase the capacity of these units to meet the growing demand for intensive care spaces, especially at the start of the pandemic. At Landspitali, the National University Hospital of Iceland (hereafter referred to as Landspitali), increasing unit capacity was a large-scale and extensive project where project management methodologies were utilised to assess risks and develop response plans. Using information gathered from interviews, this study explores the experience of managers in Landspitali’s surgical and intensive care unit in preparing for the pandemic and their evaluations of the project's success. The interviews were conducted in the autumn of 2020 after the first wave of the pandemic had passed in Iceland. The study utilised a qualitative methodology. Eight managers from Landspitali’s surgical and intensive care unit participated in semi-structured interviews. The study employs thematic analysis to analyse the findings. The data analysis reveals four themes. The first theme, ‘dealing with the unknown’, illustrates the uncertainty that was prevalent at the beginning of the pandemic. The second, ‘one step ahead’, reveals how the managers utilised resources both within and outside the hospital to prepare the intensive care unit for COVID-19 patients. The third theme, ‘fighting the virus’, highlights the challenges the managers encountered throughout the process. Lastly, the ‘in this together’ theme focuses on how the staff came together to accomplish the project. The initial uncertainty during the preparation phase posed difficulties for the managers. Working in accordance with existing response plans and utilising the findings of the situation analysis made it possible for managers to organise how space, personnel, and supplies would be utilised and thus increase the surge capacity of the units. The respondents' main challenges were facility adaptation and ensuring adequate staffing. Cooperation and solidarity among the staff, along with well-timed preventive measures implemented by the authorities, proved crucial to the success of Landspitali’s intensive care unit in dealing with the pandemic.
COVID-19大流行是近年来最严重的公共卫生危害之一，导致大量患者住院。重症监护病房的压力很大。在包括冰岛在内的许多国家，有必要提高这些单位的能力，以满足对重症监护病房日益增长的需求，特别是在大流行病开始时。在冰岛国立大学医院Landspitali(以下简称Landspitali)，提高单位能力是一个大规模和广泛的项目，利用项目管理方法来评估风险和制定应对计划。利用从访谈中收集的信息，本研究探讨了兰德斯皮塔利外科和重症监护病房管理人员在应对大流行方面的经验，以及他们对项目成功的评价。这些采访是在冰岛第一波大流行过去后的2020年秋季进行的。这项研究采用了定性方法。兰德斯皮塔利外科和重症监护室的8名管理人员参加了半结构化访谈。本研究采用主题分析法对研究结果进行分析。数据分析揭示了四个主题。第一个主题是“应对未知”，说明大流行开始时普遍存在的不确定性。第二，“领先一步”，揭示了管理人员如何利用医院内外的资源，为COVID-19患者的重症监护病房做好准备。第三个主题是“抗击病毒”，突出了管理人员在整个过程中遇到的挑战。最后，“in this together”主题关注的是员工如何团结起来完成项目。前期准备阶段的不确定性给管理者带来了困难。根据现有的应对计划和利用情况分析的结果，管理人员可以组织如何利用空间、人员和物资，从而提高各单位的应急能力。受访者面临的主要挑战是设施适应和确保足够的人员配备。事实证明，工作人员之间的合作与团结，以及当局及时采取的预防措施，对兰德斯皮塔利重症监护室在应对大流行病方面取得成功至关重要。
{"title":"The COVID-19 Pandemic and Landspitali's Operating Room and Intensive Care Unit","authors":"Audur Sesselja Gylfadottir, Vigdis Hallgrimsdottir, Edvald Moller","doi":"10.59879/cjl1q","DOIUrl":"https://doi.org/10.59879/cjl1q","url":null,"abstract":"The COVID-19 pandemic, one of the most serious public health hazards of recent times, led to a high number of hospitalisations. The pressure on intensive care units has been significant. In many countries, including Iceland, there was a need to increase the capacity of these units to meet the growing demand for intensive care spaces, especially at the start of the pandemic. At Landspitali, the National University Hospital of Iceland (hereafter referred to as Landspitali), increasing unit capacity was a large-scale and extensive project where project management methodologies were utilised to assess risks and develop response plans. Using information gathered from interviews, this study explores the experience of managers in Landspitali’s surgical and intensive care unit in preparing for the pandemic and their evaluations of the project's success. The interviews were conducted in the autumn of 2020 after the first wave of the pandemic had passed in Iceland. The study utilised a qualitative methodology. Eight managers from Landspitali’s surgical and intensive care unit participated in semi-structured interviews. The study employs thematic analysis to analyse the findings. The data analysis reveals four themes. The first theme, ‘dealing with the unknown’, illustrates the uncertainty that was prevalent at the beginning of the pandemic. The second, ‘one step ahead’, reveals how the managers utilised resources both within and outside the hospital to prepare the intensive care unit for COVID-19 patients. The third theme, ‘fighting the virus’, highlights the challenges the managers encountered throughout the process. Lastly, the ‘in this together’ theme focuses on how the staff came together to accomplish the project. The initial uncertainty during the preparation phase posed difficulties for the managers. Working in accordance with existing response plans and utilising the findings of the situation analysis made it possible for managers to organise how space, personnel, and supplies would be utilised and thus increase the surge capacity of the units. The respondents' main challenges were facility adaptation and ensuring adequate staffing. Cooperation and solidarity among the staff, along with well-timed preventive measures implemented by the authorities, proved crucial to the success of Landspitali’s intensive care unit in dealing with the pandemic.","PeriodicalId":49454,"journal":{"name":"Sylwan","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135798668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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